Effective Motor's Quality Types Determination on Motor's Current Waveforms Using the Euclidean Distance Measurement Method

摘要

This study proposes a simple and effective method, termed Euclidean Distance Measurement (EDM) method, to analyze motor's current waveforms for effectively determining the motor's quality types. This method is easily performed and does not require complex mathematic computations. It can recognize good or defective motors as well as defect types in less than 0.5 sec, and the maximum memory requirement is only about 10 MB for each motor's quality types with 16 bit sampling points. The EDM is described as the following two subsections: computing the mean vectors for each quality type and the motor's quality type determination. In the experiment, the total classification accuracy was approximately 99.68%.