基于EMD和SVM的农用柴油机故障诊断研究

针对农用柴油机振动信号的非平稳特性和在现实条件下难以获得大量故障样本的实际情况,提出一种经验模态分解和支持向量机相结合的故障诊断方法。运用经验模态分解方法对气阀机构不同工况下的去噪缸盖振动信号进行分析,计算各内禀模态函数与去噪信号的互信息值以确定主IMF分量,并求其包含时间信息的能量熵以定量描述信号不同时频段的能量分布,将其作为支持向量机的输入特征向量以判断柴油机的工作状态和故障类型。试验结果表明,该方法在小样本情况下也具有较高的精度和较强的泛化能力,但不同转速时需重新采样以保证充足的诊断精度。

Fault Diagnosis for Agricultural Diesel Engine Based on EMD and SVM

According to the non-stationarity characteristics of the vibration signal from the agricultural diesel engine with fault and the situation that it is hard to obtain enough fault samples,a diesel engine fault diagnosis method based on empirical mode decomposition(EMD) and support sector machine(SVM) was proposed.Firstly,the true vibration signals of three air valve clearances were decomposed into a finite number of intrinsic mode functions(IMF),then main components were confirmed by calculating the mutual in...