Research on edge-side simplified feature set extraction and short message transmission mechanism for partial discharge of distribution network equipment
Detection of partial discharge(PD)can effectively reflect latent defects and faults in power equipment,which is one of the important means of power grid monitoring.With the surge in the number of power equipment,especially in the distribution network equipment,massive PD monitoring data intensifies the burden of calculation,transmission and storage in the system.Therefore,this paper proposes a distributed sensing network based on wire-less sensor network,selects LoRa as the main transmission means,and constructs a short message transmission mechanism to improve data transmission efficiency.Secondly,the original feature set is selected based on the typi-cal partial discharge data of the switchgear,and an 8-dimension simplified feature set is constructed by using the method of variance analysis and edge computing to achieve data simplification and idle computing power utilization.Finally,the monitoring performance of the network is evaluated from four aspects:recognition accuracy,transmis-sion density,node power consumption and computation.This paper solves the key problems in the edge side and the transmission side,and provides a certain technical reference for the construction of ubiquitous electric Internet of Things(IoT).
万方数据
维普
