Volume 8 Issue 6
. 
Turn off MathJax
Article Contents
Article Navigation >  Journal of Traffic and Transportation Engineering  > 2008  >  8(6): 13-19
ZHANG Jian, FAN Xiao-ping, HUANG Cai-lun, CHEN Te-fang. Fusion monitoring system of locomotive wheelset state[J]. Journal of Traffic and Transportation Engineering, 2008, 8(6): 13-19.
Citation: ZHANG Jian, FAN Xiao-ping, HUANG Cai-lun, CHEN Te-fang. Fusion monitoring system of locomotive wheelset state[J]. Journal of Traffic and Transportation Engineering, 2008, 8(6): 13-19.
shu

Fusion monitoring system of locomotive wheelset state

  • 1.

    School of Information and Engineering, Central South University, Changsha 410083, Hunan, China

  • 2.

    Hunan Provincial Key Laboratory of Health Maintenance for Mechanical Equipment, Hunan University of Science and Technology, Xiangtan 411201, Hunan, China

More Information
  • Author Bio:

    ZHANG Jian (1974-), male, associate professor, doctoral student, +86-732-8290480, jzhang@hnust.edu.cn

    FAN Xiao-ping (1961-), male, professor, PhD, +86-731-8836423, xpfan@mail.csu.edu.cn

  • Received Date: 2008-07-15
  • Publish Date: 2008-12-25
    Abstract
  • In order to improve the accuracy of fault diagnosis and the uncertainty of current online condition monitoring methods for locomotive wheelset, a fusion monitoring system of locomotive wheelset was designed based on multi-sensor information fusion principle. The state of locomotive wheelset was monitored by using feature level fusion adaptive weighting algorithm, and the measured values were weighted adaptively to obtain the least-mean-square error of the measured values. The results computed by feature level fusion adaptive weighting algorithm, fuzzy data association algorithm, variable structure multiple-model estimation algorithm and BP nerve network(BPNN) algorithm were compared. Comparison result shows that when the fault occurs in the bearings of wheelset, the measured values are 22.047 0 and 21.025 0 respectively, while the estimation value from the fusion algorithm is 4.264 2, so the system has high reliability and better anti-disturbance.

     

    • FullText(HTML)
  • loading
    • References(13)
  • [1]
    应立军, 周书武, 亓琳, 等. 08-32捣固车电气系统在线监测与故障诊断系统[J]. 交通运输工程学报, 2004, 4(4): 34-36. doi: 10.3321/j.issn:1671-1637.2004.04.009

    YI NG Li-jun, ZHOUShu-wu, QI Lin, et al. On-line moni-toring and fault diagnosis systemfor electric system of 08-32tamper[J]. Journal of Traffic and Transportation Engineering, 2004, 4(4): 34-36. (in Chinese) doi: 10.3321/j.issn:1671-1637.2004.04.009
    [2]
    吴浩中, 王开文. 小波包-神经网络在摆式列车倾摆控制系统故障诊断中的应用[J]. 交通运输工程学报, 2003, 3(2): 27-30. doi: 10.3321/j.issn:1671-1637.2003.02.006

    WU Hao-zhong, WANG Kai-wen. Fault diagnosis using wavelet packet and neural networkintilting control systemof tilting train[J]. Journal of Traffic and Transportation Engi-neering, 2003, 3(2): 27-30. (in Chinese) doi: 10.3321/j.issn:1671-1637.2003.02.006
    [3]
    徐冬芳, 邓飞其. 基于多传感器数据融合的智能故障诊断系统[J]. 仪器仪表学报, 2004, 25(4): 404-406. https://www.cnki.com.cn/Article/CJFDTOTAL-YQXB2004S1174.htm

    XU Dong-fang, DENG Fei-qi. Artificial fault diagnosis sys-tem based on data fusion algorithm[J]. Chinese Journal of Scientific Instrument, 2004, 25(4): 404-406. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YQXB2004S1174.htm
    [4]
    SKARI ATOS D, KARAKASIS K, TROCHIDIS A. Rail way wheel fault diagnosis using a fuzzy-logic method[J]. Applied Acoustics, 2004, 65(10): 951-966. doi: 10.1016/j.apacoust.2004.04.003
    [5]
    黄采伦. 列车轮对在线状态监测理论与方法研究[D]. 长沙: 中南大学, 2008.
    [6]
    HALL D L, LLI NAS J. Anintroduction to multisensor data fusion[J]. Proceedings of the IEEE, 1997, 85(1): 6-23. doi: 10.1109/5.554205
    [7]
    穆荣军, 崔乃刚. 多传感器优化融合模型的理论与仿真研究[J]. 仪器仪表学报, 2006, 27(6): 326-328. https://www.cnki.com.cn/Article/CJFDTOTAL-YQXB2006S1125.htm

    MU Rong-jun, CUI Nai-gang. Theoretical and si mulation re-search on opti mizinginformation fusion method for multisen-sor[J]. Chinese Journal of Scientific Instrument, 2006, 27(6): 326-328. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YQXB2006S1125.htm
    [8]
    李若琼, 李欣, 董海鹰. 基于证据理论的多信息融合故障诊断研究[J]. 自动化仪表, 2006, 27(12): 1-4. doi: 10.3969/j.issn.1000-0380.2006.12.001

    LI Ruo-qiong, LI Xin, DONG Hai-ying. Study on the multi-in-formation fusion fault diagnosis based on evidential theory[J]. Process Automation Instrumentation, 2006, 27(12): 1-4. (in Chinese) doi: 10.3969/j.issn.1000-0380.2006.12.001
    [9]
    DASARATHY B V. Information fusion—a status update[J]. Information Fusion, 2007, 8(4): 335-336. doi: 10.1016/j.inffus.2007.04.004
    [10]
    BASIR O, YUAN Xiao-hong. Engine fault diagnosis based on multi-sensor information fusion using Dempster-Shafer evidence theory[J]. Information Fusion, 2007, 8(4): 379-386. doi: 10.1016/j.inffus.2005.07.003
    [11]
    OVASKA S J, VANLANDI NGHAM H F, KAMIYA A. Fusion of soft computing and hard computing in industrial applications: an overview[J]. IEEE Transactions on Systems Man and Cybernetics, Part C Applications and Reviews, 2002, 32(2): 72-79. doi: 10.1007/3-540-32391-0_40
    [12]
    黄丹, 黄采伦. 基于BP神经网络模型的电机故障诊断专家系统[J]. 自动化仪表, 2003, 24(3): 15-17. https://www.cnki.com.cn/Article/CJFDTOTAL-ZDYB200303002.htm

    HUANG Dan, HUANG Cai-lun. BP neural network model based expert systemof fault diagnostic of electrical mechinery[J]. Process Automation Instrumentation, 2003, 24(3): 15-17. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZDYB200303002.htm
    [13]
    HOU Zhi-jian, LI AN Zhi-wei, YAO Ye, et al. Data mining based sensor fault diagnosis and validation for building air conditioning system[J]. Energy Conversion and Manage-ment, 2006, 47(15/16): 2479-2490. https://www.sciencedirect.com/science/article/pii/S0196890405003031
    • Relative Articles
    • Supplements(0)
    • Cited By
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索
    Get Citation
    PDF
    XML

    Article Metrics

    Article views (365) PDF downloads(283) Cited by()
    Proportional views
    Related

    Copyright《Journal of Traffic and Transportation Engineering》编辑部陕ICP备05001904号-1

    Address ：Editorial Department of Journal of Traffic and Transportation Engineering, Chang 'an University, Middle Section of South Second Ring Road, Xi 'an, Shaanxi（710064） Tel：029-82334388 Email：jygc@chd.edu.cn

    All visit:Today's visit:

    Supported by: Beijing Renhe Information Technology Co. Ltd    

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return