Modeling and structural optimization of acoustic imaging sensor unit for detecting abnormal noises of dry-type transformer

Abstract

Dry-type transformers will produce abnormal noise due to defects during operation. Acoustic imaging technology can infer the position information of the sound source by collecting acoustic signals during the operation of dry-type transformers, and display them objectively and scientifically through sound image cloud images. Acoustic imaging technology uses an acoustic sensors array to collect acoustic signals, and its imaging effect is affected by the array structure. According to the acoustic signal characteristics of different states during the operation of the dry-type transformer, this paper models the acoustic imaging sensor unit for the abnormal noise defects of the dry-type transformer, analyzes and determines the detection frequency of the array; analyzes the influence of acoustic sensor array shape, array aperture, and number of array elements on the acoustic imaging of dry-type transformers, and optimized the sensing unit.