农机化研究2025，Vol.47Issue(8)：119-129,11.DOI:10.13427/j.issn.1003-188X.2025.08.017
基于介电特性和BPNN建模的小麦含水率在线检测
Online Detection of Wheat Moisture Content Based on Dielectric Properties and BPNN Modeling
摘要
Abstract
In order to meet the needs of online detection of moisture content of wheat grain,an online detection sensor of wheat grain moisture content based on the dielectric characteristics of the same side circular arc capacitance was designed on the combined harvester.The effects of four factors(temperature,frequency,capacitance and bulk density)on mois-ture content detection of six different varieties of wheat were studied.The BP neural network method was used to establish a wheat moisture content prediction model based on the relationship between moisture content and four factors(tempera-ture,frequency,capacitance and bulk density).The determination coefficients(R2)of its training and testing sets were 0.896 and 0.893.The Root Mean Square Error(RMSE)were 1.317 and 1.342,indicating that the prediction model had strong stability and prediction ability.The results showed that the temperature,frequency and bulk density were intro-duced into the online wheat moisture content detection system of the capacitive method combined harvester,which can effectively improve the detection accuracy and repeatability of the overall system.The correlation analysis of the influen-cing factors of moisture content detection of different wheat varieties and the establishment and optimization of mathemati-cal models were carried out to improve the detection accuracy of wheat moisture content by capacitive method,and to pro-vide theoretical basis for the software and hardware design of capacitive sensor in wheat moisture content detection system of combined harvester.关键词
小麦含水率/在线检测/介电特性/BP神经网络Key words
wheat moisture content/online detection/dielectric properties/BP neural network分类
农业科技引用本文复制引用
姬虹,李康,宋东方,王万章,李保谦,冯伟..基于介电特性和BPNN建模的小麦含水率在线检测[J].农机化研究,2025,47(8):119-129,11.基金项目
中央引导地方科技发展资金项目(Z20221341068) （Z20221341068）
郑州市科技惠民计划项目(2022KJHM0045) （2022KJHM0045）
河南省科技厅科技攻关项目(242102110359) （242102110359）
河南省科技厅重点软科学项目(242400411017) （242400411017）
