Kumar Dileep, Mehran Sanaullah, Shaikh Muhammad Zakir, Hussain Majid, Chowdhry Bhawani Shankar, Hussain Tanweer
NCRA Condition Monitoring Systems Lab, Mehran University of Engineering and Technology, Jamshoro, Pakistan.
Data Brief. 2022 May 23;42:108315. doi: 10.1016/j.dib.2022.108315. eCollection 2022 Jun.
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.
作为工业核心部件的旋转机械可通过振动分析进行有效监测。鉴于振动在工业状态监测中的重要性，本文报告并讨论了用于电机轴承故障检测与识别的三轴振动数据。这些数据是使用基于微机电系统（MEMS）的三轴加速度计和美国国家仪器公司的myRIO板采集的。轴承状态包括健康轴承、内圈有故障的轴承以及外圈有故障的轴承。对于每种故障轴承状态，三相感应电机在三种不同负载条件下运行。该数据集可用于评估新开发的有效轴承故障诊断方法的性能。Mendeley数据。http://dx.doi.org/10.17632/fm6xzxnf36.2
