Voiceprint recognition technology of power transformer based on artificial neural network
LI Ruiqi
LI Yan
DU Shuiting
WANG Jun
Abstract：Aiming at the application demand of transformer voiceprint recognition and the low accuracy of BP neural network pattern recognition model,an improved artificial neural network technology for transformer voiceprint recognition was proposed.MFCC coefficient of the transformer voiceprint signal was taken as the input feature vector of the model,dynamic weight factor and variation factor were introduced into BOA algorithm,the weight and threshold of BP neural network were optimized,and voiceprint recognition was carried out.The experimental results show that the recognition accuracy can reach more than 90%by using the 32-dimensional MFCC characteristic coefficients of the transformer voiceprint signal.At the same time,the operation speed of the algorithm is 9.24%and 8.64%faster,respectively,than those of PSO-BP neural network and BOA-BP neural network,and it has higher efficiency of operation and recognition accuracy.
Keywords：voiceprint recognitionBP neural networkfeature vectorweight factordynamic optimizationpattern recognitionvariation factorstate detection
Publication Date：2024-07-25
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：8( 380-387 )