Application of BPNN Optimized by Fireworks Algorithm on Structural Bearing Capacity Analysis of Transmission Tower under Icing Conditions - Jian Guo; Wu Guo (Advances in Civil Engineering)
With the increasing power demand in city development, the construction and application of transmission towers need to meet higher requirements. Icing is an extreme meteorological condition in the world, and icing disasters cause various accidents such as tower collapse and line disconnection of large-area lines every year. Therefore, it is of great significance to study the ultimate bearing capacity of transmission towers under icing conditions. The structural bearing capacity under icing is greatly affected by meteorological conditions and environmental factors, which has strong randomness and complexity, and brings a series of urgent problems to the structural stability of transmission towers. In the paper, the ultimate bearing capacity analysis and failure path research are conducted on the 500 kV linear cathead tower structure, and a structural bearing capacity prediction model based on the fireworks algorithm (FWA) is established. In order to accurately predict the structural bearing capacity, reduce the adverse effects of line icing, and ensure the structural stability of the transmission tower, the FWA is introduced into the neural network model. The self-adjusting mechanism of the local search ability and global search ability of the FWA is used to optimize the optimization process of weights and thresholds in the neural network, and a structural bearing capacity prediction model based on the FWA improved backpropagation neural network (BPNN) is proposed. Through the analysis and calculation of the measured data of the transmission tower in a certain area, and the comparative study with the traditional BPNN and the BPNN optimized by other common algorithms, the analysis and calculation results of the FWA-BPNN model used in this paper are closer to the actual value, the multiple indicators are more superior, and the model is more stable, which can realize the rapid and accurate analysis of the axial stress of tower members and maximum displacement between member nodes of the transmission tower under the icing condition.