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介绍了为华东电网开发的500kV输变电设备的状态检修系统。在该系统中,采用了如油中溶解气体(DGA)、局部放电(PD)、直流偏磁、铁心接地电流等一系列的在线监测技术及装备,并引入了如人工神经网络(ANN)、粗糙集理论(RST)等高级诊断方法进行运行中变压器故障诊断。实例分析结果表明该状态检修系统的有效性及实用性,有助于对用户提供维修决策支持。
The condition maintenance system of 500kV power transmission and transformation equipment developed for East China Power Grid was introduced. In this system, a series of on-line monitoring technologies and equipment such as DGA, PD, DC bias, core grounding current are adopted, such as artificial neural network (ANN) Rough set theory (RST) and other advanced diagnostic methods for transformer fault diagnosis during operation. The results of the example analysis show that the system is effective and practical, which helps to provide users with maintenance decision support.