Abstract:The furrow sowing with whole plasticfilm mulching on double ridges has been widely used in the arid region of northwest China, because it can resist drought and increase production. It is an inevitable trend to realize and improve the whole mechanized operation level. It is mainly reflected in the research on the construction of covered film seedbed, sowing on the film, residual film recovery and harvesting crop technology and supporting equipment. Based on the analysis of adoption, technical modes and application benefits of furrow sowing with whole plasticfilm mulching on double ridges, the correlative key mechanization technical characteristics of ridging and covering film, precision sowing on film, harvesting crop and residual film recovery and representative typical machine of whole plasticfilm mulching on double ridges were reviewed. Combined with the problems and demands in actual production and application of furrow sowing with whole plasticfilm mulching on double ridges in China, on the basis of analyzing and summarizing the existing problems of agronomy and agricultural machinery, and future research emphasis and development direction were provided as following aspects: combination of agricultural machine with agronomy under furrow sowing with whole plasticfilm mulching on double ridges, continuing to strengthen basic research and supporting machine performance optimization, and forming full mechanization technical system of whole plasticfilm mulching on double ridges. It was suggested that the key to form full mechanization technical system of whole plasticfilm mulching on double ridges were development of economic and efficient full mechanization equipment and combination of depth of agricultural machine with agronomy. It was also a scientific and reasonable technology of furrow sowing with whole plasticfilm mulching on double ridges, to realize the development direction of its production system with cost saving and efficiency increasing.

Abstract:Aiming at the problem that the mobile robot operating in complex outdoor environment reduced work completion rate due to energy limitation because of consume excessive energy when moving along the shortest paths on uneven terrains which often consisted of rapid elevation changes, an improved heuristic search algorithm called ECA* algorithm was proposed, which can optimize energy loss of the path when resources were limited. Firstly, the distance traveled and the energy lost by the robot were calculated by the establishment of robot distanceenergy loss model, which can also evaluate the future path and the energy consumption trend. Then, the distanceenergy loss model was brought into the heuristic cost function based on the traditional A* algorithm and the extended subnode was searched for the optimal path. In each iteration process, the path at the disadvantage was eliminated by comparison to ensure the efficiency of the algorithm. Finally, the energy loss of different paths searched by the improved algorithm as well as the traditional A* algorithm was compared though the design of simulation experiment. The improved algorithm can reduce the energy consumption by 14.87% through the simulated calculation which verified the effectiveness of the improved algorithm.

Abstract:Addressing the problems of deadlock and poor local path in traditional artificial potential field algorithm, some improvement measures were put forward. The obstacle detection algorithm was used to identify one effective obstacle and one intermediate point. Then a local path from starting point to the intermediate point was planed according to the gravitational field and boundary conditions. Setting the intermediate point to a new starting point and repeating this process until each local path was planed one by one. Secondly, aiming at the disadvantage of slow convergence rate and easy to fall into local optimum in basic ant colony algorithm, some improvements were proposed. The result of artificial potential field algorithm was used to build heuristic information of ant colony, so as to avoid the problems of path crossover and slow convergence. At the same time, a negative feedback loop was built to adaptively adjust the renewal speed of global pheromone and local pheromone through the iteration number. Finally, simulation experiment on three different algorithms was conducted. The results showed that under the same environment model, the proposed algorithm had fewer iterations, shorter running time and better global search ability than other two algorithms. In the given simple environment model, the iteration times of the algorithm was 3, the running time was 0.892s, and the optimal path length was 28.627m. In the given complex environment model, the iteration was 8 times, the running time was 3.376s, the optimal path length was 31.556m, and the global coverage of paths was 73.63%.

Abstract:In the agricultural field spray application process, the traditional human spray, because of large amount of labor, toxic to human body, was gradually replaced by other spray methods. One of the most popular methods is the smart spray of mobile cars. For autonomous driving vehicles applied with intelligent variable spray, the detection and accurate positioning of feature points play an important role in autonomous driving of robots. Feature detection is equivalent to the eyes of the car to obtain plant information, road condition. Accurate positioning is equivalent to the brain of the car. After the car acquires color information and depth information, it finds its exact position and guides the car to drive independently. In the process of continuous development of the visual synchronous localization algorithm of selfpropelled vehicle, the traditional path optimization based on the traditional filtering form has the phenomenon of poor positioning accuracy and floating point drift. For the stable running of the car, precise spray has a great impact. To solve this problem, a method of global nonlinear optimization with depth information was proposed. The RealSense camera was used to obtain continuous color and depth information frames in real time. Firstly, through the continuous color information frames obtained, the FAST feature points of the overlapped part were extracted, the scale invariance and rotation invariance were optimized, and the BRIEF description was calculated to obtain the feature description of two consecutive key frame repetition regions. Then, feature matching was performed by the nearest neighbor algorithm, and Nanoflann algorithm was used to accelerate the matching process. After obtaining the matching point pair of continuous key frames, the minimum distance method was used to screen the mismatched points, and the random sampling consistency method (RANSAC) based on the basic matrix was used to test the matching point pair. After eliminating the false match and obtaining the correct match point, PnP was used to calculate the pose change of continuous key frames, calculate the residual error, and build the incremental equation. Dogleg algorithm was used to estimate the pose of continuous key frames for multiple iterations and optimization to obtain the precise pose of spray car. At the same time, in the process of calculating the residual error iterative optimization, the bit-pose calculated by the RealSense acquisition depth information and the bit-pose calculated by the polar constraint solution were integrated into the iterative optimization. Compared with the single depth information correction mode, the algorithm effectively improved the positioning accuracy of the car. When the depth information collection was lost, the polar constraint compensated the process of vehicle posture estimation, and improved the robustness of accurate realtime acquisition of vehicle track.

Abstract:The green forage harvester fills the trailer hoppers in real time by its mechanical arm when it is cutting and collecting green forage. Recently, the process of forage filling needs to identify the position of the trailer hoppers through artificial visual recognition, and then control the rotation of the mechanical arm to the right direction, which has the problems of low efficiency, high loss, and manpower consumption. Aiming at the demand of agricultural production intellectualization, a method of automatic recognition and location of trailer hopper of forage harvester based on threedimensional vision was proposed, which combined several advanced image processing methods with point cloud data processing technologies to realize edge recognition, spatial location of trailer hopper. Firstly, the concept of visual odometer was used to construct the relationship between the camera and the ground threedimensional coordinate system, and singular value decomposition (SVD) algorithm was used to calculate the pose transformation matrix, which was used to rotate and translate the three dimension (3D) point cloud under the camera coordinate, and threshold processing and dimension reduction were carried out based on the ground. Secondly, random sample consensus (RANSAC) algorithm was used to fit the edge of the hopper and locate the corners, so the relationship between the mechanical arm nozzle and the trailer hopper was determined. Finally, the result of localization was directly reflected on the pixel coordinates through coordinate transformation. The method proposed can accurately find the corners of the hopper and depict the area where the trailer hopper was located. The experimental results showed that the proposed method was in less computation, at the same time with high efficiency and accuracy, which satisfied the realtime and accuracy requirements in field operation.

Abstract:The seeds movement under the highspeed operation condition of corn air suction metering device is very complicate, and it is difficult to carry out accurate analysis and calculation. The discrete element (DEM) and computational fluid dynamics (CFD) coupling method was used to accurately simulate the working process of air suction metering device, the bonding model of Zhengdan 958 corn seed cohesive particles was established, the airway structured grid was divided, and the related parameters were set up. The coupling simulation of EDEM and CFD was realized. Through simulation, the working process of the air suction metering device was accurately simulated, and the drag force and movement speed of the seeds were accurately analyzed. It was concluded that the seed filling ability of different seeds from big to small was as follows: small flat shape, round shape and big flat shape. In order to improve the operation quality of seed metering device and ensure the adaptability of seed metering device to seeds, the optimum design of seed plate structure for big flat shape was studied. The mathematical model of filling process was established to optimize the height of the plate type hole embossment and the angle parameter of the type hole embossment. Because of the complex movement caused by the interaction between seed populations and the interaction between seed populations and metering devices when the metering plate was rotated, further analysis and determination of the optimum angle were needed. In order to obtain the best performance parameters of the seed metering device, the angle of the type hole embossment, the height of the type hole embossment and the height of the seed layer were taken as the test factors, and the three factors of the seeding qualified index, multiple index and missing index were used as test indicators. Performing a threefactor quadratic rotation orthogonal combination test, the DesignExpert 8.0.6 software was used to analyze the test data by multiple regression analysis and response surface analysis. The primary and secondary factors affecting the qualified index and multiple index were obtained as follows: the height of type hole embossment, the height of seed layer and the angle of type hole embossment. The primary and secondary factors that affecting the missing index were the height of type hole embossment, the angle of type hole embossment and the height of seed layer. Using multiobjective optimization method, the optimum combination of parameters was determined as follows: the angle of type hole embossment was 35.76°, the height of type hole embossment was 3.11mm, the height of seed layer was 55.61mm, and the qualified index of seed metering was the highest. Under this condition, the qualified index of seed metering device was 9160%, the missing index was 390%, and the multiple index was 450%. The validation test of the optimization results was carried out. When the operating speed was 14km/h and the wind pressure was -3kPa, the qualified index was 91.90%, the missing index was 3.89%, and the multiple index was 4.21%. The validation results were basically consistent with the optimization results, compared with the firstgeneration seed metering device, the qualified index and missing index were better. It can ensure the precision seeding of corn.

Abstract:Aiming to solve the problem of poor seeding quality of the current airsuction vertical disc precision seed metering device caused by higher demands for working pressure during seedfilling process at high speed working conditions. One kind of air suction precision seed metering device with guided assistant seed filling plate was designed to improve the singulation index (SI) of the seed meter at high speed. Basic parameters of the curve were expounded, the source of resistance during the seedfilling was analyzed, and the ideal filling state of the various segments of the seed was presented. An optimal value of the base circle radius of the disturbance groove curve equation was proposed by the calculation of disturbance trough curve equation, the calculation of edge tilt angle, and a single factor simulation experiment was carried out with the CFD-DEM method by gassolid coupling numerical analysis with local void ratio as an indicator. In order to verify the design results, an single factor simulation experiment which compared with two domestic popular airsuction vertical disc precision seed metering devices was carried out under the working wind pressure of -5.0kPa and -6.0kPa. The results showed that the missing rate and the qualified rate were better than those of the other two seed metering devices. Twofactor experiments of operation pressure and forward speed were made on the designed seed metering devices, the optimal operating parameters were proposed by multiobjective optimization analysis. The developed seed metering device was installed on the electrical drive air suction type seeding machine, and the single factor repeating factor test was carried out at three working speeds. When the working speed was 9.11km/h, the grain distance qualified index was 95.48%, and the seedfilling had a better performance at high speed conditions.

Abstract:Aiming at the problem of large resistance of clay soil by subsoiling in midlower Yangtze River, based on the principle of sliding cutting and selfexcited vibration, a sliding cutting selfexcited vibration subsoiling device was designed. The sliding cutting angle and cutting edge angle of the sliding cutting shovel handle were analyzed and the parameters were designed. The finite element analysis showed that the strength of the shovel handle met the design requirements, and the internal and external double springs were designed to reduce the structural size of the selfexcited vibration device. The soil tank comparing test showed that, compared with the traditional arc subsoiling shovel, the fixed connection mode of sliding cutting subsoiling shovel reduced drag by 7.79%~8.81% at various speeds, and the selfexcited vibration connection mode of sliding cutting subsoiling shovel reduced drag by 15.45%~20.05% at various speeds. Field performance test showed that the soil firmness was decreased significantly at different depths after subsoiling, which was decreased by 78.18%, 56.08% and 62.72% at depths of 0～10cm, 10～20cm and 20～30cm, respectively. Soil bulk density was decreased by 14.66%~20.81% at different depths after subsoiling. Soil moisture content was decreased slightly at 0～10cm, and increased slightly at 10～20cm and 20～30cm. The average soil disturbance coefficient was 60.8% and the average soil bulkiness was 11.9%. The subsoiling depth and its stability coefficient conformed to the index. The working quality of sliding cutting selfexcited vibration subsoiling met the operation requirements as a whole. The research results can provide reference for the study of subsoiling drag reduction.

Abstract:An agricultural vertical take-off and landing (VTOL) tail-sitter UAV with symmetrical winglets and wings was designed. The main parameters of the tai-sitter, wingspan, sweep angle, winglet height and winglet thickness were investigated to optimize the structure design. Central composite design (CCD) was employed to construct 25 sample points. Numerical simulation of lift drag ratio and drag were carried out with ANSYS CFX. The response surface models (RSM) of UAV structure parameters with lift drag ratio and drag were established by Design-Expert software. The lift drag ratio was increased with the increase of wing length and height of winglet. The lift drag ratio was decreased with the increase of wing thickness at attack angle of 4°~8°, and with the decrease of wing thickness at attack angle of 10°~12°. The impact of sweep angle and wing height on the lift drag ratio was small. The drag was increased with the increase of wing length and thickness of wing, and decreased with the increase of winglet height. The drag was increased firstly with the increase of sweep angle and then decreased. The multiobjective genetic algorithm was used to optimize the structural parameters, with maximum lift drag ratio and minimum drag as optimal objects. The optimal structural parameters were wingspan of 1123mm, sweep angle of 34°, wing height of 39mm, and wing thickness of 3mm. Compared with the original configuration, the average lift drag ratio was improved by 12.4%, while the average drag was reduced by 5.3%. The response surface model was validated by wind tunnel test. The numerical simulation error of lift drag ratio and drag was less than 8.0%, and the error of response surface model was less than 3%. It was shown that the response surface model had high accuracy and good versatility, and it can be used in the optimization design of vertical takeoff and landing of tailstock UAV. The results were of great significance for the design of tailsitter UAV.

Abstract:In the spray scene, the tea tree leaves have different tilt directions which are subjected to impact by different directions of spray droplets. In order to grasp the impact behavior and influence mechanism of the droplet impact on the tea tree leaves, the elliptical spreading area was used to measure the spreading variation of the droplet during the oblique impact, and a new type of oblique impact droplet spreading and rebound mathematical prediction model, including blade inclination angle and impact angle was derived. In order to verify the theoretical accuracy, two highspeed cameras were used to test and analyze the impact process and results of spray droplets striking tea leaves.The results showed that the impact angle, initial diameter and impact velocity on the spreading area of the adherent droplets were the impact velocity, initial diameter and impact angle. The initial diameter and impact velocity had a significant effect on the droplet spread area, and were highly positively correlated. For fine and medium droplets, the impact angle had no significant effect on the spreading area; for coarse droplets, the impact angle had a significant effect, and 90° impact angle was recommended. The surface of the tea tree leaves was hydrophilic, and there was no rebound behavior when the water droplets hit the surface of the leaf. The result was consistent with the rebound prediction model. The degree of influence on the droplet splatter was the initial diameter, the impact velocity, and the impact angle. The initial diameter and impact velocity had a significant effect on droplet splatter. The larger the initial diameter and impact velocity of the droplet were, the more likely it was to splash. The impact angle had no significant effect on droplet splatter. Because the surface of tea leaves was relatively smooth, no long fluff, and the surface roughness was small, the splash threshold Kcrit was suitable to be 108.4.

Abstract:Aiming to increase the carrying capacity of maize cleaning sieve to high feed quantity to meet the requirement of rapid development of maize grain harvester. Through the analysis of mechanism of shellfish screening, the screening performance and the model of maize screening were obtained. In order to increase the probability of grain permeation, based on the screening characteristics of shell sieve and round sieve, the maize combined sieve which consisted of the shapes of shellfish and round hole was designed. Under the conditions of different feeding quantities of maize extractives, the simulation tests which included combined sieve, single round hole sieve and single shellfish screening test separately were carried out, then their screening performances were compared and analyzed. The results showed that compared with the single round hole sieve and the shellfish sieve respectively, the loss rates of maize of combined sieve was decreased by 4.79 percentage points and 7.85 percentage points when the feeding quantity was 5kg/s, the loss rates of maize of combined sieve was decreased by 5.79 percentage points and 7.84 percentage points when the feeding quantity was 6kg/s. Under the condition of feeding quantity was 2~6kg/s, the cleaning rate and sieving time were 99.22% to 97.53% and 4.87s to 5.50s partly, thus all indicators met the national standards. The performance of the combined sieve was verified by bench test. The loss rate of maize, cleaning rate of maize and screening time of the combined sieve were 1.09%, 95.94% and 6.48s, when feeding quantity was 6kg/s, respectively. Compared with the stepped sieve, the combined sieve grain loss rate was reduced by 5.60 percentage points, the screening time was shortened by 0.93s, and the performance of the cleaning device was further improved. 

Abstract:In terms of the shelling in peanut research for breeding and cultivation, the shelling machine is not only been required to be suitable to a small quantity of feeding, but also been required to decrease damage on peanuts and more efficiency and convenience of cleaning the sheller. At present, the shelling of peanuts used for domestic research plot mainly relies on manpower, which always caused “mixed” phenomena as treatments separated plot. In view of above issues, the scheme of peanut sheller with vertical tapered drum was proposed according to the latest study on the characteristics of the existed horizontal peanut hulling mechanisms. And the related design of integrated structure of this kind of sheller was brought out based on the vertical arrangement, including the hulling device, air suction cleaning device and transmission device. As the key components of the sheller, the tapered drum and the screen made up the hulling mechanism that had a great influence on hulling effect. The key components’ parameters were confirmed and the range of the parameter was determined by deeply theoretical analysis. According to the analysis, the responsible parameter interval of hulling device was selected. Taking “Silihong”, a variety of peanut as test material, the roller speed, semitaper angle of tapered drum and minimum hulling gap as the factors，the peanut removal rate and breakage rate were selected as experimental indexes. The response surface analysis method was used to test the machine performance. The results showed that when the rotating speed of the shelling drum was 340r/min, the semitaper angle of the drum was 40°, and the minimum hulling gap was 10mm, the comprehensive index of shelling was the best, the removal rate was 97.84%, and the breakage rate was 2.97%, which better matched the requirements of plot peanut shelling.

Abstract:Corn has become the first major crop in place of rice and wheat in recent years, thereby significantly influencing the lives of people given the increase in production of corn. Corn snapping roller is the main component of a corn harvesting machine and exerts a crucial effect on the quality of corn harvest. Aiming at the problems of serious grains gnawing and large loss of falling grains in the operation of vertical and horizontal roll corn harvester, a theoretical model of maize excitation heading suitable for mechanized harvesting was established under the condition of separation of ear and stalk of maize under the guidance of excitation theory. Under the guidance of the model, the shape structure and configuration of the picking roll suitable for the corn excitation movement were constructed and optimized, and the corresponding excitation heading testbed was developed. Box-Behnken experimental design method was used to study the effects of key parameters such as edge number, amplitude and rotation speed of excitation picking roll on grain loss rate and gnawing rate during ear picking. The regression equation between experimental factors and inspection indexes was established, and the corresponding response surface was generated. The results showed that the number of edges, the amplitude and the rotation speed of the picking roll had significant effects on the grain loss rate and the gnawing rate during harvesting. Finally, under the guidance of the theory of nonlinear programming, the best combination of the above three experimental factors was obtained, namely, the rotation speed of the picking roll of 950r/min, the number of edges of 8, and the amplitude of 0.75cm. Under these conditions, the average loss rate of corn grains during heading process was 0.228%, and the average breakage rate of corn grains was 0.124%, which was lower than the national technical standard of corn harvesting machinery. The research result provided theoretical support for the popularization and application of this technology.

Abstract:In order to improve picking efficiency of motordriven picking actuator of camellia fruit with rotate rubber roller, a hydraulicdriven camellia fruit picking machine was developed. The influencing factors of the interaction force between camellia fruit and rubber roller were analyzed, and the influence rules of different factors on the interaction force between camellia fruit and rubber roller were obtained by simulation. Based on the analysis result, the main working parameters of the picking device were confirmed. Taking the picking rate of camellia fruit and damage rate of camellia bud as experimental indexes, the distance between up and bottom rollers, speed of rotating frame and the diameter of rollers as experimental factors, the orthogonal indoor and outdoor tests were developed in Jiangxi Academy of Forestry and Jiangxi Agricultural University. Experimental results showed that the significant factors affecting the picking rate were represented as the distance between up and bottom rollers, the speed of rotating frame and the diameter of rubber roller. The significant factors affecting the damage rate of camellia bud were represented as the diameter of the rubber roller, the distance between up and bottom roller and the rotational speed of the rotating frame. With the optimal parameter combination, the distance between upper and lower rubber was 15mm, the rotating speed of rotating frame was 55r/min, and the diameter of robber was 30mm, which were verified experimentally with respect to comprehensive performance of the camellia fruit picking machine. Compared with motordriven picking actuator of camellia fruit with rotate rubber roller, the picking efficiency of hydraulicdriven camellia fruit picking machine was improved obviously, and its speed of rotating frame was increased by 83.33% and average picking efficiency was 210 per minute.

Abstract:For a Francis turbine, the movable guide vane is mainly used to regulate the flow rate and circulation, the relative positions of guide vane, stay vane and the runner directly affect the internal flow of water guiding mechanism and runner, which play an important role in the safe, stable and efficient operation of the turbine. The commercial software ANSYS CFX 160 was used to calculate the threedimensional steady flow in the full flow channel of a hydraulic turbine model machine. Five guide vane distribution circle diameter schemes were proposed to be analyzed, aiming at obtaining the energy characteristics and internal flow fields of the turbine under different schemes. Then the best position of the active vane placement was determined, and the results showed that by appropriately increasing the circular diameter of the guide vane distribution, the lowpressure area at the suction surface of the blade could be improved, the maximum flow velocity around guide vanes could also be reduced, the flow angle at the inlet of the runner was more reasonable, and the hydraulic losses of the guide mechanism and the runner were decreased, and the turbine operating efficiency was improved. At low flow rates, D0/D1(guide vane distribution circle diameter/runner diameter) was increased by 0.031, and the turbine corresponding efficiency was increased by 5.28 percentage points, at designing flow rate or high ones, the influence of change of guide vane distribution on the turbine efficiency was smaller than that at low flow rates. Compared with the different circle diameter schemes of guide vane, the difference between the highest efficiency and the lowest efficiency were 0.17% under the design condition and 0.48% at the high flow one, respectively. Therefore, changing the distribution circle diameter of the guide vane within a certain range had the engineering practicability in the capacityincreasing projects of the waterpower station units, which can be applied in optimizing the Francis turbine.

Abstract:In order to improve the hydraulic design of flowingpassed components of the jet centrifugal pump (JCP), the performance of rotorstator interaction on the hydraulic performance and its acoustic response characteristics of the pump were optimized. The multiobjective optimization design of rotor and stator matching was carried out by orthogonal experiment and computational fluid dynamics/computational fluid acoustic (CFD/CFA) technology. Some relevant geometric parameters of impeller and positive guide vane of JCP were considered in the test design. The effects of water head, efficiency of JCP and hydrodynamic noise in the rotors and stators were analyzed according to the impeller blade number, impeller blade profile, guide vane blade number, guide vane blade profile and clearance of rotor and stator. Multiobjective optimization scheme was determined by matrix analysis method, the optimal matching combinations of rotor and stator cascades were obtained. The results showed that under the rated conditions, after optimization, the water head remains unchanged, hydraulic efficiency was increased by 0.5 perantage points, and the overall noise in the rotor and stator cascades was decreased significantly, the impellerinduced noise was decreased by 7.1% and the guide vaneinduced noise was increased by 2.2%. It was verified that determining multiindex optimization scheme by weight matrix analysis method was feasible. The key of the design of low noise JCP was to determine the clearance between stator and rotor as well as the blades number of stator and rotor. Different matching schemes of rotor and stator cascades were more sensitive to the water head of JCP than to its efficiency, and more sensitive to the guide vane induced noise than to impeller induced noise，at the same time, the unsteady flow in guide vane influenced by rotorstator interaction was more obvious than that of the impeller. Dipole source noise was caused by pressure pulsation on the flowingpassed wall. The frequency spectrum characteristics of guide vane induced noise are basically the same as that of pressure fluctuation, but the frequency spectrum characteristics of impeller induced noise are obviously different from that of pressure fluctuation.

Abstract:Aiming to investigate the formation mechanism of highspeed water ring in the vaneless region and the effect on the stable operation of the unit under the runaway condition, the pumpturbine of one certain pumped storage power station was employed. Based on realizable k-ε turbulent model, the unsteady flow of the whole passage of pumpturbine was calculated. Some parameters such as the speed of the highspeed water ring were studied in bladeless zone. And comparing the numerical simulation results with the test, the results showed that there was an intrinsic connection between the Sshaped curve of the pump turbine and the stability of runaway operating. The value of fluid velocity in the bladeless zone was larger under the runaway condition. Highspeed water ring in the bladeless zone under runaway conditions led to instability of running under the runaway condition, the highspeed water ring became more obvious with the decrease of the opening. Under small flow conditions, due to the large angle of attack between the incoming flow direction and the blade bone line, the vortex structure of the runner blade ends was regularly developed, and the angle of attack was increased with the flow variation. Vortex evolution was random and vortex evolution affected the change of blade angle of attack. The angle of attack varied greatly over time and there was great randomness. Highspeed water rings were responsible for this random fluctuation.

Abstract:In order to adapt to the influence of production regulation on turbine performance in chemical process industry, it is required that the head of pump as turbine changes little with the flow rate, which makes the head-flow curve relatively flat. On the premise of conservation of velocity moment in volute of pump as turbine, the relationship between the theoretical head, the flow rate and the geometric parameters of the turbine was derived. The four main geometric parameters affecting the slope of the headflow curve were obtained by studying the relationship: wrap angle of volute, blade outlet angle, blade outlet edge and blade number. A low specific speed pump was selected as the research object for pump as turbine. Thirteen research schemes were determined by changing the geometric parameters of pump as turbine. The wrap angle of volute, blade outlet angle, blade outlet edge and blade number were changed in thirteen research schemes and simulated and tested by ANSYS-Fluent software. The results showed that the head-flow curve became flat with the decrease of wrap angle of volute and the increase of blade outlet angle within a certain range, and the optimal blade outlet position and blade number made the head-flow curve more flat. The influence of wrap angle of volute on the slope of head flow curve was remarkable.

Abstract:In order to study the solid-liquid twophase flow field and the hydrotransport characteristics of variable concentration in vortex pump, the basic principle and characteristics of solid-liquid twophase flow in vortex pump were summarized analytically and the characteristics of solid-liquid two phase flow were discussed based on the following aspects: energy exchange between solid and liquid, the round flow of particles and the interference between particles. The performance test of clean water and rapeseed volume fraction of CV=6% and CV=10% hydrotransport were conducted on a selfbuilt vortex pump (32WB8-12). Through the experiments, performance curves, such as qv-H, qv-P, qv-η and qv-NPSHc, were obtained. Based on the mixture multiphase flow model and the modified k-ε twoequation turbulent model, the interior twophase flow field of rapeseed liquid hydrotransport under the clear water optimal condition flow qv=9.31m3/h was numerically simulated by using SIMPLE algorithm. The pressure, velocity and sandy volume fraction, distributed on three cross sections of the vortex pump, were obtained through the numerical modeling. Meanwhile, the simulation results also showed that the rapeseed particles were mainly gathered at axial vortex center in the impeller and the annular district confront impeller in the chamber as well as around the blade inlet, and the accuracy of the numerical simulation results was verified by comparing between simulation and experiment. By comprehensive analysis, the relationship between performance and parameters of the internal flow was explained, the variable concentration similar conversion of NPSH and improvement measures for optimizing the design of the twophase flow pump were proposed.

Abstract:Citrus detection and location is the foundation of citrus automated picking systems, in light of the outdoor natural picking environment, a citrus visual feature recognition model was designed based on deep convolution neural network with good robustness for typical interfering factors, such as illumination change, uneven brightness, similar foreground and background, mutual occlusion of fruit, branches and leaves, shadow coverage and so on. The model included a deep convolutional network structure which can steadily extract the visual features of citrus under natural environment, a deep pool structure which can extract highlevel semantic features to get citrus feature map, a citrus location prediction model based on nonmaximum suppression method. Moreover, the proposed model was trained by transfer learning method. Each raw image was segmented into several subimages before citrus detection to enhance the ability of multiscale object detection, and reduce the computing time of citrus detection. A testing dataset, which contained representative interference factors of natural environment, was used to test the citrus detection model, and the proposed detection model had good robustness and realtime performance. The average detection accuracy and the average loss value of the model was 86.6% and 7.7, respectively, meanwhile, the average computing time for detecting citrus from single image was 80ms. The citrus detecting model constructed by deep convolution neural network was suitable for the citrus harvesting in the natural environment.

Abstract:Plant pest and disease is one of the three major natural disasters. Pest identification tends to consume a lot of labor, and it is difficult for naked eyes to quickly and accurately identify pest species. However, there still exist some drawbacks in the traditional deep learning algorithms for pest recognition, such as gradient explosion or gradient disappearance in deep neural networks, degradation and overfitting caused by limited sample size. In order to address these problems and improve the accuracy of pest recognition, a pest image recognition method based on improved residual network was proposed. Firstly, the pest images in the data set were converted to grayscale before edge detection was performed on them by using Richedge. To obtain a finelined pest image, the Richedge was combined with median filtering, Sobel operator and Canny operator to detect the edges of the pest images. Among them, the median filter effectively eliminated the salt and pepper noise, the Sobel operator accurately detected the position information, and the Canny operator detected the weak edge. The images after edge detection were quantized to be 224pixel×224pixel for training and classification. Then the obtained pest image set was used to train the deep neural network, which was a variant of standard residual network with additional convolution layers and channels for extracting more image features. And the dropout layer was added to each residual block of the network to prevent overfitting when it was trained on a relatively small data set. Besides, the regularization hyper parameters of the network were designed to be optimized by Bayesian method which adaptively adjusted the size of the hyper parameters with the adjustment of weights during network training. The weights of the proposed network were optimized through the Blockcg algorithm. In the optimization algorithm, the block diagonal was used to approximate the curvature matrix, which improved the convergence of the Hessian matrix; and independent conjugate gradient update was conducted for each subblock, which divided the whole issue into certain number of subproblems and reduced the complexity of local search. Eventually the values of the weights were not updated until an ideal pest classification accuracy rate was obtained. To verify the validity and robustness of the proposed method, an image data set of 38 common garden pests in north of China was collected and experiments were carried out on this data set. Experimental results empirically demonstrated that compared with the three traditional pest recognition methods for the same data set, the proposed method could make the recognition accuracy increase by 9.6 percentage points on average and the weighted average score increase by 16.3 percentage points, 10.8 percentage points and 4.5 percentage points, respectively.

Abstract:Realizing the accurate detection of moving cows in complex farming environment is the basis for behavioral perception of cows such as lameness detection and estrus behavior analysis. Aiming to solve the defects of the existing methods using parametric model to achieve the target detection of moving cows, a background modeling method based on nonparametric kernel density estimation was proposed. The probability model of the pixel was estimated according to the historical sample of each pixel, which had the disadvantage of high complexity caused by the redundant information contained in the historical sample information. The key frame detection technique was adopted to eliminate the redundant information in the sample to reduce the complexity of the algorithm and the ability to acquire the remote frame image information by the kernel function under small samples to improve the detection accuracy. In view of the lack of detected target contours, the threeframe difference method was applied to further achieve a more complete extraction of moving targets. In order to verify the effectiveness of the proposed method, the video samples of moving cows under different environments and disturbances were tested and compared with the Gaussian mixture model and the Kernel density estimation model. The experimental results showed that the average detection rate of the proposed algorithm was 95.65%, which was 15.56 percentage points higher than that of the Gaussian mixture model and 10.56 percentage points higher than that of the Kernel density estimation model. It also showed that the research algorithm had greater improvement than the Gaussian mixture model and the Kernel density estimation model in complex environments such as sunny, rainy and night time. In addition, the average realtime indicator of the algorithm was 1.11, which can basically realize the realtime and accurate detection of moving cow targets. The results were of great significance for the prevention and diagnosis of dairy cows disease and the accurate perception of cows movement behaviors.

Abstract:In order to obtain the shape parameters of growing fruit and monitor the fruit development status, an apple point index estimation method based on local point cloud was proposed. The method could estimate the shape index parameters such as volume, height and diameter of apple through apple local point cloud data. Firstly, the geometric model of apple was constructed by using the method of ellipsoidal surface equation, and the height, diameter and volume of apple geometric model were calculated. Kinect V2 was used to get point cloud data from any angle. Secondly, the passthrough filtering method was used to remove the background of point cloud data and the bounding box reduction algorithm was used to streamline the point cloud, and then the apple’s local point cloud was obtained. After that, the genetic algorithm was used to solve the optimal apple geometric model parameters. Finally, the height, diameter and volume of apple optimal matching model were used to estimate the shape index parameters of matching apple. The experiment collected local point cloud data of 250 apples at three different angles, namely the top, side and bottom of apple. Using this method, the shape indicators of 250 apples were estimated under these three angles. A linear regression method was used to analyze the linear correlation between the estimated value and the true value. The linear regression fit of each indicator was higher than 0.7. Among them, when the angle was the side of the apple, the linear regression fitting effect was the best, and the R2 was up to 0.948. And the average error of the apple volume estimation results under angles was no more than 16.16mL, the average error of the height estimation result was no more than 2.92mm, the average error of the diameter estimation result was no more than 2.35mm, and the average error was within the allowable error range. The experimental results showed that the method was stable and practical. 

Abstract:The reasonable structure of fruit tree canopy is beneficial to the effective distribution of illumination, which has vital significance to enhance the fruit yield and quality. At present, it is difficult to obtain illumination intensity data in the canopy of fruit trees, and the prediction accuracy is low. In order to study inner canopy illumination distribution, a random forest prediction model was proposed based on canopy profile shadow feature and point cloud color feature. The detailed research methods were shown as follows. Firstly, the spindle “Shanfu 6” apple tree was chosen as the research object and Kinect 2.0 was used to acquire double face point cloud data of tree, and then the complete data was obtained with preprocess. Secondly, the improved space colonization algorithm with growth angle constraint and phyllotaxis adding rules were used to rebuild apple tree 3D model. Finally, the “slice method” was used to cut canopy model every 0.1m in the vertical direction, and then the POV-Ray renderer was used to render shadows layer after layer, meanwhile, light meter was used to obtain illumination intensity data every 0.1m from top to bottom consistently, and the random forest network that with input data of color feature of every layer and output data of relative illumination intensity was built as the apple tree canopy illumination distribution prediction model. The experiment results showed that the proposed method can predict the illumination distribution accurately. The determination coefficient R2 between true value and predicted value was 0.864, and MAPE was 0.236. Random forest regression model can be used as an efficient method for prediction of canopy illumination distribution, and it can provide reference for fruit tree pruning and plastic research.

Abstract:Computer vision technology is widely applied in fish individual identification. Nevertheless, there are some problems such as small fish targets, occlusion of objects and light interference in videos and images. Some fish identification methods based on color, shape and texture also exit complicated calculations in feature extraction, such as nonmigration of features will result in low recognition accuracy and poor classification. With the help of analysis of image feature extraction of the existing VGG16 convolutional neural network model, the FTVGG16 convolutional neural network (Finetuning VGG16 convolutional neural network) was designed. As it was known, the basic deep learning tool used in this work was convolutional neural networks. The FTVGG16 convolutional neural network was composed of convolutional layers, batch normalization layers, pooling layers, Dropout layers, fully connected layers and softmax layers. The experimental results showed that the average recognition accuracy of the FTVGG16 model for fish was about 97.66%, and the average recognition rate of some fishes could reach 99.43%. It had high recognition accuracy and robustness in pictures with small fish targets and strong background interference. It could be operated through an appropriate, easytouse, and userfriendly web application for the specific case of fish identification.

Abstract:In order to accurately and rapidly obtain the vegetation coverage information of summer corn during the stages of fourleaf, jointing, heading and flowering, unmanned aerial vehicles (UAV) was used to obtain visible light images of corn field, and various vegetation indices extracted from visible light bands were analyzed and compared. Visibleband difference vegetation index (VDVI), excess green (EXG) and normalized greenblue difference index (NGBDI) were used to extract the corn vegetation coverage information of the four stages combined with supervised classification method. In the research process, targets in a single image of the experimental field were divided into soil and corn vegetation in the four stages of the corn. The VDVI pixel histograms of soil and corn classified by supervised classification method were counted respectively, and the intersection points of pixel histogram were used as the threshold of vegetation coverage extraction. Similarly, the threshold of corn vegetation coverage extraction corresponding to EXG and NGBDI was obtained. Finally, the corn vegetation coverage of the four stages was extracted by the three extraction thresholds. The errors of vegetation coverage extraction corresponding to the four growth stages of VDVI were 1.21%, 4.88%, 2.31% and 3.61%, respectively; EXG were 1.38%, 1.25%, 0.89% and 0.33%, respectively; and NGBDI were 1.61%, 3.31%, 1.99% and 3.25%, respectively. It was found that EXG had the best effect on vegetation coverage extraction during the four stages of corn. The value of threshold determined by the single image of the four corn growth stages was used as a fixed threshold, and the vegetation coverage was extracted from the panoramic image of the experimental field that had removed the single image which was used as determining threshold value, and the extraction effect was verified. The results showed that the variation of extraction error was small, indicating that the method using the supervised classification combined with the statistical histogram of visible vegetation index to determine the threshold value was better.

Abstract:In order to accurately and quickly grasp the growth information of maize in the growth cycle, different digital orthophoto maps（DOM）and digital surface model （DSM） in the four stages of the nutritional growth stage of maize were obtained by unmanned aerial vehicle（UAV）. K-means, genetic neural network and skeleton algorithm were used to extract the maize areas in the DOM, generate masks, and combined with DSM sets to obtain the height information of maize. Compared with the field measurement of plant height, the R2 of three methods were 0.853, 0.877 and 0.923, respectively, RMSE were 15.886cm, 14.519cm and 11.493cm, respectively, MAE were 13.743cm, 11.884cm and 8.927cm, respectively. The results showed that combining DOM and DSM can better extract the height value of maize in the nutritional growth stage. Compared with K-means and genetic neural network, the maize height extracted by the skeleton algorithm was highly consistent with the field measurement (R2 was 0.923, RMSE was 11.493cm, MAE was 8.927cm), and the extraction accuracy was high. Skeleton extraction combining DOM and DSM provided a way to extract plant height, which can be used as a reference for monitoring maize height by UAV remote sensing.

Abstract:Aiming to obtain the leaf area index (LAI) of largescale summer maize in a highefficiency, nondestructive and largescale manner, and provide a technical reference for remote sensing monitoring of summer maize growth. The research was based on the fieldcollected summer maize LAI and maize height, as well as combined with multispectral data of the same period, eight vegetation indexes and height with strong correlation with summer maize LAI were selected as the input variables of gradient boosting decision tree (GBDT) algorithm model for LAI inversion. The support vector machine (SVM) model and the random forest (RF) model were taken as the reference models, which were used to compare the accuracy of prediction. The results showed that the GBDT algorithm model prediction consequence were better than the other two models among the three sample groups. R2 of prediction value and measured LAI values of the sample groups 1, 2 and 3 were 0.5710, 0.7558 and 0.6441, respectively, which were higher than those of the SVM models (0.5472, 0.6791, 0.6168) and RF models (0.5505, 0.6973, 0.6295), corresponding root mean square error (RMSE) values were 0.0027, 0.0015 and 0.0016, which were lower than those of the SVM model (0.2117, 0.1523 and 0.1597) and RF model (0.2447, 0.2147 and 0.2080). The research result provided a technical method for fast and accurate monitoring of summer maize LAI remote sensing in the field.

Abstract:The designation of basic farmland reserves is a strategic requirement for the sustainable development of agriculture of the Chinese government, and it is also a foundation for ensuring national food security and social stability. The quality of cultivated land is an important evidence for the site of protected area, from the perspective of crops themselves, the quality evaluation system should not only consider external factors, but also take internal factors of crops into account. The absorption and utilization results of external conditions of crops in time series were regarded as innovative indicators to break through the traditional evaluation model, therefore, taking Jiayu County, Hubei Province as an example, vegetation index information was introduced to improve the comprehensive quality evaluation system of cultivated land, and then the weight of each evaluation index was calculated by means of analytic network process (ANP). Then local spatial autocorrelation analysis was used, and comparative analysis of the results between the quality of cultivated land and the Moran’s index in pixel scale was processed. The result showed that the overall quality of cultivated land in Jiayu County was good and it showed a strong positive correlation in spatial distribution, the local indicators of spatial association (LISA) of the whole county and cultivated land were 0.8645 and 0.9916, respectively. Besides, both results of demarcation based on pixel gave priority to the HH type (highhigh), 99.97% of pixels were classified as basic farmland. Finally, the former was superior in terms of comprehensive quality, while the latter had good effect on narrow area of the hilly region. The comprehensive quality evaluation system of cultivated land was improved by introducing the information of crops themselves in the pixel scale, which provided a useful reference for the fine delineation of basic farmland.

Abstract:Aiming to analyze the responses of urban greenland’s net ecosystem exchange (NEE) to the climatic controls and provide theoretical and technical support for carbon cycle simulation between land and atmosphere. In growing season, halfhourly daytime NEE based on eddy covariance flux data collected from 2013 to 2016 were simulated by XGBoost and back propagation artificial neural network (ANN) model. Moreover, the accuracy of model was evaluated by using the coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE) and index of agreement (IA). The experimental results showed that ANN model presented that seven input variables (photosynthetically active radiation (PAR), vapor pressure deficit (VPD), air temperature (Ta), relative humidity (RH), soil temperature (Ts), wind speed (WS) and volumetric water content at 10cm depth) performed best, yielding R2 of 0.712, RMSE of 4.394μmol/(m2·s), MAE of 3.129μmol/(m2·s) and IA of 0.911 on train dataset, and R2 of 0.748, RMSE of 4.253μmol/(m2·s), MAE of 2.971μmol/(m2·s) and IA of 0.920 on test dataset. After considering the function and interaction among the factors, the importance score of each environmental factor was decreased in the following order: PAR, VPD, Ta, RH, Ts, WS and VWC10, otherwise Ts would be more important than RH. In particularly, after calculating the numerical partial derivatives of main climatic controls for each halfhourly point, the numerical partial derivatives of PAR showed the ecosystem quantum yield with the value of 0.087, and it also indicated that PAR was no longer a main impact factor when value was greater than 1200μmol/(m2·s). Besides, the numerical partial derivatives of VPD expressed that VPD could mainly inhibit the photosynthesis, and the higher VPD aggravated the inhibition of photosynthesis by affecting photosynthetic rate. Furthermore, the numerical partial derivatives of Ta demonstrated that the photosynthetic rate was increased bit by bit and made the photosynthetic rate overpass respiration rate gradually. According to the result, PAR, VPD and Ta played an important role in controlling the NEE of urban greenland ecosystem. Also, XGBoost and ANN could be capable in capturing NEE dynamics and simulating the NEE with high accuracy. Meanwhile, the present result provided instant insight in underlying ecosystem physiology.

Abstract:Distribution maps of ET0 during rice growth season, day of growth period (DGP), crop water requirement (ETc), effective precipitation (Pe), coupling degree of ETc and Pe, and their climatic tendencies during 1970s, 1990s and 2010s were calculated and drawn by Penman-Monteith method and Arcmap spatial analysis based on daily meteorological data in 1960—2015 of 26 meteorological stations and crop coefficient of 29 rice irrigation experimental stations in Heilongjiang Province. The result showed that the average ET0 during rice growth season was 620mm, it was decreased firstly, and then increased from west to east, the decrease of wind speed, humidity, sunshine hours and the increase of temperature led to the decrease of ET0 at a climatic tendency of -3.90mm/(10a). The average DGP was 115d, and it showed an increase trend from north to south, the increase of temperature caused DGP to increase at a climatic tendency of 2.68d/(10a). The average Pe in rice growth period was 297.03mm, which was increased firstly and then decreased from west to east, the increase of DGP compensated for the decrease of rainfall, and the Pe was increased at an average climatic tendency of 0.62mm/(10a). The average ETc was 490.52mm, which was decreased firstly and then increased from west to east, the increase of DGP compensated for the effect of ET0 on ETc, and the ETc was increased at an average climatic tendency of 6.66mm/(10a). The average coupling degree of ETc and Pe was 064, which was increased firstly and then decreased from west to east, the increase of ETc was larger than that of Pe, 〖JP3〗which made the coupling degree of ETc and Pe decrease at an average climatic tendency of -0.009/(10a). The research result provided a basis for rational allocation of irrigation water resources and rice variety layout in Heilongjiang Province.

Abstract:The main purpose was to explore the spatialtemporal changes of farmland in Luntai Artificial Oasis in Dina River Watershed, aiming to provide basic data and theoretical basis for the spatial planning and management of artificial oasis in small watershed. The land use information of farmland was extracted from the remote sensing images（obtained in August 1992, August 1998, September 2007 and August 2018）and unmanned aerial vehicle data（obtained in July and August 2018 in the field survey）by means of visual interpretation supported by RS and GIS, and analyzed via mathematical statistic, dynamic degree, transfer matrix and gravity center model. Results showed that the area of farmland in Luntai Artificial Oasis was increased from 8381hm2 in 1992 to 46284hm2 in 2018. In 1992, totally 40.18% of artificial oasis was occupied by farmland, which was decreased to 37.04% in 1998, and then followed by a long time increase to 71.28% in 2018. In 1992, totally 1.61% of watershed area was occupied by farmland, which was increased to 8.91% in 2018. The area of farmland in Luntai Artificial Oasis was developed rapidly and experienced three stages: the stage of moderate increase（1992—1998）which was driven by reclamation policy launched by local government with annual average growth rate of 2.28%; the stage of rapid increase （1998—2007）which was influenced by both the cotton industry and reclamation policy with annual average growth rate of 16.85%; and the stage of moderate increase（2007—2018）which was only influenced by cotton industry with annual average growth rate of 846%. In the past 26 years, the land that was transferred into farmland（41545hm2）was far more than the land that was transferred out（3441hm2）. The land outside artificial oasis（35179hm2）was the main source supporting the extension of farmland. The land that transferred out of farmland was mainly into the forestry and fruit industry（2671hm2）. The gravity centers of farmland was gradually moved in the direction of sandy desert because the exploration and maintenance cost of sandy desert was lower than that of Gobi desert, and the cotton which was the most popular crop in Luntai Artificial Oasis had adapted to the atmosphere of the oasissandy desert transition zone in Dina River Watershed.

Abstract:In order to investigate the variation characteristics of soil nutrients of cultivated land in different elevation fields, a typical south hilly area—Ganzhou City of Jiangxi Province was selected as research case. Based on the data of totally 2928 soil nutrient samples collected in the topsoil layer (0~20cm) of the farmlands at different altitudes in 2012—2013, classical statistical analysis, variance analysis and coKriging method were employed to analyze the spatial coupling relation between soil nutrients of cultivated land and different elevations. The result showed that the correlation relationship between soil organic matter (SOM), total nitrogen (TN), total potassium (TK) and elevation were overwhelmingly positive. Meanwhile, there was a remarkable negative correlation between total phosphorus (TP), available phosphorus (AP) and elevation. However, altitude was irrelevant to available potassium (AK). According to the variance analysis of soil nutrients, the content of SOM and TN was increased with the rise of elevation when the elevation was below 250m. But the changes of soil nutrient content became inapparent above 250m. The spatial distribution map showed clearly that high value area was mainly distributed in area of high elevation around the research area. On the other side, the content of TP and AP was decreased with the rise of elevation when the elevation was below 200m. High value area was mainly distributed in area of middle and low elevation around the research area according to the spatial distribution map. Likewise, the changes of soil nutrient content were not significant above 200m. TK content was increased with elevation, however, the content of AK was fluctuated greatly. Yet their pattern was inapparent. The spatial variation of soil nutrients was due to the interaction of parent materials, soil types, land use patterns and soil erosion at different elevations. The research results could help to find out the vertical changing law of soil nutrients at different elevations, which was of great significance for ensuring grain security of China. 

Abstract:Multistage irrigation pumping system is often faced with these typic problems of scarce water resource, high lift of water pumping, coexistence of different irrigation methods, difficult allocation of water, high cost of operation etc. It is significant to optimize the water regulation to alleviate above problems. A typical multistage irrigation pumping system (Guhai irrigation system) in Ningxia Hui Autonomous Region was taken as a case study area, and a regional multiobjective optimization model was developed with a twolevel hierarchical structure for optimal regulation of irrigation water. Water requirement and energy consumption were taken as two objectives in the model so as to consider the operations of pumping stations. Meanwhile, different irrigation periods were considered to obtain detailed schedules for water allocation and operation. Based on the decompositionharmonization method for large system, a twolevel structure was constructed to better describe the characteristics of multilevel and interrelated relationship, complicated structures and multiple impact factors. The first level dealt with the optimal allocation of irrigation water supply among various crops in each pumping station. The second level sought out the optimal schemes of pumping and allocating water among multistage pumping stations. Each level was solved independently, while they were coordinated through taking water supply amount as coordinating variables. Based on the optimization model, optimal schemes for water allocation and pumping station operation were presented for all stages of pumping stations under approved amount of water resources in the study area. Results indicated that the total water shortage amount was significantly 〖JP3〗reduced from 5.77×10 6m3 to 1.30×10 4m3 in the whole system, and it was reduced from -3.22×106~2.47×106m3 to -8.30×104~9.50×104m3 among each pumping station. The spatialtemporal contradictions of water supply among multistage pumping stations were effectively alleviated through the optimization of water supply. The research provided an effective and practicable tool to optimize the regional water allocation for complex multistage pumping irrigation system, and the model can be further practiced for actual water management.

Abstract:In order to reveal relationship between temporal stability of soil water and corn ear weight under straw returning in black soil region, based on soil water content measured with TDR during June and September 2017 and corn ear weight measured with weighing method, the temporal stability of soil water under straw returning was firstly determined, and then the relationship between temporal stability of soil water and corn ear weight at the single scale and multiscale was quantitatively analyzed. The results showed that the temporal stability of soil water was increased with the increase of soil depth, and the sampling points in deeper soil layer (40～60cm and 60～80cm) which had higher soil water content had higher temporal stability; as soil depth changed, representative points of soil water under different situations were not identical, and the lowest, highest and average soil water contents for studied area could be determined with representative points of soil water content which could provide scientific guidance for estimation and regulation of soil water; the changing trend of correlation degree between temporal stability of soil water and grain weight per ear and axis weight per ear at multiscale was different from the one at the single scale, correlation degree between temporal stability of soil water in most soil layers and grain weight per ear and axis weight per ear at multiscale was more than the one at the single scale, and relationship between temporal stability of soil water and corn ear weight could be determined further with multiscale correlation analysis, which could provide theory basis for deeply revealing the influence of soil water on crop yield. Research results could provide theoretical foundation and guidance to estimate and manage soil water and increase crop yield.

Abstract:The effects of soil moisture content, dry mass accumulation and soil moisture content of capillary head, middle and tail of drip irrigation belt on crop yield under six different head pressures were investigated by laying 50m long drip irrigation belt. The results showed that the variation of average soil moisture content during the growth period was different due to the difference of drip irrigation zone type. The variation law of soil moisture content of N030 showed obvious trend of decreasing at first and then rising, and with the increase of dripper flow, the soil moisture content of N030 was increased. The change of soil moisture content was smooth in the whole growth period. The changing trend of L015 soil moisture content was smooth, and with the increase of dripper flow, the soil moisture content was changed more significantly in the whole growing period. Under the condition of L015, the soil moisture content in the whole growing period can meet the needs of crop growth, and it can provide sufficient water for crops. The lower the flow velocity and the longer the length were, the more the fertilizer was attached to the belt wall, the lower the fertilizer utilization efficiency of the tail crop was, and the less the nutrient absorption was, the lower the crop yield was. The yield uniformity of the head, middle and tail of capillary tube under different treatments was analyzed. It was found that with the increase of length of drip irrigation belt, the uniformity of crop yield of N030 was decreased gradually, and the uniformity of crop yield was increased at L015. Therefore, different drip discharges had certain effect on the yield uniformity along the length of drip irrigation belt.

Abstract:Hetao Irrigation District (HID) is a main grain production region in China, but it is characterized by less rainfall. Water shortage, soil salinization and excessive application of chemical fertilizers are main important factors that restricting the food and environmental safety in HID. Reasonable and efficient utilization of water and fertilizer resources on saline soil to improve crop production efficiency and reduce nonpoint source pollution of nitrogen are the effective ways to relieve the problem. Referring to the local conventional irrigation (300mm) and nitrogen amount (345kg/hm2) in HID, a field interactive experiment with three irrigation amounts and three nitrogen amounts was carried out in three salinization farmlands (S1, 0.247dS/m; S2, 0.839dS/m; S3, 1.286dS/m) respectively. Three irrigation amounts were 150mm, 225mm and 300mm, which was marked as W1, W2, and W3, respectively, and three nitrogen amounts were 172.5kg/hm2, 258.8kg/hm2 and 345kg/hm2, marking as N1, N2 and N3, respectively. The coupling model of water and nitrogen for maize with border irrigation under three saline soils was established and optimized, and the field experiment combined with model simulation was used to explore the response of maize yield to water and nitrogen regulation in different salinized soils, and provide scientific basis for reasonable irrigation and nitrogen management. Main conclusions were as follows: the maize yields were significantly affected by irrigation in S1, S2 and S3 soils. The yield of maize was increased firstly and then decreased with the increase of irrigation volume in S1, S2 and S3 soils. In addition, maize yields were significantly affected by nitrogen rate in S1, S2 and S3 soils （P<0.05). The yield of S1 and S2 soils was increased firstly and then decreased with the increase of nitrogen rate, but it was decreased gradually as a whole in S3 soils. With the increase of soil salinity, the interactive effect of water and nitrogen on yield was enhanced. Water and nitrogen interaction had insignificant effect on the yield （P>0.05) under S1 soil condition. Compared with W3N3 and W3N2 treatment, the yield of W2N2 was decreased by 441% and 656% （P>0.05), respectively. The maximum yield could be obtained only when the water was better and nitrogen was suitable, but the moderate reduction of irrigation and nitrogen application rate would not significantly reduce the yield in nonsaline land. The interaction effect of water and nitrogen significantly affected the yield of S2 （P<0.05), and the yield of W2N2 was significantly higher than that of the rest of treatments （P<0.05), and suitable water and nitrogen supplying were needed in middle saline soil. The yield was significantly affected by the interaction effect of water and nitrogen （P<001) in S3, and the yield of W2N1 was significantly higher than that of other treatments （P<005), and the higher yield could be obtained when suitable water and less nitrogen were supplied in heavily saline soil. Through the model optimization, the watersaving and nitrogencontrolling management for higher yield of maize in HID were as follows: nonsaline soil (irrigation amount of 25374~28626mm, nitrogen amount of 267.65~318.85kg/hm2), moderately saline soil (irrigation amount of 23325~26817mm, nitrogen amount of 225.22~272.56kg/hm2), heavily saline soil (irrigation amount of 19694~24306mm, nitrogen amount of 179.15~223.35kg/hm2).

Abstract:It is significant to take best agricultural measures and improve salinization to rapidly and accurately determinate the composition and content of soil salt. The hyperspectral integrated inversion model based on transformation of hyperspectral, characteristic bands, characteristic spectral indices screening and support vector machine (SVM) was established to improve the accuracy of watersoluble salt ions content by taking the saline soil of Yongji irrigation area of Hetao Irrigation District. The results showed that the correlation between the original spectral reflectance by pretreatment and watersoluble salt ions content was relatively low and the maximum correlation coefficient was 0.18, and the sequence of them from big to small was as follows: Ca2+, SO2-4, Mg2+, the content of salt, Na++K+ and Cl-. The optional transformation forms of salt content, Na++K+, Cl-, SO2-4, Ca2+ and Mg2+ were (1/R)″, (1/R)″, (lnR)′, (lnR)″, R′ and (lnR)″, respectively. The numbers of sensitive bands (P<0.01) were 41, 7, 9, 65, 76 and 28, respectively. Stepwise regression method was used to filtrate the characteristic bands from sensitive bands, and the average of determination coefficient (R2) and the average of root mean square error (RMSE) of each ion in the regression model based on the characteristic band were 0.35 and 0.87g/kg, of which R2 was the largest and the smallest were SO2-4 (0.52) and Ca2+ (0.20), respectively. Combined with the stepwise regression method, the characteristic bands were substituted into the spectral index to determine that there were three characteristic spectral indices for Mg2+, there were two characteristic spectral indices for salt content, and there were one characteristic spectral index for Na++K+, SO2-4 and Ca2+, respectively. The R2 of model for watersoluble salt ions content based on the characteristic bands and characteristic spectral indices was increased by 5867%, and the RMSE was decreased by 2460%, of which the maximum R2 was SO2-4 (0.74), RMSE was 0.47g/kg. 〖JP〗The model of SVM based on the characteristic bands and characteristic spectral indices combined had a significant improvement in the prediction than that merely based on the characteristic bands, for example, the average relative analysis error (RPD) was increased by 110.27%, the R2 was increased by 37.54% and the RMSE was decreased by 4012% in the training set, the R2 was increased by 5604% and the RMSE was decreased by 3939% in the verification set. The results showed that the RPD of SO2-4 reached 3000, which showed a good prediction ability. The model of salt content and Mg2+ had good quantitative prediction ability which can be used for assessment or correlation prediction, respectively. The SVM models of Na++K+ and Ca2+ had the ability to distinguish between high and low values. 

Abstract:Livestock and poultry manure may result in significant environmental challenges. Meanwhile, it is an advantageous raw material for the production of organic fertilizer due to the rich nutrients such as organic matter, nitrogen, phosphorus and potassium. Aerobic composting is an effective way to solve the livestock manure pollution problem and realize utilization of this valuable resource. However, composting is an extremely complex process of physical and chemical changes. Online detection tools of the key parameters are important for both composting process control and organic fertilizer quality assurance. Aiming to investigate the feasibility of online near infrared (NIR) spectrometer to conduct realtime analysis of moisture content (MC), pH value, electrical conductivity (EC), organic matter (OM), total carbon (TC), total nitrogen (TN) and carbon to nitrogen (C/N ratio) ratio in the whole composting process and evaluate its ability to accurately predict these changes. Totally 60 samples in the whole composting process were collected. The NIR quantitative analysis models of MC, pH value, EC, OM, TC, TN and C/N ratio were established by using the online NIR spectrometer combined with partial least square method. The research results showed that the online NIR spectrometer can realize the rapid detection of key parameters in the whole composting process (RSD<10%), with excellent predictions for MC and TN with R2C and RPD value of 0.94 and 3.62, 0.92 and 3.14, respectively, good predictions for pH value, TC and C/N ratio with R2C and RPD value of 0.90 and 1.89, 0.83 and 2.12, 0.82 and 215, respectively, approximate predictions for EC and OM with R2C and RPD value of 0.79 and 1.85, 0.80 and 1.93, respectively; the deviation between the NIRpredicted and measured values of each parameter was small, the NIR predictions were in good agreement with measured values as the composting process progressed. The above research results laid the foundation for realizing the process analysis of organic fertilizer production based on the online NIR spectroscopy. 

Abstract:Following the mechanism of seriesparallel reaction in CO2 absorption process, the intrinsic kinetic equation was established. A macroscopic kinetic equation of CO2 absorption reaction was established based on the theory of double membrane diffusion. Considering the noneideal solution, the concentration effect in the rate equation was corrected differently to obtain eight correction models. Through the orthogonal experiment design, the experimental factors were reaction temperature, initial concentration of potassium carbonate, reaction time and mixture of methane and carbon dioxide, and the level of each factor was 3. The experimental data were measured in a doubledrive reactor and the model parameters were estimated. The residual values of each model were calculated respectively. The models were contrasted by comparing the residual value sizes and distributions, and the model 4 was considered as the ideal with kinetic parameters as follows: apparent activation energy Eob was 1938394J/mol, apparent anterior factor k(0)ob was 3.0429×10-5mol/(m2·s·Pa). Through theoretical derivation based on these model parameters, the intrinsic kinetic equation of CO2 absorption by hot potash was obtained with following model parameters: the intrinsic reaction activation energy E was 5447kJ/mol, the anterior factor k0 was 3.2228×109m3/(mol〖DK〗·s). The conversion coefficient γ was calculated to be a value much greater than 2, which indicated that the CO2 absorption was a rapid reaction process that mainly happened in the membrane. 

Abstract:Aflatoxin B1 (AFB1) is the most toxic mycotoxin, which is classified as grade 1 carcinogens by the World Health Organization. A method for detection of AFB1 in moldy peanut was proposed by using lysinefunctionalized gold nanoparticles (Lys-AuNPs). AuNPs was synthesized by the citrate reduction method, of which the color was redwine. To obtain lysinefunctionalized AuNPs, lysine solution was added to the prepared AuNPs under stirring by magnetic stirrer. It was characterized by transmission electron microscope and UVvisible spectrophotometry. The detection of AFB1 was achieved through the competitive reaction mechanism between Hg2+, AFB1 and amino acids on lysine surface in the gold nanoparticles solution. As the concentration of AFB1 in Lys-AuNPs solution was increased, the color of the solution was changed from grey to red. UVvisible spectrums were measured to establish the relationship between the A725/A525 value of Lys-AuNPs solution and the concentration of AFB1. The results showed that there was a good linear relationship in the range of 1~50ng/mL, and the correlation coefficient was 0996. The detection limit of AFB1 was 0.2ng/mL and the recovery in peanut samples was 85%~110%. In addition, the concentration of AFB1 in peanut was confirmed by high performance liquid chromatography (HPLC). The method for detection of AFB1 in moldy peanuts had the advantages of quick simplicity, high sensitivity, and simple operation and so on, which can be applied to the rapid detection of aflatoxin B1 in moldy peanut and make the assay widely applicable.

Abstract:In order to detect the odor of salmon refrigerated at different refrigerating temperatures and identify its freshness more accurately, an electronic nose based on kernelbased machine learning model was designed. It consisted of five parts, which were the detection air chamber, the array of six gas sensors, the data acquisition module, the pattern recognition module and the display interface. Kernelbased machine learning model was selected as the pattern recognition method of the electronic nose, and support vector machine (SVM) was selected as the learning machine of kernelbased machine learning model. The odor fingerprint data of salmon samples respectively refrigerated at 0℃, 4℃ and 6℃ was collected to train and test the kernelbased machine learning models with different kernel functions and kernel parameters. Finally, a kernelbased machine learning model that had the best salmon freshness identification effect was determined. And it was determined that the polynomial function was taken in the kernel function, and the kernel parameters of q, γ and c were taken as 3, 15 and 0, respectively. Analysis of identification result of test set salmon samples was conducted, which showed that no days deviation correct rate was 57.14% and allowable deviation of 1 day correct rate was 92.86% at 0℃, no days deviation correct rate was 88.89% and allowable deviation of 1 day correct rate was 100% at 4℃, no days deviation correct rate was 75.00% and allowable deviation of 1 day correct rate was 100% at 6℃. It proved that the model had certain ability to identify the freshness of salmons refrigerated at different temperatures. Compared with the result of principal component analysis (PCA), the kernelbased machine learning model had a better ability.

Abstract:The structural scheme of hybrid electromagnetic actuator that integrates a tubular permanent magnet linear synchronous motor and a hydraulic damper was put forward to solve the problem that the linear electromagnetic actuator owned bad reliability. Modified skyhook control that matched the structure of hybrid electromagnetic actuator was used to optimize the performance parameters of hybrid electromagnetic actuator.Skyhook damping coefficient, passive damping coefficient and peak electromagnetic thrust force that linear motor needed to output were got. And the structural parameters of the hybrid electromagnetic actuator were optimized with the optimization goal of peak electromagnetic thrust force that linear motor needed to output. Finally, a prototype of the hybrid electromagnetic actuator was developed based on the optimized structural parameters and the bench tests on the prototype were conducted, including damping characteristics test of hybrid electromagnetic actuator prototype and active control test of hybrid electromagnetic suspension with hybrid electromagnetic actuator. Results showed that the designed hybrid electromagnetic actuator for the suspension systems could improve the vehicle dynamics performance. And in contrast to the passive suspension system, the body acceleration and suspension dynamic deflection of the hybrid electromagnetic suspension were decreased by 23.35% and 14.97%, respectively. Though the dynamic tire load was increased by 13.20%, it was in a reasonable range based on the principle of 3σ. And the effectiveness of the hybrid electromagnetic actuator prototype was verified. 

Abstract:In the structured operation environment, the application of warehouse automation equipment can greatly improve the operation efficiency. But in general, there is a lot of uncertainty in the warehouse. For example, the position and pose of the pallets in the warehouse have large uncertainty. Applying the RGB-D sensor and lidar sensor, the pallet pose and position can be estimated. After pallet recognition, forklift utilizing path planning technology can achieve picking up the pallet independently in dried fruit workspace, which improves the flexibility of the forklift. Taking the forklift with nonintegrity constraint characteristics as the research object, a pallet picking path planning method was proposed based on uniform cubic Bspline curve. Considering the multiple constraints in pallet picking process, such as minimum turning radius of the forklift, startpoint and endpoint constraints and the curvature continuity constraint, the objective function of path curvature minimization was established. The related curve parameters needed to be optimized were solved by the optimization toolbox in Matlab. The simulation results showed that for different pallet picking scenarios, the proposed method can obtain a feasible path with continuous curvature. The steering wheel angle of the planning path did not exceed the maximum of the forklift. In the warehouse, the path planning and tracking test were carried out. In the scenario where the driving distance was 6500mm, the lateral offset distance was 1500mm, and the angle offset was 15°, the results showed that at the end point of path, the transverse offset error of the path tracking was 4.71cm and the heading angle error was 9.6×10-3rad. The feasibility of the algorithm was verified, and it can be applied in similar large warehouse intelligent vehicles. The research can provide reference for the path planning of forklift in automated warehousing operation.

Abstract:Aiming at the problem that the control system of redundant driven parallel mechanism is not combined with dynamic modeling and the dynamic and static characteristics of servo valve are not considered in the design of the control system, a fifthorder transfer function model of electrohydraulic servo system was presented based on Lagrange equation of the second kind and hydrodynamics to model the mechanical and hydraulic systems of the moving platform and hydraulic system. The dominant energy optimal model was reduced to a three order model. Reducing order to more easily processed order was convenient for subsequent dynamic control. A H∞ robust control strategy based on TVC feedback optimization was proposed for the control object. It was further compared with TVC control and TVC-FAPID in step signal, linear sweep and actual broadspectrum. The comparison showed that the proposed TVC feedback effectively expanded the systems bandwidth and improved the damping ratio and natural frequency of the hydraulic system. So that H∞ robust controller can compensate the phase lag of high frequency signal. Therefore, the TVC-ROB improved the tracking performance of the highfrequency system obviously, and the displacement error percentage was only 1.26%. The H∞ control was introduced to improve the antidisturbance and antinoise performance of the system. In the high frequency section, the control energy loudness of TVC-ROB and TVC-FAPID strategies was much lower than that of TVC control, which tended to be stable. In the low frequency band, the parameters tuning of TVC control strategy was simple and easy to implement. So the TVC control strategy was often applied in engineering field. The research results had a strong guiding significance and reference value for the design of controller.

Abstract:A type of parallel drive bidirectional deflection platform was proposed. The platform was mainly composed of a base, a slider, a motor, a drive arch, a circular arc guide, a pin shaft, a moving platform, a driving gear and a support plate. The moving platform in the platform was supported by two driving arches which were crossstaggered and concentric in space, and respectively guided by semicircular guides, driven by motor fixed with base. The motor was driven to realize the largeangle deflection of the platform around the X and Y axes, and the degree of freedom of the platform was calculated by using the modified Kutzbach-Grnbler formula. A special motion pair was designed in the platform to make the movement of platform simple and easy to control. The inverse equations of the position and velocity of the platform were given. The motion relationship and coupling characteristics were analyzed. The dynamics model of the platform was established based on the Lagrange method by using the principle of virtual work. Then the dynamic simulation of the platform was performed by using ADAMS. The variation curve of the motor output torque under different external loads was obtained. The mechanical properties of the platform were analyzed and the coupling relationship with the kinematics conclusion was obtained. Finally, based on the established dynamic model, the theoretical calculations under the same conditions as the simulated external load state were made to the platform, and the theoretical calculation results were compared with the simulated values. The simulation values and theoretical calculations under different external loads were calculated. The deviation between values was small and almost equal.