Hydraulic Servo System Fault Diagnosis Based on SVM

被引:0
作者
Li Tieying [1 ]
Luan Jiahui [1 ]
Shan Tianmin [1 ]
机构
[1] BUAA, Sch Reliabil & Syst Engn, Beijing 100191, Peoples R China
来源
2012 INTERNATIONAL CONFERENCE ON FUTURE INFORMATION TECHNOLOGY AND MANAGEMENT SCIENCE & ENGINEERING (FITMSE 2012) | 2012年 / 14卷
基金
中国国家自然科学基金;
关键词
fault diagnosis; SVM; Hydraulic servo system; support vector observer; support vector classifier;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Hydraulic servo system plays an important role in aircraft power supply system. It is of great significance to study the fault diagnosis method for aircraft health management. This paper introduces a Support Vector Machine (SVM) approach to build an observer on Hydraulic servo system and obtain the fault diagnosis results by identifying of the residuals. A support vector observer estimates the output of the system. By comparing with system output, the residual is generated and then clustered by a support vector classifier for fault detection. Finally we use MATLAB/Simulink to establish fault diagnosis model and verify the correctness of this method.
引用
收藏
页码:151 / 155
页数:5
相关论文
共 8 条
[1]  
Bishop C.M., 2006, J ELECTRON IMAGING, V16, P049901, DOI DOI 10.1117/1.2819119
[2]  
Deng Naiyang, 2009, THEORY ALGORITHMS EX, P43
[3]   FAULT-DIAGNOSIS IN DYNAMIC-SYSTEMS USING ANALYTICAL AND KNOWLEDGE-BASED REDUNDANCY - A SURVEY AND SOME NEW RESULTS [J].
FRANK, PM .
AUTOMATICA, 1990, 26 (03) :459-474
[4]  
Kennedy J, 1995, 1995 IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS PROCEEDINGS, VOLS 1-6, P1942, DOI 10.1109/icnn.1995.488968
[5]   Nonlinear observer-based fault detection technique for electro-hydraulic servo-positioning systems [J].
Khan, H ;
Abou, SC ;
Sepehri, N .
MECHATRONICS, 2005, 15 (09) :1037-1059
[6]   Fault diagnosis in a hydraulic position servo system using RBF neural network [J].
School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China .
Chin J Aeronaut, 2006, 4 (346-353) :346-353
[7]  
Ming Tingtao, 2008, China Mechanical Engineering, V19, P1527
[8]   Support vector machines-based fault diagnosis for turbo-pump rotor [J].
Yuan, SF ;
Chu, FL .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2006, 20 (04) :939-952