电气技术2025，Vol.26Issue(4)：65-72,8.
基于神经网络和控制图法的换流变铁心夹件电流异常诊断方法
The diagnosis method for abnormal current in converter transformer core and clamps based on neural networks and control chart method
於杨 1陈意 1张豹 2仲金龙 1王静3
作者信息
- 1. 国网江苏省电力有限公司超高压分公司,南京 211102
- 2. 国网江苏省电力有限公司常州供电分公司,江苏 常州 213004
- 3. 国网江苏省电力有限公司常州市金坛区供电分公司,江苏 常州 213004
- 折叠
摘要
Abstract
The online monitoring system for converter transformers is a system that evaluates the transformer condition based on characteristic parameters.This system records various parameters during the operation of the converter transformer,including gas composition in the oil,SF6 gas pressure in the bushings,and leakage current in the core clamps.Among these,the core clamp current is a crucial indicator for determining the grounding condition and insulation strength of the transformer core.However,the internal electromagnetic environment of a converter transformer is quite complex during operation,and due to the limitations of sensor precision and operational conditions,the traditional threshold-based abnormal diagnosis methods for core clamp current have a high false alarm rate,posing challenges for refined operation and maintenance.This paper establishes a neural network-based core clamp current prediction model and uses the error between the predicted values and the online values as the observation metric.An abnormal diagnosis method for core clamp current based on the control chart method is proposed.The feasibility of this method is validated using core clamp current data from a±800kV converter station.The experimental results show that the proposed method can avoid false alarms and accurately diagnose true alarms.关键词
换流变压器/铁心夹件电流/神经网络/多层感知机/控制图法/异常诊断Key words
converter transformer/core and clamps current/neural network/multi-layer perceptron/control chart method/anomaly diagnosis引用本文复制引用
於杨,陈意,张豹,仲金龙,王静..基于神经网络和控制图法的换流变铁心夹件电流异常诊断方法[J].电气技术,2025,26(4):65-72,8.
