In view of practical problems for the difficulty of obtaining large number of fault samples in the field of the intelligent fault diagnosis and problems of the real-time and so on for the need of a complete retraining period in the new fault categories,the new incremental 2D principal component analysis (I2DPCA) method of fault diagnoses is applied in the nonlinear cracked rotor system.Firstly,dynamics equations of a horizontally supported nonlinear rotor system with transverse cracks are established to investigate vibration varying characteristics of the system with different crack depths and mass eccentricity.Secondly,vibration signals in the time domain are normalized to image samples,and low dimension fault features with high discrimination are extracted by the I2DPCA algorithm.Based on the above treatment,the k-nearest neighbor (KNN) classification algorithm is used to calculate the recognition rate.The results of numerical simulations and related experiments show that the fault diagnosis method based on the I2DPCA can effectively distinguish signals of different fault conditions in high rotating speed zone and small samples situation,and provide a new detection strategy for the early diagnosis of cracked rotor systems.