Abstract：For many fault diagnosis methods based on vibration signals, the diagnosis is not comprehensive under different loads. A fault diagnosis method based on power spectral density (PSD) and support vector machine (SVM) is proposed.In this method, the vibration signal power is processed by moving average filter (MAF), and the power spectral density (PSD) of the normalized signal of each period in the sample are calculated, and then the kernel method SVM is used for feature classification, so as to realize fault diagnosis. After the actual diesel engine test, the fault recognition rate of this method under different loads reaches 96.72%, and it can effectively identify the faults of the diesel engine intake and exhaust valve gap increase under different loads.
聂浩淼， 车驰东. 基于振动信号PSD-SVM方法的不定负荷下柴油机气阀间隙异常故障诊断[J]. 振动与冲击, 2024, 43(2): 299-305.
NIE Haomiao, CHE Chidong. Fault diagnosis of the gas valve of a diesel engine under uncertain load based on PSD-SVM. JOURNAL OF VIBRATION AND SHOCK, 2024, 43(2): 299-305.
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