Bridge damage detection using rotation measurements – Experimental validation. (1st January 2020)

• Record Type: Journal Article
• Authors: Huseynov, F.; Kim, C.; OBrien, E.J.; Brownjohn, J.M.W.; Hester, D.; Chang, K.C
• Is Part Of: Mechanical systems and signal processing. Volume 135(2019)
• Publication Date: 2020-01-01
• Subjects: Bridge damage detection -- Rotation measurements -- Inclinometers -- Influence line -- Health monitoring -- SHM; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2019.106380
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: Rotation is a sensitive parameter for identifying damage in a bridge. Rotation can be accurately measured using a high-grade DC accelerometer. Difference in rotation influence lines for healthy and damaged states successfully identifies damage in a model bridge. For simply supported bridges, supports are optimum sensor locations for damage identification. Abstract: This paper presents a novel bridge condition assessment methodology using direct rotation measurements. Initially, numerical analyses are carried out to develop the theoretical basis of the proposed bridge damage detection methodology. As a result of this study the difference in rotation influence lines obtained for healthy and damaged bridge states is proposed as a damage indicator. The sensitivity of rotation to damage and the effect of sensor locations on sensor sensitivities are investigated. Subsequently, extensive laboratory experiments are conducted on a 5.4 m long simply supported bridge structure in an effort to validate the results from the numerical analyses. The test structure is instrumented with rotation sensors and axle detectors and loaded with a four-axle moving vehicle. In this study, rotations are measured using high grade uniaxial accelerometers. The procedure of measuring rotations using accelerometers is explained within the scope of this study. To test the robustness of the proposed bridge condition assessment methodology, a wide range of single and multiple damage scenarios is investigated and the results from this study show that the proposed methodology can successfully identify damage on a bridge. For the model considered, damage as low as 7% change in stiffness over an extent of 2.5% bridge span is shown to be detectable.