油纸绝缘老化状态判别的局部放电特征量

采用多元统计分析方法对传统的局部放电统计特征算子进行了因子分析，从24个统计算子中提取出8个公共因子作为局部放电新特征因子，从而实现数据压缩的目的。提取的新特征因子之间不仅携带了原始统计算子的大部分方差信息，而且彼此独立，具备各自的物理意义。对油纸绝缘扁平气隙模型开展了电-热加速老化试验，并采集不同老化阶段试品的局部放电信号样本，采用新特征因子进行了已知老化状态样本的聚类和线性判别函数构造，进而对未知样本的绝缘老化状态进行判别。该方法基于实验室数据的分析得到了令人满意的结果，并为变压器油纸绝缘老化状态的诊断提供了一种可行的方案。

Partial Discharge Features Applied in Aging Condition Discrimination of Oil-paper Insulation

The multivariate statistical method is introduced in the paper to analyze conventional statistical operators of partial discharge (PD). By using factor analysis, eight new features are extracted from 27 operators that effectively realize the data reduction. These new features not only represent variance information of original operators by a limited number of variables, but also are independent of each other and have their own specific properties. An accelerating electrical-thermal aging test is implemented on an artificial oil-paper model with an internal flat air gap. During the aging test, PD signal acquisition is carried out periodically. By using the new features extracted by the proposed factor analysis method, the clustering and discrimination results of the samples with different aging stages provide significant information in the assessment of oil-paper insulation condition.