Paper Titles

Preface, Committees and Sponsors

A One Stage Damage Detection Technique Using Spectral Density Analysis and Parallel Genetic Algorithms
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Application of Wavelet Parameters for Impact Damage Detection in Plates
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A Framework for Reliability Assessment of an In-Service Bridge Using Structural Health Monitoring Data
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Modeling of Environmental Effects for Vibration-Based SHM Using Recursive Stochastic Subspace Identification Analysis
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Modal Acoustic Emission Investigation for Progressive Failure Monitoring in Thin Composite Plates under Tensile Test
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Laser Lock-In Thermography for Fatigue Crack Detection
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In Situ Blade Deflection Monitoring of a Wind Turbine Using a Wireless Laser Displacement Sensor Device within the Tower
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HomeKey Engineering MaterialsKey Engineering Materials Vol. 558A One Stage Damage Detection Technique Using...

A One Stage Damage Detection Technique Using Spectral Density Analysis and Parallel Genetic Algorithms

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Abstract:

This paper describes a new global damage identification framework for the continuous/periodic monitoring of civil structures. In order to localize and estimate the severity of damage regions, a one-stage model-based Bayesian probabilistic damage detection approach is proposed. This method, which is based on the response power spectral density of the structure, enjoys the advantage of broadband frequency information and can be implemented on input-output as well as output-only damage identification studies. A parallel genetic algorithm is subsequently used to evolve the optimal model parameters introduced for different damage conditions. Given the complex search space and the need to perform multiple time-consuming objective function evaluations, a parallel meta-heuristic provides a robust optimization tool in this domain. It is shown that this approach is capable of detecting structural damage in both noisy and noise-free environments.

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Structural Health Monitoring: Research and Applications

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Periodical:

Key Engineering Materials (Volume 558)

Pages:

1-11

DOI:

https://doi.org/10.4028/www.scientific.net/KEM.558.1

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Online since:

June 2013

Authors:

Maryam Varmazyar, Nicholas Haritos, Michael Kirley, Tim Peterson

Keywords:

Bayesian Probabilistic Approach, Damage Identification, Parallel Genetic Algorithm (PGA), Power Spectral Density, Severity

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