The invention discloses an equipment working
state recognition method based on a voiceprint recognition model, and relates to the technical field of
industrial equipment operation
state recognition. The equipment working
state recognition method based on the voiceprint recognition model comprises the following steps: collecting operation audio waveform data of target equipment, extracting acoustic representation data containing parameters such as short-time energy, a
frequency spectrum centroid, a spectrum flux, MFCC and a
zero crossing rate, inputting the acoustic representation data into a pre-trained voiceprint recognition model to extract voiceprint feature representation vectors, and carrying out voiceprint feature representation on the target equipment; according to the method, the
audio signal is divided into the frames, the acoustic features such as short-time energy, spectrum
centroid, spectrum flux, MFCC and
zero crossing rate are extracted, the inter-frame evolution relation is modeled in combination with the bidirectional neural network, and the attention mechanism is introduced to highlight the
key frame segment, so that the real-time performance of the
audio signal is improved, and the real-time performance of the
audio signal is improved. The recognition capability of working conditions such as fuzzy state boundary or unobvious transition is effectively enhanced, and the
time sequence analysis and state judgment precision is improved.