КФУ. Карточка публикации. Modernized algorithm of neural network initial weighting factors during the diagnosis of diesel engine faults

КАЗАНСКИЙ
ФЕДЕРАЛЬНЫЙ УНИВЕРСИТЕТ

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

Форма представления

Статьи в зарубежных журналах и сборниках

Год публикации

2015

Язык

английский

Авторы, сотрудники КФУ

Зубков Евгений Витальевич, автор

Илюхин Алексей Николаевич, автор

Библиографическое описание на языке оригинала

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

Аннотация

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

Ключевые слова

automated test systems,combustion engines

Название журнала

International Journal of Applied Engineering Research

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https://repository.kpfu.ru/?p_id=126592

Полная запись метаданных

Поле DC	Значение	Язык
dc.contributor.author	Зубков Евгений Витальевич	ru_RU
dc.contributor.author	Илюхин Алексей Николаевич	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/?p_id=126592	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	Статьи в зарубежных журналах и сборниках	ru_RU