Method and system for ascertaining anomalies in electric motors

摘要

A computer-based system and method for ascertaining anomalies in an electric motor, includes computing and processing a set of Fast Fourier Transforms (FFT's) of the supply current waveforms for a motor known to be in a normal condition to create a feature set of input vectors. The input vector assignments for all possible cluster groupings 1 through n are derived using Ward's method. The method includes computing the Approximate Weight of Evidence (AWE) for each cluster grouping then selecting that count associated with a maximum AWE and designating this count as s. For each cluster in each grouping 1 through s, the method finds the member vector farthest from the cluster's centroid and defines this as the cluster's radius. A single input sample for a motor under supervision is read in, following by computing and processing an FFT based on the input sample for a newly generated feature vector and then checking whether the newly generated feature vector is inside any of the clusters 1 through s as defined for each cluster by its respective radius, and if not, outputting a warning signal.