Voiceprint Feature Extraction of Large Power Transformers in Uninterrupted Diagnosis and Early Warning Technology

Abstract

Condition-based maintenance is to select the most suitable maintenance method according to the real-time operating state of the converter. Transformer condition evaluation and fault diagnosis is an important basis for condition maintenance, and it is also the key to ensure the normal implementation of condition maintenance. The main purpose of this paper is to study the application of voiceprint feature extraction in large-scale power transformers in uninterruptible power failure diagnosis and early warning technology. In this paper, a comprehensive and in-depth study of the state quantity of transformer uninterrupted detection is carried out. Experiments show that when CR<0.10, the matrix is satisfactory and consistent, and the weight distribution is reasonable.