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The Valve Electric Actuator's Fault Diagnosis Method Based on Principle Component Analysis and Support Vector Machines

机译:基于主成分分析和支持向量机的阀电动执行器故障诊断方法

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This paper, the mechanism of valve electric actuator failures is analyzed, and the fault diagnosis method based on principle component analysis (PCA) and support vector machines (SVM) is put forward. In order to reduce the dimension of feature signals, the fault diagnosis method uses PCA to extract fault feature signals. And a multi-class Support Vector Machine classifier is constructed to develop the model of failure diagnosis. The model can identify and detect the actuator's constant gain fault, the constant deviation fault and the dead zone fault. The simulation experiment result verified its feasibility and validity.
机译:本文分析了阀门电动执行器故障机制,提出了基于原理分析(PCA)和支持向量机(SVM)的故障诊断方法。为了降低特征信号的尺寸,故障诊断方法使用PCA提取故障特征信号。并且构建多级支持向量机分类器以开发故障诊断模型。该模型可以识别和检测执行器的恒定增益故障,恒定偏差故障和死区故障。仿真实验结果验证了其可行性和有效性。

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