面向可靠性试验的拖拉机作业信息智能监测系统研究

Tractor Operation Information Intelligent Monitoring System for Reliability Testing

摘要:

针对拖拉机田间可靠性试验监测人力物力消耗大、数据易缺失、故障监测手段匮乏的问题，本文设计了一种用于拖拉机可靠性试验分析的作业信息智能监测系统。基于可靠性考核标准与评价体系，确定拖拉机组的关键监测参数及计算方法，设计包括传感器、数据采集终端等的监测系统硬件、基于LabVIEW编程语言和Windows 10 IoT软件实时操作系统的监测系统软件部分和远程监测平台。最终，开展台架、试验场和田间试验，结果表明：监测系统测取的拖拉机燃油消耗与实际值的拟合决定系数R2为0.9582，测取的发动机转速与实际值的最大误差为0.47%，测取的作业面积与实际面积最大误差为3.10%，满足可靠性试验分析的精度需求；75h田间试验表明，拖拉机的高负荷作业时间为54.56h，累计燃油消耗量为512.96kg，作业面积为57.75hm2，平均小时油耗为6.83kg/h，平均单位工作量油耗为8.88kg/hm2，平均生产率达0.77hm2/h，田间作业平均负荷系数为58%，监测系统工作稳定性与可靠性较高。此外，通过该监测系统发现了1次驾驶员无法发现的故障。本文研发的监测系统可为拖拉机可靠性试验分析与验证提供有效的技术手段。

Abstract:

Aiming to address the issues of significant resource consumption, data loss, and limited fault monitoring capabilities in field reliability testing of tractors, an intelligent tractor operation information monitoring system for reliability test analysis was developed. Based on reliability assessment standards and evaluation systems, the key parameters and calculation methods required for monitoring tractor unit reliability were determined, the hardware design of the tractor operation information monitoring system was developed, including components such as sensors and a data acquisition terminal. The software component and remote monitoring platform of the system were designed by using LabVIEW and the Windows 10 IoT system. Bench test, test track trials, and field tests were carried out, and the results showed that the monitoring system achieved an R2 of 0.9582 for measured tractor fuel consumption compared with actual values, with a maximum error of 0.47% for measured engine speed and a maximum error of only 3.1% for measured operation area compared with actual area, meeting the accuracy requirements for reliability test analysis. During a 75-hour field test, the developed system reliably monitored tractor operation reliability information. Specifically, the tractor’s high-load operation time was 54.56h, cumulative fuel consumption was 512.96kg, operation area was 57.75hm2, average hourly fuel consumption was 6.83kg/h, average fuel consumption per unit workload was 8.88kg/hm2, average productivity was 0.77hm2/h, and the average field operation load coefficient was 58%. Additionally, the monitoring system identified one fault that was undetectable by the operator. The monitoring system developed can provide an effective technical tool for the analysis and validation of tractor reliability tests.