According to the characteristics of the gear pumps fault of complicated formation, strong fuzziness, combined with wavelet packet decomposition and KL transform, presented a suitable support vector machine fault diagnosis feature extraction method The feature vector was decomposed by wavelet packet, and the new feature vector set was processed by KL transform. The feature vector set was used to support vector machine model training.The result shows that the method can effectively improve the accuracy and efficiency of fault pattern recognition.