Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Kaibo Lu"'
Publikováno v:
Measurement + Control, Vol 57 (2024)
Aiming at the problem that it takes a long time and high cost to obtain complete labeled data under intelligent fault diagnosis and unlabeled data is not used. This paper proposes an improved semi-supervised mean teacher deep learning (MTDL) and Gram
Externí odkaz:
https://doaj.org/article/d06140577dd44eae92195797dd5853d9
Publikováno v:
IEEE Access, Vol 11, Pp 26099-26113 (2023)
In order to apply the advantages of image recognition for fault diagnosis using convolutional neural network (CNN), it is necessary to convert one-dimensional (1D) signal data into two-dimensional (2D) images. Traditional signal-based conversion meth
Externí odkaz:
https://doaj.org/article/8b992b2c82814bd58bb4df087f0ace82
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-12 (2022)
Abstract Online monitoring of cutting conditions is essential in intelligent manufacturing, and vibrations are one of the most effective signals in monitoring machining conditions. Generally, traditional wired accelerometers should be installed on a
Externí odkaz:
https://doaj.org/article/396db2d2fffc44d6863c70d5a663c317
Publikováno v:
Chinese Journal of Mechanical Engineering, Vol 34, Iss 1, Pp 1-12 (2021)
Abstract Gearbox condition monitoring (CM) plays a significant role in ensuring the operational reliability and efficiency of a wide range of critical industrial systems such as wind turbines and helicopters. Accurate and timely diagnosis of gear fau
Externí odkaz:
https://doaj.org/article/be50e129c69b4db7a58c82c22cc3cf2c
Publikováno v:
Proceedings of IncoME-VI and TEPEN 2021 ISBN: 9783030990749
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cb7405f18f2bffe192b786afea207950
https://doi.org/10.1007/978-3-030-99075-6_47
https://doi.org/10.1007/978-3-030-99075-6_47
Publikováno v:
2022 27th International Conference on Automation and Computing (ICAC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::32696528b721d834fef2181fb90babc1
https://doi.org/10.1109/icac55051.2022.9911094
https://doi.org/10.1109/icac55051.2022.9911094
Publikováno v:
Chinese Journal of Mechanical Engineering, Vol 34, Iss 1, Pp 1-12 (2021)
Gearbox condition monitoring (CM) plays a significant role in ensuring the operational reliability and efficiency of a wide range of critical industrial systems such as wind turbines and helicopters. Accurate and timely diagnosis of gear faults will
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::79fb4a676d17eca38884a46a745cb246
https://doaj.org/article/be50e129c69b4db7a58c82c22cc3cf2c
https://doaj.org/article/be50e129c69b4db7a58c82c22cc3cf2c
Publikováno v:
IEEE/ASME Transactions on Mechatronics. 26:2027-2037
To improve the efficiency and accuracy of fault diagnostics of planetary gearboxes, an intelligent diagnosis approach is proposed based on deep convolutional neural networks (CNNs) and vibration bispectrum (BSP). Rather than using raw vibration signa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::41ec9c0fb79d3262e68e049be0d005e4
https://doi.org/10.1109/tmech.2020.3029058
https://doi.org/10.1109/tmech.2020.3029058
Publikováno v:
The International Journal of Advanced Manufacturing Technology. 111:3259-3271
It seems a universally accepted doctrine that chatter resistance of a machining system can be improved with increasing stiffness of its components. However, the viewpoint that the tool stiffness reduction would be beneficial to cutting stability of f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::667a6fb6b97b91fec9db9a8697f05b13
https://doi.org/10.1007/s00170-020-06339-x
https://doi.org/10.1007/s00170-020-06339-x
Publikováno v:
The International Journal of Advanced Manufacturing Technology. 104:3007-3015
Chatter happens frequently in turning of flexible parts, jeopardizing the dynamic stability of the operation. The chatter stability prediction is dependent on the accurate estimation of the structural parameters of the cutting system. This paper aims
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0b937f6563432dafc168581af72efaaf
https://doi.org/10.1007/s00170-019-04224-w
https://doi.org/10.1007/s00170-019-04224-w