Localization of mechanical and electrical defects in dry-type transformers using an optimized acoustic imaging approach
Zhanxi Zhang,
Youyuan Wang,
Zhihe Li and
Jinzhan Liu
PLOS ONE, 2023, vol. 18, issue 11, 1-20
Abstract:
This paper presents an acoustic imaging localization system designed to pinpoint common defects in dry-type transformers by analyzing the unique sounds they produce during operation. The system includes an optimized microphone array and an improved multiple signal classification algorithm. Sound signal characteristics of typical defects, such as foreign object intrusion, screw loosening, and partial discharge, are investigated. A 64-element, 8-arm spiral microphone array is designed using a particle swarm optimization algorithm. The multiple signal classification algorithm enhances acoustic imaging quality in field environments by transforming the input from time-domain to preprocessed frequency-domain signals. The power spectra of subarray and main array are combined, forming the optimization algorithm’s output. Experimental results demonstrate the system’s effectiveness and accuracy.
Date: 2023
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0294674 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 94674&type=printable (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0294674
DOI: 10.1371/journal.pone.0294674
Access Statistics for this article
More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().