A method of diesel engine fuel system fault diagnosis based on wavelet transform and fuzzy C-means clustering is presented. Five characteristic parameters of reflecting fault state are distilled with wavelet transform of pressure wave of high-pressure oil pipe of diesel. The theory and generic approach of fuzzy C-means clustering algorithm (FCM) is given, and the validity of evaluating fuzzy clustering making use of partition coefficient, partition entropy and parting coefficient is pointed out. Identification of fault mode can be completed utilizing standard fault character modes established by FCM algorithm, and calculating and comparing the similarity degree between this standard mode and sample. The arithmetic is applied to all kinds of typical faults diagnose in the diesel engine fuel system. Measuring results indicate that the precision of fault diagnosis is increased with the analysis of wavelet and FCM.