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Article Navigation >  Journal of Traffic and Transportation Engineering  > 2003  >  3(4): 44-47
WANG Yun-song, CHU Fu-lei, LIU Ya-dong. Fault diagnosis of diesel engine based on neural network[J]. Journal of Traffic and Transportation Engineering, 2003, 3(4): 44-47.
Citation: WANG Yun-song, CHU Fu-lei, LIU Ya-dong. Fault diagnosis of diesel engine based on neural network[J]. Journal of Traffic and Transportation Engineering, 2003, 3(4): 44-47.
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Fault diagnosis of diesel engine based on neural network

  • 1.

    School of Traffic and Vehicle, Shandong University of Technology, Zibo 255049, China

  • 2.

    Department of Precision Instruments and Mechanics, Tsinghua University, Beijing 100084, China

  • 3.

    The 53RD Research Institute of China North Industries Group Corporation, Jinan 250031, China

More Information
  • Author Bio:

    WANG Yun-song(1966-), male, professor, 86-533-2781895, wangyunsong@sdut.edu.cn

  • Received Date: 2003-02-20
  • Publish Date: 2003-04-25
    Abstract
  • Based on virtual instrument technology, the fault diagnosis system for diesel engine was developed. Its digital treatment system was consisted of sensors and PCI-6023E collectors, its design software was LABVIEW6. 0. This system character parameters were defined by engine's typical faults. In this system, the collected data were treated with BP neural network to diagnose engine's faults. The tested results show that this system is feasiable.

     

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    • References(9)
  • [1]
    Kajior Watanabe. Incipient fault diagnosis of chemical proces-ses via artificial neural networks[J]. Journal of AICHE, 1989, 3(11): 1803-1812
    [2]
    王文成. 神经网络及其在汽车工程中的应用[M]. 北京: 北京理工大学出版社, 1998.
    [3]
    赵振宇. 模糊理论和神经网络的基础和应用[M]. 北京: 清华大学出版社, 1993.
    [4]
    Bosch W. The fuel indicator-a new measuring instrument fordisplay of the characteristics of individual injection[J]. SAE660749.
    [5]
    Fan J Y. An approach to fault diagnosis of chemical processesvia neural network[J]. Journal of AICHE, 1993, 39 (1): 82-87. doi: 10.1002/aic.690390109
    [6]
    徐丽娜. 神经网络控制[M]. 哈尔滨: 哈尔滨工业大学出版社, 1993.
    [7]
    戴葵. 神经网络应用技术[M]. 北京: 国防科技大学出版社, 1998.
    [8]
    申焱. 基于Kohonen网络的机械故障模式识别[J]. 交通运输工程学报, 2002, 2(2): 55-59. http://transport.chd.edu.cn/article/id/200202013

    SHEN Yan. Pattern recognition of mechanical fault based on Kohonen neural network[J]. Journal of Traffic and Transportation Engineering, 2002, 2(2): 55-59. (in Chinese) http://transport.chd.edu.cn/article/id/200202013
    [9]
    John J Hopfield. Artificial neural networks[J]. IEEE Circuits and Devices Magzine, 1988, 18(12): 3-10.
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