Adaptive Variational Mode Decomposition for Bearing Fault Detection

Rolling element bearings are commonly used in rotary mechanical and electrical equipment. According to investigation, more than half of rotating machinery defects related bearing faults. However, reliable fault detection still remains a challenging task, especially industrial applications. The objective this work is propose an adaptive variational mode decomposition (AVMD) technique for non-stationary signal analysis detection. AVMD includes several steps processing: 1) Signal characteristics analyzed determine the center frequency parameters. 2) ensemble-kurtosis index suggested decompose target select most representative intrinsic functions (IMFs). 3) envelope spectrum performed using selected IMFs identify characteristic features effectiveness proposed examined by experimental tests under different conditions, with comparison other techniques.