Experimental Study on Structural Health Monitoring using Blind Source Separation Method
碩士 === 國立臺灣大學 === 土木工程學研究所 === 103 === In most civil structures, the input excitation is hard to be measured. Thus, the output-only system identification has gained lots of interest. In this research the application of output-only system identification technique known as Second Order Blind Identific...
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| Format: | Others |
| Language: | en_US |
| Published: |
2015
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| Online Access: | http://ndltd.ncl.edu.tw/handle/11239520576407394600 |
| Summary: | 碩士 === 國立臺灣大學 === 土木工程學研究所 === 103 === In most civil structures, the input excitation is hard to be measured. Thus, the output-only system identification has gained lots of interest. In this research the application of output-only system identification technique known as Second Order Blind Identification (SOBI) algorithm in civil structures is carried out.
The objective of the first part of this thesis is to inspect whether SOBI algorithm is workable on time-invariant and time-variant system when subject to either white noise excitation or earthquake excitation and compared the results to Covariance Driven Stochastic Subspace Identification (SSI-COV). SOBI algorithm is applied on: (1) Vehicle-bridge interaction system under different traffic loading (time-invariant system). (2) Steel bridge under continuous scour (time-variant system). Through the results of identification the dynamic characteristics of the system are verified and damage detection using different damage index is also investigated.
The objective of second part of this thesis is to inspect the identification ability of using SOBI algorithm when system turned into lightly non-linearity. A shaking table test of two 3-story steel structures are carried out (one is the symmetric structure and the other is the unsymmetrical structure). For specimen 1, dynamic characteristics identified by SOBI algorithm are combined with ABAQUS CAE to estimate the local property, such as member stress. For specimen 2, additional lateral and torsion modes are identified using SOBI and the result is compared with the subspace identification technique.
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