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.