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Technical equipment testing

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Volume 77 / No. 3 / 2025

Pages : 894-903

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DESIGN AND TEST OF A WIRELESS MONITORING SYSTEM FOR FEED RATE IN COMBINE HARVESTER BASED ON BOTTOM PLATE PRESSURE OF CHAIN-RAKE CONVEYOR

基于链耙输送器底板压力的联合收割机喂入量无线监测系统设计与试验

DOI : https://doi.org/10.35633/inmateh-77-73

Authors

(*) Chao ZHANG

College of Agricultural Engineering, Shanxi Agricultural University, Taigu, China

Qingling LI

College of Agricultural Engineering, Shanxi Agricultural University, Taigu, China

Shaobo YE

College of Agricultural Engineering, Shanxi Agricultural University, Taigu, China

Decong ZHENG

College of Agricultural Engineering, Shanxi Agricultural University, Taigu, China

(*) Corresponding authors:

sxndgxyzhangchao@sxau.edu.cn |

Chao ZHANG

Abstract

Feed rate is a critical operating parameter in combine harvesters, as it directly influences working efficiency and harvesting quality. To enable real-time and accurate feed rate monitoring, this study proposes a wireless monitoring approach based on pressure measurements at the bottom plate of the chain-rake conveyor inlet. A coupling model relating feed rate, chain-rake speed, and bottom plate pressure was established through theoretical analysis. To enhance robustness against signal fluctuations, the trimean was selected as the feature metric. A monitoring system incorporating LoRa wireless transmission was developed to achieve data acquisition, transmission, and visualization. Bench test results showed that the established model achieved a goodness-of-fit R² of 0.9963, and the predictive relative error was below 5% under most working conditions, demonstrating that the system provides high accuracy and stability in complex operating environments. The proposed method offers an effective technical solution for feed rate monitoring in combine harvesters.

Abstract in Chinese

喂入量是联合收获机作业过程中的关键参数,直接影响作业效率与质量。为实现喂入量的实时准确监测,本文提出一种基于链耙输送器入口处底板压力的无线监测方法。通过理论分析建立喂入量、链耙转速与底板压力之间的耦合模型,采用三均值(Trimean)作为鲁棒特征量以抑制信号波动干扰,设计了一套基于Lora无线传输的监测系统,实现数据采集、传输与可视化。台架试验结果表明,所建模型拟合优度R²达0.9963,在多数工况下预测相对误差低于5%,验证了该监测系统在复杂作业环境下具有良好的准确性与稳定性,为联合收获机喂入量检测提供了有效的技术支撑。


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