Volume 6 Number 2 (Feb. 2011)
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JSW 2011 Vol.6(2): 209-216 ISSN: 1796-217X
doi: 10.4304/jsw.6.2.209-216

The Application of Fuzzy Neural Network in Fault Self-diagnosis System of Automatic Transmission

Kong Huifang1, Ren Guoqing2, He Jizhu1, Xiao Benxian1

1School of Electrical Engineering and Automation, Hefei University of Technology, Hefei, China
2Anhui Jianghuai Automotive Co., Ltd., Hefei, China


Abstract—According to the design procedure of fault selfdiagnosis system and features of automatic transmission system, the list of relation and mapping between fault symptoms and fault causes are made in this paper. Applying the approach of fault self-diagnosis based on fuzzy neural network, fault diagnosis of the automatic transmission electronic control system is realized. The structure of fuzzy neural network and its corresponding learning method and pretreating strategy about the training samples are introduced in this paper. Using MATLAB as simulation platform, this fault diagnosis method is simulated with neural networks toolbox. The simulation results show that this fault diagnosis approach is effective and applied.

Index Terms—fuzzy logic, neural network technique, automatic transmission (AT), fault diagnosis

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Cite: Kong Huifang, Ren Guoqing, He Jizhu, Xiao Benxian, "The Application of Fuzzy Neural Network in Fault Self-diagnosis System of Automatic Transmission," Journal of Software vol. 6, no. 2, pp. 209-216, 2011.

General Information

  • ISSN: 1796-217X (Online)
  • Frequency:  Quarterly
  • Editor-in-Chief: Prof. Antanas Verikas
  • Executive Editor: Ms. Yoyo Y. Zhou
  • Abstracting/ Indexing: DBLP, EBSCO, CNKIGoogle Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
  • E-mail: jsweditorialoffice@gmail.com
  • APC: 500USD
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