500 kV输电铁塔力学失效分析和失效预测研究

Study on Mechanical Failure Analysis and Failure Prediction of 500 kV Transmission Tower

针对中国南方地区典型覆冰线路,采用有限元仿真方法建立了500 kV输电铁塔的仿真模型,开展了不均匀覆冰下不同覆冰厚度和不同风速等工况的力学特性分析,统计得到铁塔的薄弱点位置规律。基于薄弱点构件的轴向应力和节点位移,开展输电铁塔力学失效分析,并通过基于BP神经网络的输电铁塔力学失效预测方法研究,实现对输电铁塔最大轴向应力和节点位移的预测。结果表明:相同风速和基本冰厚下,长、短档距侧冰厚值相差越大,薄弱点构件轴向应力和节点位移值越大;随着覆冰厚度的增加,风速对节点位移的影响更大;相同冰风荷载下,长档距侧重覆冰对轴向应力和节点位移的影响要大于短档距侧重覆冰;不均匀覆冰工况下,500 kV输电铁塔的薄弱点位置主要分布在输电铁塔塔头地线支架处、上下曲臂连接处、瓶颈处以及铁塔的塔身处。该预测方法可以实现对其最大轴向应力和节点位移的有效预测,为重冰区输电铁塔的失效预测提供了参考。

This paper focuses on typical icing transmission lines in southern China and uses finite element simulation method to establish the simulation model of 500 kV transmission towers.The mechanical characteristics of different icing thicknesses and wind speeds under uneven icing working conditions are analyzed,and the weak point position rules of the towers are statistically obtained.Based on the axial stress and nodal displacement of weak point components,the mechanical failure analysis of the transmission tower was carried out,and the prediction of the maximum axial stress and nodal displacement of the transmission tower was realized through the research of the transmission tower mechanical failure prediction method based on BP neural network.The study results show that the greater the difference between the ice thickness values of the long and short pitch sides,the greater the axial stress and node displacement values of the weak point members under the same wind speed and basic ice thickness.As the thickness of ice cover increases,the influence of wind speed on node displacement becomes greater.Under the same ice wind load,the influence of longpitch heavy icing on axial stress and nodal displacement is greater than that of shortpitch heavy icing.Under uneven icing working conditions,the weak points position of 500 kV transmission towers are mainly distributed at the ground wire support of the tower head,the connection between the upper and lower curved arms,the bottleneck,and the body of the tower.The prediction method can effectively predict the maximum axial stress and nodal displacement providing a reference to the failure prediction of transmission towers in heavy ice areas.