Optimal sensor placement for model updating of civil engineering structures subjected to future dynamic loadings
Making use of statistical approach to figure out the optimal sensor locations of the structure where the sensors can measure the most information of the structure parameters. These structure parameters can show the structure conditions and behaviors. Through measurement, it will help us to update th...
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sg-ntu-dr.10356-642132023-03-03T16:53:21Z Optimal sensor placement for model updating of civil engineering structures subjected to future dynamic loadings Wu, Sheng Cheung Joseph Sai Hung School of Civil and Environmental Engineering DRNTU::Engineering::Civil engineering Making use of statistical approach to figure out the optimal sensor locations of the structure where the sensors can measure the most information of the structure parameters. These structure parameters can show the structure conditions and behaviors. Through measurement, it will help us to update the models, finding the damage areas and localization applications. Since, there are many inevitable uncertainties in the parameters and as well as the measured data, it is necessary to take them into account. Information entropy is a kind of special measurement of the uncertainties in the model parameters and it is used as the requirement for choosing of best sensor locations. To handle the large uncertainties, we make use of the Bayesian statistical methodology. In order to minimize the entropy over sets of combination of sensor locations we use a heuristic algorithm. With large model uncertainties, the optimal sensor configurations will be calculated by entropy measures by Bayesian methodology. This project will use a truss bridge structure with 29 degree of freedom to illustrate in this report. Bachelor of Engineering (Civil) 2015-05-25T06:36:26Z 2015-05-25T06:36:26Z 2015 2015 Final Year Project (FYP) http://hdl.handle.net/10356/64213 en Nanyang Technological University 76 p. application/pdf |
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DRNTU::Engineering::Civil engineering Wu, Sheng Optimal sensor placement for model updating of civil engineering structures subjected to future dynamic loadings |
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Making use of statistical approach to figure out the optimal sensor locations of the structure where the sensors can measure the most information of the structure parameters. These structure parameters can show the structure conditions and behaviors. Through measurement, it will help us to update the models, finding the damage areas and localization applications. Since, there are many inevitable uncertainties in the parameters and as well as the measured data, it is necessary to take them into account. Information entropy is a kind of special measurement of the uncertainties in the model parameters and it is used as the requirement for choosing of best sensor locations. To handle the large uncertainties, we make use of the Bayesian statistical methodology. In order to minimize the entropy over sets of combination of sensor locations we use a heuristic algorithm. With large model uncertainties, the optimal sensor configurations will be calculated by entropy measures by Bayesian methodology. This project will use a truss bridge structure with 29 degree of freedom to illustrate in this report. |
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Cheung Joseph Sai Hung |
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Cheung Joseph Sai Hung Wu, Sheng |
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Final Year Project |
author |
Wu, Sheng |
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Wu, Sheng |
title |
Optimal sensor placement for model updating of civil engineering structures subjected to future dynamic loadings |
title_short |
Optimal sensor placement for model updating of civil engineering structures subjected to future dynamic loadings |
title_full |
Optimal sensor placement for model updating of civil engineering structures subjected to future dynamic loadings |
title_fullStr |
Optimal sensor placement for model updating of civil engineering structures subjected to future dynamic loadings |
title_full_unstemmed |
Optimal sensor placement for model updating of civil engineering structures subjected to future dynamic loadings |
title_sort |
optimal sensor placement for model updating of civil engineering structures subjected to future dynamic loadings |
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2015 |
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http://hdl.handle.net/10356/64213 |
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1759856195992027136 |