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Fault Diagnosis of Valve Train of Internal Combustion Engine based on the Artificial Neural Network and Support Vector Machine

机译:基于人工神经网络的内燃机阀门训练的故障诊断,支持向量机

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摘要

The theory of artificial neural network and support vector machine has been introduced. According to the characteristics of vibration signal for the valve mechanism, fault diagnosis has been proposed for abnormal valve clearance based on artificial neural network (ANN) and support vector machine (SVM). Two kinds of intelligent technology have been compared in fault identification by changing the number of training samples. The diagnosis has indicated that at small number of training samples SVM has high generalization ability, and at large number of training samples, ANN has exact recognition when it comes to diagnosing valve train.
机译:介绍了人工神经网络和支持向量机的理论。根据阀机构的振动信号的特点,已经提出了基于人工神经网络(ANN)的异常阀间隙和支持向量机(SVM)的故障诊断。通过改变训练样本的数量,在故障识别中进行了两种智能技术。诊断表明,在少量训练样本中,SVM具有高泛化能力,并且在大量训练样本中,ANN在诊断阀门列车时具有精确的识别。

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