作　　者： (杨玥）; (张胜军）; (康琪）;

机构地区： 内蒙古电力科学研究院,呼和浩特010020

出　　处： 《内蒙古电力技术》 2017年第4期20-23,共4页

摘　　要： 为实现对电力设备海量数据进行快速准确地分析,正确提供电力设备健康状态的实时评估结果,结合典型数据分析方法,将影响设备评价结果的海量电气特征量进行融合,设计了电力设备状态智能预警系统。该系统由数据集合层、数据融合层、告警级别配置层和告警信息展示层构成,通过对电力设备不同维度数据之间的关联分析,经由设备预警模型和设备预警逻辑判断后生成预警信息,从而达到自动对故障设备准确定位并判断故障类别的预警目标。 In order to analyze the massive data of power equipment quickly and accurately, and correctly provide real-time assessment of the health status, by combining the typical data analysis methods, make the large quantity of electrical characteristic parameters which influence the result of equipment evaluation fuse, an intelligent alert system of power equipment status is designed. The system consists of data collection layer, data fusion layer, alarm level configuration layer and alarm information display layer, based on the correlation analysis between different dimensional data of power equipment, and generate early warning informations through the equipment warning models and logic, so as to automatically locate the fault device and determine the fault category of the early warning target.

关 键 词： 状态检修 智能预警 阈值 显著性差异 纵横比