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.

About the authors

N. A. Nechval

BVEF Research Institute, University of Latvia

Author for correspondence.
Email: nechval@junik.lv
Latvia, Riga, 1050

G. Berzins

BVEF Research Institute, University of Latvia

Email: nechval@junik.lv
Latvia, Riga, 1050

K. N. Nechval

Transport and Telecommunication Institute

Email: nechval@junik.lv
Latvia, Riga, 1019

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