基于灰色聚类与证据合成的变压器状态评估

Transformer State Assessment Based on Gray Clustering and Evidence Synthesis

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。

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.