Fault classification of water hydraulic system by vibration analysis with support vector machine

被引：0
|
作者：
Chen, H. X. [1 ]
Chua, Patrick S. K. [1 ]
Lim, G. H. [1 ]
机构：
[1] Nanyang Technol Univ, Sch Mech & Aerosp Engn, Singapore 639798, Singapore
来源：
JOURNAL OF TESTING AND EVALUATION | 2007年 / 35卷 / 04期
关键词：
fault diagnosis; support vector machine; water hydraulic system; feature extraction; wavelet transform; neural network;
D O I：
暂无
中图分类号：
TB3 [工程材料学];
学科分类号：
0805 ; 080502 ;
摘要：
This paper presents a new neural network approach to the fault diagnosis of a water hydraulic system based on the wavelet analysis of a vibration signal. A novel feature of this approach is that the vibration signals acquired from the water hydraulic motor are employed for analysis. Wavelet transform (WT) is first applied as a feature extraction technique to analyze the time-domain vibration signal. The performance of support vector machine (svm) is then investigated and compared with the conventional neural network. The results confirm the applicability of the proposed method for the fault detection in a modern water hydraulic system.
引用
收藏
页码：408 / 415
页数：8
相关论文
共 50 条
  • [1] Fault classification of rotor vibration signal based on support vector machine
    Shanghai Institute of Special Equipment Inspection and Technical Research, Shanghai 200062, China
    不详
    [J]. Zhendong Gongcheng Xuebao, 2006, 2 (238-241):
  • [2] FEATURE EXTRACTION, OPTIMIZATION AND CLASSIFICATION BY SECOND GENERATION WAVELET AND SUPPORT VECTOR MACHINE FOR FAULT DIAGNOSIS OF WATER HYDRAULIC POWER SYSTEM
    Chen, Han Xin
    Chua, Patrick S. K.
    Lim, Geok Hian
    [J]. INTERNATIONAL JOURNAL OF FLUID POWER, 2006, 7 (02) : 39 - 52
  • [3] Hydraulic System Fault Diagnosis Based on Support Vector Machine Decision Tree
    Li, Sheng
    Zhang, Peilin
    Wang, Guode
    [J]. 2011 INTERNATIONAL CONFERENCE ON FUTURE COMPUTER SCIENCE AND APPLICATION (FCSA 2011), VOL 3, 2011, : 342 - 345
  • [4] Support Vector Machine for Vibration Fault Classification of Steam Turbine-Generator Sets
    Sun, Huo-Ching
    Huang, Yann-Chang
    [J]. INTERNATIONAL CONFERENCE ON ADVANCES IN ENGINEERING 2011, 2011, 24 : 38 - 42
  • [5] Fault Classification of Waste Heat Recovery System Based on Support Vector Machine
    Zhang, Jianhua
    Meng, Jia
    Wang, Rui
    Hou, Guolian
    [J]. PROCEEDINGS OF THE 2014 9TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA), 2014, : 733 - +
  • [6] Support vector classification for fault diagnostics of an electrical machine
    Pöyhönen, S
    Negrea, M
    Arkkio, A
    Hyötyniemi, H
    Koivo, H
    [J]. 2002 6TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS, VOLS I AND II, 2002, : 1719 - 1722
  • [7] Analysis of support vector machine classification
    Wu, QA
    Zhou, DX
    [J]. JOURNAL OF COMPUTATIONAL ANALYSIS AND APPLICATIONS, 2006, 8 (02) : 99 - 119
  • [8] An Online Incremental Support Vector Machine for Fault Diagnosis using Vibration Signature Analysis
    Gul, Sufi Tabassum
    Imran, Munhal
    Khan, Abdul Qayyum
    [J]. 2018 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY (ICIT), 2018, : 1467 - 1472
  • [9] Fault Detection of a Flow Control Valve Using Vibration Analysis and Support Vector Machine
    Venkata, Santhosh Krishnan
    Rao, Swetha
    [J]. ELECTRONICS, 2019, 8 (10)
  • [10] Fault Classification Model of Rotor Based on Support Vector Machine
    Niu, Wei
    Wang, GuoQing
    Zhai, ZhengJun
    Cheng, Juan
    [J]. MECHANICAL, MATERIALS AND MANUFACTURING ENGINEERING, PTS 1-3, 2011, 66-68 : 1982 - +
12345