Structural Safety Assessment of the Transmission Tower Using Bayesian Network

Abstract

To clarify the disaster-causing factors and preventive measure for the transmission tower, a structural safety assessment method based on Bayesian network is proposed in this study. Firstly, various disaster-causing factors triggering structural damage of transmission towers are systematically analyzed, and three layers network model is constructed based on Bayesian causality. And then, the a priori probability and conditional probability of the network model are quantitatively calculated by combining expert scoring and fuzzy theory. A connectivity tree is formed by building a doxastic map and eliminating elements of the Build Constructive Tree (BuildCT) algorithm. Finally, forward and backward reasoning algorithm using the monitoring data is implemented to capture probabilities of disaster-causing and resulting factors for maintenance. Results shows that the possibility of wind bias tripping is the most feasible factor to be triggered under specific meteorological conditions condition, which is in line with expectation of experts. And strong winds and Serious icing are the key causative factors for tower disconnection and excessive deformation.