
Bearing Data Center Seeded Fault Test
Data
1.Welcome/Overview
Welcome to the Case Western Reserve University Bearing Data Center Website.
This website provides access to ball bearing test data for normal and faulty bearings.
Experiments were conducted using a 2 hp Reliance Electric motor, and acceleration data was
measured at locations near to and remote from the motor bearings. These web pages are unique
in that the actual test conditions of the motor as well as the bearing fault status have been carefully
documented for each experiment.
该网站提供正常和故障轴承的滚珠轴承测试数据。 使用 2 马力 Reliance Electric 电动机
进行实验,并且在靠近和远离电动机轴承的位置处测量加速度数据。 这些网页的独特之处
在于,每个实验都仔细记录了电机的实际测试条件以及轴承故障状态。
Motor bearings were seeded with faults using electro-discharge machining (EDM). Faults
ranging from 0.007 inches in diameter to 0.040 inches in diameter were introduced separately at
the inner raceway, rolling element (i.e. ball) and outer raceway. Faulted bearings were reinstalled
into the test motor and vibration data was recorded for motor loads of 0 to 3 horsepower (motor
speeds of 1797 to 1720 RPM).
使用电火花加工(EDM)为电机轴承提供故障。 在内滚道,滚动元件(即滚珠)和外
滚道上分别引入直径为 0.007 英寸至直径为 0.040 英寸的故障。 将故障轴承重新安装到测试
电机中,并记录 0 至 3 马力(电机速度为 1797 至 1720 RPM)的电机负载的振动数据。
2.Project History
Experiments are often required in order to validate new technologies, theories and techniques.
These motor bearing experiments were initiated in order to characterize the performance of IQ
PreAlert, a motor bearing condition assessment system developed at Rockwell. From the time of
this original impetus, the experimental program has expanded to provide a motor performance
database which can be used to validate and/or improve a host of motor condition assessment
techniques. Some projects which have recently or are currently making use of this database
include: Winsnode condition assessment technology, model based diagnostic techniques, and
motor speed determination algorithms.
为了验证新技术,理论和技术,通常需要进行实验。 这些电机轴承实验的开始是为了
表征 IQ PreAlert 的性能,IQ PreAlert 是罗克韦尔开发的电机轴承状态评估系统。 从该原始
动力的时间开始,实验程序已经扩展到提供电动机性能数据库,该数据库可用于验证和/或
改进许多电动机状态评估技术。 最近或正在使用该数据库的一些项目包括:Winsnode 条件
评估技术,基于模型的诊断技术和电机速度确定算法。