Fault detection and isolation using neural networks in structural dynamic systems
In general, there is a possibility of degradation in stiffness due to environmental loadings such as earthquakes, for multi-storey steel frame structures, which are designed with enough stiffness and strength. Study on the identification of failure of such systems and taking corrective actions will...
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| Format: | Thesis |
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2008
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| Online Access: | http://hdl.handle.net/10356/5020 |
| _version_ | 1826113714949980160 |
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| author | Pandian Thirupura Sundari |
| author2 | Sundararajan, Narasimhan |
| author_facet | Sundararajan, Narasimhan Pandian Thirupura Sundari |
| author_sort | Pandian Thirupura Sundari |
| collection | NTU |
| description | In general, there is a possibility of degradation in stiffness due to environmental loadings such as earthquakes, for multi-storey steel frame structures, which are designed with enough stiffness and strength. Study on the identification of failure of such systems and taking corrective actions will go a long way in improving the safety of the systems. In this dissertation, the above structural dynamic system represented by a spring mass damper system (two masses) is considered here for the ease and understanding of solving this problem. |
| first_indexed | 2024-10-01T03:27:25Z |
| format | Thesis |
| id | ntu-10356/5020 |
| institution | Nanyang Technological University |
| last_indexed | 2024-10-01T03:27:25Z |
| publishDate | 2008 |
| record_format | dspace |
| spelling | ntu-10356/50202023-07-04T15:11:01Z Fault detection and isolation using neural networks in structural dynamic systems Pandian Thirupura Sundari Sundararajan, Narasimhan School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems DRNTU::Engineering::Computer science and engineering::Computing methodologies In general, there is a possibility of degradation in stiffness due to environmental loadings such as earthquakes, for multi-storey steel frame structures, which are designed with enough stiffness and strength. Study on the identification of failure of such systems and taking corrective actions will go a long way in improving the safety of the systems. In this dissertation, the above structural dynamic system represented by a spring mass damper system (two masses) is considered here for the ease and understanding of solving this problem. Master of Science (Computer Control and Automation) 2008-09-17T10:03:26Z 2008-09-17T10:03:26Z 2006 2006 Thesis http://hdl.handle.net/10356/5020 Nanyang Technological University application/pdf |
| spellingShingle | DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems DRNTU::Engineering::Computer science and engineering::Computing methodologies Pandian Thirupura Sundari Fault detection and isolation using neural networks in structural dynamic systems |
| title | Fault detection and isolation using neural networks in structural dynamic systems |
| title_full | Fault detection and isolation using neural networks in structural dynamic systems |
| title_fullStr | Fault detection and isolation using neural networks in structural dynamic systems |
| title_full_unstemmed | Fault detection and isolation using neural networks in structural dynamic systems |
| title_short | Fault detection and isolation using neural networks in structural dynamic systems |
| title_sort | fault detection and isolation using neural networks in structural dynamic systems |
| topic | DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems DRNTU::Engineering::Computer science and engineering::Computing methodologies |
| url | http://hdl.handle.net/10356/5020 |
| work_keys_str_mv | AT pandianthirupurasundari faultdetectionandisolationusingneuralnetworksinstructuraldynamicsystems |