國立虎尾科技大學 |

Identification Methods for Structural Health Monitoring

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Identification Methods for Structural Health Monitoring/ edited by Eleni Chatzi, Costas Papadimitriou.
其他作者:	Chatzi, Eleni.
面頁冊數:	IX, 170 p. 53 illus., 39 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Building repair. -
電子資源:	https://doi.org/10.1007/978-3-319-32077-9
ISBN:	9783319320779

Identification Methods for Structural Health Monitoring
Identification Methods for Structural Health Monitoring[electronic resource] /edited by Eleni Chatzi, Costas Papadimitriou. - 1st ed. 2016. - IX, 170 p. 53 illus., 39 illus. in color.online resource. - CISM International Centre for Mechanical Sciences, Courses and Lectures,5670254-1971 ;. - CISM International Centre for Mechanical Sciences, Courses and Lectures,559.

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:

1254762
Building repair.

LC Class. No.: TH3301-3411

Dewey Class. No.: 690.24

Identification Methods for Structural Health Monitoring
LDR:02989nam a22004095i 4500 001 977933
003 DE-He213
005 20200702172054.0
007 cr nn 008mamaa
008 201211s2016 gw | s |||| 0|eng d
020 $a 9783319320779 $9 978-3-319-32077-9
024 7 $a 10.1007/978-3-319-32077-9 $2 doi
035 $a 978-3-319-32077-9
050 4 $a TH3301-3411
072 7 $a TNKX $2 bicssc
072 7 $a TEC009020 $2 bisacsh
072 7 $a TNKX $2 thema
082 0 4 $a 690.24 $2 23
245 1 0 $a Identification Methods for Structural Health Monitoring $h [electronic resource] / $c edited by Eleni Chatzi, Costas Papadimitriou.
250 $a 1st ed. 2016.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a IX, 170 p. 53 illus., 39 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a CISM International Centre for Mechanical Sciences, Courses and Lectures, $x 0254-1971 ; $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 Building repair. $3 1254762
650 0 $a Buildings—Repair and reconstruction. $3 1254763
650 1 4 $a Building Repair and Maintenance. $3 671099
700 1 $a Chatzi, Eleni. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1271523
700 1 $a Papadimitriou, Costas. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1109093
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783319320755
776 0 8 $i Printed edition: $z 9783319320762
776 0 8 $i Printed edition: $z 9783319811901
830 0 $a CISM International Centre for Mechanical Sciences, Courses and Lectures, $x 0254-1971 ; $v 559 $3 1262093
856 4 0 $u https://doi.org/10.1007/978-3-319-32077-9
912 $a ZDB-2-ENG
912 $a ZDB-2-SXE
950 $a Engineering (SpringerNature-11647)
950 $a Engineering (R0) (SpringerNature-43712)