Aimed at the wear monitoring problem of marine diesel engine,the used oils of 14 sets of diesel engine of the same type used in a certain fleet were monitored,and 105 oil samples were obtained.The content of 21 typical elements was measured by atomic emission spectrometer.The total amount of ferromagnetic debris was measured by magnetic debris monitor and magnetic force measurement method.A total of 18 oil samples with ferromagnetic debris mass fraction greater than 0 and Fe element mass fraction greater than average were selected from 105 oil samples.The nonferromagnetic debris (greater than 10 μm ) from the 18 oil samples was analyzed by the filter membrane method,and the maximum size and average size of the nonferromagnetic debris were counted.Principle component analysis(PCA) method was applied to analyze the spectral data,PQ value,magnetic force value,and the maximum size and average size of the nonferromagnetic debris of the 18 oil samples.The results show that the PCA method can integrate the various debris monitoring characteristics to cluster the wear status of the diesel engine.The results of the membrane image analysis confirms that the clustering results are reliable.