Fault detection and isolation in industrial control valve based on artificial neural networks diagnosis

• Hafaifa Ahmed

  Applied Automation and Industrial Diagnostic Laboratory, Faculty of Science and Technology, University of Djelfa 17000 DZ, Algeria.

• Djeddi Ahmed Zohair

  Applied Automation and Industrial Diagnostic Laboratory, Faculty of Science and Technology, University of Djelfa 17000 DZ, Algeria.

• Daoudi Attia

  Applied Automation and Industrial Diagnostic Laboratory, Faculty of Science and Technology, University of Djelfa 17000 DZ, Algeria.

The industrial systems become more complex in our days; the increasing complexity explains the need for a monitoring system performance, safe and reliable. This need for security and reliability requires the implementation of preferment diagnostic systems to report any malfunction in this industrial processes. In this paper, we develop a supervision system based on artificial neural networks approach to generate defects indicators for our examined industrial control valve.

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