2026-04-30T00:21:04Zhttps://uvadoc.uva.es/oai/request
oai:uvadoc.uva.es:10324/595372023-05-08T19:00:34Zcom_10324_1166com_10324_931com_10324_894col_10324_1338
UVaDOC author Merizalde Zamora, Yury Humberto author Hernández Callejo, Luis author Duque Pérez, Óscar author Alonso Gómez, Víctor 2023-05-08T12:23:52Z 2023-05-08T12:23:52Z 2021 Applied Sciences, 2021, Vol. 11, Nº. 15, 6942 2076-3417 https://uvadoc.uva.es/handle/10324/59537 10.3390/app11156942 6942 15 Applied Sciences 11 2076-3417 To ensure the profitability of the wind industry, one of the most important objectives is to minimize maintenance costs. For this reason, the components of wind turbines are continuously monitored to detect any type of failure by analyzing the signals measured by the sensors included in the condition monitoring system. Most of the proposals for the detection and diagnosis of faults based on signal processing and artificial intelligence models use a fault-free signal and a signal acquired on a system in which a fault has been provoked; however, when the failures are incipient, the frequency components associated with the failures are very close to the fundamental component and there are incomplete data, the detection and diagnosis of failures is difficult. Therefore, the purpose of this research is to detect and diagnose failures of the electric generator of wind turbines in operation, using the current signal and applying generative adversarial networks to obtain synthetic data that allow for counteracting the problem of an unbalanced dataset. The proposal is useful for the detection of broken bars in squirrel cage induction generators, which, according to the control system, were in a healthy state. eng Atribución 4.0 Internacional Wind turbines Artificial intelligence Inteligencia artificial Motores de inducción Diagnosis of broken bars in wind turbine squirrel cage induction generator: Approach based on current signal and generative adversarial networks info:eu-repo/semantics/article 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URL https://uvadoc.uva.es/bitstream/10324/59537/1/Diagnosis-of-Broken-Bars-in-Wind-Turbine-Squirrel-Cage-Induction-Generator.pdf File MD5 cdccf820f7f5ca5f58e29827197a9e7a 1206266 application/pdf Diagnosis-of-Broken-Bars-in-Wind-Turbine-Squirrel-Cage-Induction-Generator.pdf