Sensor selection and placement using low complexity dynamic programming
In this paper, a novel approach is proposed for sensor selection and placement in systems for the purpose of fault detection and isolation (FDI). This new approach benefits from the basic fact that faults are embedded in the analytical redundancy relations (ARRs) and that the occurrence of a fault w...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2013
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| Online Access: | https://hdl.handle.net/10356/105522 http://hdl.handle.net/10220/17953 http://dx.doi.org/10.1109/ICPHM.2012.6299519 |
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| author | Chi, Guoyi Le, Tung Wang, Danwei Yu, Ming Luo, Ming |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Chi, Guoyi Le, Tung Wang, Danwei Yu, Ming Luo, Ming |
| author_sort | Chi, Guoyi |
| collection | NTU |
| description | In this paper, a novel approach is proposed for sensor selection and placement in systems for the purpose of fault detection and isolation (FDI). This new approach benefits from the basic fact that faults are embedded in the analytical redundancy relations (ARRs) and that the occurrence of a fault will cause the corresponding ARRs to change. For FDI purposes, each ARR is connected to a set of sensors that represent the measurable variables. New concepts of fault associated sets and fault distinguishable sets are introduced to develop a low complexity dynamic programming algorithm to minimize the number of sensors needed and simultaneously to guarantee all possible faults being detectable and isolable. A case study of a fuel-cell system shows that the proposed method performs well when the numbers of faults and sensors are moderate. |
| first_indexed | 2024-10-01T03:21:26Z |
| format | Conference Paper |
| id | ntu-10356/105522 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:21:26Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/1055222019-12-06T21:52:57Z Sensor selection and placement using low complexity dynamic programming Chi, Guoyi Le, Tung Wang, Danwei Yu, Ming Luo, Ming School of Electrical and Electronic Engineering IEEE Conference on Prognostics and Health Management (2012 : Denver, Colorado, US) In this paper, a novel approach is proposed for sensor selection and placement in systems for the purpose of fault detection and isolation (FDI). This new approach benefits from the basic fact that faults are embedded in the analytical redundancy relations (ARRs) and that the occurrence of a fault will cause the corresponding ARRs to change. For FDI purposes, each ARR is connected to a set of sensors that represent the measurable variables. New concepts of fault associated sets and fault distinguishable sets are introduced to develop a low complexity dynamic programming algorithm to minimize the number of sensors needed and simultaneously to guarantee all possible faults being detectable and isolable. A case study of a fuel-cell system shows that the proposed method performs well when the numbers of faults and sensors are moderate. 2013-11-29T07:14:41Z 2019-12-06T21:52:57Z 2013-11-29T07:14:41Z 2019-12-06T21:52:57Z 2012 2012 Conference Paper Chi, G., Le, T., Wang, D., Yu, M., & Luo, M. (2012).Sensor selection and placement using low complexity dynamic programming. 2012 IEEE Conference on Prognostics and Health Management (PHM), 1-6. https://hdl.handle.net/10356/105522 http://hdl.handle.net/10220/17953 http://dx.doi.org/10.1109/ICPHM.2012.6299519 en |
| spellingShingle | Chi, Guoyi Le, Tung Wang, Danwei Yu, Ming Luo, Ming Sensor selection and placement using low complexity dynamic programming |
| title | Sensor selection and placement using low complexity dynamic programming |
| title_full | Sensor selection and placement using low complexity dynamic programming |
| title_fullStr | Sensor selection and placement using low complexity dynamic programming |
| title_full_unstemmed | Sensor selection and placement using low complexity dynamic programming |
| title_short | Sensor selection and placement using low complexity dynamic programming |
| title_sort | sensor selection and placement using low complexity dynamic programming |
| url | https://hdl.handle.net/10356/105522 http://hdl.handle.net/10220/17953 http://dx.doi.org/10.1109/ICPHM.2012.6299519 |
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