Paper
6 November 2006 A fault diagnosis method based on parametric estimation in hydraulic servo system
Hongmei Liu, Pingchao Ouyang, Shaoping Wang
Author Affiliations +
Abstract
Due to the fault occurrence could commonly be considered as results of the physical parameters variation of the system and this variation usually is embodied by model coefficients variation of the system, faults can be detected and diagnosed according to the model parameter variation of the system. In this paper, a parametric estimation method, which is extended to extract features existing in input and output data of the monitored system, is employed to realize the FDD for a hydraulic servo system. An Auto-Regressive model with exogenous input (ARX) is selected to approximate the dynamic behavior of the system. Then according to the feature vector constructed by the coefficient of ARX model, faults are classified in feature space using RBF neural network to realize the fault localization. Experiments and simulations results indicate that the proposed method is effective in fault diagnosis for hydraulic servo system.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hongmei Liu, Pingchao Ouyang, and Shaoping Wang "A fault diagnosis method based on parametric estimation in hydraulic servo system", Proc. SPIE 6357, Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence, 63575A (6 November 2006); https://doi.org/10.1117/12.717595
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Servomechanisms

Neural networks

Amplifiers

Actuators

Device simulation

Systems modeling

Mathematical modeling

Back to Top