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Computational and Experimental Techniques for Identification of Damage
Details
Mostly the structural members and machine elements are subjected to progressive static and dynamic loading and that may cause initiation of defects in the form of crack. That may lead to catastrophic failure or collapse of the structures. Thereby the importance of identification of damage in the structures is not only for leading safe operation but also to prevent the loss of economy and lives. The structural steel is widely used in various engineering systems such as bridges, railway coaches, ships, automobiles, etc. The glass fiber reinforced epoxy layered composite material has become popular for constructing the various engineering structures due to its valuable characteristics such as higher stiffness and strength to weight ratio, better damage tolerance capacity and wear resistance. The various automated artificial intelligent techniques such as fuzzy controller, neural network and hybrid AI techniques based multiple faults diagnosis systems are developed using vibration response of cracked cantilever beams. The Computational techniques, numerical and experimental methods can be successfully used as damage assessment tool to identify the faults presents in structural members.
Autorentext
Dr. Irshad Ahmad Khan currently working as Associate Professor in Department of Mechanical Engineering, Sagar Institute of Research & Technology, Bhopal. He has received his M-Tech and PhD degree from National Institute of Technology, Rourkela. He has published many research papers in national and international journal and conferences.
Weitere Informationen
- Allgemeine Informationen
- GTIN 09783330085565
- Genre Mechanical Engineering
- Sprache Englisch
- Anzahl Seiten 236
- Herausgeber LAP LAMBERT Academic Publishing
- Größe H220mm x B150mm x T15mm
- Jahr 2017
- EAN 9783330085565
- Format Kartonierter Einband
- ISBN 3330085568
- Veröffentlichung 22.05.2017
- Titel Computational and Experimental Techniques for Identification of Damage
- Autor Irshad Ahmad Khan
- Gewicht 369g