Ultrasonic Guided Waves-based Structural Health Monitoring: for Key Industrial Equipment

Zhanjun Wu, Zhi Wang, Yishou Wang

ISBN 10: 3659597236 / ISBN 13: 9783659597237

Published by LAP LAMBERT Academic Publishing 2014-09-24, 2014

About this Item

Seller Inventory # 6666-IUK-9783659597237

Bibliographic Details

• Title: Ultrasonic Guided Waves-based Structural Health Monitoring: for Key Industrial Equipment
• Publisher: LAP LAMBERT Academic Publishing 2014-09-24
• Publication Date: 2014
• Language: English
• ISBN 10: 3659597236
• ISBN 13: 9783659597237
• Binding: Paperback
• Condition: New

About this title

Synopsis

Key industrial equipment (such as pipelines, aircraft structure and tanks) should meet the requirements for reliability, integrity and safety for a long-term operation. During its service, defects that might be caused by natural disasters or external impacts could lead to a significant reduction in a structure’s strength and fatigue life. Therefore, structural health monitoring techniques, which are capable of achieving continuous monitoring and on-line damage detection, are important for increasing the service life and reducing the sustainment costs of key industrial equipment. Guided waves-based structural health monitoring technology is a multidisciplinary study which requires a deep understanding of materials, sensors, modeling forms, electronic circuits, signal processing methods, and diagnostic algorithms. Therefore, this book provides the readers with a summary of the fundamental knowledge as well as methods of ultrasonic guided waves and introduces them to some case studies of structural health monitoring as they are applied in the context of the key industrial equipment monitoring problems.

About the Author

Zhanjun Wu is a professor at the school of Aeronautics and Astronautics, Dalian University of Technology, China. He earned his Ph.D Degree in Engineering Mechanics at Harbin Institute of Technology in 2001. His main research interests include Advanced Composites, Aerospace Structures and Structural Health Monitoring.