| Форма представления | Статьи в зарубежных журналах и сборниках |
| Год публикации | 2023 |
| Язык | английский |
|
Кошкина Ирина Александровна, автор
Уленгов Руслан Анатольевич, автор
|
| Библиографическое описание на языке оригинала |
Ovseenko G.A, Kashaev R.S, Koshkina I.A, The possibility of artificial neural network application in prototyping in instrument making industry//Proceedings of the 2023 5th International Youth Conference on Radio Electronics, Electrical and Power Engineering, REEPE 2023. - 2023. - Vol., Is.. - . |
| Аннотация |
The article explores the direction of using
artificial neural networks to solve problems of classification of
defects in the details of the instrument-making industry on the
example of cellular panels. An algorithm for constructing and
operating principle of a defect classification system based on a
multilayer perceptron is described. Studies of the developed
system are presented, in the classification of which experimental
data obtained during the control of samples of cellular panels by
the low-speed impact method were used. The developed neural
network made it possible to perform nonlinear separation and
classification of objects according to a set of diagnostic features,
to identify a complex relationship between the degree of damage
to the control object and the values of informative parameters.
The disadvantages of the system in training a neural network
are shown, which can be attributed to the need to train a
multilayer perceptron to the existence of a training sample
containing information about possible defects. |
| Ключевые слова |
neural network application, instrument making industry |
| Название журнала |
Proceedings of the 2023 5th International Youth Conference on Radio Electronics, Electrical and Power Engineering, REEPE 2023
|
| URL |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85154603583&doi=10.1109%2fREEPE57272.2023.10086823&partnerID=40&md5=e031ec579004ed5fea552a81dfd86ae8 |
| Пожалуйста, используйте этот идентификатор, чтобы цитировать или ссылаться на эту карточку |
https://repository.kpfu.ru/?p_id=284466 |
Полная запись метаданных  |
| Поле DC |
Значение |
Язык |
| dc.contributor.author |
Кошкина Ирина Александровна |
ru_RU |
| dc.contributor.author |
Уленгов Руслан Анатольевич |
ru_RU |
| dc.date.accessioned |
2023-01-01T00:00:00Z |
ru_RU |
| dc.date.available |
2023-01-01T00:00:00Z |
ru_RU |
| dc.date.issued |
2023 |
ru_RU |
| dc.identifier.citation |
Ovseenko G.A, Kashaev R.S, Koshkina I.A, The possibility of artificial neural network application in prototyping in instrument making industry//Proceedings of the 2023 5th International Youth Conference on Radio Electronics, Electrical and Power Engineering, REEPE 2023. - 2023. - Vol., Is.. - . |
ru_RU |
| dc.identifier.uri |
https://repository.kpfu.ru/?p_id=284466 |
ru_RU |
| dc.description.abstract |
Proceedings of the 2023 5th International Youth Conference on Radio Electronics, Electrical and Power Engineering, REEPE 2023 |
ru_RU |
| dc.description.abstract |
The article explores the direction of using
artificial neural networks to solve problems of classification of
defects in the details of the instrument-making industry on the
example of cellular panels. An algorithm for constructing and
operating principle of a defect classification system based on a
multilayer perceptron is described. Studies of the developed
system are presented, in the classification of which experimental
data obtained during the control of samples of cellular panels by
the low-speed impact method were used. The developed neural
network made it possible to perform nonlinear separation and
classification of objects according to a set of diagnostic features,
to identify a complex relationship between the degree of damage
to the control object and the values of informative parameters.
The disadvantages of the system in training a neural network
are shown, which can be attributed to the need to train a
multilayer perceptron to the existence of a training sample
containing information about possible defects. |
ru_RU |
| dc.language.iso |
ru |
ru_RU |
| dc.subject |
neural network application |
ru_RU |
| dc.subject |
instrument making industry |
ru_RU |
| dc.title |
The possibility of artificial neural network application in prototyping in instrument making industry |
ru_RU |
| dc.type |
Статьи в зарубежных журналах и сборниках |
ru_RU |
|
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