基于压力补偿的种子棉花湿度回收的电阻感应
Liang Fang1,2, Ruoyu Zhang1,2, Hongwei Duan1,2
1College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832000, China.
Sensors (Basel, Switzerland)
|October 28, 2023
概括
这项研究引入了一种新的压力补偿电阻传感方法,用于精确测量种子棉花的水分回收 (MR). 反向传播神经网络 (BPNN) 模型显示出卓越的预测准确性,为收获操作提供了可靠的解决方案.
科学领域:
- 农业工程 农业工程
- 传感器技术 传感器技术
- 织科学 织科学
背景情况:
- 在收获期间精确地测量种子棉花的水分回收 (MR) 是至关重要的,但具有挑战性.
- 现有的方法可能会受到不同的贝尔参数的影响.
- 开发强大的传感技术对于高效的棉花加工至关重要.
研究的目的:
- 为种子棉花MR测量提出和评估一种新的电阻传感方法.
- 将压力补偿纳入,以提高测量准确度.
- 分析贝尔参数对导电性的影响,以便更好地预测MR.
主要方法:
- 设计了一个实验平台来模拟在收获期间的棉压缩.
- 分析了压缩体积,密度,接触压力和种子棉花导电性之间的相关性.
- 使用支持向量回归 (SVR),随机森林 (RF) 和反向传播神经网络 (BPNN) 开发和比较预测模型.
主要成果:
- 在接触压力和压缩密度 (p < 0.01) 之间发现了显著的相关性.
- 非线性模型更好地描述了密度,压力和导电性之间的关系.
- 在MR预测方面,BPNN取得了最高的准确性 (R2=0.986,RMSE=0.204%).
结论:
- 建议的压力补偿电阻传感方法对于种子棉的MR测量是可靠的.
- 对于预测种子棉花MR,BPNN提供了卓越的性能.
- 这项研究为在棉花收获期间准确,快速的MR测量提供了技术参考.
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