Fault Detection in a Water Hydraulic Motor Using a Wavelet Transform

摘要

This paper is concerned with the detection of a piston crack in a water hydraulic motor used in a fluid power system. The wavelet-based signal processing technique to detect a piston crack was studied. A complete procedure of wavelet-based vibration signal analysis was developed. A modified noise reduction method based on wavelet analysis for feature extraction of the impulse peak vibration excited by the piston was applied to the vibration data of a water hydraulic motor. A continuous wavelet transform (CWT) and a wavelet packet (WP) were applied to the analysis of the impulse vibration signals. The feature values of the peaks excited by the impulse vibration signals can be extracted by using WP to decompose and compress the de-noise signals. Moreover, the signal component indicative of a fault was identified through the analysis of the vibration signal in the time domain in wavelet analysis. This technique was shown to be a powerful tool for the fault detection of a water hydraulic motor.