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A novel fault prognostic approach based on particle filters and differential evolution

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Abstract

This paper proposes an improved fault prognostic approach based on a modified particle filter with a built-in differential evolution characteristic. The main methodological contribution of this study is to handle the problem of sample impoverishment faced by particle filters when only a few particles are resampled. This is done by incorporating modified mutation and selection operators for differential evolution into the proposed particle filter. The proposed method is performed to deal with two real applications of condition monitoring and fault prognosis, namely an accelerated degradation of bearings under operating conditions from the platform PRONOSTIA and a high-speed computer numerical control (CNC) milling machine 3-flute cutters.

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Acknowledgements

This work was supported by the Brazilian National Research Council (CNPq) and the Research Foundation of the State of Minas Gerais (FAPEMIG), Brazil.

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Authors and Affiliations

  1. Federal Institute of Norte de Minas Gerais, Campus Montes Claros, Montes Claros, Brazil

    Luciana B. Cosme

  2. Graduate Program in Electrical Engineering, Federal University of Minas Gerais, Av. Antônio Carlos 6627, Belo Horizonte, MG, Brazil

    Luciana B. Cosme

  3. Department of Computer Science, UNIMONTES, Av. Rui Braga, sn, Vila Mauricéia, Montes Claros, Brazil

    Marcos F. S. V. D’Angelo

  4. Department of Electronics Engineering, Federal University of Minas Gerais, Belo Horizonte, Brazil

    Walmir M. Caminhas & Reinaldo M. Palhares

  5. Harbin Institute of Technology, Harbin, China

    Shen Yin

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  1. Luciana B. Cosme
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  2. Marcos F. S. V. D’Angelo
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  3. Walmir M. Caminhas
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  4. Shen Yin
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Correspondence to Luciana B. Cosme.

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Cosme, L.B., D’Angelo, M.F.S.V., Caminhas, W.M. et al. A novel fault prognostic approach based on particle filters and differential evolution. Appl Intell 48, 834–853 (2018). https://doi.org/10.1007/s10489-017-1013-1

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