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The Application of Fuzzy Reasoning System in Monitoring EDM

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2003)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2773))

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Abstract

EDM (electrical discharge machining) is a very complicated and stochastic process. It is very difficult to monitor its working conditions effectively as lacking adequate knowledge on the discharge mechanism. This paper proposed a new method to monitor this process. In this method, electrical impedance between the electrode and the workpiece was taken as the monitoring signal. Through analyzing this signal and using a fuzzy reasoning system as classifier, sparks and arcs were differentiated effectively, which is difficult when using other conventional monitoring methods. The proposed method first partitions the collected voltage and current trains into separated pulses using Continuous Wavelet Transform. Then apply Hilbert Transform and calculate electrical impedance of each pulse. After that, extract features from this signal and form a feature vector. Finally a fuzzy logic reasoning system was developed to classify the pulses as sparks and arcs.

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Author information

Authors and Affiliations

  1. Department of Manufacturing and Production Engineering, Nanyang Technological University, Singapore, 639798

    Xiao Zhiyun & Ling Shih-Fu

Authors
  1. Xiao Zhiyun
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  2. Ling Shih-Fu
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Editor information

Editors and Affiliations

  1. Computing Laboratory, Oxford University, Parks Road, OXI 3QD, United Kingdom

    Vasile Palade

  2. Intelligent Systems and Signal Processing Labs, Moulsecoomb, University of Brighton, BN2 4GJ, Brighton, United Kingdom

    Robert J. Howlett

  3. Knowledge-Based Intelligent Engineering Systems Centre, Mawson Lakes, University of South Australia, 5095, Adelaide, SA, Australia

    Lakhmi Jain

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© 2003 Springer-Verlag Berlin Heidelberg

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Zhiyun, X., Shih-Fu, L. (2003). The Application of Fuzzy Reasoning System in Monitoring EDM. In: Palade, V., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2003. Lecture Notes in Computer Science(), vol 2773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45224-9_95

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  • DOI: https://doi.org/10.1007/978-3-540-45224-9_95

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40803-1

  • Online ISBN: 978-3-540-45224-9

  • eBook Packages: Springer Book Archive

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