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Intelligent fault diagnosis in lead-zinc smelting process

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Abstract

According to the fault characteristic of the imperial smelting process (ISP), a novel intelligent integrated fault diagnostic system is developed. In the system fuzzy neural networks are utilized to extract fault symptom and expert system is employed for effective fault diagnosis of the process. Furthermore, fuzzy abductive inference is introduced to diagnose multiple faults. Feasibility of the proposed system is demonstrated through a pilot plant case study.

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Authors and Affiliations

  1. School of Information Science & Engineering, Central South University, Changsha, 410083, PRC

    Wei-Hua Gui, Chun-Hua Yang & Jing Teng

Authors
  1. Wei-Hua Gui
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  2. Chun-Hua Yang
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  3. Jing Teng
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Corresponding author

Correspondence to Chun-Hua Yang.

Additional information

This work was supported by National 973 Program (No. 2002CB312200) and National Natural Science Foundation of PRC (No. 60634020).

Wei-Hua Gui received his B.Eng. degree in control science and engineering and the M. Eng. degree in control science and engineering both from Central South University, Changsha, China in 1976 and 1981, respectively. From 1986 to 1988 he was a visiting scholar at Universität-GH-Duisburg, Germany. He has been a professor in the School of Information Science & Engineering, Central South University, Changsha, China, since 1991.

His main research interests include modeling and optimal control of complex industrial process, distributed robust control, and fault diagnoses of complex industrial process.

Chun-Hua Yang received her M. Eng. degree in automatic control engineering and the Ph. D. degree in control science and engineering both from Central South University, China in 1988 and 2002, respectively, and was with the Electrical Engineering Department, Katholieke Universiteit Leuven, Belgium from 1999 to 2001. She is currently a professor in the School of Information Science & Engineering, Central South University.

Her research interests include modeling and optimal control of complex industrial process, intelligent control system, and fault-tolerant computing of real-time systems.

Jing Teng received her B. Eng. in electronic information engineering from Central South University, Changsha, China in 2003. From 2003 to 2006 she was a Ph. D. student in Central South University and currently transferring to University of Technology of Troyes, France, to finish her Ph. D. degree.

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Gui, WH., Yang, CH. & Teng, J. Intelligent fault diagnosis in lead-zinc smelting process. Int J Automat Comput 4, 135–140 (2007). https://doi.org/10.1007/s11633-007-0135-z

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  • DOI: https://doi.org/10.1007/s11633-007-0135-z

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