and safety of aging structures. The widespread use of Structural Health Monitoring (SHM) systems is limited due to unavailability of specialized data acquisition equipment, high cost of generic equipment, and absence of fully automatic decision support systems.

This paper introduces a new toolbox of graphical-interface software algorithms for the numerical simulation of vibration tests, analysis of modal data, finite element model correlation, and the comparison of both linear and nonlinear damage identification techniques. This toolbox is unique because it contains several different vibration-based damage identification algorithms, categorized as those which use only measured response and sensor location information (“non-model-based” techniques) and those which use finite element model correlation (“model-based ” techniques). Another unique feature of this toolbox is the wide range of algorithms for experimental modal analysis. The toolbox also contains a unique capability that utilizes the measured coherence functions and Monte Carlo analysis to perform statistical uncertainty analysis on the modal parameters and damage identification results. This paper contains a detailed description of the various modal analysis, damage identification, and model correlation capabilities of toolbox, and also shows a sample application which uses the toolbox to analyze the statistical uncertainties on the results of a series of modal tests performed on a highway bridge.

this paper describes a fuzzy logic expert system designed to mimic the human decision process. An expert system allows for easy encoding of expert knowledge as a set of rules. "Fuzziness" of the expert system allows better treatment of the uncertainties of the problem and to simplify the expert system itself. The fuzzy expert system has been designed based on a finite element (FE) model of a simple beam and has provided reliable detection of damage for every tested damage scenario (100% recognition). The same system recognized damages with 100% accuracy, and no false positives or negatives on mode shapes acquired by impact testing and/or non-contact laser vibrometer techniques

Abstract not found

Several methods for damage detection based on identifying changes in strain energy mode shapes have been recently described in the literature. Most of these methods require knowing strain energy distribution for the undamaged structure (baseline strain energy mode shapes). This is especially true for detection of small damages, where changes in the strain energy mode shapes cannot be observed otherwise. Usually, the mode shapes from the structure under test should be compared to the baseline mode shapes to provide sufficient data for damage detection. However, these methods do not cover damage detection on structures where baseline mode shapes cannot be readily obtained, for example, structures with preexisting damage. Conventional methods, like building a finite element model of a structure to be used as a baseline might be an expensive and time-consuming task that can be impossible for complex structures. This paper suggests a method for extraction of localized changes (damage peaks) from strain energy mode shapes based on Fourier analysis of the strain energy distribution. A detailed analytical proof is given for the case of a pinned-pinned beam and a numerical proof for the free-free beam. The analytical predictions have been confirmed both by the finite element model and impact testing experiments on a free-free aluminum beam, including single and multiple damage scenarios.

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This paper introduces a new toolbox of graphical-interface software algorithms for the numerical simulation of vibration tests, analysis of modal data, finite element model correlation, and the comparison of both linear and nonlinear damage identification techniques. This toolbox is unique because it contains several different vibration -based damage identification algorithms, categorized as those which use only measured response and sensor location information ("non-model-based" techniques) and those which use finite element model correlation ("model-based" techniques). Another unique feature of this toolbox is the wide range of algorithms for experimental modal analysis. The toolbox also contains a unique capability that utilizes the measured coherence functions and Monte Carlo analysis to perform statistical uncertainty analysis on the modal parameters and damage identification results.

A method is derived to detect and localize linear damage in a structure using the measured modal vibration parameters. This method is applicable when the vibration strain energy is stored in the axial or torsional modes, which differentiates it from previously derived strain-energy-based methods. The new method is compared to the previously derived flexibility-change method for comparison. Both methods are verified by application to an analytical eight degree of freedom model. Experimental validation for both methods is also presented by application to an experimental eight degree of freedom spring-mass structure.

report develops methodologies to evaluate the integrity and effectiveness of external bonding of carbon fiber reinforced polymer

Transportation (Contract/Grant Number: DTRT06-G-0011). The composite honeycomb sandwich materials (beams and decks) used in this study were fabricated by Kansas Structural