Damage Detection In Plate Structures Using Guided Ultrasonic Waves
Download Damage Detection In Plate Structures Using Guided Ultrasonic Waves PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Damage Detection In Plate Structures Using Guided Ultrasonic Waves book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Damage Detection in Plate Structures Using Guided Ultrasonic Waves
This dissertation focuses on the detection and localization of damage in plate-like structures using active guided ultrasonic wave inspection common to the research areas of non-destructive evaluation (NDE) and structural health monitoring (SHM). Inspection consists of first interrogating the structure with a narrowband input waveform, exciting multiple plate modes, and then analyzing the resulting damage scattered wave field using a signal processing method (detector) to decide if damage is present or not. The successful application of guided waves in plate structures is unfortunately difficult due to the wave propagation environment being dispersive, multi-modal, and multi-path. This dissertation attempts to reduce these problems and to extend the knowledge in ultrasonic guided wave structural health monitoring (UGWSHM) by : characterizing the wave propagation environment through theoretical modeling of guided wave modes excited via circular piezoelectric transducers, developing signal processing techniques to experimentally estimate dispersion curves in-situ and applying novel statistical signal processing methods to detect and locate damage through multi-mode and multi-frequency array detectors. Experiments are performed on aluminum and carbon fiber laminate plates to identify propagating guided wave modes and to detect and locate damage, validating the proposed models and signal processing methods.
Identification of Damage Using Lamb Waves
Author: Zhongqing Su
language: en
Publisher: Springer Science & Business Media
Release Date: 2009-09-01
Lamb waves are guided waves that propagate in thin plate or shell structures. There has been a clear increase of interest in using Lamb waves for identifying structural damage, entailing intensive research and development in this field over the past two decades. Now on the verge of maturity for diverse engineering applications, this emerging technique serves as an encouraging candidate for facilitating continuous and automated surveillance of the integrity of engineering structures in a cost-effective manner. In comparison with conventional nondestructive evaluation techniques such as ultrasonic scanning and radiography which have been well developed over half a century, damage identification using Lamb waves is in a stage of burgeoning development, presenting a number of technical challenges in application that need to be addressed and circumvented. It is these two aspects that have encouraged us to write this book, with the intention of consolidating the knowledge and know-how in the field of Lamb-wave-based damage identification, and of promoting widespread attention to mature application of this technique in the practical engineering sphere. This book provides a comprehensive description of key facets of damage identification technique using Lamb waves, based on the authors’ knowledge, comprehension and experience, ranging from fundamental theory through case studies to engineering applications.
Structural Health Monitoring
Author: Charles R. Farrar
language: en
Publisher: John Wiley & Sons
Release Date: 2012-11-19
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.