基于机器视觉的陈皮热泵干燥含水率预测模型研究

doi:10.13733/j.jcam.issn.2095-5553.2024.07.015

摘要/Abstract

摘要： 为定量预测陈皮热泵干燥过程中含水率的变化，基于机器视觉技术提取陈皮干燥过程中的图像特征，建立含水率预测模型。采集不同干燥时期的陈皮图像，采用图像处理的方法对陈皮图像进行预处理操作，提取陈皮图像的6个颜色特征和6个纹理特征共计12个图像特征，分析特征参数和含水率变化关系，将相关图像特征作为模型的输入，陈皮的含水率作为模型的输出，分别建立基于BP神经网络和支持向量机的陈皮干燥含水率预测模型进行对比分析，得到不同干燥时期含水率最佳预测模型。结果表明，支持向量机的预测效果更好，准确率达到99.01%，均方误差达到0.006 5，模型运行稳定，含水率预测结果准确且快速，能够为陈皮干燥过程中的含水率在线预测提供科学依据。

关键词: 陈皮, 热泵干燥, 机器视觉, 特征提取, 含水率预测, 支持向量机

Abstract: In order to quantitatively predict the change of moisture content in the drying process of tangerine peel heat pump, the image features in the drying process of tangerine peel were extracted based on image processing technology, and the moisture content prediction model was established. Tangerine peel images in different drying periods were collected, image processing was used to preprocess the tangerine peel images, and a total of 12 image features including 6 color features and 6 texture features were extracted. The relationship between feature parameters and moisture content changes was analyzed, the relevant image features were taken as the input of the model, and the moisture content of tangerine peel was taken as the output of the model. The prediction models of tangerine peel drying moisture content based on BP neural network and support vector machine were respectively established for comparative analysis, and the best prediction models of moisture content in different drying periods were obtained. The results show that the prediction effect of support vector machine is better, with an accuracy of 99.01% and a mean square error of 0.006 5. The model runs stably, and the prediction result of moisture content is accurate and fast, which can provide a scientific basis for the online prediction of moisture content in the drying process of tangerine peel.

Key words: dried tangerine peel, heat pump drying, machine vision, feature extraction, moisture content prediction, support vector machine

中图分类号:

TP391.41

王雷, 钟康生, 郭小宝, 盛斌, 肖波, 荆磊. 基于机器视觉的陈皮热泵干燥含水率预测模型研究[J]. 中国农机化学报, 2024, 45(7): 97-103.

Wang Lei, , Zhong Kangsheng, , Guo Xiaobao, Sheng Bin, Xiao Bo, Jing Lei. Research on prediction model of drying moisture content of tangerine peel heat pump based on machine vision[J]. Journal of Chinese Agricultural Mechanization, 2024, 45(7): 97-103.

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