Isbn: 9781032812823 - structural health monitoring using emerging signal processing approaches with artificial intelligence algorithms (9 resultados)

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Condición: New.

Paperback. Condición: Brand New. 232 pages. 6.14x0.51x9.21 inches. In Stock.

Condición: New. Chunwei Zhang is a Chair Distinguished Professor at Shenyang University of Technology. He is the Founding Director of the Multidisciplinary Center for Infrastructure Engineering (MCIE) at Shenyang University of Technology, and of the Str.

Taschenbuch. Condición: Neu. Neuware - Structural 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.…

Paperback. Condición: new. Paperback. Structural 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 stateoftheart review of the applications in time, frequency, and timefrequency domains of signalprocessing 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 signalprocessing techniques to evaluate sensitivity in damage identification. Chapters summarize the application of the HilbertHuang 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. This presents a comprehensive 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. It covers a range of experimental techniques and introduces ANNs for automated damage identification. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condición: new. Paperback. Structural 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 stateoftheart review of the applications in time, frequency, and timefrequency domains of signalprocessing 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 signalprocessing techniques to evaluate sensitivity in damage identification. Chapters summarize the application of the HilbertHuang 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. This presents a comprehensive 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. It covers a range of experimental techniques and introduces ANNs for automated damage identification. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Paperback. Condición: new. Paperback. Structural 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 stateoftheart review of the applications in time, frequency, and timefrequency domains of signalprocessing 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 signalprocessing techniques to evaluate sensitivity in damage identification. Chapters summarize the application of the HilbertHuang 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. This presents a comprehensive 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. It covers a range of experimental techniques and introduces ANNs for automated damage identification. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…