A fast and robust method for damage detection of truss structures

• Published in: Applied Mathematical Modelling Vol. 68; pp. 368 - 382
• Main Authors: Nobahari, M., Ghasemi, M.R., Shabakhty, N.
• Format: Journal Article
• Language: English
• Published: New York Elsevier Inc 01.04.2019; Elsevier BV
• Subjects: Algorithms; Computation; Damage assessment; Damage detection; Genetic algorithms; Modal frequency; Mode shapes; Optimization algorithm; Residual force vector; Search algorithms; Structural damage; Trusses; Mode shapes; Optimization algorithm; Damage detection; Residual force vector; Modal frequency
• ISSN: 0307-904X; 1088-8691; 0307-904X
• DOI: 10.1016/j.apm.2018.11.025

•This paper proposes a two-stage damage detection method for truss structures.•First stage focused on the damage localization and in the second stage, the damage severities are evaluated.•To localize the suspected damaged elements, using the concept of residual force vector, a new index is proposed.•To evaluate the damage severities, the damage detection problem formulated as an optimization problem and solved by GA. Use of optimization search algorithms is recognized as an efficient method for solving structural damage identification problems. Although these algorithms demonstrated their robustness to identify the location and extent of multiple damages in structural systems, they impose so much computational efforts to the damage assessing process that it reduces their attraction. In this paper by utilizing the concept of residual force vector, an efficient approach based on a Truss Element Damage Index (TEDI) is defined to assist in a fast and reliable prediction of damaged elements. Based on the proposed technique, the first step focuses on location detection of most probable damaged members. The healthy members will then be eliminated from the total list of variables. This can reduce the computational effort significantly. In the second step to identify damaged locations and severities, the Genetic Algorithm is employed to search for the optimum solution in the new search space resulted from the first step. Three test examples are considered to investigate the efficiency of proposed method for damage identification.