Fourier-Based Adaptive Signal Decomposition Method Applied to Fault Detection in Induction Motors

Time-frequency analysis is commonly used for fault detection in induction motors. A variety of signal decomposition techniques have been proposed the literature, such as Wavelet transform, Empirical Mode Decomposition (EMD), Multiple Signal Classification (MUSIC), among others. They successfully many works related with topic. Nevertheless, studied signals present amplitude changes and chirp-type frequency components that are difficult to track isolate aforementioned techniques. The contribution this work introduction a novel technique time-frequency based on an adaptive band-pass filter Short Time Fourier Transform (STFT), namely Fourier-Based Adaptive (FBASD) method. This method capable tracking extracting nonstationary within user-selected band. With these components, methodology detecting classifying broken rotor bars motors using startup transient current also proposed.