System and Damage Identification of Civil Structures


Book Description

In recent years, structural health monitoring has received increasing attention in the civil engineering research community with the objective to identify structural damage at the earliest possible stage and evaluate the remaining useful life (damage prognosis) of structures. Vibration-based, non-destructive damage identification is based on changes in dynamic characteristics (e.g., modal parameters) of a structure for identifying structural damage. Experimental modal analysis (EMA) has been used as a technology for identifying modal parameters of a structure based on its measured vibration data. It should be emphasized that the success of damage identification based on EMA depends strongly on the accuracy and completeness of the identified structural dynamic properties. The objective of the research work presented in this thesis is to develop new, and improve/extend existing system identification and damage identification methods for vibration based structural health monitoring. In the first part of the thesis, a new system identification method is developed to identify modal parameters of linear dynamic systems subjected to measured (known) arbitrary dynamic loading from known initial conditions. In addition, a comparative study is performed to investigate the performance of several state-of-the-art input-output and output-only system identification methods when applied to actual large structural components and systems. In the second part of the thesis, a finite element model updating strategy, a sophisticated damage identification method, is formulated and computer implemented. This method is then successfully applied for damage identification of two large test structures, namely a full-scale sub-component composite beam and a full-scale seven-story R/C building slice, at various damage levels. The final part of the thesis investigates, based on numerical response simulation of the seven-story building slice, the effects of the variability/uncertainty of several input factors on the variability/uncertainty of system identification and damage identification results. The results of this investigation demonstrate that the level of confidence in the damage identification results obtained through FE model updating is a function of not only the level of uncertainty in the identified modal parameters, but also choices made in the design of experiments (e.g., spatial density of measurements) and modeling errors (e.g., mesh size).




Dynamics of Civil Structures, Volume 2


Book Description

Dynamics of Civil Structures, Volume 2: Proceedings of the 35th IMAC, A Conference and Exposition on Structural Dynamics, 2017, the second volume of ten from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of the Dynamics of Civil Structures, including papers on: Modal Parameter Identification Dynamic Testing of Civil Structures Control of Human Induced Vibrations of Civil Structures Model Updating Damage Identification in Civil Infrastructure Bridge Dynamics Experimental Techniques for Civil Structures Hybrid Simulation of Civil Structures Vibration Control of Civil Structures System Identification of Civil Structures




Damage Identification of Civil Structures Via Response Reconstruction


Book Description

To ensure the safety and functionality of civil structures, it is vital to detect and quantify structural deteriorations in a timely manner for remedial work, before these deteriorations propagate and become detrimental to the entire structure. Structural health monitoring has been developing in past two decades, aiming to continually monitor loading conditions and assess structural conditions so that prompt decisions can be made if any damage is detected and quantified. Vibration-based damage identification, as a significant focus for structural condition assessment and health monitoring, has been the subject of many research efforts in recent years. Despite considerable progress in the structural health assessment of oil rigs, mechanical systems, and aerospace structures, such assessment still encounters some obstacles when it is applied to complex civil structures. These barriers mainly exhibit the following aspects: (1) the limited number of sensors compared to the number of structural components, which makes it difficult to capture enough dynamic responses for structural condition assessment; (2) the significance of model error, which is due to the difficulty of establishing a finite element (FE) model to represent the real dynamic behavior of large and complex structures; (3) the ill-posedness and non-identifiability of the inverse problem, which is due to the significant dimension of damaged areas corresponding to the numerous structural components; (4) the fact that the higher mode vibrations of cumbersome civil structures, which are more sensitive to local damage, are not easily excited under operating conditions; and (5) the enormous, unaffordable computational demand associated with the large dimensions of discretized FE model matrices and the scope of dynamic FE analysis during iterations.




Deep Learning Applications, Volume 2


Book Description

This book presents selected papers from the 18th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2019). It focuses on deep learning networks and their application in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial environments, and highlights novel ways of using deep neural networks to solve real-world problems. Also offering insights into deep learning architectures and algorithms, it is an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers.




Nonlinear Finite Element Model Updating for Nonlinear System and Damage Identification of Civil Structures


Book Description

Structural health monitoring (SHM) is defined as the capability to monitor the performance behavior of civil infrastructure systems as well as to detect, localize, and quantify damage in these systems. SHM technologies contribute to enhance the resilience of civil infrastructures, which are vulnerable to structural aging, degradation, and deterioration and to extreme events due to natural and man-made hazards. Given the limited financial resources available to renovate or replace them, it is crucial to implement SHM methodologies, which can help detect safety threats at an early stage, evaluate the operational risk of the infrastructure after a catastrophic event, and prioritize the urgency of the repair/retrofit or replacement of these structures. This research focuses on the development of a novel framework for nonlinear structural system identification. This framework consists of updating mechanics-based nonlinear finite element (FE) structural models using Bayesian inference methods. Recognizing structural damage as the manifestation of structural material nonlinearity, the developed framework provides a new methodology for post-disaster SHM and DID of real-world civil structures. This research is subdivided in two parts. The first part investigates the accuracy of state-of-the-art nonlinear FE modeling in predicting the cyclic and dynamic inelastic response behavior of reinforced concrete structural components and systems. Sources of inaccuracy and uncertainty in the FE modeling and simulation approach are investigated by comparing the FE-predicted structural response with high-fidelity experimental results. In the second part of this research, two frameworks for nonlinear FE model updating are proposed, developed, and validated using numerically simulated data. In the proposed frameworks, different Bayesian estimation methods are utilized to update the nonlinear FE model of a civil structure using the recorded input excitation and response of the structure during a damage-inducing earthquake event. The initial frameworks are then extended to output-only nonlinear structural system and damage identification methods. This extension not only overcomes the shortcomings of the initial frameworks in handling unmeasured or noisy input measurements, but also paves the way to a general approach to account for model uncertainties. Finally, a new information-theoretic approach is developed for the purposes of nonlinear FE model identifiability, experimental design, and optimal sensor placement.




Earthquakes and Health Monitoring of Civil Structures


Book Description

Health monitoring of civil structures (HMS) is a new discipline, which contributes to successful and on time detection of damages to structures. This book is a collection of chapters on different topics written by leading scientists in the field. It is primarily focused on the latest achievements in monitoring the earthquake effect upon the health of civil structures. The first chapter of the book deals with the geotechnical and structural aspects of the 2010-2011 Christchurch earthquakes. Further chapters are dedicated to the latest HMS techniques of identification of damage to structures caused by earthquakes. Real time damage detection as well as sensors and acquisition systems used for that purpose are presented. The attention is focused on automated modal analysis, dynamic artificial neural networks and wavelet techniques used in HMS. Particular emphasis is put on wireless sensors and piezo-impendance transducers used for evaluation of seismically induced structural damage. The discussion is followed by presentation of case studies of application of health monitoring for buildings and other civil structures, including a super tall structure. The book ends with a presentation of shaking table tests on physical models for the purpose of monitoring their behaviour under earthquake excitation. Audience The book is primarily intended for engineers and scientists working in the field of application of the HMS technique in earthquake engineering. Considering that real time health monitoring of structures represents a sophisticated approach applying the latest techniques of monitoring of structures, many experts from other industries will also find this book useful.




Topics on the Dynamics of Civil Structures, Volume 1


Book Description

Topics on the Dynamics of Civil Structures, Volume 1, Proceedings of the 30th IMAC, A Conference and Exposition on Structural Dynamics, 2012, the first volume of six from the Conference, brings together 45 contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Structural Dynamics, including papers on: Human Induced Vibrations Bridge Dynamics Operational Modal Analysis Experimental Techniques and Modeling for Civil Structures System Identification for Civil Structures Method and Technologies for Bridge Monitoring Damage Detection for Civil Structures Structural Modeling Vibration Control Method and Approaches for Civil Structures Modal Testing of Civil Structures




Dynamics of Civil Structures, Volume 2


Book Description

Dynamics of Civil Structures, Volume 2. Proceedings of the 34th IMAC, A Conference and Exposition on Dynamics of Multiphysical Systems: From Active Materials to Vibroacoustics, 2016, the second volume of ten from the Conference brings together contributions to this important area of research and engineering. Th e collection presents early fi ndings and case studies on fundamental and applied aspects of Structural Dynamics, including papers on: • Modal Parameter Identifi cation • Dynamic Testing of Civil Structures • Human Induced Vibrations of Civil Structures • Model Updating • Operational Modal Analysis • Damage Detection • Bridge Dynamics • Experimental Techniques for Civil Structures • Hybrid testing • Vibration Control of Civil Structures




Dynamic Methods for Damage Detection in Structures


Book Description

Non destructive testing aimed at monitoring, structural identification and di- nostics is of strategic importance in many branches of civil and mechanical - gineering. This type of tests is widely practiced and directly affects topical issues regarding the design of new buildings and the repair and monitoring of existing ones. The load bearing capacity of a structure can now be evaluated using well established mechanical modelling methods aided by computing facilities of great capability. However, to ensure reliable results, models must be calibrated with - curate information on the characteristics of materials and structural components. To this end, non destructive techniques are a useful tool from several points of view. Particularly, by measuring structural response, they provide guidance on the validation of structural descriptions or of the mathematical models of material behaviour. Diagnostic engineering is a crucial area for the application of non destructive testing methods. Repeated tests over time can indicate the emergence of p- sible damage occurring during the structure's lifetime and provide quantitative estimates of the level of residual safety.




Vibration-based Damage Identification and Health Monitoring of Civil Structures


Book Description

Civil structures undergo progressive deterioration due to ageing under the effects of environmental conditions. This deterioration has become a worldwide concern. In addition, natural and man-made hazards such as earthquakes, hurricanes, and explosions can also cause structural damages or exacerbate existing damage. Vibration-based structural damage identification and health monitoring has been the subject of significant research in structural engineering over the past decade. The research work presented in this dissertation consists of: (1) a comparative study of output-only system identification techniques as applied to the Alfred Zampa Memorial Bridge based on dynamic field test data, through which the performance of different output-only system identification methods applied to the bridge vibration data and corresponding to different excitation sources is investigated; (2) development of a simulation framework for wind-induced ambient vibration response of Vincent Thomas Bridge using a detailed three-dimensional finite element model of the bridge and a state-of-the-art stochastic wind excitation model, which provides a validated framework to study the effects of realistic damage scenarios in long-span cable-supported bridges on their identified modal parameters; (3) damage identification of a full-scale seven-story reinforced concrete building slice tested on the UCSD-NEES shake table using a sensitivity-based finite element model updating strategy based on the modal parameters identified from ambient vibration data; (4) development and implementation of a state-of-the-art long-term continuous monitoring system on the Voigt Bridge Testbed, which will serve as a live laboratory for structural health monitoring technologies; (5) development of an automated system identification procedure for extracting modal parameters of the Voigt Bridge as a function of time; and (6) investigation of the environmental effects on the identified modal parameters of the Voigt Bridge and objective criterion for damage detection under varying environmental conditions. The research work presented and the results obtained in this dissertation contribute significantly to the development of robust and reliable vibration-based structural health monitoring systems for large and complex real-world structures.