Fault diagnosis and prognosis of hybrid systems using bond graph models and computational intelligence
Fault diagnosis and prognosis have received a lot of attention from the Prognostics and Health Management (PHM) society in the past decades. PHM society is a non-profit organization dedicated to the advancement of PHM as an engineering discipline. The society was incorporated in early 2009 as a New...
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| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
2012
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| Online Access: | https://hdl.handle.net/10356/50480 |
| _version_ | 1811689543549583360 |
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| author | Yu, Ming |
| author2 | Wang Dan Wei |
| author_facet | Wang Dan Wei Yu, Ming |
| author_sort | Yu, Ming |
| collection | NTU |
| description | Fault diagnosis and prognosis have received a lot of attention from the Prognostics and Health Management (PHM) society in the past decades. PHM society is a non-profit organization dedicated to the advancement of PHM as an engineering discipline. The society was incorporated in early 2009 as a New York corporation. The flagship event of the society is the Annual Conference of the PHM Society.
As the complexity of industrial systems increases, fault diagnosis become more and
more important since it is a crucial means to maintain system safety and reliability.
Faults need to be detected close to their occurrence time, so that corrective actions can
be taken in a timely manner, and thus avoid catastrophic consequences. These actions
include resetting control parameters to compensate for the faults, or reconfiguring the
system to minimize the effects of the fault. |
| first_indexed | 2024-10-01T05:49:46Z |
| format | Thesis |
| id | ntu-10356/50480 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:49:46Z |
| publishDate | 2012 |
| record_format | dspace |
| spelling | ntu-10356/504802023-07-04T16:55:10Z Fault diagnosis and prognosis of hybrid systems using bond graph models and computational intelligence Yu, Ming Wang Dan Wei School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering Fault diagnosis and prognosis have received a lot of attention from the Prognostics and Health Management (PHM) society in the past decades. PHM society is a non-profit organization dedicated to the advancement of PHM as an engineering discipline. The society was incorporated in early 2009 as a New York corporation. The flagship event of the society is the Annual Conference of the PHM Society. As the complexity of industrial systems increases, fault diagnosis become more and more important since it is a crucial means to maintain system safety and reliability. Faults need to be detected close to their occurrence time, so that corrective actions can be taken in a timely manner, and thus avoid catastrophic consequences. These actions include resetting control parameters to compensate for the faults, or reconfiguring the system to minimize the effects of the fault. DOCTOR OF PHILOSOPHY (EEE) 2012-06-06T02:26:52Z 2012-06-06T02:26:52Z 2012 2012 Thesis Yu, M. (2012). Fault diagnosis and prognosis of hybrid systems using bond graph models and computational intelligence. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/50480 10.32657/10356/50480 en 205 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering Yu, Ming Fault diagnosis and prognosis of hybrid systems using bond graph models and computational intelligence |
| title | Fault diagnosis and prognosis of hybrid systems using bond graph models and computational intelligence |
| title_full | Fault diagnosis and prognosis of hybrid systems using bond graph models and computational intelligence |
| title_fullStr | Fault diagnosis and prognosis of hybrid systems using bond graph models and computational intelligence |
| title_full_unstemmed | Fault diagnosis and prognosis of hybrid systems using bond graph models and computational intelligence |
| title_short | Fault diagnosis and prognosis of hybrid systems using bond graph models and computational intelligence |
| title_sort | fault diagnosis and prognosis of hybrid systems using bond graph models and computational intelligence |
| topic | DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering |
| url | https://hdl.handle.net/10356/50480 |
| work_keys_str_mv | AT yuming faultdiagnosisandprognosisofhybridsystemsusingbondgraphmodelsandcomputationalintelligence |