基于X射线图像特征的核桃挤压破壳高露仁检测装置设计与试验

Design and Experiment of Walnut Compression Shell-breaking High-grade Kernels Detection Device Based on X-ray Image Features

摘要:

核桃破壳过程中高露仁的精准检测对优化破壳工艺具有重要意义,传统方法依赖人工检测,效率低且准确性不稳定。本文聚焦核仁结构变化,提出一种基于X射线图像的高露仁检测方法。搭建了集成力学加载控制和X射线成像的可旋转试验平台,通过设定加载速度与变形量阈值控制破壳,并利用旋转装置实现双视角成像;采用图像处理与YOLO v8n-seg-DN模型对核仁结构进行识别与分割,并提取最大核仁区域面积占比(Pmax)与相对核仁块数指数(RIkbc)两项图像特征;对图像特征与高露仁率进行相关性分析;采用岭回归方法建立图像特征与高露仁率之间的相关关系;通过三因素五水平中心复合设计试验,分析加载速度(10~50mm/min)、挤压变形量(5~9mm)、核桃等效直径对高露仁率的影响。结果表明:试验平台稳定可控,速度与变形量平均误差控制在5%以内;Pmax与高露仁率呈显著正相关(相关系数为0.931),RIkbc与高露仁率呈显著负相关(相关系数为-0.926),Pmax和RIkbc之间存在显著共线性(方差膨胀因子为13.067);模型验证集R2为0.92、RMSEp为8.89%、RPD为3.46,表现出较高的精度;加载速度、挤压变形量和核桃等效直径对高露仁率具有显著负向影响,且模型值与实测值的变化趋势总体一致,表明建立的模型能够有效替代传统的检测方法;在加载速度为10~30mm/min、挤压变形量为5~6mm、核桃等效直径为33~35mm时,高露仁率基本保持在70%以上,为核桃低损伤破壳工艺优化提供了一种新的技术路径。

Abstract:

The precise detection of high-grade kernels during walnut shell-breaking is significant for optimizing the shelling process. Traditional methods rely on manual inspection, which is inefficient and has unstable accuracy. Focusing on internal structural changes, an X-ray imaging-based method for detecting high-grade kernels was proposed. A rotating experimental platform integrating mechanical loading control and X-ray imaging was established. The shelling process was controlled by adjusting the loading speed and deformation threshold, and dual-view imaging was enabled via a rotating device. Then image processing and the YOLO v8n-seg-DN model were applied to detect and segment the kernels, and two image features were extracted from the segmented regions: the maximum kernel area proportion (Pmax) and the relative kernel block count index (RIkbc). Correlation analysis was performed between the image features and the proportion of high-grade kernels. Ridge regression was employed to predict the proportion of high-grade kernels from the extracted image features. A three-factor five-level central composite design experiment was conducted to evaluate the effects of loading speed (10 ~ 50 mm/ min), extrusion deformation (5 ~ 9 mm), and walnut equivalent diameter on high-grade kernel proportion. The results showed that the experimental platform was stable and controllable, with the average errors of loading speed and deformation within 5% . Pmax was significantly positively correlated with high-grade kernel proportion ( the correlation coefficient was 0. 931), RIkbc was significantly negatively correlated (the correlation coefficient was - 0. 926), and there was significant collinearity between Pmax and RIkbc (the VIF was 13. 067). The model validation set yielded R2 of 0. 92, RMSEp of 8. 89% , and RPD of 3. 46, indicating high accuracy. Loading speed, extrusion deformation, and walnut equivalent diameter all had significant negative effects on high-grade kernel proportion, and the predicted values closely matched the measured values, demonstrating that the developed model can effectively substitute traditional detection methods. When the loading speed was 10 ~ 30 mm/ min, the extrusion deformation was 5 ~ 6 mm, and the walnut equivalent diameter was 33 ~ 35 mm, the proportion of high-grade kernel remains above 70% , providing a technical approach for optimizing walnut low-damage shelling processes.