Computational Technology Resources - CSETS

Keywords: differential evolution, genetic algorithm, health monitoring, optimal sensor placement, parametric identification, particle swarm optimization, seismic protection.

Abstract

Soft computing based tools and methodologies are attracting growing interest in the field of structural dynamic monitoring. Within this framework, neural networks, evolutionary computation,metaheuristic and swarm intelligence are becoming very popular in sensor network design, signal processing, system identification, model updating and structural diagnostic. Current research also shows increasing use of fuzzy logic for damage detection and structural diagnostic. The paper provides a short state-of-the-art review about the most recent research on soft computing theories and techniques for structural dynamic monitoring, with the focus on optimal sensor placement, mechanical system identification and health monitoring. Finally, some experimental applications are included to highlight how soft computing methods can be employed effectively in this field. They are concerned with the experimental parametric identification of nonlinear passive devices for seismic protection using differential evolution and particle swarm optimization.

purchase the full-text of this chapter (price £20)

go to the previous chapter
go to the next chapter
return to the table of contents
return to the book description
purchase this book (price £75 +P&P)

	Computational & Technology Resources an online resource for computational, engineering & technology publications
	not logged in - login
Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Computational Science, Engineering & Technology Series ISSN 1759-3158 CSETS: 32 CIVIL AND STRUCTURAL ENGINEERING COMPUTATIONAL METHODS Edited by: Y. Tsompanakis, P. Iványi and B.H.V. Topping Chapter 8 Soft Computing Applications in Structural Dynamic Monitoring G. Quaranta¹ and G.C. Marano² ¹Department of Structural and Geotechnical Engineering, Sapienza University of Rome, Italy ²Department of Civil Engineering and Architecture, Technical University of Bari, Italy doi:10.4203/csets.32.8 purchase the full-text of this chapter Full Bibliographic Reference for this chapter G. Quaranta, G.C. Marano, "Soft Computing Applications in Structural Dynamic Monitoring", in Y. Tsompanakis, P. Iványi and B.H.V. Topping, (Editors), "Civil and Structural Engineering Computational Methods", Saxe-Coburg Publications, Stirlingshire, UK, Chapter 8, pp 157-170, 2013. doi:10.4203/csets.32.8 Keywords: differential evolution, genetic algorithm, health monitoring, optimal sensor placement, parametric identification, particle swarm optimization, seismic protection. Abstract Soft computing based tools and methodologies are attracting growing interest in the field of structural dynamic monitoring. Within this framework, neural networks, evolutionary computation,metaheuristic and swarm intelligence are becoming very popular in sensor network design, signal processing, system identification, model updating and structural diagnostic. Current research also shows increasing use of fuzzy logic for damage detection and structural diagnostic. The paper provides a short state-of-the-art review about the most recent research on soft computing theories and techniques for structural dynamic monitoring, with the focus on optimal sensor placement, mechanical system identification and health monitoring. Finally, some experimental applications are included to highlight how soft computing methods can be employed effectively in this field. They are concerned with the experimental parametric identification of nonlinear passive devices for seismic protection using differential evolution and particle swarm optimization. purchase the full-text of this chapter (price £20) go to the previous chapter go to the next chapter return to the table of contents return to the book description purchase this book (price £75 +P&P)
Back to top	©Civil-Comp Limited 2023 - terms & conditions