Stability Analysis and Fault Detection of Telecommunication Towers Using Decision Tree Algorithm under Wind Speed Condition

This paper presents a decision tree (DT) modeling technique to estimate any increase in the load on telecommunication towers. A structural analysis was done for the lattice and mono-pole towers using TNX Tower software to determine the basic features of the towers, such as tilt angle, deflection, twist, and acceleration. The structure analysis generated a data set based on wind speeds. This data set was then used to train a machine-learning algorithm to estimate the loads on the structure. Any change in the applied loads greater than the loads considered in the design might be identified using such a predictor, allowing appropriate action to be taken in response. Finally, a classification is performed with the support of DT to keep track of the current condition of the tower and determine whether or not the applied load estimated by the algorithm is safe for the tower structure. © 2022 IEEE.