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With the development of sensor technology, when facing the explosive growth of large power data, the existing data acquisition and monitoring system (SCADA) is increasingly inadequate in data processing ability and lack of intelligence. In this paper, a novel intelligent monitoring system for power distribution equipment based on cloud edge collaborative computing is designed to effectively improve the efficiency and intelligence of mass data processing. At the edge end, an improved intelligent data acquisition device is adopted as the edge computing node, where the original data is collected and uploaded with variable frequency, in order to enhance the value density of data and reduce the network load and cloud load. In addition, data monitoring cloud platform is designed in the cloud, where a data mining model is established by using Apriori frequent item set algorithm, to provide more accurate monitoring and diagnosis services for upper applications, and guide the edge end to conduct intelligent control of devices. The reliability and performance of the designed system are validated by the intelligent monitoring project of box substation power distribution equipment. Keywords-Component; Edge Computing; Cloud Edge Collaboration Computing; Fault Diagnosis

Design of Intelligent Monitoring System for Power Distribution Equipment Based on Cloud Edge Collaborative Computing