Study on Fault Diagnosis for Power Transformer Based on Cloud Matter Element Analysis Principle and DGA

XIE Qing1; PENG Peng2; TANG Shan3; LI Yan-qing1; ZHENG Na1; L Fang-cheng1

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Study on Fault Diagnosis for Power Transformer Based on Cloud Matter Element Analysis Principle and DGA

更新时间：2025-04-26

- Study on Fault Diagnosis for Power Transformer Based on Cloud Matter Element Analysis Principle and DGA
- High VoltageApparatus Vol. 45, Issue 6, Pages: 74-77+82(2009)
- 作者机构：
  
  1. 华北电力大学电力系统保护与动态安全监控教育部重点实验室
  2. 广东深圳供电公司
  3. 广东大亚湾核电运营管理有限责任公司
- 作者简介：
- 基金信息：
- DOI：
  CLC： TM41
- Published：2009
- 稿件说明：
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[1]谢庆,彭澎,唐山,李燕青,郑娜,律方成.基于云物元分析原理的电力变压器故障诊断方法研究[J].高压电器,2009,45(06):74-77+82.

XIE Qing1, PENG Peng2, TANG Shan3, et al. Study on Fault Diagnosis for Power Transformer Based on Cloud Matter Element Analysis Principle and DGA[J]. High voltageapparatus, 2009, 45(6): 74-77+82.
[1]谢庆,彭澎,唐山,李燕青,郑娜,律方成.基于云物元分析原理的电力变压器故障诊断方法研究[J].高压电器,2009,45(06):74-77+82. DOI：

XIE Qing1, PENG Peng2, TANG Shan3, et al. Study on Fault Diagnosis for Power Transformer Based on Cloud Matter Element Analysis Principle and DGA[J]. High voltageapparatus, 2009, 45(6): 74-77+82. DOI：

摘要

变压器油中溶解气体分析（DGA）是电力变压器故障诊断的重要方法。针对物元理论变压器故障诊断方法中

在建立故障模式物元模型时没有考虑边界值的不确定性的不足

首次在变压器故障诊断研究方面引入云模型

结合云模型的不确定推理特性以及物元理论能同时进行定性定量分析问题的优点

提出了一种基于云物元分析原理和DGA相结合的电力变压器故障诊断新方法。通过建立变压器故障诊断的云物元模型和计算特征云物元与标准云物元之间的关联函数

实现对变压器故障模式的有效识别。实例分析验证了方法的正确性和有效性。

Abstract

Dissolved gas-in-oil analysis（DGA） is an important method to find the hidden or incipient insulation faults of oil-immersed power transformer.Matter element theory was employed to research the fault diagnosis of transformer with qualitative and quantity advantages.However

the method did not consider the uncertain essence of the fault diagnosis of transformer.And in the fact

there were two uncertain characteristic in it

random and fuzzy.Hence a new fault diagnosis method is presented in this paper.The method has two advantages of considering two uncertain characteristic and realizing fault diagnosis qualitatively and quantitatively based on cloud model and matter element theory.By building the cloud matter element models of transformer fault diagnosis and calculating the correlation function of feature matter element models and standard ones

fault modes of transformer are identified effectively.Then

the results of examples research indicate the method is effective.

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Related Institution

International Education Institute, North China Electric Power University

College of Automation,Northwestern Polytechnic University

西北工业大学自动化学院陕西西安710072

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State Key Laboratory of Safety and New Technology of Power Transmission&Distribution Equipment and System,Chongqing University

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