A new gibbs-sampling based algorithm for Bayesian Model updating of linear dynamic systems with incomplete complex modal data

Model updating using measured system dynamic response has a wide range of applications in structural health monitoring, control and response prediction. In this paper, we are interested in model updating of a linear structural dynamic system with non-classical damping based on incomplete modal...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Hung, Cheung Sai, Bansal, Sahil
مؤلفون آخرون: School of Civil and Environmental Engineering
التنسيق: Conference or Workshop Item
اللغة:English
منشور في: 2013
الموضوعات:
الوصول للمادة أونلاين:https://hdl.handle.net/10356/105851
http://hdl.handle.net/10220/17969
http://www.iaeng.org/publication/IMECS2013/
الوسوم: إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
المؤسسة: Nanyang Technological University
اللغة: English
id sg-ntu-dr.10356-105851
record_format dspace
spelling sg-ntu-dr.10356-1058512019-12-06T21:59:14Z A new gibbs-sampling based algorithm for Bayesian Model updating of linear dynamic systems with incomplete complex modal data Hung, Cheung Sai Bansal, Sahil School of Civil and Environmental Engineering International MultiConference of Engineers and Computer Scientists (2013 : Hong Kong) DRNTU::Engineering::Civil engineering Model updating using measured system dynamic response has a wide range of applications in structural health monitoring, control and response prediction. In this paper, we are interested in model updating of a linear structural dynamic system with non-classical damping based on incomplete modal data including modal frequencies, damping ratios, and partial complex mode shapes of some of the dominant modes. To quantify the uncertainties and plausibility of the model parameters, a Bayesian approach is adopted. A new Gibbssampling based algorithm is proposed that allows for an efficient update of the probability distribution of the model parameters. The effectiveness and efficiency of the proposed method are illustrated by a numerical example involving a linear structural dynamic system with complex modes. 2013-12-02T07:25:54Z 2019-12-06T21:59:14Z 2013-12-02T07:25:54Z 2019-12-06T21:59:14Z 2013 2013 Conference Paper Hung, C. S., & Bansal, S. (2013). A new gibbs-sampling based algorithm for Bayesian Model updating of linear dynamic systems with incomplete complex modal data. International MultiConference of Engineers and Computer Scientists 2013, 2. https://hdl.handle.net/10356/105851 http://hdl.handle.net/10220/17969 http://www.iaeng.org/publication/IMECS2013/ en
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Civil engineering
spellingShingle DRNTU::Engineering::Civil engineering
Hung, Cheung Sai
Bansal, Sahil
A new gibbs-sampling based algorithm for Bayesian Model updating of linear dynamic systems with incomplete complex modal data
description Model updating using measured system dynamic response has a wide range of applications in structural health monitoring, control and response prediction. In this paper, we are interested in model updating of a linear structural dynamic system with non-classical damping based on incomplete modal data including modal frequencies, damping ratios, and partial complex mode shapes of some of the dominant modes. To quantify the uncertainties and plausibility of the model parameters, a Bayesian approach is adopted. A new Gibbssampling based algorithm is proposed that allows for an efficient update of the probability distribution of the model parameters. The effectiveness and efficiency of the proposed method are illustrated by a numerical example involving a linear structural dynamic system with complex modes.
author2 School of Civil and Environmental Engineering
author_facet School of Civil and Environmental Engineering
Hung, Cheung Sai
Bansal, Sahil
format Conference or Workshop Item
author Hung, Cheung Sai
Bansal, Sahil
author_sort Hung, Cheung Sai
title A new gibbs-sampling based algorithm for Bayesian Model updating of linear dynamic systems with incomplete complex modal data
title_short A new gibbs-sampling based algorithm for Bayesian Model updating of linear dynamic systems with incomplete complex modal data
title_full A new gibbs-sampling based algorithm for Bayesian Model updating of linear dynamic systems with incomplete complex modal data
title_fullStr A new gibbs-sampling based algorithm for Bayesian Model updating of linear dynamic systems with incomplete complex modal data
title_full_unstemmed A new gibbs-sampling based algorithm for Bayesian Model updating of linear dynamic systems with incomplete complex modal data
title_sort new gibbs-sampling based algorithm for bayesian model updating of linear dynamic systems with incomplete complex modal data
publishDate 2013
url https://hdl.handle.net/10356/105851
http://hdl.handle.net/10220/17969
http://www.iaeng.org/publication/IMECS2013/
_version_ 1681047146271342592