The invention discloses a motor fault detection method and
system based on voiceprint recognition. According to the method, an annular
microphone array is adopted to collect motor sound signals in a non-
contact mode, a three-channel time-
frequency data set is constructed through empirical mode
decomposition (EMD) and a Mel-frequency cepstral coefficient (MFCC), fault diagnosis is carried out in combination with a CNN + ResNet network, and
dynamic time warping (DTW) and CNN fusion matching is supported. The
system comprises a preprocessing module, a fault
template library and a matching
algorithm, integrates
wavelet denoising and multi-beam acquisition technologies, covers a
frequency band of 50Hz-20kHz, can display a fault type and
trend analysis in real time, and triggers secondary
verification when the confidence coefficient is insufficient. According to the scheme, the anti-interference capability is improved through array
signal processing,
model parameters are optimized in combination with transfer learning, non-contact detection is achieved, the real-time performance and accuracy of fault diagnosis are remarkably improved, and the method is suitable for industrial motor health monitoring.