Research on the Application of EEMD Fuzzy Clustering in Fault Diagnosis of Common Rail Systems
As a kind of reciprocating running machinery,the occurrence of faults in high-pressure common rail diesel engine is a grad-ual process with ambiguity.For the problems of difficult identification of eigenvalues and fuzzy classification boundaries in the diagno-sis of the fault degree of high-pressure common rail diesel engine oil supply system,a fault diagnosis method based on EEMD(ensem-ble empirical modal decomposition)-fuzzy clustering is proposed in this paper.By decomposing the oil supply system rail pressure signal into a series of IMFs(intrinsic modal functions)through EEMD,the eigenvalues in the intrinsic modal functions are extracted using the feature extraction criterion determined by the over-zero rate curve,and a fuzzy clustering model is established to diagnose the fault degree.On this basis,the rail pressure signals are obtained by bench experiments,the relevant eigenvalues are extracted for identifica-tion,the diagnostic results are analyzed,and the correctness of the method is verified.
High-Pressure Common RailFault DiagnosisEnsemble Empirical Mode DecompositionFuzzy Clustering
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