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In view of the problems such as low accuracy, low efficiency and easy to misdiagnosis and missed diagnosis for aircraft engine fault diagnosis, an intelligent method of aircraft engine lubricating system fault diagnosis is presented. It is based on the Dynamic Principal Component Analysis (DPCA) method and the Least Square Support Vector Machine (LSSVM) method. At first, the DPCA method is employed to preprocess the lubricating system variables and detect whether there is a fault online. If there is a fault, the LSSVM method is used to state recognition. Then, the lubricating system of a certain type of aircraft engine is taken as an instance to verify the validity of the proposed method. Results show that the method can effectively improve the accuracy of fault diagnosis.