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Author: Soheil Saadat
Publisher:
Published: 2002*
Total Pages: 159
ISBN-13:
DOWNLOAD EBOOKKeywords: system identification, artificial neural networks, non-linear systems, health monitoring and damage detection, progressive damage.
Author:
Publisher:
Published: 2003
Total Pages:
ISBN-13:
DOWNLOAD EBOOKIn 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.
Author: Christopher Niezrecki
Publisher: Springer
Published: 2017-03-20
Total Pages: 99
ISBN-13: 3319541099
DOWNLOAD EBOOKStructural Health Monitoring & Damage Detection, Volume 7: Proceedings of the 35th IMAC, A Conference and Exposition on Structural Dynamics, 2017, the seventh 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 Structural Health Monitoring & Damage Detection, including papers on: Structural Health Monitoring Damage Detection System Identification Active Controls
Author: Daniel Balageas
Publisher: John Wiley & Sons
Published: 2010-01-05
Total Pages: 496
ISBN-13: 0470394404
DOWNLOAD EBOOKThis 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.
Author: Alexandre Cury
Publisher: Springer Nature
Published: 2021-10-23
Total Pages: 490
ISBN-13: 3030817164
DOWNLOAD EBOOKThe 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.
Author: Chunwei Zhang
Publisher: CRC Press
Published: 2024-11-06
Total Pages: 245
ISBN-13: 1040150063
DOWNLOAD EBOOKStructural health monitoring is a powerful tool across civil, mechanical, automotive, and aerospace engineering, allowing the assessment and measurement of physical parameters in real time. Processing changes in the vibration signals of a dynamic system can detect, locate, and quantify any damage existing in the system. This book presents a comprehensive state‐of‐the‐art review of the applications in time, frequency, and time‐frequency domains of signal‐processing techniques for damage perception, localization, and quantification in various structural systems. Experimental investigations are illustrated, including the development of a set of damage indices based on the signal features extracted through various signal‐processing techniques to evaluate sensitivity in damage identification. Chapters summarize the application of the Hilbert–Huang transform based on three decomposition methods such as empirical mode decomposition, ensemble empirical mode decomposition, and complete ensemble empirical mode decomposition with adaptive noise. Also, the chapters assess the performance and sensitivity of different approaches, including multiple signal classification and empirical wavelet transform techniques in damage detection and quantification. Artificial neural networks for automated damage identification are introduced. This book suits students, engineers, and researchers who are investigating structural health monitoring, signal processing, and damage identification of structures.
Author: Izuru Takewaki
Publisher: WIT Press
Published: 2012
Total Pages: 273
ISBN-13: 1845646282
DOWNLOAD EBOOKSystem 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.
Author: Alfred Wicks
Publisher: Springer Science & Business
Published: 2014-04-18
Total Pages: 288
ISBN-13: 3319045709
DOWNLOAD EBOOKThis 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
Author: Christopher Niezrecki
Publisher: Springer
Published: 2018-05-29
Total Pages: 209
ISBN-13: 3319744763
DOWNLOAD EBOOKStructural 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
Author: Hua-Peng Chen
Publisher: John Wiley & Sons
Published: 2018-01-29
Total Pages: 326
ISBN-13: 1119166624
DOWNLOAD EBOOKA critical review of key developments and latest advances in Structural Health Monitoring technologies applied to civil engineering structures, covering all aspects required for practical application Structural Health Monitoring (SHM) provides the facilities for in-service monitoring of structural performance and damage assessment, and is a key element of condition based maintenance and damage prognosis. This comprehensive book brings readers up to date on the most important changes and advancements in the structural health monitoring technologies applied to civil engineering structures. It covers all aspects required for such monitoring in the field, including sensors and networks, data acquisition and processing, damage detection techniques and damage prognostics techniques. The book also includes a number of case studies showing how the techniques can be applied in the development of sustainable and resilient civil infrastructure systems. Structural Health Monitoring of Large Civil Engineering Structures offers in-depth chapter coverage of: Sensors and Sensing Technology for Structural Monitoring; Data Acquisition, Transmission, and Management; Structural Damage Identification Techniques; Modal Analysis of Civil Engineering Structures; Finite Element Model Updating; Vibration Based Damage Identification Methods; Model Based Damage Assessment Methods; Monitoring Based Reliability Analysis and Damage Prognosis; and Applications of SHM Strategies to Large Civil Structures. Presents state-of-the-art SHM technologies allowing asset managers to evaluate structural performance and make rational decisions Covers all aspects required for the practical application of SHM Includes case studies that show how the techniques can be applied in practice Structural Health Monitoring of Large Civil Engineering Structures is an ideal book for practicing civil engineers, academics and postgraduate students studying civil and structural engineering.
