AN INTRODUCTION TO COMPRESSIVE SENSING AND ITS POTENTIAL APPLICATIONS IN STRUCTURAL ENGINEERING
The Shannon/Nyquist sampling theorem specifies that to avoid losing information when capturing a signal,one must sample at least two times faster than the signal bandwidth. In order to capture and represent compressible signals at a rate significantly below the Nyquist rate,a new method,called compressive sensing (CS),is therefore proposed. CS theory asserts that one can recover certain signals from far fewer samples or measurements than traditional methods use. It employs non-adaptive linear projections that preserve the structure of the sparse signal; the signal is then reconstructed from these projections using an optimization process. It is believed that CS has far reaching implications,while most publications concentrate on signal processing fields (especially for images). In this paper,we provide a concise introduction of CS and then discuss some of its potential applications in structural engineering. The recorded vibration time history of a steel beam and the wave propagation result on a steel rebar are studied in detail. CS is adopted to reconstruct the time histories by using only parts of the signals. The results under different conditions are compared,which confirm that CS will be a promising tool for structural engineering.
Compressive sensing Structural engineering Sampling rate Optimization
Ying Wang Hong Hao
School of Civil and Resource Engineering,the University of Western Australia,Crawley,WA 6009,Australia
国际会议
The Eleventh International Symposium on Structural Engineering(第十一届结构工程国际研讨会)
广州
英文
1089-1094
2010-12-01（万方平台首次上网日期，不代表论文的发表时间）