A DATA-DRIVEN INTELLIGENT EARLY WARNING METHOD FOR TRANSMISSION TOWER TILT

Aiming at the problem of transmission tower tilt caused by unstable geological structure, this paper proposes a data-driven intelligent early warning technology for transmission tower tilt. First, by introducing the static finite element theory of the transmission tower structure, the finite element model of the transmission tower structure is constructed. Then, the load loading method and calculation process in the transmission tower structure model are described in detail. Second, we analyse the deployment of the tower structure monitoring system and the execution process of the finite element program and introduce the monitoring and early warning workflow, and finally give a judgement and early warning strategy for the deflection and tilt of the tower structure. The proposed early warning technology can use various monitoring data to perform real-time calculation of finite element program, and realise real-time early warning evaluation according to deflection and tilt thresholds. The experimental results show that the error between the actual measured value and the predicted value of the Tensile steel pipe rod tower by the early warning system is only 0.2%, which exceeds 125.25% of the threshold value, and it successfully predicts that its state is in a dangerous state. © 2024 American Society of Civil Engineers (ASCE). All rights reserved.