Title :
A comparison of neural networks and model-based methods applied for fault diagnosis of electro-hydraulic control systems
Author :
Dai, Shi Jie ; Shi, Zhan Qun ; Wang, Ji Zhong ; Yue, Hong
Author_Institution :
Res. Inst. of Robotics & Autom., Hebei Univ. of Technol., Tianjin, China
Abstract :
The paper aims to investigate two advanced methods used in fault diagnosis of electro-hydraulic (EH) control systems. The theoretical background of the neural network method and model-based approach are presented and the implementation of these methods is summarised with procedures in easy steps to follow for application. The pros and cons of these methods are also analysed based on fault detection capability. It is concluded that a combination of the neural network method and the model-based approach will be beneficial.
Keywords :
condition monitoring; electrohydraulic control equipment; fault diagnosis; observers; radial basis function networks; RBF network; condition monitoring; electro-hydraulic control systems; fault detection capability; fault diagnosis; model-based methods; neural networks; Application software; Automatic control; Control system synthesis; Control systems; Digital audio players; Electrical fault detection; Fault detection; Fault diagnosis; Neural networks; Robotics and automation;
Conference_Titel :
Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on
Print_ISBN :
0-7803-7508-4
DOI :
10.1109/ICMLC.2002.1176736