Abstract
The intrinsic low-dimensional structure, which is implicit in the large-scale data sets of structural seismic and typhoon responses, is exploited for efficient data compression. Such a low-dimensional structure, empirically, stems from few modes that are active in the structural dynamic responses. Originally, limited to the sensor and time-history dimension, the structural seismic and typhoon response data set generally does not have an explicit low-rank representation (e.g., by singular value decomposition or principal component analysis), which is critical in multi-channel data compression. By the proposed matrix reshape scheme, the low-rank structure of the large-scale data set stands out, regardless of the original data dimension. Examples demonstrate that the developed method can significantly compress the large-scale structural seismic and typhoon response data sets, which were recorded by the structural health monitoring system of the super high-rise Canton Tower.
Original language | English |
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Pages (from-to) | 1119-1131 |
Number of pages | 13 |
Journal | Structural Control and Health Monitoring |
Volume | 22 |
Issue number | 8 |
DOIs | |
Publication status | Published - 1 Jan 2015 |
Keywords
- data compression
- Large scale SHM
- Low rank representation
- Matrix reshaping
- Seismic response
- Typhoon response
- Very large scale data
ASJC Scopus subject areas
- Civil and Structural Engineering
- Building and Construction
- Mechanics of Materials