Výsledky vyhledávání

Deep meta-learning and variational autoencoder for coupling fault diagnosis of rolling bearing under variable working conditions

Autor: Changchang Che, Huawei Wang, Ruiguan Lin, Xiaomei Ni

Publikováno v: Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science. 236:9900-9913

Considering the characteristics of rolling bearing such as variable working conditions, unbalanced fault sample size, and multiple coupling fault types, it is a great challenge to achieve general accurate fault diagnosis model. In this paper, deep me

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4196c7c2428333d8314d85c408ce06fe
https://doi.org/10.1177/09544062221101834

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Attention-based Gate Recurrent Unit for remaining useful life prediction in prognostics

Autor: Ruiguan Lin, Huawei Wang, Minglan Xiong, Zhaoguo Hou, Changchang Che

Publikováno v: Applied Soft Computing. 143:110419

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6149f14bab372b392c257b2eba3b5658
https://doi.org/10.1016/j.asoc.2023.110419

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Semi-supervised multitask deep convolutional generative adversarial network for unbalanced fault diagnosis of rolling bearing

Autor: Changchang Che, Huawei Wang, Ruiguan Lin, Xiaomei Ni

Publikováno v: Journal of the Brazilian Society of Mechanical Sciences and Engineering. 44

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::77b3dd865229a0b94e2c2dcc53035068
https://doi.org/10.1007/s40430-022-03576-x

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Knowledge representation and reuse model of civil aircraft structural maintenance cases

Autor: Ruiguan Lin, Huawei Wang, Junzhou Wang, Ningyue Wang

Publikováno v: Expert Systems with Applications. 216:119460

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::9bf939938579e15c997e567a738c83d2
https://doi.org/10.1016/j.eswa.2022.119460

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Remaining useful life prediction in prognostics using multi-scale sequence and Long Short-Term Memory network⋆

Autor: Yaowei Yu, Changchang Che, Ruiguan Lin, Huawei Wang, Xiaomei Ni

Publikováno v: Journal of Computational Science. 57:101508

The development of sensors and artificial intelligence technology provides practical tools for aircraft Prognosis and Health Management (PHM). The remaining useful life (RUL) prediction is the critical process of PHM. A novel data-driven framework is

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::0ca2ebf1171b5cdbc34c754c0c9b7fed
https://doi.org/10.1016/j.jocs.2021.101508

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Akademický článek

Deep meta-learning and variational autoencoder for coupling fault diagnosis of rolling bearing under variable working conditions.

Autor: Che, Changchang, Wang, Huawei, Lin, Ruiguan, Ni, Xiaomei

Publikováno v: Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science (Sage Publications, Ltd.); Sep2022, Vol. 236 Issue 17, p9900-9913, 14p

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