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Parametric and Neural Network Wiener and Hammerstein Models in Fault Detection and Isolation

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Fault Diagnosis

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Abstract

In the last two decades, model-based fault detection and isolation (FDI) has been investigated intensively (Frank, 1990; Chen and Patton, 1999; Patton et al., 1989). These methods require both a nominal model of the system considered, i.e., a model of the system under its normal operating conditions, and models of the system under its faulty conditions. The nominal model is used in the fault detection step to generate residuals, defined as a difference between the output signals of the system and its model. The analysis of these residuals gives an answer to the question whether a fault occurs or not. If it does occur, the fault isolation step is performed in a similar way analyzing residual sequences generated with the models of the system under its faulty conditions (Fig. 10.1).

This work was partially supported by the European Union in the framework of the FP 5 RTN: Development and Application of Methods for Actuators Diagnosis in Industrial Control Systems, DAMADICS (2000–2003), and within the grant of the State Committee for Scientific Research in Poland, KBN, No. 131/E-372/SPUB-M/5 PR UE/DZ 58/200l.

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Authors and Affiliations

  1. Institute of Control and Computation Engineering, University of Zielona Góra, Podgórna 50, 65-246, Zielona Góra, Poland

    Andrzej Janczak

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  1. Andrzej Janczak
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Editors and Affiliations

  1. Institute of Control and Computation Engineering, University of Zielona Góra, ul. Podgorna 50, 65-246, Zielona Góra, Poland

    Józef Korbicz

  2. Dept. of Automatic Control W.E.T.I., Technical University of Gdańsk, ul. Narutowicza 11/12, 80-952, Gdańsk, Poland

    Zdzisław Kowalczuk

  3. Institute of Automatic Control and Robotics, Warsaw University of Technology, ul. Chodkiewicza 8, 02-525, Warszawa, Poland

    Jan M. Kościelny

  4. Dept. of Fundamentals of Machine Design, Silesian University of Technology Gliwice, Konarskiego 18a, 44-100, Gliwice, Poland

    Wojciech Cholewa

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Janczak, A. (2004). Parametric and Neural Network Wiener and Hammerstein Models in Fault Detection and Isolation. In: Korbicz, J., Kowalczuk, Z., Kościelny, J.M., Cholewa, W. (eds) Fault Diagnosis. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18615-8_10

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  • DOI: https://doi.org/10.1007/978-3-642-18615-8_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-62199-4

  • Online ISBN: 978-3-642-18615-8

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