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Fault diagnosis of a nonlinear hybrid system using adaptive unscented Kalman filter bank

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Abstract

In this paper, a model-based fault diagnosis scheme of a nonlinear hybrid system using an adaptive unscented Kalman filter (AUKF) bank is proposed. The hybrid system is an amalgamation of discrete dynamics and continuous states. Fault diagnosis for simultaneous occurrences of multiple faults such as leakage fault, clogging fault, sensor fault, and actuator fault on a benchmark three-tank system are simulated. The residual signal based output generates some discrete modes that guarantee the uniqueness of the concerning fault. The efficacy of the proposed scheme is compared with that of the adaptive extended Kalman filter (AEKF) bank on the same system to prove its better response over AEKF.

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Authors and Affiliations

  1. Electrical Engineering Department, MCKV Institute of Engineering, Liluah, Howrah, West Bengal, 711204, India

    Chandrani Sadhukhan

  2. Electronic and Telecommunication Engineering Department, MCKV Institute of Engineering, Liluah, Howrah, West Bengal, 711204, India

    Swarup Kumar Mitra

  3. Electronic and Telecommunication Engineering Department, Jadavpur University, Jadavpur, West Bengal, 700032, India

    Mrinal Kanti Naskar

  4. Department of Mechanical and Aeronautical Engineering, University of Pretoria, Pretoria, 0002, South Africa

    Mohsen Sharifpur

  5. Institute of Research and Development, Duy Tan University, Da Nang, 550000, Vietnam

    Mohsen Sharifpur

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  1. Chandrani Sadhukhan
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  2. Swarup Kumar Mitra
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  3. Mrinal Kanti Naskar
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  4. Mohsen Sharifpur
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Correspondence to Chandrani Sadhukhan or Mohsen Sharifpur.

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Sadhukhan, C., Mitra, S.K., Naskar, M.K. et al. Fault diagnosis of a nonlinear hybrid system using adaptive unscented Kalman filter bank. Engineering with Computers 38, 2717–2728 (2022). https://doi.org/10.1007/s00366-020-01235-0

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  • DOI: https://doi.org/10.1007/s00366-020-01235-0

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