Gaussian and Non-Gaussian Information Based Hydraulic Component Internal Leakage Fault Diagnosis

Internal leakage is primary fault mode of hydraulic components, typically caused by seal failure or damage. However, the fluid inside hydraulic components exhibits complex motion characteristics, and its external vibration signals often have intricate distributions, making fault diagnosis challenging. This paper focuses on the internal leakage of hydraulic directional valve and proposes a fault diagnosis method based on Gaussian and N on-Gaussian information. First, time and frequency domain features are extracted from the vibration signals of the hydraulic directional valve. Then, the correlation between internal leakage and signal features is analyzed. Finally, Gaussian and Non-Gaussian information is extracted based on the correlated signal features, and these are used to construct statistics for detecting the presence of internal leakage. In complex data distribution scenarios for fault diagnosis, this method offers a novel solution without requiring a large number of fault samples or complex parameter optimization. Experimental studies validate the performance of this method, demonstrating that it outperforms several classical fault diagnosis methods in terms of robustness and accuracy. This research provides an effective approach for detecting internal leakage faults in hydraulic directional valves.