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分析了电液伺服阀静态特性与故障模式之间的映射关系 ,介绍了基于BP神经网络电液伺服阀故障模式识别的方法 ,并进行了实验研究 ,结果表明该方法故障模式识别准确率较高 ,可以进一步与伺服阀试验台测试功能进行结合 ,形成一种具有自学习、自动测试与智能诊断功能的检测系统
The relationship between the static characteristics of electrohydraulic servo valve and the failure mode is analyzed. The method of fault pattern recognition of electro-hydraulic servo valve based on BP neural network is introduced and the experimental research is carried out. The results show that the accuracy of the fault pattern recognition is high , Can be further combined with the servo valve test bench testing capabilities to form a self-learning, automatic testing and intelligent diagnostic testing system