Microcontroller Realization of an Induction Motors Fault Detection Method based on FFT and Statistics of Fractional Moments

Induction Motors (IM) are the most widely used motors in industry. Although this type of machines is very reliable, different faults may occur. It is extremely important to detect faults at the earliest stages to reduce financial and energy losses and to overcome catastrophic accidents. Monitoring of mechanical vibrations and electrical currents are widely applied for that purpose. Recently, an effective method for fault detection and identification combining Fast Fourier Transform (FFT) and Statistics of Fractional Moments (SFM), thereby called FFT+SFM, was proposed by some of the authors. This paper shows how the FFT+SFM method can be implemented in microcontroller-based systems for real-time condition monitoring of IM. The method is optimized with respect to microcontroller features and hence it's implemented on a microcontroller. The optimized method is implemented by a C-code algorithm that is run on a microcontroller from the STM32F722 series by STMicroelectronics. The execution time and results of each algorithm iteration are measured to show the efficiency and effectiveness of the proposed algorithm. Results prove that the realization of the FFT+SFM method can be used in real-time condition monitoring systems of IM.