A Novel Approach for Speed and Failure Detection in Brushless DC Motors Based on Chaos

This paper presents an approach developed to quantify the chaotic behavior for the characterization of electromechanical systems. A technique named Signal Analysis based on Chaos using Density of Maxima (SAC-DM) is presented. This technique uses a simple peak counting algorithm in the time domain of the current signal to detect faults. To demonstrate the potential of SAC-DM, an experiment is presented where a small brushless direct current (BLdc) motor at different speeds, with a regular and an unbalanced propeller, is used. The results demonstrate that the SAC-DM was able to detect the speed of the BLdc motor in 99.16% of the cases, and to identify the unbalanced system in 99.79% of the cases, when the speed is at 50%.