Feasibility Analysis of a Time-frequency Domain Slef-silimarity Denoising Method for Sound Detection in Distribution Transformers

LONG Xiangjin; LIU Yuan; SU Sheng; CHEN Feng; LI Bin

doi:10.13296/j.1001-1609.hva.2026.03.008

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Feasibility Analysis of a Time-frequency Domain Slef-silimarity Denoising Method for Sound Detection in Distribution Transformers

Research & Analysis | 更新时间：2026-03-11

- Feasibility Analysis of a Time-frequency Domain Slef-silimarity Denoising Method for Sound Detection in Distribution Transformers
- High Voltage Apparatus Vol. 62, Issue 3, Pages: 61-68(2026)
- 作者机构：
  
  长沙理工大学电气与信息工程学院，长沙 410114
  国网安徽省电力有限公司广德市供电公司，安徽广德 242200
  湖南省电力公司长沙供电分公司，长沙 410004
- 作者简介：
- 基金信息：
- DOI：10.13296/j.1001-1609.hva.2026.03.008
  CLC：
- Received：03 August 2025，
  
  Revised：2025-10-05，
  
  Published：16 March 2026
- 稿件说明：
移动端阅览
LONG Xiangjin, LIU Yuan, SU Sheng, et al. Feasibility Analysis of a Time-frequency Domain Slef-silimarity Denoising Method for Sound Detection in Distribution Transformers[J]. High Voltage Apparatus, 2026, 62(3): 61-68.
DOI：

LONG Xiangjin, LIU Yuan, SU Sheng, et al. Feasibility Analysis of a Time-frequency Domain Slef-silimarity Denoising Method for Sound Detection in Distribution Transformers[J]. High Voltage Apparatus, 2026, 62(3): 61-68. DOI： 10.13296/j.1001-1609.hva.2026.03.008.

摘要

利用声音信号对配电设备进行状态监测具有廉价、无接触的优势，但也存在强环境噪声干扰的问题。已有研究利用环境噪声与配电变压器运行声音时、频域自相似性差异的采用无类簇参数的聚类算法进行去噪并取得了较好的仿真结果。不同运行工况的变压器故障噪声存在差异。若该去噪方法造成了变压器声音样本的不同运行工况缺漏，筛选后声音样本集可能无法包含早期故障的声音样本导致后续状态识别环节漏判。因此文中以位于不同工作环境的箱式变压器为例，根据配电设备运行声音与环境噪声时、频域自相似性差异，筛选出不受环境噪声干扰的声音样本。通过平稳声音片段与配电变压器不同运行工况的时间分布特性，论证了该方法能覆盖配电变压器全运行工况，为后续基于声音信号的配电变压器状态监测用于生产实践提供有力支撑。

Abstract

The use of sound signals for condition monitoring of power distribution equipment offers the advantages of being low coat and contactless. It

however

also has the drawback of being susceptible to strong ambient noise. Existing study has sucessfully denoised sound signals by leveraging the differences in time-frequency domain selfsimilarity between ambient noise and distribution transformer operating sounds through the use of a parameter-free clustering algorithm

achieving promising simulation results. The fault noise of transformer under different operating conditions has diefrence. If the denoising method causes the leakage of transformer sound signal samples in different operating conditions

the sound sample set after screening may not contain the early fault sound samples

resulting in misjudgment in the subsequent state recognition process. Therefore

in this paper the box transformers in different working environments are taken as an example

the sound samples free from the interference of environmental noise are screened out in accordance with the time and frequency domain self-similarity differences between the operating sound of distribution equipment and the environmental noise. It is proved through the time distribution characteristics of stationary sound segments and distribution transformers in different operating conditionsthat the meth od can cover all operating conditions of distribution transformers

which provides a strong support for the subsequent state monitoring of distribution transformers based on sound signal for production practice.

关键词

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references

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