A Data-Driven Noise Reduction Method and Its Application for the Enhancement of Stress Wave Signals
Joint Authors
Fang, Yi-Ming
Xiang, Xuan-Qi
Li, Guan-Hui
Li, Jian
Feng, Hai-Lin
Source
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-11-20
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Natural & Life Sciences (Multidisciplinary)
Medicine
Information Technology and Computer Science
Abstract EN
Ensemble empirical mode decomposition (EEMD) has been recently used to recover a signal from observed noisy data.
Typically this is performed by partial reconstruction or thresholding operation.
In this paper we describe an efficient noise reduction method.
EEMD is used to decompose a signal into several intrinsic mode functions (IMFs).
The time intervals between two adjacent zero-crossings within the IMF, called instantaneous half period (IHP), are used as a criterion to detect and classify the noise oscillations.
The undesirable waveforms with a larger IHP are set to zero.
Furthermore, the optimum threshold in this approach can be derived from the signal itself using the consecutive mean square error (CMSE).
The method is fully data driven, and it requires no prior knowledge of the target signals.
This method can be verified with the simulative program by using Matlab.
The denoising results are proper.
In comparison with other EEMD based methods, it is concluded that the means adopted in this paper is suitable to preprocess the stress wave signals in the wood nondestructive testing.
American Psychological Association (APA)
Feng, Hai-Lin& Fang, Yi-Ming& Xiang, Xuan-Qi& Li, Jian& Li, Guan-Hui. 2012. A Data-Driven Noise Reduction Method and Its Application for the Enhancement of Stress Wave Signals. The Scientific World Journal،Vol. 2012, no. 2012, pp.1-7.
https://search.emarefa.net/detail/BIM-465196
Modern Language Association (MLA)
Feng, Hai-Lin…[et al.]. A Data-Driven Noise Reduction Method and Its Application for the Enhancement of Stress Wave Signals. The Scientific World Journal No. 2012 (2012), pp.1-7.
https://search.emarefa.net/detail/BIM-465196
American Medical Association (AMA)
Feng, Hai-Lin& Fang, Yi-Ming& Xiang, Xuan-Qi& Li, Jian& Li, Guan-Hui. A Data-Driven Noise Reduction Method and Its Application for the Enhancement of Stress Wave Signals. The Scientific World Journal. 2012. Vol. 2012, no. 2012, pp.1-7.
https://search.emarefa.net/detail/BIM-465196
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-465196