The invention discloses a
transformer live detection method based on a dynamic time
algorithm and relates to the technical field of
transformer fault diagnosis. The
transformer live detection method disclosed by the invention comprises the following steps: by utilizing an
acoustic vibration array, acquiring
acoustic vibration signals of a transformer running under multiple
normal conditions, and preprocessing the acquired
acoustic vibration signals of the transformer by utilizing a
spectral subtraction algorithm, thus obtaining pure acoustic vibration signals; extracting characteristic quantities, namely template characteristics, from the pure acoustic vibration signals by virtue of a
Mel frequency cepstrum coefficient established on the basis of Fourier and
cepstrum analysis; detecting anacoustic vibration
signal of a to-be-detected transformer by adopting a
signal-to-
noise ratio management
spectral subtraction algorithm; extracting the characteristic quantities by utilizing the samemethod; and performing similarity comparison with the template characteristics by utilizing a
time sequence of characteristic vectors of the acoustic
signal, and performing statistics on the characteristic quantities with the highest similarity, thus a recognition result is obtained, and the problem that speed of recognizing an acoustic signal of a transformer broken down is low is effectively solved.