KFU. Card publication. Modernized algorithm of neural network initial weighting factors during the diagnosis of diesel engine faults

KAZAN
FEDERAL UNIVERSITY

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MODERNIZED ALGORITHM OF NEURAL NETWORK INITIAL WEIGHTING FACTORS DURING THE DIAGNOSIS OF DIESEL ENGINE FAULTS

Form of presentation

Articles in international journals and collections

Year of publication

2015

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Authors, employees of KFU

Zubkov Evgeniy Vitalevich, author

Ilyukhin Aleksey Nikolaevich, author

Bibliographic description in the original language

Modernized algorithm of neural network initial weighting factors during the diagnosis of diesel engine faults /Ilyukhin, A.N., Zubkov, E.V. //International Journal of Applied Engineering Research. - 2015. - 10 (24). - pp. 44848-44854

Annotation

Solution of the design problem, development and future use of the automated test systems (ATS) of internal combustion engines (ICE) involves, first of all, the analysis of a number of important requirements for the development of technical, mathematical, software, information, linguistic, organization and methodological support of the automated system. Currently, the need for a widespread adoption and operation of the automated systems in actual test conditions of stations of manufacturers and engineering research institutions imposes certain restrictions on designing computer-aided design facilities, real test technologies of various types and modifications of internal combustion engines. This situation comes from a sufficiently large number of tested engines, aggregates and units of different modifications, and also the need for phase-by-phase error elimination in the existing algorithms, including when conducting research and development test of engines. Requirements of real engine

Keywords

automated test systems,combustion engines

The name of the journal

International Journal of Applied Engineering Research

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=126592&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Zubkov Evgeniy Vitalevich	ru_RU
dc.contributor.author	Ilyukhin Aleksey Nikolaevich	ru_RU
dc.date.accessioned	2015-01-01T00:00:00Z	ru_RU
dc.date.available	2015-01-01T00:00:00Z	ru_RU
dc.date.issued	2015	ru_RU
dc.identifier.citation	Modernized algorithm of neural network initial weighting factors during the diagnosis of diesel engine faults /Ilyukhin, A.N., Zubkov, E.V. //International Journal of Applied Engineering Research. - 2015. - 10 (24). - pp. 44848-44854	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=126592&p_lang=2	ru_RU
dc.description.abstract	International Journal of Applied Engineering Research	ru_RU
dc.description.abstract	Solution of the design problem, development and future use of the automated test systems (ATS) of internal combustion engines (ICE) involves, first of all, the analysis of a number of important requirements for the development of technical, mathematical, software, information, linguistic, organization and methodological support of the automated system. Currently, the need for a widespread adoption and operation of the automated systems in actual test conditions of stations of manufacturers and engineering research institutions imposes certain restrictions on designing computer-aided design facilities, real test technologies of various types and modifications of internal combustion engines. This situation comes from a sufficiently large number of tested engines, aggregates and units of different modifications, and also the need for phase-by-phase error elimination in the existing algorithms, including when conducting research and development test of engines. Requirements of real engine	ru_RU
dc.language.iso	ru	ru_RU
dc.subject	automated test systems	ru_RU
dc.subject	combustion engines	ru_RU
dc.title	Modernized algorithm of neural network initial weighting factors during the diagnosis of diesel engine faults	ru_RU
dc.type	Articles in international journals and collections	ru_RU