Real-Time Online Prediction Method for Structural Strength of Transmission Towers
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摘要: 以某220 kV双回路直线杆塔为对象,建立塔线体系有限元模型,对基础沉降、滑移、均匀和不均匀覆冰等情况下塔线的变形和应力进行参数化分析,提取杆塔支点和导地线挂点位移及杆件应力,建立数据集。将杆塔支点和挂点作为监测点,利用建立的数据集和BP神经网络算法,以监测点位移为输入,建立计算杆塔应力的代理模型。提出利用监测点位移和代理模型快速输出杆塔所有杆件应力,对杆塔结构强度进行实时预测的方法,为输电线路运行状态实时感知及安全预警技术奠定基础。Abstract: Taking a 220 kV double-circuit suspension tower as the research object, this study built a finite-element tower-line system model to parametrically analyze the deformations and stresses of the tower lines in the cases of settlement and slip of the foundation as well as uniform and non-uniform icing. A dataset was created by extracting the displacements of the pivot points on the tower and those of the hanging points of the conductors and ground wires, as well as the stresses of the members. With the pivot points on the tower and the hanging points as the monitoring points, a surrogate model for calculating the stress of the tower was built with the displacements of the monitoring points as the inputs by utilizing the dataset created and the back-propagation (BP) neural network algorithm. A method of predicting the structural strength of the tower in real time by rapidly outputting the stresses of all the members of the tower on the basis of the displacements of the monitoring points and the surrogate model was proposed to pave the way for real-time perception of the operation status of transmission lines and safety early warning technologies.
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Key words:
- transmission tower /
- BP neural network /
- stress distribution /
- surrogate model /
- structural strength
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