Koha online

Your cart is empty.
Normal view MARC view ISBD view

Online Damage Detection in Structural Systems [electronic resource] :Applications of Proper Orthogonal Decomposition, and Kalman and Particle Filters / by Saeed Eftekhar Azam.

by Eftekhar Azam, Saeed [author.]; SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: SpringerBriefs in Applied Sciences and Technology: Publisher: Cham : Springer International Publishing : 2014.Description: XII, 135 p. 87 illus. online resource.ISBN: 9783319025599.Subject(s): Engineering | Vibration | Building construction | Engineering | Vibration, Dynamical Systems, Control | Signal, Image and Speech Processing | Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences | Building Repair and MaintenanceDDC classification: 620 Online resources: Click here to access online
Contents:
Introduction -- Recursive Bayesian estimation of partially observed dynamic systems -- Model Order Reduction of dynamic systems via Proper Orthogonal Decomposition -- POD-Kalman observer for linear time invariant dynamic systems -- Dual estimation and reduced order modeling of damaging structures -- Summary of the recursive Bayesian inference schemes.
In: Springer eBooksSummary: This monograph assesses in depth the application of recursive Bayesian filters in structural health monitoring. Although the methods and algorithms used here are well established in the field of automatic control, their application in the realm of civil engineering has to date been limited. The monograph is therefore intended as a reference for structural and civil engineers who wish to conduct research in this field. To this end, the main notions underlying the families of Kalman and particle filters are scrutinized through explanations within the text and numerous numerical examples. The main limitations to their application in monitoring of high-rise buildings are discussed, and a remedy based on a synergy of reduced order modeling (based on proper orthogonal decomposition) and Bayesian estimation is proposed. The performance and effectiveness of the proposed algorithm is demonstrated via pseudo-experimental evaluations.
Tags from this library: No tags from this library for this title. Add tag(s)
Log in to add tags.
    average rating: 0.0 (0 votes)

Introduction -- Recursive Bayesian estimation of partially observed dynamic systems -- Model Order Reduction of dynamic systems via Proper Orthogonal Decomposition -- POD-Kalman observer for linear time invariant dynamic systems -- Dual estimation and reduced order modeling of damaging structures -- Summary of the recursive Bayesian inference schemes.

This monograph assesses in depth the application of recursive Bayesian filters in structural health monitoring. Although the methods and algorithms used here are well established in the field of automatic control, their application in the realm of civil engineering has to date been limited. The monograph is therefore intended as a reference for structural and civil engineers who wish to conduct research in this field. To this end, the main notions underlying the families of Kalman and particle filters are scrutinized through explanations within the text and numerous numerical examples. The main limitations to their application in monitoring of high-rise buildings are discussed, and a remedy based on a synergy of reduced order modeling (based on proper orthogonal decomposition) and Bayesian estimation is proposed. The performance and effectiveness of the proposed algorithm is demonstrated via pseudo-experimental evaluations.

There are no comments for this item.

Log in to your account to post a comment.
@ Jomo Kenyatta University Of Agriculture and Technology Library

Powered by Koha