# Design and Test of Real-Time Detection System for Cleaning Loss of Rapeseed Harvester
## 5 Conclusions  
(1) Based on the impact of the piezoelectric effect, different impact velocities were simulated under laboratory conditions to obtain the impact signals generated by kernels and impurities. A signal processing circuit based on a hardware integral circuit and a triple circuit comparison circuit was designed to analyze the impact signals. The integration results enter the triple voltage comparison for threshold selection. Through bench tests, the optimal distinction thresholds under different impact velocities were obtained. According to the bench test results, a fitting model relating the fan speed to the distinction threshold was constructed. The fitting model can provide a reference for field harvesting loss detection under different fan speeds and has a certain reference value.  
(2) The energy distinction method was designed to realize the real-time and accurate detection of the lost kernels. The energy distinction method consists of hardware integration and voltage threshold selection. The in-phase integral circuit was designed to obtain the different energy conditions of kernels and impurities' signals, that is, different integral voltage values. After the output voltage value enters the triple voltage comparisoncircuit, the threshold value where the signal is located is selected according to the different integration results of the kernels and the impurities, and it is simultaneously converted into three different pulse signals for detection and counting. Through a bench calibration test, it was found that the detection accuracy of the developed rapeseed cleaning loss detection system could reach 98%.  
(3) The scale coefficient of the system was obtained through a pre-experiment as 3.2, and a field experiment and test were carried out on a harvester. Under the operating conditions of 700, 900 and 1200 r/min, the maximum error of the results for the rapeseed kernel cleaning loss was 5%. The test results show that the rapeseed kernel cleaning loss detection system can identify the signal of lost kernels well and has the ability to run the detection process under complex harvesting conditions, and can feed back the cleaning loss for the harvester in real time, assist operators to adjust the harvesting speed and reduce unnecessary grain loss.  
Conceptualization, Y.Y. and L.J.; methodology, Y.Y.; software, Y.Y.; validation, Y.Y.; formal analysis, Y.Y.; investigation, T.J.; resources, G.W.; data curation, Y.Y. and L.J.; writing--original draft preparation, Y.Y.; writing--review and editing, Y.Y. and L.J.; visualization, Y.Y.; supervision, M.Z.; project administration, M.Z.; funding acquisition, L.J. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the institute-level basic scientific research business expenses project of the Chinese Academy of Agricultural Sciences (S202204), the Jiangsu Modern Agricultural Industry Key Technology Innovation Project CX(22)2010, the National Key Research and Development Program (2023 YFD200100301) and the Jiangsu Province modern agricultural machinery equipment and technology promotion project (NJ2024-20).  
Not applicable.  
The data presented in this study are available on request from the corresponding author because our organization has privacy requirements for the data of paper results.  
The authors thank the editor and anonymous reviewers for providing helpful suggestions for improving the quality of this manuscript.  
The authors declare no conflicts of interest.