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Triaxial bearing vibration dataset of induction motor under varying load conditions

Rotating machines as core component of an industry can effectively be monitored through vibration analysis. Considering the importance of vibration in industrial condition monitoring, this article reports and discusses triaxial vibration data for motor bearing faults detection and identification. Th...

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Detalles Bibliográficos
Autores principales: Kumar, Dileep, Mehran, Sanaullah, Shaikh, Muhammad Zakir, Hussain, Majid, Chowdhry, Bhawani Shankar, Hussain, Tanweer
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9156863/
https://www.ncbi.nlm.nih.gov/pubmed/35664656
http://dx.doi.org/10.1016/j.dib.2022.108315
Descripción
Sumario:Rotating machines as core component of an industry can effectively be monitored through vibration analysis. Considering the importance of vibration in industrial condition monitoring, this article reports and discusses triaxial vibration data for motor bearing faults detection and identification. The data is acquired using a MEMS based triaxial accelerometer and the National Instruments myRIO board. The bearing conditions include healthy bearing, bearings with inner race faults, and bearings with outer race faults. For each faulty bearing condition, the three-phase induction motor is operated under three different load conditions. The dataset can be used to assess performance of newly developed methods for effective bearing fault diagnosis. Mendeley Data. http://dx.doi.org/10.17632/fm6xzxnf36.2.