Volume 5, Issue 4, December 2019, Page: 68-73
Predicting of the Residual Resource of Car Assemblies
Ivanov Vladimir, Department of Road Transport, State University of Polotzk, Novopolotsk, Republic of Belarus
Vigerina Tatyana, Department of Road Transport, State University of Polotzk, Novopolotsk, Republic of Belarus
Pilipenko Stanislav, Department of Road Transport, State University of Polotzk, Novopolotsk, Republic of Belarus
Received: Feb. 13, 2019;       Accepted: Apr. 12, 2019;       Published: Oct. 26, 2019
DOI: 10.11648/j.ijtet.20190504.11      View  20      Downloads  7
Abstract
The research paper introduces a method that can be used for the forecasting the residual life of automobile aggregates (through the example of automobile engines). The results of a test-drive have shown that the proposed method is less labor intensive and has a satisfactory forecast accuracy. In the research the tenets of the reliability theory and mathematical statistics were used as well as information on the post-repair operating time of repaired engines based on the value of the initial main parameter (the gap between the piston and cylinder) for 41 engines. The probability density of this parameter follows the Gauss’ law. In our work we accept the nonlinear change in the mathematical expectation of the main parameter depending on the operating time in the form of a power law. The probability density of the aggregate resource is distributed according to the Weibull law. Adequacy of theoretical information to experimental data was determined by the Fisher criterion. The forecasting of the residual life of the aggregates is relevant when the operating time approaches their limit state. The relative forecast error varies from 0.021 to 0.130, which is quite acceptable for the real-world applications.
Keywords
Assembly, Reliability, Longevity, Diagnostic Parameter, Residual Resource, Prediction
To cite this article
Ivanov Vladimir, Vigerina Tatyana, Pilipenko Stanislav, Predicting of the Residual Resource of Car Assemblies, International Journal of Transportation Engineering and Technology. Vol. 5, No. 4, 2019, pp. 68-73. doi: 10.11648/j.ijtet.20190504.11
Copyright
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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