Damage identification in a complex truss structure using modal characteristics correlation method and sensitivity-weighted search space. (January 2019)

• Record Type: Journal Article
• Authors: Nguyen, Khac-Duy; Chan, Tommy HT; Thambiratnam, David P; Nguyen, Andy
• Other Names: Nguyen Andy guest-editor.; Chan Tommy HT guest-editor.; Zhu Xinqun guest-editor.
• Is Part Of: Structural health monitoring. Volume 18:Number 1(2019)
• Page Start: 49
• Page End: 65
• Publication Date: 2019-01
• Subjects: Damage identification -- modal strain energy -- correlation-based method -- genetic algorithm -- search space -- complex truss structure; Structural health monitoring -- Periodicals; Structural stability -- Periodicals; Strength of materials -- Periodicals; Nondestructive testing -- Periodicals; Constructions -- Stabilité -- Périodiques; Résistance des matériaux -- Périodiques; Contrôle non destructif -- Périodiques; Electronic journals; 624.17
• DOI: 10.1177/1475921718809471
• Languages: English
• ISSNs: 1475-9217

Abstract

Damage identification for complex structures is a challenging task due to the large amount of structural elements, limited number of measured modes and uncertainties in referenced numerical models. This article presents a study on enhancing the effectiveness of modal characteristics correlation methods for damage identification of complex structures. First, a correlation method using change in the ratio of modal strain energy to eigenvalue is introduced. Damage information is determined via a forward approach by optimizing the correlation level between the patterns of the analytical and measured changes in the ratio of modal strain energy to eigenvalue. Different from traditional optimization-based forward methods that require accurate numerical models, damage sensitivity coefficients of the ratio of modal strain energy to eigenvalue are directly estimated from the experimental modal information. To enhance the damage identification capability, both the elemental modal strain energy–eigenvalue ratio and the total modal strain energy–eigenvalue ratio components are examined in the correlation function. Second, a sensitivity-weighted search space scheme incorporated with genetic algorithm is developed to overcome the ill-posed problem that causes false detection errors. Finally, the correlation method and the enhanced technique are experimentally tested on a complex truss model with nearly 100 elements. To deal with the huge number of degrees of freedom in this structure, a multi-layout roving test with the adoption of redundant channels is designed, and a three-criterion strategy is used for the selection of modes. Results demonstrate the effectiveness of the proposed damage assessment framework to locate and estimate damage in complex truss structures.