Supply Chain Optimisation pp 263-275

Part of the Applied Optimization book series (APOP, volume 94) | Cite as

Identification-Based Condition Monitoring of Technical Systems

A Neural Network Approach
  • Anatoly Pashkevich
  • Gennady Kulikov
  • Peter Fleming
  • Mikhail Kazheunikau

Abstract

A novel identification-based technique for fault detection and condition monitoring of hydro- and electromechanical servomechanisms is proposed. It is based on neural network analyses of the control charts presenting behavior of the dynamic model parameters. There were derived analytical expressions that allow minimizing impact of the measurement errors on the identification accuracy. The proposed technique has been implemented in a software tool that allows automating the decision-making.

Key words

condition monitoring identification control charts neural networks 

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Copyright information

© Springer Science + Business Media, Inc. 2005

Authors and Affiliations

  • Anatoly Pashkevich
    • 1
  • Gennady Kulikov
    • 2
  • Peter Fleming
    • 3
  • Mikhail Kazheunikau
    • 1
  1. 1.Belarusian State University of Informatics and RadioelectronicsMinskBelarus
  2. 2.Ufa State Aviation Technical UniversityRussia
  3. 3.University of SheffieldUK

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