A METHOD FOR MONITORING RICE SEED LOSS BASED ON WOA-BP ALGORITHM

ABSTRACT The combine harvester is a widely used piece of agricultural equipment in modern agriculture, and the seed loss rate is one of the important indexes used to measure its operational performance, so the monitoring of the seed loss rate is crucial for adjusting the operational parameters of co...

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Bibliographic Details
Main Authors: Jin Chen, Ting Shi, Yaoming Li, Yahui Zhu, Caoyuan Niu
Format: Article
Language:English
Published: Sociedade Brasileira de Engenharia Agrícola 2025-01-01
Series:Engenharia Agrícola
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Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162025000100300&lng=en&tlng=en
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Summary:ABSTRACT The combine harvester is a widely used piece of agricultural equipment in modern agriculture, and the seed loss rate is one of the important indexes used to measure its operational performance, so the monitoring of the seed loss rate is crucial for adjusting the operational parameters of combine harvesters and improving the quality of grain harvesting. Aiming at the problems of the slow response speed and low monitoring accuracy of the existing domestic seed loss rate monitoring models, this paper proposed a rice seed loss rate monitoring method based on the whale optimization algorithm-back propagation neural network (WOA-BP). The loss rate monitoring device consisted of a piezoelectric ceramic sensor module, charge amplification circuit, band-pass filter circuit, analog-to-digital (AD) converter, main control unit, etc. The WOA-BP algorithm, which has a high accuracy and fast response speed, was used to classify and count the signals to realise seed loss rate monitoring. The indoor test results showed that the relative errors of the monitoring results are less than 8.5% under the condition of a conveying speed of 1.3-2.1m/s, and the relative errors showed an increasing trend as the proportion of straw increased.
ISSN:0100-6916