Quasi-static macrostrain-based structural damage detection with distributed long-gauge fiber Bragg grating sensing. (November 2020)

• Record Type: Journal Article
• Authors: Zhou, Zhenwei; Wan, Chunfeng; Fang, Da; Xie, Liyu; Tang, Hesheng; Yang, Caiqian; Ding, Youliang; Xue, Songtao
• Is Part Of: Journal of intelligent material systems and structures. Volume 31:Number 18(2020)
• Page Start: 2137
• Page End: 2151
• Publication Date: 2020-11
• Subjects: damage detection -- complete ensemble empirical mode decomposition adaptive noise method -- quasi-static macrostrain -- long-gauge fiber Bragg grating sensor; Smart materials -- Periodicals; Intelligent control systems -- Periodicals; Artificial intelligence -- Periodicals; Matériaux intelligents -- Périodiques; Commande intelligente -- Périodiques; Intelligence artificielle -- Périodiques; 620.11
• DOI: 10.1177/1045389X20942320
• Languages: English
• ISSNs: 1045-389X

Abstract

The distributed long-gauge fiber Bragg grating sensing technology has been studied and developed in recent years for structural health monitoring of civil engineering structures. Also, the corresponding damage identification method is one of the research hotspots and still needs to be enhanced. In this article, a novel damage detection method based on the distributed long-gauge fiber Bragg grating sensing technique is proposed to detect and localize damages. The method is based on the advanced complete ensemble empirical mode decomposition adaptive noise algorithm. Measured macrostrain responses from the long-gauge fiber Bragg grating sensors are decomposed into intrinsic mode functions, and the quasi-static macrostrains are extrapolated and extracted. A damage indicator is therefore proposed and built based on the quasi-static macrostrain time history. The effectiveness of the proposed damage detection approach was validated by numerical simulations of a cantilever beam. The robustness of the method was further verified by considering the noise pollution contained within the measured macrostrain. Experiments with a practical cantilever steel beam with different damage scenarios were also conducted and studied. Results proved that the proposed method could not only detect but also locate the damages accurately, and therefore has the promising potential for structural damage detection in civil engineering.