Research On Wire Icing Monitoring Based On FBG Tension And Inclination Sensor

In order to ensure the stable operation of the power system,Yunnan Power Grid has developed an on-line monitoring system for conductor icing in the heavily icing areas of northeastern Yunnan in recent years.In order to provide the technical basis for DC ice melting for power grid staff,this paper studies the theoretical analytical formula of ice thickness and the layout principle of monitoring sensors.The principle analysis,performance test and calibration of key tension and inclination sensors are carried out.The real-time curve is drawn between the monitoring data and the calculated value of ice thickness,and the icing degree of conductors is analyzed.The main research work of this paper is as follows:(1)The basic mechanical parameters of the vertical plane transmission line without icing are studied,and the angle_of the insulator string deviating from the vertical plane is taken into account.The static equilibrium equation is established in the wind deviation plane,and the equivalent icing thickness mechanism model of transmission line is derived.The tower-line coupling system of transmission line is established,and the mechanical characteristics of the tower-line coupling system under different icing conditions are analyzed by ANSYS simulation,which provides a theoretical basis for the layout of sensors.(2)The detection principle of optical fiber sensor is studied.The key pull sensor and inclination sensor of the icing monitoring system are tested and calibrated.The sensor is applied to a 110 kV transmission line in Yunnan Province.The real-time monitoring data of the sensor are collected,and the ice-covered thickness mechanism model is analyzed.The ice-covered equivalent thickness calculation value is obtained.The monitoring results are analyzed to determine the ice-covered state.(3)In practical application,because the sensor temperature compensation is not in place or other external forces are not completely eliminated,resulting in icing thickness error.In order to solve this problem,a correction model of equivalent thickness of icing is proposed in this paper.A simulated annealing chicken flock-BP neural network nonlinear model between the monitoring data of tension,inclination angle and wind yaw angle and the theoretical calculation error of icing thickness is established,and its calculation results are used to correct the theoretical model.The experimental results show that the proposed method can improve the soft sensing accuracy of ice thickness.