A Wavelet-Based Approach for Online External Leakage Diagnosis and Isolation from Internal Leakage in Hydraulic Actuators

This paper presents experimental evaluation of applying wavelet transform for on-line external leakage fault detection and isolation from internal leakage in hydraulic actuators. In this work, the more realistic case of an actuator that is driven to track pseudorandom position reference inputs against a load is considered. The wavelet-based method developed in this paper, decomposes a limited-duration pressure signal at either chamber of a hydraulic actuator into effective approximate and detail wavelet coefficients. The limited-duration pressure signal is collected using a sliding window technique. It is shown that the root mean square (RMS) value of the level four approximate wavelet coefficient collectively establishes a feature index that can effectively be used for on-line detection of external leakage. Once the external leakage occurs, this index value decreases proportionally. Therefore, one can report the faulty operating condition by monitoring this index. Additionally, built upon the previous work in which the level two detail coefficient was found to be sensitive to internal leakage fault, we further investigate the isolation of external leakage from internal leakage in an actuator. Extensive validation tests demonstrate the effectiveness of the proposed technique, given any position reference input, loading condition, and controller type or effectiveness. Experimental tests show promising results for detecting external leakage as low as 0.3 L/min and isolating it from internal leakage as low as 0.48 L/min, during an on-line testing procedure.