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Bearings are often used in engineering practice but it is easily damaged. Especially identification of their weak response in the early, which has important value and significance. To improve safety reliability and maintainability of the operation bearing, proposed fault diagnosis method and applied research based on principal component analysis and dynamic time warping. It can accurate identify the dynamic response of the early weak and diagnosis.First, fault samples and measured signals were de-noised by wavelet then,they were EMD decomposed, Several IMF components were striked to PCA,And all PCA components were analyzed to obtain the relevant eigenvectors composed by eigenvalues,Calculated the Dynamic Time Warping of eigenvectors that signals being measured between the known sample signals of fault feature vectors,In terms of the two signals,the smaller the distance, the more similar,Moreover, The method can also be applied to the fault diagnosis of rotor, rubbing and gear.Application examples of engineering show that this method can accurate classify faults, efficient troubleshooting.