Boundary Strategy for Optimization-based Structural Damage Detection Problem using Metaheuristic Algorithms

Abstract

The present paper proposes a new strategy namely Boundary Strategy (BS) in the process of optimization-based damage detection using metaheuristic algorithms. This strategy gradually neutralizes the effects of structural elements that are healthy in the optimization process. BS causes the optimization method to find the optimum solution better than conventional methods that do not use the proposed BS. This technique improves both aspects of the accuracy and convergence speed of the algorithms in identifying and quantifying the damage. To evaluate the performance of the developed strategy, a new damage-sensitive cost function, which is defined based on vibration data of the structure, is optimized utilizing the Shuffled Shepherd Optimization Algorithm (SSOA). Different examples including truss, beam, and frame are investigated numerically in order to indicate the applicability of the proposed technique. The proposed approach is also applied to other well-known optimization algorithms including TLBO, GWO, and MFO. The obtained results illustrate that the proposed method improves the performance of the utilized algorithms in identifying and quantifying of the damaged elements, even for noise-contaminated data.

Efficiency of the slime mold algorithm for damage detection of large‐scale structures

“…Prey matrix and stepsize i ! can be determined by the mathematical relations, which are presented in Faramarzi et al [62] State #2: The velocity of predator [62] is equal to that of the prey, 1 3 Maximum_Iterations < Iteration < 2 3 Maximum_Iterations.…”

“…Not every structure is always in an ideal state, and it may experience different situations such as strong earthquakes, cyclic and extreme loading, erosion, and temperature variations. [ 1 ] To extend a structure's service life, provide safety, and avoid human disasters, damaged elements should be identified and replaced with healthy ones. [ 2 ] Finite element methods have become the most popular techniques used for numerical modeling of structural behavior.…”

Development of Structural Damage Detection Method Working with Contaminated Vibration Data via Autoencoder and Gradient Boosting

“…An intelligent structural damage detection system [1][2][3] is an indispensable and critical component of smart structures because it can timely provide an accurate evaluation of the actual state of a structure with reduced manual labor and a low budget. Towards an intelligent structural damage detection (SDD) application, using vibration signal [4] for performing SDD tasks is a convenient way compared to other methods such as manual visual inspection, impact test, etc., since it can be carried out when the structure is in daily service condition and exposed to random operational and environmental loads, without requiring any interruption.…”

A hybrid PSO and Grey Wolf Optimization algorithm for static and dynamic crack identification

“…Mishra et al [36] compared the performance of 10 optimization algorithms in vibrational response in large scale unique trusses. And several new optimization algorithms were used to solve the damage identification problems [37][38][39][40][41][42]. presented an approach for damage identification based on improved ANN and damage indicator.…”