基于告警信号文本挖掘的电力调控智能分析和故障诊断技术  

Intelligent Analysis and Fault Diagnosis Technology for Power Regulation Based on Text Mining of Alarm Signals

作　　者：张宁 ZHANG Ning(State Grid Lingshou County Power Supply Company,Shijiazhuang 050500,China)

机构地区：[1]国网灵寿县供电公司,河北石家庄050500

出　　处：《通信电源技术》2023年第20期64-66,共3页Telecom Power Technology

摘　　要：为提高电力调控故障处理效率,避免故障扩大,应用告警信号文本挖掘相关技术,制定一套切实可行的电力调控故障诊断方法。在预处理告警信号文本的基础上确定电力调控故障诊断流程,结合实时告警信号向量化处理情况,应用支持向量机(Support Vector Machine,SVM)对告警信号进行科学分类。以某电力调控系统实际告警信号为例,验证了所提故障诊断方法的有效性和可行性。In order to improve the efficiency of power regulation fault processing and avoid fault expansion,this article proposes an effective power regulation fault diagnosis method based on text mining of alarm signals.First,based on the pre-processing of alarm signal text,the fault diagnosis process of power regulation is determined.At the same time,combined with the real-time alarm signal vectorization processing,Support Vector Machine(SVM)is applied to scientifically classify the alarm signals.Secondly,taking the actual alarm signal of a certain power regulation system as an example,the effectiveness and reliability of the fault diagnosis method in this paper are verified.

关 键 词：电力调控 文本挖掘 向量空间模型 支持向量机(SVM) 

分 类 号：TM76[电气工程—电力系统及自动化]