基于趋势分析的变电站设备异常检测方法

基于时序数据的趋势分析方法, 提出一种基于趋势分析的电力设备绝缘性异常检测方法, 以解决变电站电容型电力设备异常的实时检测问题. 首先, 用在线监测获得的介质损耗因数数据, 通过对监测数据流进行合理分割, 采用最小二乘法将其拟合成直线; 其次，基于拟合直线特征值进行异常趋势的检测分析； 最后， 获得电容型设备的绝缘性异常检测结果. 根据对变电站电容型设备实测数据的分析判断, 验证了该方法的有效性和实用性.

Abnormality Detection Method of Substation Equipment Based on Tendency Analysis

Based on tendency analysis of time series data, the author proposed a method of insulation abnormality detection  based on tendency analysis for power equipment  to solve the problem of real-time detection of abnormal capacitive power equipment in the substation. Firstly, the data of dielectric loss factor obtained from on-line monitoring was used to divide the monitoring data stream reasonably, and the method of least square was used to fit it into a straight line. Secondly, based on the characteristic value of fitting line, the abnormal tendency was detected and analyzed. Finally, the insulation abnormality detection results of capacitive equipment were obtained. According to the analysis and judgement of the measured data of capacitive equipement in the substation, the effectiveness and practicability of the method were verified.