Using Frequency B-Splines for an accurate and faster calculation of adaptive transforms for electric machines diagnosis

Abstract

Early detection of faults in electric motors is crucial to prevent unplanned downtime and expensive repairs. Transient analysis through time-frequency transforms reveals important information on the motor condition. Computational time of these transforms becomes a problem when dealing with thousands of motors in just one industry. Researchers focus on obtaining the best quality results, usually using Gabor functions as t-f atoms. This paper shows how Frequency B-Splines can reach the same quality with nearly 40% less computational time. To achieve this goal, the slope criterion is applied to select the optimal atoms parameters. A formula that relates the slope of the Heisenberg Box of a FBS with its parameters is deduced. The proper time interval where the FBS must be defined is also determined. Results are shown not only with lab tests, but also through a field case