Triaxial bearing vibration dataset of induction motor under varying load conditions

Dileep Kumar; Sanaullah Mehran; Muhammad Zakir Shaikh; Majid Hussain; Bhawani Shankar Chowdhry; Tanweer Hussain

doi:10.1016/j.dib.2022.108315

Triaxial bearing vibration dataset of induction motor under varying load conditions

Data Brief. 2022 May 23:42:108315. doi: 10.1016/j.dib.2022.108315. eCollection 2022 Jun.

Authors

Dileep Kumar¹, Sanaullah Mehran¹, Muhammad Zakir Shaikh¹, Majid Hussain¹, Bhawani Shankar Chowdhry¹, Tanweer Hussain¹

Affiliation

¹ NCRA Condition Monitoring Systems Lab, Mehran University of Engineering and Technology, Jamshoro, Pakistan.

Abstract

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.

Keywords: Bearing; Condition Monitoring; Fault diagnosis; Induction motor; Triaxial Vibration.