Vibration analysis with lifting scheme and generalized cross validation in fault diagnosis of water hydraulic system

This paper presents a novel method to analyze the vibration signals in the fault diagnosis of water hydraulic motor. The method of feature extraction from the vibration signals of the water hydraulic motor based on the second-generation wavelet is investigated. The second-generation wavelet consists of a lifting scheme. The algorithm and method of multi-decomposition based on the lifting scheme for vibration analysis is developed. The denoise method for the vibration signals is proposed on the lifting scheme and the generalized cross validation (GCV). The relationship between the signal-to-noise (SNR) and GCV is presented. The corrupted simulated signal is used to test the proposed denoise algorithm. The method for extracting the feature values from the impulse vibration signals based on the statistical method is studied. The results show the applicability of this method for fault diagnosis of a water hydraulic motor.