Structural damage detection considering sensor performance degradation and measurement noise effect
In the real civil structures, material deterioration, overloading and environmental corrosion inevitably lead to sensor performance degradation or sensor fault. Sensor performance degradation or sensor fault usually introduce observable changes in the measured structural responses, which may be inco...
| Main Authors: | , , |
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| Format: | Journal Article |
| Published: |
Elsevier
2019
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| Online Access: | http://hdl.handle.net/20.500.11937/70829 |
| _version_ | 1848762313525428224 |
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| author | Ma, S. Jiang, S. Li, Jun |
| author_facet | Ma, S. Jiang, S. Li, Jun |
| author_sort | Ma, S. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | In the real civil structures, material deterioration, overloading and environmental corrosion inevitably lead to sensor performance degradation or sensor fault. Sensor performance degradation or sensor fault usually introduce observable changes in the measured structural responses, which may be incorrectly interpreted as structural damage. This paper proposes a novel approach to quickly distinguish sensor fault from structural damage and locate the faulty or degraded sensors. Two steps are involved in this approach. In the first step, the root mean square of the generalized likelihood ratio test (GLRT) is used to detect and localize the structural damage or degraded sensors. In the second step, a new index is proposed used along with the statistical process control chart to distinguish sensor performance degradation from structural damage. The proposed index is the percentage of the extreme value of the largest principal component scores of the generalized likelihood ratio, which not only has excellent noise tolerance but also can distinguish sensor performance degradation from structural damage. The applicability and efficiency of the proposed approach are validated by numerical studies on a planar 11-element truss structure and experimental studies on a simply-supported steel beam in the laboratory. The results demonstrate that the proposed approach can locate the damage accurately when taking into account of sensor performance degradation and environmental noise in the measurements. The proposed index is able to accurately and quickly determine the source of the novelty in the responses. |
| first_indexed | 2025-11-14T10:45:35Z |
| format | Journal Article |
| id | curtin-20.500.11937-70829 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T10:45:35Z |
| publishDate | 2019 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-708292019-06-27T03:26:17Z Structural damage detection considering sensor performance degradation and measurement noise effect Ma, S. Jiang, S. Li, Jun In the real civil structures, material deterioration, overloading and environmental corrosion inevitably lead to sensor performance degradation or sensor fault. Sensor performance degradation or sensor fault usually introduce observable changes in the measured structural responses, which may be incorrectly interpreted as structural damage. This paper proposes a novel approach to quickly distinguish sensor fault from structural damage and locate the faulty or degraded sensors. Two steps are involved in this approach. In the first step, the root mean square of the generalized likelihood ratio test (GLRT) is used to detect and localize the structural damage or degraded sensors. In the second step, a new index is proposed used along with the statistical process control chart to distinguish sensor performance degradation from structural damage. The proposed index is the percentage of the extreme value of the largest principal component scores of the generalized likelihood ratio, which not only has excellent noise tolerance but also can distinguish sensor performance degradation from structural damage. The applicability and efficiency of the proposed approach are validated by numerical studies on a planar 11-element truss structure and experimental studies on a simply-supported steel beam in the laboratory. The results demonstrate that the proposed approach can locate the damage accurately when taking into account of sensor performance degradation and environmental noise in the measurements. The proposed index is able to accurately and quickly determine the source of the novelty in the responses. 2019 Journal Article http://hdl.handle.net/20.500.11937/70829 10.1016/j.measurement.2018.08.040 Elsevier restricted |
| spellingShingle | Ma, S. Jiang, S. Li, Jun Structural damage detection considering sensor performance degradation and measurement noise effect |
| title | Structural damage detection considering sensor performance degradation and measurement noise effect |
| title_full | Structural damage detection considering sensor performance degradation and measurement noise effect |
| title_fullStr | Structural damage detection considering sensor performance degradation and measurement noise effect |
| title_full_unstemmed | Structural damage detection considering sensor performance degradation and measurement noise effect |
| title_short | Structural damage detection considering sensor performance degradation and measurement noise effect |
| title_sort | structural damage detection considering sensor performance degradation and measurement noise effect |
| url | http://hdl.handle.net/20.500.11937/70829 |