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Examination of the reliability of a technical object after its regeneration in a maintenance system with an artificial neural network

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Abstract

This article presents the issues of an examination and evaluation of the reliability of a technical object after its regeneration in a maintenance system. The preventive activities (regeneration) of an object are conducted in a maintenance system which includes an artificial neural network. The author made an attempt in the paper to prove that an artificial neural network has an indirect influence on the quality of preventive activities organized for a technical object and hence on the level of its reliability. This influence is the result of the fact that information developed by a neural network constitutes the basis in the process of the generation of an expert knowledge base on the basis of which the maintenance system is organized. This paper also covers the theoretical basis. Those quantities were defined which may be used in reliability tests of technical objects. The possibilities were presented of testing the reliability: the quality of the use of an object after its regeneration. These tests may be carried out in a short period of time and in a longer period of time after the preventive activities have been carried out for a device. This article also presents the idea of a reliability test conducted for a technical object on the example of a device which controls the work of a petrol engine. For this purpose, the structure of a maintenance system was designed on the basis of an expert knowledge base determined for an object. Diagnostic information from an artificial neural network constitutes the basis for these activities. A substantial part of the article is devoted to the description of the method of the reliability test of the object and to an analysis of the results obtained. The test was carried out in a simulation manner after a long period of time following regeneration of a technical object.

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Authors and Affiliations

  1. Department of Mechanics, Technical University of Koszalin, 15-17 Raclawicka St., 75-620, Koszalin, Poland

    Stanisław Duer

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  1. Stanisław Duer
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Correspondence to Stanisław Duer.

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Duer, S. Examination of the reliability of a technical object after its regeneration in a maintenance system with an artificial neural network. Neural Comput & Applic 21, 523–534 (2012). https://doi.org/10.1007/s00521-011-0723-2

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  • DOI: https://doi.org/10.1007/s00521-011-0723-2

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