Damage Identification on the Tilff Bridge by Vibration Monitoring Using Optical Fiber Strain Sensors

Reynders, Edwin; Roeck, Guido De; Bakır, Pelin Gündeş; Sauvage, Claude

doi:10.1061/(asce)0733-9399(2007)133:2(185)

Cited by 95 publications

(64 citation statements)

References 8 publications

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“…Optimum solutions of the problem are reached through sensitivity-based constrained optimization algorithms. In recent years, sensitivity-based FE model updating methods have been applied successfully for condition assessment of structures [10,11].…”

Section: Introductionmentioning

confidence: 99%

Damage identification study of a seven-story full-scale building slice tested on the UCSD-NEES shake table

He²,

et al. 2010

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A full-scale seven-story reinforced concrete building section was tested on the UCSD-NEES shake table during the period October 2005 -January 2006. The shake table tests were designed to damage the building progressively through four historical earthquake records. At various levels of damage, ambient vibration tests and low amplitude white noise base excitations with root-mean-square accelerations of 0.03g and 0.05g were applied to the building, which responded as a quasi-linear system with parameters evolving as a function of structural damage.Modal parameters (natural frequencies, damping ratios and mode shapes) of the building were identified at different damage levels based on the response of the building to ambient as well as low amplitude white noise base excitations, measured using DC coupled accelerometers. This paper focuses on damage identification of this building based on changes in identified modal parameters. A sensitivity-based finite element model updating strategy is used to detect, localize and quantify damage at each damage state considered. Three sets of damage identification results 1. Corresponding author. Tel.: +1 858-822-4545; fax: +1 858-822-2260. E-mail address: jpconte@ucsd.edu 2 are obtained using modal parameters identified based on ambient, 0.03g, and 0.05g RMS white noise test data, respectively. The damage identification results obtained in all three cases do not exactly coincide, but they are consistent with the concentration of structural damage observed at the bottom two stories of the building. The difference in the identified damage results is mainly due to the significant difference in the identified modal parameters used in the three cases. The assumption of a quasi-linear dynamic system is progressively violated with increasing level of excitation. Therefore, application of nonlinear FE model updating strategies is recommended in future studies to resolve the errors caused by structural response nonlinearity.

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Section: Introductionmentioning

confidence: 99%

Damage identification study of a seven-story full-scale building slice tested on the UCSD-NEES shake table

He²,

et al. 2010

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“…For example, comparing the natural frequencies of a structure over time, a decreased frequency may indicate damage since a less stiff structure will vibrate at a lower rate (Reynders et al 2007). Similarly, changes in the modal displacements and modal curvatures can be used to deduce the presence and location of damage (Reynders et al 2007). The MAC is a method that gives a scalar value to describe how closely two mode shapes match.…”

Section: Acceleration-based Systems Using Ambient Vibrationmentioning

confidence: 99%

“…where is the mode shape from an analytical model (or baseline measurements) of the pristine structure, and is the mode shape of the structure in its service condition at a later time (Reynders et al 2007). A value of unity indicates perfect correlation between the two mode shapes, and lower values indicate a lesser agreement.…”

Section: Acceleration-based Systems Using Ambient Vibrationmentioning

confidence: 99%

Development of a structural health monitoring system for the life assessment of critical transportation infrastructure.

Roach¹,

Jáuregui

Daumueller

2012

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Recent structural failures such as the I-35W Mississippi River Bridge in Minnesota have underscored the urgent need for improved methods and procedures for evaluating our aging transportation infrastructure. This research seeks to develop a basis for a Structural Health Monitoring (SHM) system to provide quantitative information related to the structural integrity of metallic structures to make appropriate management decisions and ensuring public safety.This research employs advanced structural analysis and nondestructive testing (NDT) methods for an accurate fatigue analysis. Metal railroad bridges in New Mexico will be the focus since many of these structures are over 100 years old and classified as fracture-critical. The term fracture-critical indicates that failure of a single component may result in complete collapse of 4 the structure such as the one experienced by the I-35W Bridge. Failure may originate from sources such as loss of section due to corrosion or cracking caused by fatigue loading. Because standard inspection practice is primarily visual, these types of defects can go undetected due to oversight, lack of access to critical areas, or, in riveted members, hidden defects that are beneath fasteners or connection angles. Another issue is that it is difficult to determine the fatigue damage that a structure has experienced and the rate at which damage is accumulating due to uncertain history and load distribution in supporting members. A SHM system has several advantages that can overcome these limitations. SHM allows critical areas of the structure to be monitored more quantitatively under actual loading. The research needed to apply SHM to metallic structures was performed and a case study was carried out to show the potential of SHM-driven fatigue evaluation to assess the condition of critical transportation infrastructure and to guide inspectors to potential problem areas. This project combines the expertise in transportation infrastructure at New Mexico State University with the expertise at Sandia National Laboratories in the emerging field of SHM.5

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“…Furthermore, actual construction practices often cannot be reproduced in small-/medium-scale test specimens. The few instances of successful application of FE model updating methods for the condition assessment of large-scale structures include the damage identification studies on the Z24 Bridge in Switzerland (Teughels and De Roeck 2004), the use of dynamic strain measurements from fiber optic sensors for FE model updating of the Tilff Bridge (Reynders et al 2007), the use of a neural network method based on modal frequencies and a validated FE model to identify the stiffness reduction in a one-third-scaled one-story concrete frame (Zhou et al 2007), and FE model updating based on identified modal properties of a full-scale composite beam (Moaveni et al 2008) and a full-scale seven-story RC shear wall building slice (Moaveni et al 2010).…”

Section: Introductionmentioning

confidence: 99%

Finite-Element Model Updating for Assessment of Progressive Damage in a 3-Story Infilled RC Frame

et al. 2013

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This paper presents a study on the identification of progressive damage, using an equivalent linear finite-element model updating strategy, in a masonry infilled RC frame that was tested on a shake table. A two-thirds-scale, 3-story, 2-bay, infilled RC frame was tested on the UCSD-NEES shake table to investigate the seismic performance of this type of construction. The shake table tests induced damage in the structure progressively through scaled historical earthquake records of increasing intensity. Between the earthquake tests and at various levels of damage, low-amplitude white-noise base excitations were applied to the infilled RC frame. In this study, the effective modal parameters of the damaged structure have been identified from the white-noise test data with the assumption that it responded in a quasi-linear manner. Modal identification has been performed using a deterministic-stochastic subspace identification method based on the measured input-output data. A sensitivity-based finite-element model updating strategy has been employed to detect, locate, and quantify damage (as a loss of effective local stiffness) based on the changes in the identified effective modal parameters. The results indicate that the method can reliably identify the location and severity of damage observed in the tests.

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Damage Identification on the Tilff Bridge by Vibration Monitoring Using Optical Fiber Strain Sensors

Cited by 95 publications

References 8 publications

Damage identification study of a seven-story full-scale building slice tested on the UCSD-NEES shake table

Damage identification study of a seven-story full-scale building slice tested on the UCSD-NEES shake table

Development of a structural health monitoring system for the life assessment of critical transportation infrastructure.

Finite-Element Model Updating for Assessment of Progressive Damage in a 3-Story Infilled RC Frame

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