基于云边缘协同计算的配电设备智能监控系统设计

Xu Erbao, Li Yan, Y. Mingshun, Chen Xi
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引用次数: 1

摘要

随着传感器技术的发展,面对爆发式增长的大电力数据,现有的数据采集与监控系统(SCADA)在数据处理能力上越来越不足,智能化程度也越来越低。为了有效提高海量数据处理的效率和智能化,本文设计了一种基于云边缘协同计算的配电设备智能监控系统。在边缘端,采用改进的智能数据采集设备作为边缘计算节点,对原始数据进行变频采集和上传,增强数据的价值密度,减少网络负载和云负载。此外,在云中设计数据监控云平台,利用Apriori频繁项集算法建立数据挖掘模型,为上层应用提供更精准的监控和诊断服务,引导边缘端对设备进行智能控制。通过箱式变电站配电设备智能监控工程,验证了所设计系统的可靠性和性能。Keywords-Component;边计算;云边缘协同计算;故障诊断
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of Intelligent Monitoring System for Power Distribution Equipment Based on Cloud Edge Collaborative Computing
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
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