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Localization of mechanical and electrical defects in dry-type transformers using an optimized acoustic imaging approach

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  • Zhanxi Zhang
  • Youyuan Wang
  • Zhihe Li
  • Jinzhan Liu

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.

Suggested Citation

  • Zhanxi Zhang & Youyuan Wang & Zhihe Li & Jinzhan Liu, 2023. "Localization of mechanical and electrical defects in dry-type transformers using an optimized acoustic imaging approach," PLOS ONE, Public Library of Science, vol. 18(11), pages 1-20, November.
    • Handle: RePEc:plo:pone00:0294674
    DOI: 10.1371/journal.pone.0294674
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