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采棉机籽棉回潮率传感器设计与试验OA

Design and Experiment of Moisture Regain Sensor for Seed Cotton in Cotton Pickers

中文摘要英文摘要

针对采棉机在采收作业中,籽棉回潮率在线检测受环境温度与接触压力干扰大的问题,本文基于电阻法原理,设计了一种集成温度与压力补偿机制的采棉机籽棉回潮率传感器.通过优化电阻检测电路以拓宽测量范围,结合温度与压力传感单元,设计了可同步采集环境温度、接触压力及籽棉电阻的传感器硬件系统,并进行了校准与性能测试.搭建试验平台分析了温度、压力及回潮率对籽棉导电特性的影响规律,建立了融合多参数补偿的回潮率预测模型,结果表明,所设计的硬件电路温度测量平均绝对误差小于 0.4℃,压力测量平均相对误差小于 0.2%,电阻测量平均相对误差小于 3%;回潮率预测模型中BPNN算法效果最佳,决定系数(R2)为 0.986,均方根误差(RMSE)为0.377%.为了验证回潮率传感器的可靠性,进行了室内静态和田间收获试验.室内静态试验结果表明,传感器检测范围为4%~15%,平均绝对误差为0.22%,平均相对误差为2.32%;田间收获试验结果表明,检测结果绝对误差不大于0.5%,相对误差不大于 4.32%.研究结果为采棉机籽棉回潮率在线检测提供有效的技术支撑.

Aiming at the problem that the online detection of moisture regain of seed cotton during cotton picking operations is significantly interfered by environmental temperature and contact pressure,a moisture regain sensor for seed cotton in cotton pickers was designed based on the resistive method,integrating temperature and pressure compensation mechanisms.By optimizing the resistance detection circuit to broaden the measurement range and combining temperature and pressure sensing units,a sensor hardware system capable of synchronously collecting environmental temperature,contact pressure,and seed cotton resistance was designed,and it was calibrated and performance tested.An experimental platform was built to analyze the influence of temperature,pressure,and moisture regain on the conductive characteristics of seed cotton,and a moisture regain prediction model incorporating multi-parameter compensation was established.The results showed that the designed hardware circuit had an average absolute error of less than 0.4℃for temperature measurement,an average relative error of less than 0.2%for pressure measurement,and an average relative error of less than 3%for resistance measurement.In the moisture regain prediction model,the BPNN algorithm performed best,with a coefficient of determination(R2)of 0.986 and a root mean square error(RMSE)of 0.377%.To verify the reliability of the moisture regain sensor,indoor static tests and field harvesting tests were conducted.The indoor static test results indicated that the sensor's detection range was from 4%to 15%,with an average absolute error of 0.22%and an average relative error of 2.32%.The field harvesting test results showed that the absolute error of the detection results was no greater than 0.5%,and the relative error was no greater than 4.32%.The tests demonstrated good accuracy and practicality,providing effective technical support for the online detection of moisture regain of seed cotton in cotton pickers.

方亮;刘康;黄杰;常金强;石喻文;曾兆权;张若宇

石河子大学机械电气工程学院,石河子 832003||农业农村部西北农业装备重点实验室,石河子 832003石河子大学机械电气工程学院,石河子 832003||农业农村部西北农业装备重点实验室,石河子 832003石河子大学机械电气工程学院,石河子 832003||农业农村部西北农业装备重点实验室,石河子 832003石河子大学机械电气工程学院,石河子 832003||兵团智慧农场数字化装备技术创新中心,石河子 832003石河子大学机械电气工程学院,石河子 832003||农业农村部西北农业装备重点实验室,石河子 832003石河子大学机械电气工程学院,石河子 832003||石河子大学能源与材料学院,石河子 832003石河子大学机械电气工程学院,石河子 832003||农业农村部西北农业装备重点实验室,石河子 832003

农业科技

籽棉回潮率采棉机电阻法传感器补偿算法

seed cotton moisture regaincotton pickersresistance methodsensorcompensation algorithms

《农业机械学报》 2026 (4)

62-71,10

国家重点研发计划项目(2022YFD2002400)、国家棉花产业技术体系岗位科学家项目(CARS-15-17)、新疆棉花产业技术体系专项(XJARS-03)、兵团科技攻关计划项目(2023AB014)、石河子大学高层次人才科研启动项目(CJXZ202104)和兵团研究生科研创新项目(BTYJXM-2024-K07)

10.6041/j.issn.1000-1298.2026.04.007

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