Identifying Damage Locations of Shear Building Structures Under Sparse Sensors
碩士 === 國立交通大學 === 土木工程系所 === 102 === Structures may be damaged due to ageing of material or by external force. It is necessary to acquire accurate and real-time information on the structure condition. For this purpose, structure health monitoring (SHM) for civil engineering has received considerable...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2014
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| Online Access: | http://ndltd.ncl.edu.tw/handle/34674991286203730718 |
| Summary: | 碩士 === 國立交通大學 === 土木工程系所 === 102 === Structures may be damaged due to ageing of material or by external force. It is necessary to acquire accurate and real-time information on the structure condition. For this purpose, structure health monitoring (SHM) for civil engineering has received considerable attention. Identify damage locations is one important research of structure health monitoring. Many damage detection method has been developed in last decade. Most of damage detection method use complete mode shapes information. In practical cases, we often use sparse sensors because of the high cost of sensor. Mode shape expansion techniques deal with these condition in order to acquire all degrees of freedom’s mode shape information. But traditional expansion techniques can’t expand well due to the change of structure parameter. This study use spline curve-fitting to expand mode shape information without using any structure parameter. Use pseudo story strategy and line search strategy to improve expanded mode shape information accuracy. Then use expanded mode shape information on damage detection. This study use matlab to simulate shear building structure. The result show that the expansion method of this study is better than traditional expansion method in lower mode. Also, this study identify damage locations successfully in the absence of sensor error.
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