大葉大學圖書館 |

Identification methods for structural health monitoring[electronic resource] /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	624.17
書名/作者:	Identification methods for structural health monitoring/ edited by Eleni N. Chatzi, Costas Papadimitriou.
其他作者:	Chatzi, Eleni N.
出版者:	Cham : : Springer International Publishing :, 2016.
面頁冊數:	ix, 170 p. : : ill. (some col.), digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Structural health monitoring.
標題:	Engineering.
標題:	Building Repair and Maintenance.
ISBN:	9783319320779
ISBN:	9783319320755
內容註:	Introduction -- Parametric and non parametric identification methods: an overview -- Parametric methods for the treatment of nonlinear dynamics -- Bayesian parameter estimation -- Bayesian operational modal analysis -- Bayesian uncertainty quantification and propagation (UQ+P): state-of-the-art tools for linear and nonlinear structural dynamics models -- Efficient data fusion and practical considerations for structural identification -- Implementation of identification methodologies on large scale structures.
摘要、提要註:	The papers in this volume provide an introduction to well known and established system identification methods for structural health monitoring and to more advanced, state-of-the-art tools, able to tackle the challenges associated with actual implementation. Starting with an overview on fundamental methods, introductory concepts are provided on the general framework of time and frequency domain, parametric and non-parametric methods, input-output or output only techniques. Cutting edge tools are introduced including, nonlinear system identification methods; Bayesian tools; and advanced modal identification techniques (such as the Kalman and particle filters, the fast Bayesian FFT method) Advanced computational tools for uncertainty quantification are discussed to provide a link between monitoring and structural integrity assessment. In addition, full scale applications and field deployments that illustrate the workings and effectiveness of the introduced monitoring schemes are demonstrated.
電子資源:	http://dx.doi.org/10.1007/978-3-319-32077-9

Identification methods for structural health monitoring[electronic resource] /
Identification methods for structural health monitoring[electronic resource] /edited by Eleni N. Chatzi, Costas Papadimitriou. - Cham :Springer International Publishing :2016. - ix, 170 p. :ill. (some col.), digital ;24 cm. - CISM International Centre for Mechanical Sciences,v.5670254-1971 ;. - CISM International Centre for Mechanical Sciences ;v.565..

Introduction -- Parametric and non parametric identification methods: an overview -- Parametric methods for the treatment of nonlinear dynamics -- Bayesian parameter estimation -- Bayesian operational modal analysis -- Bayesian uncertainty quantification and propagation (UQ+P): state-of-the-art tools for linear and nonlinear structural dynamics models -- Efficient data fusion and practical considerations for structural identification -- Implementation of identification methodologies on large scale structures.

The papers in this volume provide an introduction to well known and established system identification methods for structural health monitoring and to more advanced, state-of-the-art tools, able to tackle the challenges associated with actual implementation. Starting with an overview on fundamental methods, introductory concepts are provided on the general framework of time and frequency domain, parametric and non-parametric methods, input-output or output only techniques. Cutting edge tools are introduced including, nonlinear system identification methods; Bayesian tools; and advanced modal identification techniques (such as the Kalman and particle filters, the fast Bayesian FFT method) Advanced computational tools for uncertainty quantification are discussed to provide a link between monitoring and structural integrity assessment. In addition, full scale applications and field deployments that illustrate the workings and effectiveness of the introduced monitoring schemes are demonstrated.

ISBN: 9783319320779

Standard No.: 10.1007/978-3-319-32077-9doiSubjects--Topical Terms:

511470
Structural health monitoring.

LC Class. No.: TA656.6

Dewey Class. No.: 624.17

Identification methods for structural health monitoring[electronic resource] /
LDR:02602nam a2200337 a 4500 001 450638
003 DE-He213
005 20161020092513.0
006 m d
007 cr nn 008maaau
008 161210s2016 gw s 0 eng d
020 $a 9783319320779 $q (electronic bk.)
020 $a 9783319320755 $q (paper)
024 7 $a 10.1007/978-3-319-32077-9 $2 doi
035 $a 978-3-319-32077-9
040 $a GP $c GP
041 0 $a eng
050 4 $a TA656.6
072 7 $a TNKX $2 bicssc
072 7 $a TEC009020 $2 bisacsh
072 7 $a HOM010000 $2 bisacsh
082 0 4 $a 624.17 $2 23
090 $a TA656.6 $b .I19 2016
245 0 0 $a Identification methods for structural health monitoring $h [electronic resource] / $c edited by Eleni N. Chatzi, Costas Papadimitriou.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a ix, 170 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a CISM International Centre for Mechanical Sciences, $x 0254-1971 ; $v v.567
505 0 $a Introduction -- Parametric and non parametric identification methods: an overview -- Parametric methods for the treatment of nonlinear dynamics -- Bayesian parameter estimation -- Bayesian operational modal analysis -- Bayesian uncertainty quantification and propagation (UQ+P): state-of-the-art tools for linear and nonlinear structural dynamics models -- Efficient data fusion and practical considerations for structural identification -- Implementation of identification methodologies on large scale structures.
520 $a The papers in this volume provide an introduction to well known and established system identification methods for structural health monitoring and to more advanced, state-of-the-art tools, able to tackle the challenges associated with actual implementation. Starting with an overview on fundamental methods, introductory concepts are provided on the general framework of time and frequency domain, parametric and non-parametric methods, input-output or output only techniques. Cutting edge tools are introduced including, nonlinear system identification methods; Bayesian tools; and advanced modal identification techniques (such as the Kalman and particle filters, the fast Bayesian FFT method) Advanced computational tools for uncertainty quantification are discussed to provide a link between monitoring and structural integrity assessment. In addition, full scale applications and field deployments that illustrate the workings and effectiveness of the introduced monitoring schemes are demonstrated.
650 0 $a Structural health monitoring. $3 511470
650 1 4 $a Engineering. $3 372756
650 2 4 $a Building Repair and Maintenance. $3 467156
700 1 $a Chatzi, Eleni N. $3 646951
700 1 $a Papadimitriou, Costas. $3 646952
710 2 $a SpringerLink (Online service) $3 463450
773 0 $t Springer eBooks
830 0 $a CISM International Centre for Mechanical Sciences ; $v v.565. $3 646947
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-32077-9
950 $a Engineering (Springer-11647)