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The use of diesel cylinder head vibration signal for fault diagnosis must eliminate signal interference non-periodic and random components. The periodic components related to the working cycle of the diesel engine are retained, so as to achieve the purpose of fault feature extraction. A time-frequency correlation-based diesel engine fault feature extraction method is proposed in this paper. First, the Wavelet transform is applied to the vibration signals of diesel engines collected in three continuous working cycles to realize the time-frequency distribution of the signals. Then three time-frequency distributions are estimated by cross-correlation, so as to eliminate noise interference and extract periodic transient characteristics. The experimental results of simulation signals and real signals show that this method can effectively extract the periodic transient impact characteristics of diesel engines.

Diesel engine combustion feature extraction based on time-frequency correlation