Development of Method for Optimization of Diagnostic Algorithms for Car Engines
https://doi.org/10.21122/2227-1031-2022-21-4-331-339
Abstract
In modern practice of diagnosing complex technical devices, along with developing built-in diagnostic systems, a wide niche is still occupied by troubleshooting based on logical patterns. Logical algorithms for troubleshooting are the basis for diagnostic maps of car power plants. They do not always have an optimal structure in terms of achieving the lowest cost and time indicators of the diagnostic process. Thus, the problem of structural optimization of logical diagnostic algorithms is relevant, as well as the formation of a simple and understandable standardized procedure for optimizing diagnostic algorithms. The paper substantiates the criterion for evaluating the effectiveness of a diagnostic algorithm and the structure of the initial data for calculating the criterion. Variants of visual formalization of a diagnostic map are proposed in order to increase visibility and carry out further actions to optimize its structure, as well as options for formalizing visual information in digital form for its processing by computing means. The procedure for optimizing the structure in the JavaScript programming language has been developed and implemented. The reverse transition from a digital form to graphic one is described, which will immediately introduce the results into the practice of car service organizations. An analysis of a sample of 22 diagnostic maps has shown that the proposed optimization method will reduce the average cost of diagnostics up to 17 %.
About the Author
I. A. SerebryakovBelarus
Address for correspondence:
Serebryakov Ihar A. -
Belarusian National Technical University,
12, Ya. Kolasа str.,
220013, Minsk, Republic of Belarus.
Tel.: +375 17 293-91-17
serabrakovtea@bntu.by
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Review
For citations:
Serebryakov I.A. Development of Method for Optimization of Diagnostic Algorithms for Car Engines. Science & Technique. 2022;21(4):331-339. (In Russ.) https://doi.org/10.21122/2227-1031-2022-21-4-331-339