Investigation on Reciprocating Engine Condition Classification by Using Wavelet Packet Hilbert Spectrum
Nowadays, empirical mode decomposition (EMD) and Hilbert spectrum (HS) have been broadly investigated on non-stationary and nonlinear signal processing, especially on vibration signal analysis. But as diesel engine vibration signal wide frequency band, it leads to this method not decompose intrinsic mode function (IMF) successfully. Therefore, the obtained IMF is less meaning. For a better recognition of diesel condition because of its wider frequency band, this paper uses wavelet packet as preprocessing for HS analysis. It can effectively reduce wide frequency band and noise interference. Thus, the developed method is named as Wavelet Packet Hilbert Spectrum (WPHS). Experimental data of a DI135 diesel engine with different fuel supply advanced angle is used to evaluate effectiveness of the developed methodology on diesel pattern recognition. According to the recognition result, it can be concluded that this approach is very promising for reciprocating engine condition classification and preventative maintenance.
KeywordsDiesel Engine Fault Diagnosis Empirical Mode Decomposition Instantaneous Frequency Vibration Signal
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