In view of practical problems for the difficulty of obtaining large nu mber of fault samples in the field of the intelligent fault diagnosis and proble ms of the real-time and so on for the need of a complete retraining period in t h e new fault categories,the new incremental 2D principal component analysis (I2D PCA) 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.Se condly,vibration signals in the time domain are normalized to image samples,an d low dimension fault features with high discrimination are extracted by the I2D PCA algorithm.Based on the above treatment,the k-nearest neighbor (KNN) class i fication algorithm is used to calculate the recognition rate.The results of num erical simulations and related experiments show that the fault diagnosis method based on the I2DPCA can effectively distinguish signals of different fault condi tions in high rotating speed zone and small samples situation,and provide a new detection strategy for the early diagnosis of cracked rotor systems.