Fault Diagnosis of Massage Chair Motor Based on Wavelet Packet Algorithm

Common motors for massage chairs include electrical and mechanical failures. Because of the non-stationarity of the current signal of DC brushed motors, electrical faults proposed a wavelet packet algorithm to decompose the collected current signals in time and frequency domains and calculate the frequency characteristics of the motor. While selecting sym8 for signal noise reduction, wavelet was selected Function and optimal tree, combined with MATLAB function to reconstruct the decomposed signal to obtain the frequency spectrum and energy characteristic map of the motor signal, and from the theoretical level combined with wavelet packet analysis to diagnose and analyze the type of massage chair motor failure.