Paper Info
Title
Blind source separation towards decentralized modal identification using compressive sampling
Abstract
Wireless sensing technology has gained significant attention in the field of structural health monitoring (SHM). Various decentralized modal identification methods have been developed employing wireless sensors. However, one of themajor bottlenecks - especially dealing with long-term SHM - is the large volume of transmitted data. To overcome this problem, we present compressed sensing as a data reduction preprocessing tool within the framework of blind source separation. The results of source separation are ultimately used for modal identification of linear structures under ambient vibrations. When used together with sparsifying time-frequency decompositions, we show that accurate modal identification results are possible with high compression ratios. The main novelty in the method proposed here is in the application of compressive sensing for decentralized modal identification of civil structures.
Year
DOI
Venue
2012
10.1109/ISSPA.2012.6310463
Information Science, Signal Processing and their Applications
Keywords
Field
DocType
blind source separation,computerised instrumentation,condition monitoring,signal reconstruction,structural engineering computing,vibrations,wireless sensor networks,SHM,blind source separation,civil structures,compressive sampling,data reduction preprocessing tool,decentralized modal identification methods,sparsifying time-frequency decompositions,structural health monitoring,wireless sensing technology
Telecommunications,Computer science,Electronic engineering,Condition monitoring,Artificial intelligence,Blind signal separation,Compressed sensing,Source separation,Pattern recognition,Structural health monitoring,Wireless sensor network,Signal reconstruction,Modal
Conference
ISBN
Citations 
PageRank 
978-1-4673-0380-4
0
0.34
References 
Authors
5
3
Name
Order
Citations
PageRank
Ayan Sadhu100.34
Bo Hu216127.21
Sriram Narasimhan300.34