東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Weighting Matrices and Model Order D...

Hong, Ah Lum.

Linked to FindBook

Google Book

Amazon

博客來

Weighting Matrices and Model Order Determination in Stochastic System Identification for Civil Infrastructure Systems.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Weighting Matrices and Model Order Determination in Stochastic System Identification for Civil Infrastructure Systems./
Author:	Hong, Ah Lum.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2010,
Description:	174 p.
Notes:	Source: Dissertations Abstracts International, Volume: 72-06, Section: B.
Contained By:	Dissertations Abstracts International72-06B.
Subject:	Mechanics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3432035
ISBN:	9781124334585

Weighting Matrices and Model Order Determination in Stochastic System Identification for Civil Infrastructure Systems.
Hong, Ah Lum.

Weighting Matrices and Model Order Determination in Stochastic System Identification for Civil Infrastructure Systems. - Ann Arbor : ProQuest Dissertations & Theses, 2010 - 174 p.

Source: Dissertations Abstracts International, Volume: 72-06, Section: B.

Thesis (Ph.D.)--Columbia University, 2010.

This research work consists in the development of a new robust stochastic system identification technique for the identification of dynamic characteristics of large-scale and complex civil infrastructure systems. Based on a stochastic state-space model framework, a new approach for state variable estimation is developed by proposing a new set of weighting matrices for the purpose of properly determining the order of a numerical model of the structure under consideration. For the development of such a new approach, a theoretical interpretation and investigation of the stochastic system identification process is provided within a general framework of the stochastic subspace method. This work addresses four main topics of research: (1) to define existing stochastic subspace approaches in a unified framework that can be readily modified according to a desired performance. This unification is performed in a general multivariate analysis framework by using certain sets of weighting matrices; (2) to evaluate differences of the existing approaches in their performances for system identification. In this phase of research, after the investigation of the properties that each approach considers in its identification process of a dynamic system, the evaluation of their performance is conducted, in numerical and practical applications, with respect to the ability to highlight structural properties against noise ones in terms of the solution for singular value problem; (3) to develop a new robust stochastic subspace approach that properly discriminates structural modes, including both strongly and weakly excited modes, from noise ones in estimating state vectors from the singular value problem. Such a new approach is developed by proposing a new set of weighting matrices and its efficiency over the existing approaches is verified by using analytical, experimental and field data; and (4) to address frequently encountered problems in practical applications of a general subspace method. Considering such problems, complementary methods for the implementation of the subspace method are also investigated.

ISBN: 9781124334585Subjects--Topical Terms:

525881
Mechanics.
Subjects--Index Terms:

Civil infrastructure

Weighting Matrices and Model Order Determination in Stochastic System Identification for Civil Infrastructure Systems.
LDR:03193nmm a2200325 4500 001 2268055
005 20200810100232.5
008 220629s2010 ||||||||||||||||| ||eng d
020 $a 9781124334585
035 $a (MiAaPQ)AAI3432035
035 $a AAI3432035
040 $a MiAaPQ $c MiAaPQ
100 1 $a Hong, Ah Lum. $3 3545312
245 1 0 $a Weighting Matrices and Model Order Determination in Stochastic System Identification for Civil Infrastructure Systems.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2010
300 $a 174 p.
500 $a Source: Dissertations Abstracts International, Volume: 72-06, Section: B.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisor: Betti, Raimondo.
502 $a Thesis (Ph.D.)--Columbia University, 2010.
520 $a This research work consists in the development of a new robust stochastic system identification technique for the identification of dynamic characteristics of large-scale and complex civil infrastructure systems. Based on a stochastic state-space model framework, a new approach for state variable estimation is developed by proposing a new set of weighting matrices for the purpose of properly determining the order of a numerical model of the structure under consideration. For the development of such a new approach, a theoretical interpretation and investigation of the stochastic system identification process is provided within a general framework of the stochastic subspace method. This work addresses four main topics of research: (1) to define existing stochastic subspace approaches in a unified framework that can be readily modified according to a desired performance. This unification is performed in a general multivariate analysis framework by using certain sets of weighting matrices; (2) to evaluate differences of the existing approaches in their performances for system identification. In this phase of research, after the investigation of the properties that each approach considers in its identification process of a dynamic system, the evaluation of their performance is conducted, in numerical and practical applications, with respect to the ability to highlight structural properties against noise ones in terms of the solution for singular value problem; (3) to develop a new robust stochastic subspace approach that properly discriminates structural modes, including both strongly and weakly excited modes, from noise ones in estimating state vectors from the singular value problem. Such a new approach is developed by proposing a new set of weighting matrices and its efficiency over the existing approaches is verified by using analytical, experimental and field data; and (4) to address frequently encountered problems in practical applications of a general subspace method. Considering such problems, complementary methods for the implementation of the subspace method are also investigated.
590 $a School code: 0054.
650 4 $a Mechanics. $3 525881
650 4 $a Civil engineering. $3 860360
653 $a Civil infrastructure
653 $a Weighting matrices
690 $a 0346
690 $a 0543
710 2 $a Columbia University. $3 571054
773 0 $t Dissertations Abstracts International $g 72-06B.
790 $a 0054
791 $a Ph.D.
792 $a 2010
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3432035