DocumentCode
2071210
Title
Noise Reduction Technology of Random Vibration Signal Based on Singular Entropy Theory
Author
Jianwei, Zhang ; Huokun, Li
Author_Institution
North China Univ. of Water Conservancy & Electr. Power, Zhengzhou, China
fYear
2009
fDate
26-28 Dec. 2009
Firstpage
32
Lastpage
35
Abstract
Structural random vibration effective information extraction is one of the most important issues to study the dynamic characteristics of engineering structures. Combined with singular entropy theory, an effective method of noise reduction for random vibration signal is put forward. Construct analog signal with varying degrees of noise, and the noise is reduced based on the wavelet method, IIR numeric filter, and singular entropy technique separately, and also the SNR index is calculated separately after noise reduction. Study shows that this method can determine the proper order of singular spectrum of the random vibration signal, and ensure the integrity of information contained in the signal after noise reduction and the maximum SNR improvement to a large extent. This is essential to extract the accurate signal feature and reliable analysis.
Keywords
IIR filters; acoustic signal processing; entropy; noise abatement; signal denoising; structural engineering; vibrations; wavelet transforms; IIR numeric filter; analog signal; dynamic characteristics; engineering structures; information extraction; noise reduction technology; random vibration signal; singular entropy technique; singular entropy theory; structural random vibration; wavelet method; Data mining; Entropy; Matrix decomposition; Noise reduction; Power engineering and energy; Signal analysis; Signal processing; Signal to noise ratio; Singular value decomposition; Testing; noise reduction technology; order determination; singular entropy theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Science and Engineering (ISISE), 2009 Second International Symposium on
Conference_Location
Shanghai
Print_ISBN
978-1-4244-6325-1
Electronic_ISBN
978-1-4244-6326-8
Type
conf
DOI
10.1109/ISISE.2009.113
Filename
5447223
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