This article explores the application of intelligent fault detection technology in distribution network automation,focusing on key technologies such as multi-source data fusion processing,fault pattern recognition and prediction,real-time monitoring,and rapid response.By constructing a novel multi-source heterogeneous data fusion processing technology,rapid and accurate fault detection and localization are achieved.Additionally,this article proposes a fault pattern recognition and prediction model that integrates convolutional neural networks and long short-term memory networks,as well as a real-time monitoring and rapid response system based on stream data computation.Simulation experimental results demonstrate that the proposed system outperforms traditional methods in terms of fault detection success rate,localization accuracy,and self-healing recovery time,providing effective support for the intelligent upgrading of distribution networks.
distribution network automationintelligent fault detectionmulti-source data fusion
维普
万方数据
