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Keywords: BP neural network, fuzzy control, cutting platform height, multisensor ABSTRACT In this paper, BP neural network is used to collect header height, AMEsim is used to simulate and analyze header height adjustment hydraulic system, and fuzzy PID control is used to adjust header lifting hydraulic cylinder to stabilize header height. The experimental results of harvesting different crops show that under the header height automatic control system, the error between the actual height of crop harvesting and the set height is within 15 mm, and the harvesting effect is good, which can meet the automatic regulation requirements of the header height of the multi crop combine harvester. 摘要 为了提高调节的精度，采用 BP 神经网络多传感器融合处理技术采集割台实时高度，通过 AMEsim 软件对割台 高度调节液压系统进行仿真分析，最后采用模糊 PID 控制比例电磁阀调节割台升降液压缸从而稳定割台高度。 通过收获油菜、谷子和水稻的试验结果证明：在割台高度自动控制系统下，作物收获的实际高度与设定高度误
收割机割台高度调节技术
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