Vibration Analysis for Fault Detection of Wind Turbines by Combining Machine-Learning Techniques and 3D Scanning Laser

Autor:	Javier Vives, Eduardo Roses Albert, Emilio Quiles, Juan Palací, Teresa Fuster
Rok vydání:	2022
Předmět:	General Computer Science Article Subject General Mathematics General Neuroscience General Medicine
Zdroj:	Computational intelligence and neuroscience. 2022
ISSN:	1687-5273
Popis:	With this research, we apply range-resolved interferometry (RRI) to the maintenance of wind turbines using some of the most relevant machine-learning (ML) techniques. The degeneration of electrical and mechanical components of wind turbines can be predicted, detected, and anticipated using this method of automatic and autonomous learning. The vibrations in two different failure states are detected with the help of a scanner laser. In-process measurements taken by RRI agree with manual measurements, laser scanning measurements, and in-process hand measurements made following each working cycle. Consequently, the proposed method will be very useful for monitoring and diagnosing faults in wind turbines. The system will also be able to perform low-cost in-process measurements.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ce20c03a9bd3085077b1f0a90d188e2c https://pubmed.ncbi.nlm.nih.gov/36601275 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
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