WAVELET--BASED PRESSURE ANALYSIS FOR HYDRAULIC PUMP HEALTH DIAGNOSIS

The diagnosis of hydraulic pump health in real-time is important for increasing hydraulic system reliability and performance. Because of high noise levels in the pump pulsation pressure signal, many existing health diagnosis methods, such as limit checking, spectrum analysis, and logic reasoning, cannot effectively perform a reliable on-line health diagnosis for hydraulic pumps. Wavelet analysis, a waveform signal analysis method performed by breaking up an evaluating signal into shifted and scaled versions of a standard wavelet, can identify feature signals in multiple decomposed band windows of the original signal. The methodology for applying this wavelet analysis in real-time health diagnosis for hydraulic pumps was investigated in this study. Results obtained from both simulation analysis and on-line experimental validation verified that the wavelet analysis method can improve the capability of diagnosing the health conditions of piston pumps, and more importantly can identify the types of pump defects based on the patterns and the amplitudes of obtained wavelet coefficients.