Structural identification and damage detection through long-gauge strain measurements. (15th September 2015)

• Record Type: Journal Article
• Authors: Zhang, Jian; Guo, S.L.; Wu, Z.S.; Zhang, Q.Q.
• Is Part Of: Engineering structures. Volume 99(2015:Sep. 15)
• Page Start: 173
• Page End: 183
• Publication Date: 2015-09-15
• Subjects: Long-gauge sensing -- Macro strain -- Signal processing -- Strain modal identification -- Damage detection -- Singular value decomposition; Structural engineering -- Periodicals; Structural analysis (Engineering) -- Periodicals; Construction, Technique de la -- Périodiques; Génie parasismique -- Périodiques; Pression du vent -- Périodiques; Earthquake engineering; Structural engineering; Wind-pressure; Periodicals; 624.105
• DOI: 10.1016/j.engstruct.2015.04.024
• Languages: English
• ISSNs: 0141-0296

Abstract

Highlights: Long-gauge FBG sensors have been used for structural monitoring. Two methods have been proposed for macro strain modal identification. Macro modal strain based damage indexes have been proposed. Abstract: Strain measurements from traditional point-type gauges only reveal structural local information. This feature significantly limits the development and application of strain modal theory in civil engineering. The long-gauge fiber optic strain sensor emerging recently has the unique merit of reflecting both local and global information of a structure by measuring the averaged strain within a long gauge length (e.g., 1–2 m). Based on this advantage, strain modal identification by processing the dynamic macro strain measurement is investigated. First, the macro strain frequency response function is derived based on the mapping relationship between the long gauge strain and displacement. Then, two methods are proposed for structural strain modal identification and their results are compared. Moreover, damage indexes based on identified macro strain modal shapes are investigated for structural damage detection. The example of a steel stringer bridge model successfully illustrates that the proposed methods accurately identify structural macro strain modal shapes, and the results also reveals that macro strain based indexes are much more robust than traditional modal parameter based indexes for structural damage detection.