bearing dataset

This bearing datasets has high data quality and obvious fault characteristics, so it is a commonly used bearing fault diagnosis standard dataset. In this datasets, three unbalanced datasets under different loads are constructed to testify the recognition effect of the proposed method. The test bench is composed of 2HP (1.5KW) induction motor, fan end bearing, driver end bearing, torque translator and load motor. By using EDM technology, single point faults with different depths were machined on the inner race, outer race and rolling element of the test bearing. The fault diameters were 7 mils, 14 mils and 21 mils, respectively.本轴承数据集数据质量优异且故障特征显著，是轴承故障诊断领域常用的标准数据集。本数据集构建了三种不同负载下的非平衡数据集，用于验证所提方法的识别效果。该试验台由2HP（1.5KW）感应电动机、风扇端轴承、驱动端轴承、扭矩转换器以及负载电机组成。通过电火花加工（Electrical Discharge Machining，EDM）技术，在试验轴承的内圈、外圈与滚动体上加工出不同深度的单点故障，上述故障的直径分别为7密耳、14密耳与21密耳。