Hydraulic System Fault Diagnosis Method Based on HPSO AND WP-EE

Abstract

A fault diagnosis approach of hydraulic system based on Hybrid Particle Swarm Optimization (HPSO) algorithm and Wavelet Packet Energy Entropy (WP-EE) is presented. A heuristic algorithm is adopted to give a transition from particle swarm search to gradient descending search. A HPSO algorithm is formed with the heuristic algorithm, which is used to optimize BP neural network weights and threshold. Then an application of fault diagnosis with HPSO and WP-EE based on a valve-controlled hydraulic motor system is presented. After wavelet packet decomposition of the acquired hydraulic pressure signal, the WP-EE is extracted; the eigenvector of wavelet packet is constructed. Taking this eigenvector as fault sample, the neural network based on HPSO algorithm is trained to implement the fault diagnosis for the hydraulic system. The test result shows that the fault recognition accuracy and the efficiency in the hydraulic system are improved by this method.

A Fault Feature Extraction Method for the Fluid Pressure Signal of Hydraulic Pumps Based on Autogram

“…Therefore, pressure fluctuation can reflect the running condition of the hydraulic system or component [3][4][5][6][7][8]. Fault diagnosis for the hydraulic systems or components based on the fluid pressure signal has been studied by many scholars at home and abroad [9][10][11][12][13][14][15][16]. Zhang put forward a method of flow measurement based on the new sensor, where the flow rate could be measured in hydraulic system by applying the mathematical model, and then flow detection of a 7 piston-pump was realized based on the sensor signal [9].…”

“…You proposed a fusion method using the hybrid particle swarm optimization algorithm and wavelet packet energy entropy. Neural network weights and threshold were optimized by the algorithm, and wavelet packet energy entropy was used for the eigenvector, and then the fault of hydraulic system could be diagnosed effectively [15]. In contrast to the traditional way of detecting the ship fault in the time domain, Li presented a novel method in the frequency domain.…”