基于改进层次聚类的同家族变压器状态变化规律分析

Condition evolution regularity analysis of power transformer in the same family based on improved hierarchical clustering

在变压器状态综合评估的研究中,家族质量缺陷史对变压器健康状态有重要影响,目前多是凭专家经验主观确定。提出利用层次聚类分析技术对同家族变压器状态变化规律进行分析,根据分析结果定量计算家族质量缺陷史对变压器健康状态的影响程度。为提高聚类的准确性,提出用变压器状态变化曲线的斜率距离作为曲线形状的相似性判据,同时用曲线间点数值距离和斜率距离构成交集约束判据进行聚类。实例分析表明改进的层次聚类算法优于传统的层次聚类算法,由聚类分析结果计算家族质量缺陷史对变压器健康状态的影响得出的结果更合理。

Family quality default history affects the healthy condition of power transformer greatly in integrated condition assessment. And now, it is usually subjectively decided by expert＇s experience. A new quantitatively computing method is proposed, that is, using hierarchical clustering technology to analyze the potential evolution regularity and then computing the influence degree of family quality default history on healthy condition of power transformer. To make the clustering result more accurate, line slope distance of condition evolution is proposed as line shape similarity criterion, both data distance criterion and line slope distance criterion are used to cluster data. The experimental result shows that our method is better than traditional hierarchical clustering method, and it is more reasonable to use clustering analysis to calculate the influence degree of family quality default history on power transformer healthy condition.