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The Committee of Networks Approach to Condition Monitoring

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Condition Monitoring Using Computational Intelligence Methods

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Abstract

This chapter presents the committee of neural networks method, to which was applied pseudo modal energies, modal properties (natural frequencies and mode shapes), and wavelet transform data simultaneously to identify faults in cylindrical shells. The method was tested to identify faults in a population of ten steel seam-welded cylindrical shells. The committee technique identified faults better than the three individual techniques.

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Authors and Affiliations

  1. Faculty of Engineering and the Built Environment, University of Johannesburg, Auckland Park, Johannesburg, South Africa

    Tshilidzi Marwala

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  1. Tshilidzi Marwala
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Marwala, T. (2012). The Committee of Networks Approach to Condition Monitoring. In: Condition Monitoring Using Computational Intelligence Methods. Springer, London. https://doi.org/10.1007/978-1-4471-2380-4_5

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  • DOI: https://doi.org/10.1007/978-1-4471-2380-4_5

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  • Print ISBN: 978-1-4471-2379-8

  • Online ISBN: 978-1-4471-2380-4

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