This report contains a review of the technical literature concerning the detection, location, and characterization of structural damage via techniques that examine changes in measured structural vibration response. The report first categorizes the methods according to required measured data and analysis technique. The analysis categories include changes in modal frequencies, changes in measured mode shapes (and their derivatives), and changes in measured flexibility coefficients. Methods that use property (stiffness, mass, damping) matrix updating, detection of nonlinear response, and damage detection via neural networks are also summarized. The applications of the various methods to different types of engineering problems are categorized by type of structure and are summarized. The types of structures include beams, trusses, plates, shells, bridges, offshore platforms, other large civil structures, aerospace structures, and composite structures. The report describes the development of the damage-identification methods and applications and summarizes the current state-of-the-art of the technology. The critical issues for future research in the area of damage identification are also discussed.

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Damage identification and health monitoring of structural and mechanical systems from changes in their vibration characteristics: A literature review

This paper provides an overview of methods to detect, locate, and characterize damage in structural and mechanical systems by examining changes in measured vibration response. Research in vibration-based damage identification has been rapidly expanding over the last few years. The basic idea behind this technology is that modal parameters (notably frequencies, mode shapes, and modal damping) are functions of the physical properties of the structure (mass, damping, and stiffness). Therefore, changes in the physical properties will cause detectable changes in the modal properties. The motivation for the development of this technology is presented. The methods are categorized according to various criteria such as the level of damage detection provided, model-based versus non-model-based methods, and linear versus nonlinear methods. The methods are also described in general terms including difficulties associated with their implementation and their fidelity. Past, current, and future-planned applications of this technology to actual engineering systems are summarized. The paper concludes with a discussion of critical issues for future research in the area of vibration-based damage identification.

A summary review of vibration-based damage identification methods

A comprehensive review on modal parameter-based damage identification methods for beam- or plate-type structures is presented, and the damage identification algorithms in terms of signal processing...

Vibration-based Damage Identification Methods: A Review and Comparative Study:

Vibration of cracked structures: A state of the art review

This book focuses on structural health monitoring in the context of machine learning. The authors review the technical literature and include case studies. Chapters include: operational evaluation, sensing and data acquisition, introduction to probability and statistics, machine learning and statistical pattern recognition, and data prognosis.

Structural Health Monitoring: A Machine Learning Perspective

Damage detection from changes in curvature mode shapes

Damage Detection in Structures Using Changes in Flexibility

Modified Chain-code Computer Vision Techniques For Interrogation Of Vibration Signatures For Structural Fault Detection

Technologies of analytical and experimental modal analysis have been investigated for their application in damage detection of bridges. In the context of experiments performed on a typical highway bridge in North Carolina, various signals and signal-processed data that can be used for interrogation are presented. By introducing simulated failures in a highway bridge in Pennsylvania and in a number of laboratory bridge models and analytical models, experimental results are examined for their ability to detect faults.

Modal Technology for Damage Detection of Bridges

. The existence of a global martingale solution to a cross-diﬀusion system with multiplicative Wiener noise in a bounded domain with no-ﬂux boundary conditions is shown. The model describes the dynamics of population densities of diﬀerent species due to segregation cross-diﬀusion eﬀects. The diﬀusion matrix is generally neither symmetric nor positive semideﬁnite. This diﬃculty is overcome by exploiting the Rao entropy structure. The existence proof uses a stochastic Galerkin method, uniform estimates from the Rao entropy inequality, and the Skorokhod–Jakubowski theorem. Furthermore, an exponential equilibration result is proved for suﬃciently small Lipschitz constants of the noise by using the relative Rao entropy. Numerical tests illustrate the behavior of solutions in one space dimension for two and three population species.

M. Biswas

Papers

Damage detection from changes in curvature mode shapes

Damage Detection in Structures Using Changes in Flexibility

Modified Chain-code Computer Vision Techniques For Interrogation Of Vibration Signatures For Structural Fault Detection

Modal Technology for Damage Detection of Bridges

Global martingale solutions to a segregation cross-diffusion system with stochastic forcing