UM
Non-probabilistic uncertainty quantification for dynamic characterization functions using complex ratio interval arithmetic operation of multidimensional parallelepiped model
Zhao,Meng Yun1; Yan,Wang Ji2; Yuen,Ka Veng2; Beer,Michael3,4,5
2021-07-01
Source PublicationMechanical Systems and Signal Processing
ISSN0888-3270
Volume156
AbstractUncertainty quantification for the experimental estimations of dynamic characterization functions, including frequency response functions (FRFs) and transmissibility functions (TFs), is of practical importance in improving the robustness of the real applications of these functions for system identification and structural health monitoring. Interval analysis is an appealing tool for dealing with the uncertainties of engineering problems in which only the bounds of uncertain parameters are available. FRFs and TFs are complex-valued random variables. However, due to the negligence of the dependencies of complex-valued variables, the existing complex ratio interval arithmetic operation can be overly conservative. In this study, the polar representation of complex ratio numbers was extended to complex ratio polar intervals and a multidimensional parallelepiped (MP) interval model was introduced to accommodate the dependence between the numerator and the denominator. Based on the explicit expressions of the MP model through a dependence matrix, two new global extrema searching schemes with and without the regularization of the uncertainty domain of the MP model were proposed in order to derive the explicit formulas of the upper and lower bounds of the magnitudes and phases of the FRFs and TFs. The new schemes were then applied to the uncertainty propagation for a numerically simulated beam and a bridge subjected to a single excitation. The results showed that the interval overestimation problem could be significantly alleviated by using the new complex-valued ratio interval arithmetic operation of the parallelepiped model.
KeywordComplex interval division Frequency response function Interval analysis Parallelepiped model Structural health monitoring Transmissibility
DOI10.1016/j.ymssp.2020.107559
URLView the original
Language英语
Fulltext Access
Citation statistics
Cited Times [WOS]:0   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Affiliation1.Department of Civil Engineering,Hefei University of Technology,Anhui,China
2.State Key Laboratory of Internet of Things for Smart City and Department of Civil and Environmental Engineering,University of Macau,China
3.Institute for Risk and Reliability,Leibniz Universität Hannover,Hannover,Germany
4.Institute for Risk and Uncertainty and School of Engineering,University of Liverpool,United Kingdom
5.International Joint Research Center for Engineering Reliability and Stochastic Mechanics,Tongji University,China
Recommended Citation
GB/T 7714
Zhao,Meng Yun,Yan,Wang Ji,Yuen,Ka Veng,et al. Non-probabilistic uncertainty quantification for dynamic characterization functions using complex ratio interval arithmetic operation of multidimensional parallelepiped model[J]. Mechanical Systems and Signal Processing,2021,156.
APA Zhao,Meng Yun,Yan,Wang Ji,Yuen,Ka Veng,&Beer,Michael.(2021).Non-probabilistic uncertainty quantification for dynamic characterization functions using complex ratio interval arithmetic operation of multidimensional parallelepiped model.Mechanical Systems and Signal Processing,156.
MLA Zhao,Meng Yun,et al."Non-probabilistic uncertainty quantification for dynamic characterization functions using complex ratio interval arithmetic operation of multidimensional parallelepiped model".Mechanical Systems and Signal Processing 156(2021).
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Zhao,Meng Yun]'s Articles
[Yan,Wang Ji]'s Articles
[Yuen,Ka Veng]'s Articles
Baidu academic
Similar articles in Baidu academic
[Zhao,Meng Yun]'s Articles
[Yan,Wang Ji]'s Articles
[Yuen,Ka Veng]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Zhao,Meng Yun]'s Articles
[Yan,Wang Ji]'s Articles
[Yuen,Ka Veng]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.