Review on the new development of vibration-based damage identification for civil engineering structures: 2010–2019

• Published in: Journal of sound and vibration Vol. 491; p. 115741
• Main Authors: Hou, Rongrong, Xia, Yong
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Ltd 20.01.2021; Elsevier Science Ltd
• Subjects: Algorithms; Artificial intelligence; Civil engineering; Crack propagation; Damage detection; Damage identification; Identification methods; Machine learning; Model updating; Review; Structural damage; Vibration; Vibration analysis; Vibration method; Damage identification; Review; Vibration method; Model updating
• ISSN: 0022-460X; 1095-8568
• DOI: 10.1016/j.jsv.2020.115741

Structural damage identification has received considerable attention during the past decades. Although several reviews have been presented, some new developments have emerged in this area, particularly machine learning and artificial intelligence techniques. This article reviews the progress in the area of vibration-based damage identification methods over the past 10 years. These methods are classified in terms of different damage indices and analytical/numerical techniques used with discussions of their advantages and disadvantages. The challenges and future research for vibration-based damage identification are summarised. This review aims to help researchers and practitioners in implementing existing damage detection algorithms effectively and developing more reliable and practical methods for civil engineering structures in the future.