Zobrazeno 1 - 10
of 107
pro vyhledávání: '"Myeongsu Kang"'
Publikováno v:
IEEE Access, Vol 6, Pp 52345-52354 (2018)
With the increasing demand for unsupervised learning for fault diagnosis, the subspace clustering has been considered as a promising technique enabling unsupervised fault diagnosis. Although various subspace clustering methods have been developed to
Externí odkaz:
https://doaj.org/article/9baf16246031463aae8b555d79df1c64
Publikováno v:
IEEE Access, Vol 6, Pp 42566-42577 (2018)
The selection of tests required to make complex systems testable is a fundamental of system-level fault diagnosis. To evaluate the test selection, testability metric estimation (TME) is required. The influence of unreliable (imperfect) tests, whose o
Externí odkaz:
https://doaj.org/article/44cc01fe576b4ef4bf02192695d4d059
Publikováno v:
Energies, Vol 11, Iss 8, p 2149 (2018)
Gas turbine hot component failures often cause catastrophic consequences. Fault detection can improve the availability and economy of hot components. The exhaust gas temperature (EGT) profile is usually used to monitor the performance of the hot comp
Externí odkaz:
https://doaj.org/article/45922ad13d2a4f5a950441aa85b4a275
Publikováno v:
Shock and Vibration, Vol 2015 (2015)
To early identify cylindrical roller bearing failures, this paper proposes a comprehensive bearing fault diagnosis method, which consists of spectral kurtosis analysis for finding the most informative subband signal well representing abnormal symptom
Externí odkaz:
https://doaj.org/article/9985a63965674b5da0182e4dee29f9d0
Publikováno v:
IEEE Transactions on Industrial Electronics. 67:2272-2282
Multifractal detrended fluctuation analysis (MF-DFA) has been used for vibration-based fault diagnosis because it is able to uncover multifractality buried in nonlinear and nonstationary vibration signals and thus offers an opportunity to explore a n
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a0f97cb1b1845ace8a30f3ebf9ae80b5
https://doi.org/10.1109/tie.2019.2892667
https://doi.org/10.1109/tie.2019.2892667
Publikováno v:
IEEE Transactions on Industrial Electronics. 66:4696-4706
Wavelet transform, an effective tool to decompose signals into a series of frequency bands, has been widely used for vibration-based fault diagnosis in machinery. Likewise, the use of deep learning algorithms is becoming popular to automatically lear
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::394447e31250b8a6507aa881b3ed760e
https://doi.org/10.1109/tie.2018.2866050
https://doi.org/10.1109/tie.2018.2866050
Publikováno v:
IEEE Transactions on Industrial Electronics. 65:9728-9738
The dominant components in the stator current of a typical induction motor contain a substantial amount of information that is not related to bearing faults and can be considered as “ noise ” to bearing fault detection. The presence of the noise
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6ee0a4af1bb36d4f0b558622aad1eb11
https://doi.org/10.1109/tie.2018.2821645
https://doi.org/10.1109/tie.2018.2821645
Publikováno v:
IEEE Transactions on Industrial Electronics. 65:4290-4300
One of the significant tasks in data-driven fault diagnosis methods is to configure a good feature set involving statistical parameters. However, statistical parameters are often incapable of representing the dynamic behavior of planetary gearboxes u
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dde091d6b7c274aadc0385cedf695b9b
https://doi.org/10.1109/tie.2017.2762639
https://doi.org/10.1109/tie.2017.2762639
Publikováno v:
IEEE Access, Vol 6, Pp 42566-42577 (2018)
The selection of tests required to make complex systems testable is a fundamental of system-level fault diagnosis. To evaluate the test selection, testability metric estimation (TME) is required. The influence of unreliable (imperfect) tests, whose o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::08bbd230a360b244df300c64f557b43b
https://ieeexplore.ieee.org/document/8419687/
https://ieeexplore.ieee.org/document/8419687/
Publikováno v:
IEEE Transactions on Industrial Electronics. 63:6325-6335
The fact that rolling element bearing faults have an amplitude-modulating effect on their characteristic frequencies calls for sub-band analysis to determine an optimal sub-band signal that contains intrinsic information about bearing faults. In this
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::369c28e642c9a6ff3774ece6a018a04a
https://doi.org/10.1109/tie.2016.2574986
https://doi.org/10.1109/tie.2016.2574986