Condition Monitoring and Fault Diagnosis of Distribution Network Based on Artificial Intelligence
In order to improve the operation efficiency and reliability of distribution network,this paper studies the condition monitoring and fault diagnosis of distribution network.Based on artificial intelligence,combined with deep learning technology,real-time monitoring and fault diagnosis of distribution network state are carried out,and the running state of distribution network is analyzed in order to identify potential fault modes.In the research process,relying on the big data processing and analysis technology,feature extraction and classification are carried out on the basis of Convolutional Neural Networks(CNN),and time series analysis is carried out on the basis of Recurrent Neural Network(RNN),so as to effectively monitor and diagnose the operation state of the distribution network.The experimental results show that the proposed method has achieved remarkable results in the condition monitoring and fault diagnosis of distribution network,and its diagnostic accuracy reaches 90%,which provides effective technical support for the operation and maintenance of distribution network and can ensure the stable operation of distribution network.
distribution networkcondition monitoringfault diagnosisartificial intelligencedeep learning
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