Vibration based Structural Health Monitoring using output-only measurements under changing environment

Structural damage diagnosis under varying environmental conditions—Part I: A linear analysis

Structural health monitoring and damage detection techniques are tools of great importance in the off-shore, civil, mechanical and aeronautical engineering communities, both for safety reasons and because of the economic benefits that can result. The need to be able to detect damage in complex structures has led to the development of a vast range of techniques, of which many are based upon structural vibration analysis. In the present article, some of the latest advances in Structural Health Monitoring and Damage Detection are reviewed, with an emphasis on composite structures on the grounds that this class of materials currently has a wide range of engineering applications. FOREWORD-It should be noted that this review is not intended to be a general, all-encompassing review covering the whole range of structural health monitoring (SHM); it was planned as the starting point for a study focusing on damage detection, localization and assessment for certain kinds of structure. Thus, the line of thought behind the search and the structure of this review is a result of objectives beyond the scope of the paper itself. Nevertheless, it was considered that, once the above was understood, an updated synopsis such as this could also be useful for other researchers in the same field. ©2006 SAGE Publications.

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A review of vibration-based structural health monitoring with special emphasis on composite materials

Vibration based structural health monitoring of an arch bridge: From automated OMA to damage detection

A review of vibration-based damage detection in civil structures : from traditional methods to Machine Learning and Deep Learning applications

Structural damage diagnosis under varying environmental conditions—part II: local PCA for non-linear cases

Null subspace-based damage detection of structures using vibration measurements

This paper presents an application of statistical process control techniques for damage diagnosis using vibration measurements. A Kalman model is constructed by performing a stochastic subspace identification to fit the measured response histories of the undamaged (reference) structure. It will not be able to reproduce the newly measured responses when damage occurs. The residual error of the prediction by the identified model with respect to the actual measurement of signals is defined as a damage-sensitive feature. The outlier statistics provides a quantitative indicator of damage. The advantage of the method is that model extraction is performed by using only the reference data and that no further modal identification is needed. On-line health monitoring of structures is therefore easily realized. When the structure consists of the assembly of several sub-structures, for which the dynamic interaction is weak, the damage may be located as the errors attain the maximum at the sensors instrumented in the ...

Ai-Min Yan

Papers

Structural damage diagnosis under varying environmental conditions—Part I: A linear analysis

Structural damage diagnosis under varying environmental conditions—part II: local PCA for non-linear cases

Null subspace-based damage detection of structures using vibration measurements

Structural damage diagnosis by Kalman model based on stochastic subspace identification

Structural damage diagnosis under changing environmental conditions