Back to Search
Start Over
A comparative study of the stochastic simulation methods applied in structural health monitoring.
- Source :
-
Engineering Computations . 2014, Vol. 31 Issue 7, p1484-1513. 30p. - Publication Year :
- 2014
-
Abstract
- Purpose – The purpose of this paper is to discuss the characteristics of several stochastic simulation methods applied in computation issue of structure health monitoring (SHM). Design/methodology/approach – On the basis of the previous studies, this research focusses on four promising methods: transitional Markov chain Monte Carlo (TMCMC), slice sampling, slice-Metropolis-Hasting (M-H), and TMCMC-slice algorithm. The slice-M-H is the improved slice sampling algorithm, and the TMCMC-slice is the improved TMCMC algorithm. The performances of the parameters samples generated by these four algorithms are evaluated using two examples: one is the numerical example of a cantilever plate; another is the plate experiment simulating one part of the mechanical structure. Findings – Both the numerical example and experiment show that, identification accuracy of slice-M-H is higher than that of slice sampling; and the identification accuracy of TMCMC-slice is higher than that of TMCMC. In general, the identification accuracy of the methods based on slice (slice sampling and slice-M-H) is higher than that of the methods based on TMCMC (TMCMC and TMCMC-slice). Originality/value – The stochastic simulation methods evaluated in this paper are mainly two categories of representative methods: one introduces the intermediate probability density functions, and another one is the auxiliary variable approach. This paper provides important references about the stochastic simulation methods to solve the ill-conditioned computation issue, which is commonly encountered in SHM. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 02644401
- Volume :
- 31
- Issue :
- 7
- Database :
- Academic Search Index
- Journal :
- Engineering Computations
- Publication Type :
- Academic Journal
- Accession number :
- 124860097
- Full Text :
- https://doi.org/10.1108/EC-07-2013-0185