Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Aisong Qin"'
Publikováno v:
Applied Sciences, Vol 11, Iss 1, p 153 (2020)
The hydropower units have a complex structure, complicated and changing working conditions, complexity and a diversity of faults. Effectively evaluating the healthy operation status and accurately predicting the failure for the hydropower units using
Externí odkaz:
https://doaj.org/article/183ec457b6cb4d38a854ca5ef76abca9
Publikováno v:
Shock and Vibration, Vol 2017 (2017)
Remaining useful life (RUL) prediction can provide early warnings of failure and has become a key component in the prognostics and health management of systems. Among the existing methods for RUL prediction, the Wiener-process-based method has attrac
Externí odkaz:
https://doaj.org/article/9523a053383e44df9b1870c9ecea2a66
Publikováno v:
International Journal of Distributed Sensor Networks, Vol 11 (2015)
Fault diagnosis is an area which is gaining increasing importance in rotating machinery. Along with the continuous advance of science and technology, the structures of rotating machinery become increasingly of larger scale and higher speed and more c
Externí odkaz:
https://doaj.org/article/87b0fd8682f24d24bc0cae8e93b31ba0
Publikováno v:
International Journal of Distributed Sensor Networks, Vol 9 (2013)
Rotating machinery is widely used in modern industry. It is one of the most critical components in a variety of machinery and equipment. Along with the continuous development of science and technology, the structures of rotating machinery become of l
Externí odkaz:
https://doaj.org/article/80305917d6834f08bd0bad1ecef28324
Publikováno v:
Insight - Non-Destructive Testing and Condition Monitoring. 65:43-51
It is significant to predict the vibration trend of a hydropower generator unit (HGU) based on historical data for the stable operation of units and the maintenance of power system safety. Therefore, a novel combined model based on ensemble empirical
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::352181be435aed6a1247fdd2ea717790
https://doi.org/10.1784/insi.2023.65.1.43
https://doi.org/10.1784/insi.2023.65.1.43
Publikováno v:
IEEE Sensors Journal. 22:12139-12151
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cce48e4ed0e6155a2d20eb066068feab
https://doi.org/10.1109/jsen.2022.3174396
https://doi.org/10.1109/jsen.2022.3174396
Publikováno v:
IEEE Sensors Journal. 22:9649-9664
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0b9b1f467cfd8ea7e9acb7cce560bbda
https://doi.org/10.1109/jsen.2022.3164177
https://doi.org/10.1109/jsen.2022.3164177
Publikováno v:
IEEE Transactions on Instrumentation and Measurement. 71:1-12
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::96922a9db53f0405b6d0310d7fe4643f
https://doi.org/10.1109/tim.2021.3136264
https://doi.org/10.1109/tim.2021.3136264
Publikováno v:
Engineering Applications of Artificial Intelligence. 122:106100
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e358da2063ace17f34a28e891eb2714e
https://doi.org/10.1016/j.engappai.2023.106100
https://doi.org/10.1016/j.engappai.2023.106100
Publikováno v:
IEEE Sensors Journal. 20:11439-11453
In this study, a new intelligent fault diagnosis approach based on composite multi-scale dimensionless indicators (CMDIs) and affinity propagation (AP) clustering is proposed to identify working conditions of mechanical components. For this goal, CMD
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c41a0d4118aa38282302e3020968b417
https://doi.org/10.1109/jsen.2020.2995817
https://doi.org/10.1109/jsen.2020.2995817