高压电器2025，Vol.61Issue(9)：50-57,8.DOI:10.13296/j.1001-1609.hva.2025.09.007
融合历史案例与监测数据的GIS设备智能状态评估
Intelligent Condition Assessment of GIS Integrating Historical Cases and Monitoring Data
摘要
Abstract
Gas insulated switchgear(GIS)has been widely used in power grid due to its excellent performance,and it is necessary to assess its insulation condition to ensure safe and stable operation of power grid.However,the analysis of traditional GIS condition assessment model is only based on the partial discharge data collected from sensors,and the information recorded in numbers of historical cases is ignored,which makes it difficult to improve the accuracy of the model.Therefore,a GIS intelligence condition assessment model combined with historical cases is proposed in this paper.First,the partial discharge data of GIS over the past 5 days is analyzed by using the convolutional neural network,and the feature vectors of the partial discharge pattern are extracted.Then,the characters in the case text are converted into word embedding vectors by using the word embedding model,and the case feature vectors of the text are extracted by using the long short-term memory(LSTM)neural network.Finally,the pattern feature vector and the case feature vector are added,and LSTM is used for information analysis to eventually obtain the insulation condition of GIS.The verification on the actual samples collected by the power company is performed,showing tat the algorithm proposed in this paper can effectively assess the insulation conditon of GIS,and the effect is improved by 11.45%compared to the traditional models.关键词
局部放电/状态评估/GIS/神经网络Key words
partial discharge/condition assessment/GIS/neural networks引用本文复制引用
周录波,田嘉鹏,王栋..融合历史案例与监测数据的GIS设备智能状态评估[J].高压电器,2025,61(9):50-57,8.基金项目
国家电网有限公司科技项目资助(SGSHCG00ZSJS2200419).Project Supported by Science and Technology Projects of State Grid Corporation of China(SGSHCG00ZSJS2200419). （SGSHCG00ZSJS2200419）
