Transformer State Assessment Based on Gray Clustering and Evidence Synthesis

MIAO Fei; REN Jianwen; TANG Guoqing; WEI Junjiao

doi:10.13296/j.1001-1609.hva.2016.03.008

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Transformer State Assessment Based on Gray Clustering and Evidence Synthesis

更新时间：2025-04-26

- Transformer State Assessment Based on Gray Clustering and Evidence Synthesis
- High VoltageApparatus Vol. 52, Issue 3, Pages: 50-55(2016)
- 作者机构：
  
  1. 徐州供电公司
  2. 华北电力大学新能源电力系统国家重点实验室
  3. 包头供电局
- 作者简介：
- 基金信息：
- DOI：10.13296/j.1001-1609.hva.2016.03.008
  CLC： TM41
- Published：2016
- 稿件说明：
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[1]苗飞,任建文,汤国庆,魏俊姣.基于灰色聚类与证据合成的变压器状态评估[J].高压电器,2016,52(03):50-55.

MIAO Fei, REN Jianwen, TANG Guoqing, et al. Transformer State Assessment Based on Gray Clustering and Evidence Synthesis[J]. High voltageapparatus, 2016, 52(3): 50-55.
[1]苗飞,任建文,汤国庆,魏俊姣.基于灰色聚类与证据合成的变压器状态评估[J].高压电器,2016,52(03):50-55. DOI： 10.13296/j.1001-1609.hva.2016.03.008.

MIAO Fei, REN Jianwen, TANG Guoqing, et al. Transformer State Assessment Based on Gray Clustering and Evidence Synthesis[J]. High voltageapparatus, 2016, 52(3): 50-55. DOI： 10.13296/j.1001-1609.hva.2016.03.008.

摘要

针对变压器状态信息的不确定性

建立了变压器层次化状态评估模型

组建了变压器的状态指标体系

综合指标的主、客观权重设计了其最优权重。运用灰色聚类方法对单项指标作聚类分析以得到综合指标所处状态

改进了D-S证据理论中的冲突证据合成规则

将聚类系数作为基本概率赋值函数以评价变压器的整体状态。实例分析结果显示

文中建立的评估模型具有较高的识别准确率

可以有效地把握变压器的运行状态并为变压器实行状态检修提供良好的指导作用。

Abstract

A hierarchical model of transformer state assessment is built by taking uncertain information of transformer into consideration. A transformer state index system is established. The indexes can be given optimal weights by considering their subjective and objective weights. The gray clustering method is used to cluster every index to get the state of comprehensive indexes. The rules of conflict evidence synthesis in D-S evidence theory are improved

and the clustering coefficient is taken as a function of basic probability assignment for assessing the overall state of transformer. Practical example shows that the proposed model is simple

effective

and accurate

and it may be applied to condition-based maintenance of transformers.

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