2021 Fiscal Year Annual Research Report
Development of Seismic Damage Assessment Method for Instrumented Large Civil Structures using Sparse Representation Techniques
| Project/Area Number |
18K04320
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| Research Institution | Yokohama National University |
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Principal Investigator |
シリンゴリンゴ ディオン 横浜国立大学, 先端科学高等研究院, 特任教員(准教授) (60649507)
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| Project Period (FY) |
2018-04-01 – 2022-03-31
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| Keywords | system identification / seismic records / seismic-isolated bridge / sparse representation / wavelet decomposition / moveable bearing / structural monitoring |
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| Outline of Annual Research Achievements |
Structural identification by sparse representation model was developed and implemented using real data from full-scale seismic monitoring of three bridges. In the Tokachi Bridge sparse time-invariant,time-variant recursive subspace identification and sparse regularization methods were developed to confirm influence of moveable SFP bearings on bridge responses. In Katsuta Viaduct,techniques for detecting bearing malfunction from bridge seismic response were developed using wavelet transform time-varying identification and statistical sparse clustering technique.In Shin-Nakagawa Bridge an-FE model was developed and damages related to isolation bearing were simulated. The results were compared with monitoring from 63 seismic events in 45 months (2017-2020) using the CWT-DWT and sparse model analysis.
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