Over the past 30 years detecting damage in a structure from changes in global dynamic parameters has received considerable attention from the civil, aerospace and mechanical engineering communities. The basis for this approach to damage detection is that changes in the structure's physical properties (i.e., boundary conditions, stiffness, mass and/or damping) will, in turn, alter the dynamic characteristics (i.e., resonant frequencies, modal damping and mode shapes) of the structure. Changes in properties such as the flexibility or stiffness matrices derived from measured modal properties and changes in mode shape curvature have shown promise for locating structural damage. However, to date there has not been a study reported in the technical literature that directly compares these various methods. The experimental results reported in this paper and the results of a numerical study reported in an accompanying paper attempt to fill this void in the study of damage detection methods. Five methods for damage assessment that have been reported in the technical literature are summarized and compared using experimental modal data from an undamaged and damaged bridge. For the most severe damage case investigated, all methods can accurately locate the damage. The methods show varying levels of success when applied to less severe damage cases. This paper concludes by summarizing some areas of the damage identification process that require further study.
This paper extends the study of damage identification algorithms summarized in the accompanying paper 'Comparative study of damage identification algorithms: I. Experiment' to numerical examples. A finite element model of a continuous three-span portion of the I-40 bridges, which once crossed the Rio Grande in Albuquerque, NM, was constructed. Dynamic properties (resonant frequencies and mode shapes) of the undamaged and damaged bridge that were predicted by the numerical models were then correlated with experimental modal analysis results. Once correlated with the experimental results, eight new damage scenarios were introduced into the numerical model including a multiple damage case. Also, results from two undamaged cases were used to study the possibility that the damage identification methods would produce false-positive readings. In all cases analytical modal parameters were extracted from time-history analyses using signal processing techniques similar to those used in the experimental investigation. This study provides further comparisons of the relative accuracy of these different damage identification methods when they are applied to a set of standard numerical problems.
Because the 1-40 Bridges over the Rio Grande were to be razed during the summer of 1993, the investigators were able to introduce damage into the structure in order to test various damage identification methods. To support this research effort, NMSU contracted Los Alamos National Laboratory (LANL) to perform experimental modal analyses, and to develop experimentally verified numerical models of the bridge. Previous reports (LA-12767-MS and LA-12979-MS) summarize the results of the experimental modal analyses and the results obtained from numerical modal analyses conducted with finite element models. This report summarizes the application of five damage identification algorithms reported in the technical literature to the previously reported experimental and numerical modal data.Damage or fault detection, as determined by changes in the dynamic properties or response of structures, is a subject which has received considerable attention in the technical literature beginning approximately 30 years ago, and with a significant increase in reported studies appearing during the last five years. The basic idea is that modal parameters, notably frequencies, mode shapes, and modal damping, are a function of the physical properties of the structure (mass, damping, stiffness, and boundary conditions). Therefore, changes in physical properties of the structure, such as its stiffness or flexibility, will cause changes in the modal properties. Early methods for detecting damage based on changes in the structure's dynamic properties primarily examined changes in the resonant frequencies. However, this parameter has proved to be insensitive to lower levels of damage and does not provide a means to locate the damage. Current methods that have shown promise in both detecting damage at an early stage and locating the damage examine changes in the mode shapes of the structure.The major contribution of this study is a direct comparison of five damage identification methods that were applied to the same experimental and numerical modal data. The experimental data were measured on an actual highway bridge. The numerical data was generated from finite element models of the same bridge that had been benchmarked against the measured response. With the numerical models many more damage scenarios could be investigated to further study the relative accuracy of the various damage identification methods. In all cases, the numerical studies were intended to simulate the measurement techniques that would be used if these methods were to be incorporated into an on-line monitoring system for highway bridges. This restriction implies that dynamic properties must be measured from ambient traffic-induced vibration sources.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.