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Intelligent Constructing Exact Statistical Prediction and Tolerance Limits on Future Random Quantities for Prognostics and Health Management of Complex Systems

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Abstract

In the paper presented a novel technique of intelligent constructing exact statistical prediction and tolerance limits on future random quantities for prognostics and health management of complex systems under parametric uncertainty is proposed. The aim of this technique is to develop and publish original scientific contributions and industrial applications dealing with the topics covered by Prognostics and Health Management (PHM) of complex systems. PHM is a set of means, approaches, methods and tools that allows monitoring and tracking the health state of a system in order to detect, diagnose and predict its failures. This information is then exploited to take appropriate decisions to increase the system’s availability, reliability and security while reducing its maintenance costs. The proposed technique allows one to construct developments and results in the areas of condition monitoring, fault detection, fault diagnostics, fault prognostics and decision support.

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ACKNOWLEDGMENTS

The authors would like to thank the anonymous reviewers for their valuable comments that helped to improve the presentation of this paper.

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Authors and Affiliations

  1. BVEF Research Institute, University of Latvia, 1050, Riga, Latvia

    N. A. Nechval & G. Berzins

  2. Transport and Telecommunication Institute, 1019, Riga, Latvia

    K. N. Nechval

Authors
  1. N. A. Nechval
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  2. G. Berzins
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  3. K. N. Nechval
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Correspondence to N. A. Nechval.

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Nechval, N.A., Berzins, G. & Nechval, K.N. Intelligent Constructing Exact Statistical Prediction and Tolerance Limits on Future Random Quantities for Prognostics and Health Management of Complex Systems. Aut. Control Comp. Sci. 53, 532–549 (2019). https://doi.org/10.3103/S0146411619060087

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