Research on Fault Diagnosis of Power Communication Network Based on Improved Convolutional Neural Network
Zhongmiao Kang, Shina Xu, Zanhong Wu, Peiming Zhang · 2022 4th International Conference on Communications, Information System and Computer Engineering (CISCE) · 2022
With the increasing complexity of power grid construction, traditional power maintenance methods are difficult to meet the current grid maintenance needs. Based on the needs of new smart grid communication system maintenance, this paper proposes a power communication network maintenance method based on improved convolutional neural networks. First, establish a model of power communication network failure, analyze modules with more failure probability, and propose a quantitative model to reduce the risk cost of communication failure, and improve it based on the long-short memory deep neural network, and determine the power grid communication based on the output of the model. The strategy of equipment maintenance provides a certain strategy for the construction of smart communication grid.