Download or read book System Identification for Structural Health Monitoring written by Izuru Takewaki and published by WIT Press. This book was released on 2012 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: System identification (SI) techniques are important in reducing gaps between the constructed structural systems and their structural design models and in health monitoring for damage detection. Modal-parameter SI and physical-parameter SI are two major branches in SI.Special character of this book: (1) The physical-parameter SI method explained in this book requires only two accelerometers for measurement of records. Furthermore only a simple manipulation of Fourier transformation is required.(2) The stiffness and damping can be identified simultaneously.(3) The modal parameter SI can supplement or support the result by the physical-parameter SI method.(4) In place of usual low-pass or high-pass filter techniques, a novel noise-bias compensation method is explained. Because the noise itself is not known in many cases, the identification and elimination of noise is a tough problem.(5) A new technique of system identification is explained in the case where an inner vibration source exists.(6) The accuracy of the explained SI methods is examined by the actual recorded data.(7) MATLAB codes are available.This book is intended for Structural Engineers, Mechanical Engineers, Researchers, Graduate and undergraduate students.
Download or read book Identification Methods for Structural Health Monitoring written by Eleni Chatzi and published by Springer. This book was released on 2016-05-25 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt: The papers in this volume provide an introduction to well known and established system identification methods for structural health monitoring and to more advanced, state-of-the-art tools, able to tackle the challenges associated with actual implementation. Starting with an overview on fundamental methods, introductory concepts are provided on the general framework of time and frequency domain, parametric and non-parametric methods, input-output or output only techniques. Cutting edge tools are introduced including, nonlinear system identification methods; Bayesian tools; and advanced modal identification techniques (such as the Kalman and particle filters, the fast Bayesian FFT method). Advanced computational tools for uncertainty quantification are discussed to provide a link between monitoring and structural integrity assessment. In addition, full scale applications and field deployments that illustrate the workings and effectiveness of the introduced monitoring schemes are demonstrated.
Download or read book Applications of Nonlinear System Identification to Structural Health Monitoring written by and published by . This book was released on 2004 with total page 10 pages. Available in PDF, EPUB and Kindle. Book excerpt: The process of implementing a damage detection strategy for aerospace, civil and mechanical engineering infrastructure is referred to as structural health monitoring (SHM). In many cases damage causes a structure that initially behaves in a predominantly linear manner to exhibit nonlinear response when subject to its operating environment. The formation of cracks that subsequently open and close under operating loads is an example of such damage. The damage detection process can be significantly enhanced if one takes advantage of these nonlinear effects when extracting damage-sensitive features from measured data. This paper will provide an overview of nonlinear system identification techniques that are used for the feature extraction process. Specifically, three general approaches that apply nonlinear system identification techniques to the damage detection process are discussed. The first two approaches attempt to quantify the deviation of the system from its initial linear characteristics that is a direct result of damage. The third approach is to extract features from the data that are directly related to the specific nonlinearity associated with the damaged condition. To conclude this discussion, a summary of outstanding issues associated with the application of nonlinear system identification techniques to the SHM problem is presented.
Download or read book Structural Health Monitoring written by Daniel Balageas and published by John Wiley & Sons. This book was released on 2010-01-05 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is organized around the various sensing techniques used to achieve structural health monitoring. Its main focus is on sensors, signal and data reduction methods and inverse techniques, which enable the identification of the physical parameters, affected by the presence of the damage, on which a diagnostic is established. Structural Health Monitoring is not oriented by the type of applications or linked to special classes of problems, but rather presents broader families of techniques: vibration and modal analysis; optical fibre sensing; acousto-ultrasonics, using piezoelectric transducers; and electric and electromagnetic techniques. Each chapter has been written by specialists in the subject area who possess a broad range of practical experience. The book will be accessible to students and those new to the field, but the exhaustive overview of present research and development, as well as the numerous references provided, also make it required reading for experienced researchers and engineers.
Download or read book Structural System Identification written by Eleni N. Chatzi and published by CRC Press. This book was released on 2018-12-15 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Our built infrastructure comprises an evolving organism, which requires monitoring and diagnostics throughout its service life in order to ensure a reliable and safe operation. To this end, Structural Identification (St-Id) exploits sensory feedback in order to reveal an abundance of information on the system throughout its life-cycle. The decoding of this information into an adequate representation of the system, may in turn serve as a tool for life-cycle assessment, maintenance planning and early prognosis and warning. This graduate level textbook and professional guide provides both an overview of well-established structural identification methods, as well as an introduction to selected advanced state-of-the-art tools, which are particularly suited for implementation in a practical setting. Both parametric and non-parametric methods are discussed, formulated in the time or frequency domain. The challenging issues of state and parameter identification are addressed. Moreover, special topics pertaining to nonlinear and non-stationarity behavior are further visited. The presented methods are demonstrated using MATLAB, with sample code provided for the featured examples.
Download or read book Structural Health Monitoring and Detection of Progressive and Existing Damage Using Artificial Neural Networks based System Identification written by Soheil Saadat and published by . This book was released on 2002* with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt: Keywords: system identification, artificial neural networks, non-linear systems, health monitoring and damage detection, progressive damage.
Download or read book The 4th International Workshop on Structural Control written by Andrew Smyth and published by DEStech Publications, Inc. This book was released on 2005 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents the research and applications on sensing technologies to monitor and control the structure and health of buildings, bridges, installations, and other constructed facilities.
Download or read book Structural Health Monitoring Based on Data Science Techniques written by Alexandre Cury and published by Springer Nature. This book was released on 2021-10-23 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: The modern structural health monitoring (SHM) paradigm of transforming in situ, real-time data acquisition into actionable decisions regarding structural performance, health state, maintenance, or life cycle assessment has been accelerated by the rapid growth of “big data” availability and advanced data science. Such data availability coupled with a wide variety of machine learning and data analytics techniques have led to rapid advancement of how SHM is executed, enabling increased transformation from research to practice. This book intends to present a representative collection of such data science advancements used for SHM applications, providing an important contribution for civil engineers, researchers, and practitioners around the world.
Download or read book Structural Health Monitoring written by Charles R. Farrar and published by John Wiley & Sons. This book was released on 2012-11-19 with total page 735 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by global leaders and pioneers in the field, this book is a must-have read for researchers, practicing engineers and university faculty working in SHM. Structural Health Monitoring: A Machine Learning Perspective is the first comprehensive book on the general problem of structural health monitoring. The authors, renowned experts in the field, consider structural health monitoring in a new manner by casting the problem in the context of a machine learning/statistical pattern recognition paradigm, first explaining the paradigm in general terms then explaining the process in detail with further insight provided via numerical and experimental studies of laboratory test specimens and in-situ structures. This paradigm provides a comprehensive framework for developing SHM solutions. Structural Health Monitoring: A Machine Learning Perspective makes extensive use of the authors’ detailed surveys of the technical literature, the experience they have gained from teaching numerous courses on this subject, and the results of performing numerous analytical and experimental structural health monitoring studies. Considers structural health monitoring in a new manner by casting the problem in the context of a machine learning/statistical pattern recognition paradigm Emphasises an integrated approach to the development of structural health monitoring solutions by coupling the measurement hardware portion of the problem directly with the data interrogation algorithms Benefits from extensive use of the authors’ detailed surveys of 800 papers in the technical literature and the experience they have gained from teaching numerous short courses on this subject.
Download or read book Structural Health Monitoring and Detection of Progressive and Existing Damage Using Artificial Neural Networks Based System Identification written by and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent decades, the growing number of civil and aerospace structures has accelerated the development of damage detection and health monitoring approaches. Many are based upon non-destructive and non-invasive sensing and analysis of structural characteristics, and most use structural response information to identify the existence, location, and time of damage. Model based techniques such as parametric and non-parametric system identification seek to identify changes in the parameters of a dynamic structural model. Restoring forces in real structures can exhibit highly non-linear characteristics, thus accurate non-linear system identification is critical. Parametric system identification approaches are commonly used, but these require a priori assumptions about restoring force characteristics. Non-parametric approaches do not require such information, but they typically lack direct associations between the model and the structural dynamics, providing limited utility for accurate health monitoring and damage detection. This dissertation presents a novel 'Intelligent Parameter Varying' (IPV) health monitoring and damage detection technique that accurately detects the existence, location, and time of damage occurrence without any assumptions about the constitutive nature of structural non-linearities. This technique combines the advantages of parametric techniques with the non-parametric capabilities of artificial neural networks by incorporating artificial neural networks into a traditional parametric model. This hybrid approach benefits from the effectiveness of traditional modeling approaches and from the adaptation and learning capabilities of artificial neural networks. The generality of this IPV approach makes it suitable to a wide range of dynamic systems, including those with non-linear and time-varying characteristics. This IPV technique is demonstrated using a lumped-mass structural model with an embedded array of artificial neural networks. These networks i.
Download or read book Structural Health Monitoring 2000 written by Fu-Kuo Chang and published by CRC Press. This book was released on 1999-09-07 with total page 1104 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprising 102 papers presented by researchers from all over the world, the proceedings of this workshop contain current information about a variety of structural health monitoring technologies, as well as their current and potential applications in various fields. Emphasis is placed on those technologies that are promising for future applications in industry and government and the infrastructures that are needed to support such technological development. The content of the workshop is divided into keynote presentations (ten altogether), aerospace applications, general applications, civil applications, integration and systems, sensors, and signal processing and diagnostic methods. Includes the editor's summary report on the results of the panel discussions and presentations from the First International Workshop on Structural Health Monitoring held at Stanford U. in September 1997. Annotation c. Book News, Inc., Portland, OR (booknews.com)
Download or read book Structural Health Monitoring Photogrammetry DIC Volume 6 written by Christopher Niezrecki and published by Springer. This book was released on 2018-05-29 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: Structural Health Monitoring Photogrammetry & DIC, Volume 6: Proceedings of the 36th IMAC, A Conference and Exposition on Structural Dynamics, 2018, the sixth volume of nine 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 Structural Health Monitoring & Damage Detection, including papers on: Structural Health Monitoring Damage Detection System Identification Active Controls
Download or read book Structural Health Monitoring written by Alessandro Pegoretti and published by SAE International. This book was released on 2018-11-20 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: Structural Health Management (SHM) is a key part of the Integrated Vehicle Health Management (IVHM) approach, whose main aim is to develop an integrated end-to-end system to monitor the overall health of a vehicle. Structural Health Monitoring: Current State and Future Trends, edited by Professor Alessandro Pegoretti, a scholar from the University of Trento in Italy, introduces the reader to recent developments involved in health monitoring of aerospace structures. The chapters, represented by seminal SAE International technical papers, offer an overview of the most recent advances in the sensing techniques for SHM, analysis of SHM data and its applications in aerospace. SHM can allow a continuous in-service inspection of the vehicle, thus reducing the cost associated with manual inspection at predetermined time intervals. The availability of reliable information on the loading conditions and health state of structural components by the implementation of SHM can be beneficial for several reasons, such as: • To prevent catastrophic failure • To reduce the number and the cost of unnecessary inspections • To improve the design of structural parts, with a reduction of the weight and the costs of overdesigned components Structural Health Monitoring: Current State and Future Trends offers a unique perspective on this field.
Download or read book New Trends in Vibration Based Structural Health Monitoring written by Arnaud Deraemaeker and published by Springer Science & Business Media. This book was released on 2012-01-28 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of articles covering the six lecture courses given at the CISM School on this topic in 2008. It features contributions by established international experts and offers a coherent and comprehensive overview of the state-of-the art research in the field, thus addressing both postgraduate students and researchers in aerospace, mechanical and civil engineering.
Download or read book Structural Health Monitoring Volume 5 written by Alfred Wicks and published by Springer Science & Business. This book was released on 2014-04-18 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: This fifth volume of eight from the IMAC - XXXII 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 Structural Dynamics, including papers on: Linear Systems Substructure Modelling Adaptive Structures Experimental Techniques Analytical Methods Damage Detection Damping of Materials & Members Modal Parameter Identification Modal Testing Methods System Identification Active Control Modal Parameter Estimation Processing Modal Data
Download or read book STRUCTURAL SYSTEM IDENTIFICATION AND HEALTH MONITORING written by ELENI N.. DERTIMANIS CHATZI (VASILIS.) and published by . This book was released on 2023 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Smart Sensors for Structural Health Monitoring written by Simon Laflamme and published by MDPI. This book was released on 2019-11-13 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: Smart sensors are technologies designed to facilitate the monitoring operations. For instance, power consumption can be minimized through on-board processing and smart interrogation algorithms, and state detection enhanced through collaboration between sensor nodes. Applied to structural health monitoring, smart sensors are key enablers of sparse and dense sensor networks capable of monitoring full-scale structures and components. They are also critical in empowering operators with decision making capabilities. The objective of this Special Issue is to generate discussions on the latest advances in research on smart sensing technologies for structural health monitoring applications, with a focus on decision-enabling systems. This Special Issue covers a wide range of related topics such as innovative sensors and sensing technologies for crack, displacement, and sudden event monitoring, sensor optimization, and novel sensor data processing algorithms for damage and defect detection, operational modal analysis, and system identification of a wide variety of structures (bridges, transmission line towers, high-speed trains, masonry light houses, etc.).
