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Optimal sensor placement approaches for the design of inverse experiments by simulation
Dissertation (MEng)--University of Pretoria, 2017.
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| Format: | Thesis |
| Language: | English |
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University of Pretoria
2017
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| _version_ | 1867613548108054528 |
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| access_status_str | Open Access |
| author2 | Wilke, Daniel Nicolas |
| author_browse | Wilke, Daniel Nicolas |
| author_facet | Wilke, Daniel Nicolas |
| collection | Thesis |
| dc_rights_str_mv | © 2017 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
| description | Dissertation (MEng)--University of Pretoria, 2017. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/59503 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:37:53.400Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2017 |
| publishDateRange | 2017 |
| publishDateSort | 2017 |
| publisher | University of Pretoria |
| publisherStr | University of Pretoria |
| record_format | dspace |
| source_str | UPSpace — University of Pretoria Institutional Repository |
| spelling | oai:repository.up.ac.za:2263/59503 Optimal sensor placement approaches for the design of inverse experiments by simulation Wilke, Daniel Nicolas Chae, Younghwan UCTD Optimal sensor placement Inverse experiments Simulation Engineering, built environment and information technology theses SDG-09 SDG-09: Industry, innovation and infrastructure Engineering, built environment and information technology theses SDG-07 SDG-07: Affordable and clean energy Engineering, built environment and information technology theses SDG-12 SDG-12: Responsible consumption and production Dissertation (MEng)--University of Pretoria, 2017. This dissertation serves to present the research conducted on sensor placement optimisation (SPO) using sensitivity analyses of virtual experiments in order to design virtual inverse problems. Two classes of SPO methods are considered namely mode-based and mode-free approaches. The mode-based approaches make use of SIMPLS and SVD to extract useful data by examining the correlation between the target variables (characterising variables) and the sensor measurement variables, while the mode-free approaches eliminate the need of spending the extra time required to extract modes, which ultimately leads to successful sensor placement for solving inverse problems. The aim of the mode-free approach is to maximise the variance explained subject to uniqueness of the information of each sensor. Both approaches aim to maximise the potential of an experimental setup to solve an inverse problem by using the right number of sensors and placing them at the optimal spatial positions. SPO is not only capable of designing an experiment but it is also capable of classifying the well-posed or ill- posed nature of an existing experiment that can be modelled, which saves both time and cost. The approach followed in this study was to design a simple virtual inverse problem for which the well or ill-posedness of the problem can be controlled. Numerous virtual experiments were conducted that varied from well-posed to severely ill-posed to allow for rigorous testing of the various approaches. The e ect of model error and stochastic noise on ability to reliably place sensors is also investigated. National Research Foundation (NRF) mi2025 Mechanical and Aeronautical Engineering MEng Unrestricted SDG-09: Industry, innovation and infrastructure SDG-07: Affordable and clean energy SDG-12: Responsible consumption and production 2017-03-22T13:41:57Z 2017-03-22T13:41:57Z 2017 2017 Dissertation Chae, Y 2017, Optimal sensor placement approaches for the design of inverse experiments by simulation, MEng Dissertation, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/59503> A2017 http://hdl.handle.net/2263/59503 en © 2017 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria |
| spellingShingle | UCTD Optimal sensor placement Inverse experiments Simulation Engineering, built environment and information technology theses SDG-09 SDG-09: Industry, innovation and infrastructure Engineering, built environment and information technology theses SDG-07 SDG-07: Affordable and clean energy Engineering, built environment and information technology theses SDG-12 SDG-12: Responsible consumption and production Optimal sensor placement approaches for the design of inverse experiments by simulation |
| title | Optimal sensor placement approaches for the design of inverse experiments by simulation |
| title_full | Optimal sensor placement approaches for the design of inverse experiments by simulation |
| title_fullStr | Optimal sensor placement approaches for the design of inverse experiments by simulation |
| title_full_unstemmed | Optimal sensor placement approaches for the design of inverse experiments by simulation |
| title_short | Optimal sensor placement approaches for the design of inverse experiments by simulation |
| title_sort | optimal sensor placement approaches for the design of inverse experiments by simulation |
| topic | UCTD Optimal sensor placement Inverse experiments Simulation Engineering, built environment and information technology theses SDG-09 SDG-09: Industry, innovation and infrastructure Engineering, built environment and information technology theses SDG-07 SDG-07: Affordable and clean energy Engineering, built environment and information technology theses SDG-12 SDG-12: Responsible consumption and production |
| url | http://hdl.handle.net/2263/59503 |