Download or read book Vibration based Damage Detection Using Machine Learning Techniques with Application to Offshore Wind Turbines written by Y. Zhang and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Vibration based Techniques For Damage Detection And Localization In Engineering Structures written by Ali Salehzadeh Nobari and published by World Scientific. This book was released on 2018-05-04 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the oil and gas industries, large companies are endeavoring to find and utilize efficient structural health monitoring methods in order to reduce maintenance costs and time. Through an examination of the vibration-based techniques, this title addresses theoretical, computational and experimental methods used within this trend.By providing comprehensive and up-to-date coverage of established and emerging processes, this book enables the reader to draw their own conclusions about the field of vibration-controlled damage detection in comparison with other available techniques. The chapters offer a balance between laboratory and practical applications, in addition to detailed case studies, strengths and weakness are drawn from a broad spectrum of information.
Download or read book Artificial Intelligence Applications for Sustainable Construction written by Moncef L. Nehdi and published by Elsevier. This book was released on 2024-02-13 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence Applications for Sustainable Construction presents the latest developments in AI and ML technologies applied to real-world civil engineering concerns. With an increasing amount of attention on the environmental impact of every industry, more construction projects are going to require sustainable construction practices. This volume offers research evidence, simulation results, and case studies to support this change. Sustainable construction, in fact, not only uses renewable and recyclable materials when building new structures or repairing deteriorating ones, but also adopts all possible methods to reduce energy consumption and waste. The concisely written but comprehensive, practical knowledge put forward by this international group of highly specialized editors and contributors will prove to be beneficial to engineering students and professionals alike. Presents convincing “success stories that encourage application of AI-powered tools to civil engineering Provides a wealth of valuable technical information to address and resolve many challenging construction problems Illustrates the most recent shifts in thinking and practice for sustainable construction
Download or read book Vibration based SHM for Detection and Localization of Damage Application to Wind Turbine Blades written by Yaowen Ou and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 Experimental Vibration Analysis for Civil Engineering Structures written by Maria Pina Limongelli and published by Springer Nature. This book was released on 2023-08-28 with total page 782 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents peer-reviewed contributions from the 10th International Conference on Experimental Vibration Analysis for Civil Engineering Structures (EVACES), held in Milan, Italy on August 30-September 1, 2023. The event brought together engineers, scientists, researchers, and practitioners, providing a forum for discussing and disseminating the latest developments and achievements in all major aspects of dynamic testing for civil engineering structures, including instrumentation, sources of excitation, data analysis, system identification, monitoring and condition assessment, in-situ and laboratory experiments, codes and standards, and vibration mitigation. The topics included but were not limited to: damage identification and structural health monitoring; testing, sensing and modeling; vibration isolation and control; system and model identification; coupled dynamical systems (including human–structure, vehicle–structure, and soil–structure interaction); and application of advanced techniques involving the Internet of Things, robot, UAV, big data and artificial intelligence.
Download or read book Rotating Machinery Hybrid Test Methods Vibro Acoustics Laser Vibrometry Volume 8 written by Dario Di Maio and published by Springer. This book was released on 2017-03-27 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rotating Machinery, Hybrid Testing, Vibro-Acoustics & Laser Vibrometry, Volume 8: Proceedings of the 35th IMAC, A Conference and Exposition on Structural Dynamics, 2017, the eighth 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 Rotating Machinery, Hybrid Testing, Vibro-Acoustics & Laser Vibrometry, including papers on: Rotating Machinery Vibro-Acoustics Experimental Techniques Advances in Wind Energy Scanning Laser Doppler Vibrometry Methods Hybrid Test Methods
Download or read book Condition Monitoring with Vibration Signals written by Hosameldin Ahmed and published by John Wiley & Sons. This book was released on 2020-01-07 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides an extensive, up-to-date treatment of techniques used for machine condition monitoring Clear and concise throughout, this accessible book is the first to be wholly devoted to the field of condition monitoring for rotating machines using vibration signals. It covers various feature extraction, feature selection, and classification methods as well as their applications to machine vibration datasets. It also presents new methods including machine learning and compressive sampling, which help to improve safety, reliability, and performance. Condition Monitoring with Vibration Signals: Compressive Sampling and Learning Algorithms for Rotating Machines starts by introducing readers to Vibration Analysis Techniques and Machine Condition Monitoring (MCM). It then offers readers sections covering: Rotating Machine Condition Monitoring using Learning Algorithms; Classification Algorithms; and New Fault Diagnosis Frameworks designed for MCM. Readers will learn signal processing in the time-frequency domain, methods for linear subspace learning, and the basic principles of the learning method Artificial Neural Network (ANN). They will also discover recent trends of deep learning in the field of machine condition monitoring, new feature learning frameworks based on compressive sampling, subspace learning techniques for machine condition monitoring, and much more. Covers the fundamental as well as the state-of-the-art approaches to machine condition monitoringguiding readers from the basics of rotating machines to the generation of knowledge using vibration signals Provides new methods, including machine learning and compressive sampling, which offer significant improvements in accuracy with reduced computational costs Features learning algorithms that can be used for fault diagnosis and prognosis Includes previously and recently developed dimensionality reduction techniques and classification algorithms Condition Monitoring with Vibration Signals: Compressive Sampling and Learning Algorithms for Rotating Machines is an excellent book for research students, postgraduate students, industrial practitioners, and researchers.
Download or read book Proceedings of the UNIfied Conference of DAMAS IncoME and TEPEN Conferences UNIfied 2023 written by Andrew D. Ball and published by Springer Nature. This book was released on with total page 1219 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Proceedings of the Second International Conference on Innovations in Computing Research ICR 23 written by Kevin Daimi and published by Springer Nature. This book was released on 2023-06-16 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Second International Conference on Innovations in Computing Research (ICR’23) brings together a diverse group of researchers from all over the world with the intent of fostering collaboration and dissemination of the innovations in computing technologies. The conference is aptly segmented into six tracks: Data Science, Computer and Network Security, Health Informatics and Medical Imaging, Computer Science and Computer Engineering Education, Internet of Things, and Smart Cities/Smart Energy. These tracks aim to promote a birds-of-the-same-feather congregation and maximize participation. The Data Science track covers a wide range of topics including complexity score for missing data, deep learning and fake news, cyberbullying and hate speech, surface area estimation, analysis of gambling data, car accidents predication model, augmenting character designers’ creativity, deep learning for road safety, effect of sleep disturbances on the quality of sleep, deep learning-based path-planning, vehicle data collection and analysis, predicting future stocks prices, and trading robot for foreign exchange. Computer and Network Security track is dedicated to various areas of cybersecurity. Among these are decentralized solution for secure management of IoT access rights, multi-factor authentication as a service (MFAaaS) for federated cloud environments, user attitude toward personal data privacy and data privacy economy, host IP obfuscation and performance analysis, and vehicle OBD-II port countermeasures. The Computer Science and Engineering Education track enfolds various educational areas, such as data management in industry–academia joint research: a perspective of conflicts and coordination in Japan, security culture and security education, training and awareness (SETA), influencing information security management, engaging undergraduate students in developing graphical user interfaces for NSF funded research project, and emotional intelligence of computer science teachers in higher education. On the Internet of Things (IoT) track, the focus is on industrial air quality sensor visual analytics, social spider optimization meta-heuristic for node localization optimization in wireless sensor networks, and privacy aware IoT-based fall detection with infrared sensors and deep learning. The Smart Cities and Smart Energy track spans various areas, which include, among others, research topics on heterogeneous transfer learning in structural health monitoring for high-rise structures and energy routing in energy Internet using the firefly algorithm.
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 Proceedings of the 10th International Operational Modal Analysis Conference IOMAC 2024 written by Carlo Rainieri and published by Springer Nature. This book was released on with total page 749 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Application of Vibration based Damage Detection Techniques to Civil Infrastructure written by Setonam Komla Dzvukamanja and published by . This book was released on 2008 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Data Science in Engineering Volume 10 written by Ramin Madarshahian and published by Springer Nature. This book was released on 2023-12-07 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science in Engineering, Volume 10: Proceedings of the 41st IMAC, A Conference and Exposition on Structural Dynamics, 2023, the tenth 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 Data Science in Engineering, including papers on: Novel Data-driven Analysis Methods Deep Learning Gaussian Process Analysis Real-time Video-based Analysis Applications to Nonlinear Dynamics and Damage Detection High-rate Structural Monitoring and Prognostics
Download or read book Neural Networks and Deep Learning written by Charu C. Aggarwal and published by Springer. This book was released on 2018-08-25 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural architectures in different applications. Why do neural networks work? When do they work better than off-the-shelf machine-learning models? When is depth useful? Why is training neural networks so hard? What are the pitfalls? The book is also rich in discussing different applications in order to give the practitioner a flavor of how neural architectures are designed for different types of problems. Applications associated with many different areas like recommender systems, machine translation, image captioning, image classification, reinforcement-learning based gaming, and text analytics are covered. The chapters of this book span three categories: The basics of neural networks: Many traditional machine learning models can be understood as special cases of neural networks. An emphasis is placed in the first two chapters on understanding the relationship between traditional machine learning and neural networks. Support vector machines, linear/logistic regression, singular value decomposition, matrix factorization, and recommender systems are shown to be special cases of neural networks. These methods are studied together with recent feature engineering methods like word2vec. Fundamentals of neural networks: A detailed discussion of training and regularization is provided in Chapters 3 and 4. Chapters 5 and 6 present radial-basis function (RBF) networks and restricted Boltzmann machines. Advanced topics in neural networks: Chapters 7 and 8 discuss recurrent neural networks and convolutional neural networks. Several advanced topics like deep reinforcement learning, neural Turing machines, Kohonen self-organizing maps, and generative adversarial networks are introduced in Chapters 9 and 10. The book is written for graduate students, researchers, and practitioners. Numerous exercises are available along with a solution manual to aid in classroom teaching. Where possible, an application-centric view is highlighted in order to provide an understanding of the practical uses of each class of techniques.
Download or read book Condition Monitoring with Vibration Signals written by Hosameldin Ahmed and published by John Wiley & Sons. This book was released on 2019-12-03 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides an extensive, up-to-date treatment of techniques used for machine condition monitoring Clear and concise throughout, this accessible book is the first to be wholly devoted to the field of condition monitoring for rotating machines using vibration signals. It covers various feature extraction, feature selection, and classification methods as well as their applications to machine vibration datasets. It also presents new methods including machine learning and compressive sampling, which help to improve safety, reliability, and performance. Condition Monitoring with Vibration Signals: Compressive Sampling and Learning Algorithms for Rotating Machines starts by introducing readers to Vibration Analysis Techniques and Machine Condition Monitoring (MCM). It then offers readers sections covering: Rotating Machine Condition Monitoring using Learning Algorithms; Classification Algorithms; and New Fault Diagnosis Frameworks designed for MCM. Readers will learn signal processing in the time-frequency domain, methods for linear subspace learning, and the basic principles of the learning method Artificial Neural Network (ANN). They will also discover recent trends of deep learning in the field of machine condition monitoring, new feature learning frameworks based on compressive sampling, subspace learning techniques for machine condition monitoring, and much more. Covers the fundamental as well as the state-of-the-art approaches to machine condition monitoringguiding readers from the basics of rotating machines to the generation of knowledge using vibration signals Provides new methods, including machine learning and compressive sampling, which offer significant improvements in accuracy with reduced computational costs Features learning algorithms that can be used for fault diagnosis and prognosis Includes previously and recently developed dimensionality reduction techniques and classification algorithms Condition Monitoring with Vibration Signals: Compressive Sampling and Learning Algorithms for Rotating Machines is an excellent book for research students, postgraduate students, industrial practitioners, and researchers.
Download or read book Application of Vibration based Techniques for Modal Identification and Damage Detection in Structures written by Chaewoon Lim and published by . This book was released on 2017 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: All structures such as bridges, buildings and dams are deteriorated by environmental conditions like corrosion, earthquake and traffic after they are built. Therefore, vibration-based damage identification (VBDI) techniques have attracted attention to verify the safety and functionality of structures. Conventional damage identification techniques such as non-destructive evaluation (NDE) methods have many obstacles and are not practical to be implemented in order to detect damage. One of the main obstacles is that the conventional methods are focused on local structural damage and easily affected by measurement noise. Moreover, there are several uncertainties that restrict the successful application of the damage detection. On the other hand, vibration-based techniques can be used when the global vibration characteristics is available. To do this, it is required to perform modal identification, perform model updating, and detect local changes in a structure. The objectives of this study are: (a) to develop vibration-based techniques for modal identification by output-only information through the experimental and numerical study of bridges and frame structures; and (b) to study the VBDI techniques to perform model updating and damage detection using the changes in the dynamic characteristics of structures and determine their performance in practical structures. Two existing bridges, a Pre-stressed Concrete Bridge (PSCB) and a Steel Box Bridge (STB) tested earlier were used here as case studies and the data from the vibration test were used to verify modal identification using output-only information. In this study, two output-only methods, Frequency Domain Decomposition (FDD) and Stochastic Subspace Identification (SSI) were studied to compare the results from the vibration test. In addition to this, laboratory experiments on three-story steel frame were carried out to generate additional data for testing the system identification and model updating methods. Further, various damage scenarios were created in the frame to obtain the vibration signals corresponding to such conditions. The vibration data from the undamaged and damaged frame were used to study the performance of existing VBDI methods. Based on the above study, it is concluded that both FDD and SSI techniques provide accurate results for modal identification in the case of studied structures. FDD is relatively simpler, but it may miss some modal information when two modes are closer. However, in the cases studied here, the modes are quite apart from each other. Among many available VBDI methods, the matrix update method performs better than others when the measurement noise is small. Otherwise, data-driven models such as those based on Genetic Algorithm should be used.
