KFU. Card publication. Improvement of 'winner takes all' neural network training for the purpose of diesel engine fault clustering

KAZAN
FEDERAL UNIVERSITY

- RUS
- 中文
- ES

IMPROVEMENT OF 'WINNER TAKES ALL' NEURAL NETWORK TRAINING FOR THE PURPOSE OF DIESEL ENGINE FAULT CLUSTERING

Form of presentation

Articles in international journals and collections

Year of publication

2017

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Authors, employees of KFU

Ilyukhin Aleksey Nikolaevich, author

Authors, students KFU

Gibadullin Ruslan Arturovich, author

Bibliographic description in the original language

Iliukhin, A.N. Improvement of 'winner takes all' neural network training for the purpose of diesel engine fault clustering/Iliukhin, A.N., Gibadullin, R.A.//2016 2nd International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2016 - Proceedings 7911587

Annotation

2016 2nd International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2016 - Proceedings

Keywords

Clustering algorithms; Engines; Faulting; Manufacture; Neural networks; Personnel training; Plasma diagnostics; Testing Automated test systems; Computing devices; Diagnostic systems; diesel; Knowledge database; Modified neural networks; Network structures; Neural network training

The name of the journal

2016 2nd International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2016 - Proceedings

URL

http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7911587

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

https://repository.kpfu.ru/eng/?p_id=157863&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Ilyukhin Aleksey Nikolaevich	ru_RU
dc.contributor.author	Gibadullin Ruslan Arturovich	ru_RU
dc.date.accessioned	2017-01-01T00:00:00Z	ru_RU
dc.date.available	2017-01-01T00:00:00Z	ru_RU
dc.date.issued	2017	ru_RU
dc.identifier.citation	Iliukhin, A.N. Improvement of 'winner takes all' neural network training for the purpose of diesel engine fault clustering/Iliukhin, A.N., Gibadullin, R.A.//2016 2nd International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2016 - Proceedings 7911587	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=157863&p_lang=2	ru_RU
dc.description.abstract	2016 2nd International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2016 - Proceedings	ru_RU
dc.description.abstract	To create a diagnostic system for diesel engines, it is necessary to analyze a huge amount of data obtained from the automated test systems for diesel engines. Therefore, it is worth to implement the analysis with the help of an artificial neural network. The application of the artificial neural network for diesel engine fault clustering allows reducing the amount of stored data by creation of a knowledge database for the weighting factors. Self-training makes it possible to revise this database, improving the accuracy of clustering, and to modify network structure, in case the new types of faults will appear. The modified neural network training algorithm involves the usage of input vector data originally found within each cluster group as the initial weighting factors. This algorithm allows decreasing the load on the computing devices by reducing the number of training cycles in comparison with other existing algorithms. The efficiency of the method can be improved with a larger numb	ru_RU
dc.language.iso	ru	ru_RU
dc.subject		ru_RU
dc.title	Improvement of 'winner takes all' neural network training for the purpose of diesel engine fault clustering	ru_RU
dc.type	Articles in international journals and collections	ru_RU