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International Symposium on Neural Networks

ISNN 2006: Advances in Neural Networks - ISNN 2006 pp 364–369Cite as

Fault Detection and Diagnosis Using Neural Network Design

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3973))

Abstract

In this work, a fault detection method is designed based on neural networks. The proposed method is that a neural network is built on-line for the normal mode, while other one is used to diagnose the faults. The simulation shows the effectiveness of the proposed method.

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References

  1. Rangwala, S., Liang, S., Dornfeld, D.: Pattern Recognition of Acoustic Emission Signals During Punch Stretching. Mechanical Systems and Signal Processing 1, 321–332 (1987)

    Article  Google Scholar 

  2. Prateepasen, A., Au, Y.H.J., Jones, B.E.: Acoustic Emission and Vibration for Tool Wear Monitoring in Single-point Machining Using Belief Nework. In: IEEE Instrumentation and Measurement Technology Conference, Hungary, pp. 1541–1546 (2001)

    Google Scholar 

  3. Isermann, R., Ayoubi, M., Konrad, H., Reiβ, T.: Model Based Detection of Tool Wear and Breakage for Machine Tools. In: Int. Conf. on Syst. Man & Cyber., Le Touquet, vol. 3, pp. 72–77 (1993)

    Google Scholar 

  4. Colbaugh, R., Glass, K.: Real-time Tool Wear Estimation Using Recurrent Neural Networks. In: Proc. of the 1995 IEEE Int. Symp. on Intelligent Contr., Monterey, USA, pp. 357–362 (1995)

    Google Scholar 

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Author information

Authors and Affiliations

  1. National University of Singapore, 4 Engineering Drive 3, 117576, Singapore

    Kok Kiong Tan, Sunan Huang & Tong Heng Lee

Authors
  1. Kok Kiong Tan
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  2. Sunan Huang
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  3. Tong Heng Lee
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

  3. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Zurada

  4. Laboratory for Computational Biology, Shanghai Center for Systems Biomedicine, 800 Dong Chuan Rd, 200240, Shanghai, China

    Bao-Liang Lu

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

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© 2006 Springer-Verlag Berlin Heidelberg

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Cite this paper

Tan, K.K., Huang, S., Lee, T.H. (2006). Fault Detection and Diagnosis Using Neural Network Design. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3973. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760191_54

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  • DOI: https://doi.org/10.1007/11760191_54

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34482-7

  • Online ISBN: 978-3-540-34483-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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