An Improved Method on Reducing Measurement Noise Based on Hilbert-Huang Transform

被引：2

作者：

Cheng, Jiulong ^{[1
]}

Sun, Xiaoyun ^{[2
]}

Lv, Dandan ^{[2
]}

An, Guoqing ^{[2
]}

Zou, D. H. Steve ^{[3
]}

机构：

[1] China Univ Min & Technol, State Key Lab Coal Resources & Safe Min, Beijing 100083, Peoples R China

[2] Hebei Univ Sci& Technol, sch Elect Engn & Informat Sci, Shijiazhuang 050018, Peoples R China

[3] Dalhousie Univ, Halifax, NS, Canada

来源：

2009 IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND INTELLIGENT SYSTEMS, PROCEEDINGS, VOL 3 | 2009年

基金：

中国国家自然科学基金;

关键词：

Hilbert-Huang transform; HHT method; cross-correlation method; IMF coefficients; EMPIRICAL MODE DECOMPOSITION;

D O I：

10.1109/ICICISYS.2009.5358082

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

For nonstationary signal in rock bolts detecting, an effective denoise method based on Hilbert-Huang transform (HHT) is presented, cross-correlation for denoise signal is used to estimate the length of rock bolts At first, by empirical mode decomposition (EMD) algorithm, a sum of intrinsic mode functions (IMF) are got, and then, the IMF coefficients in useful signal dominative layer are proceeded using soft threshold method, those IMF coefficients are reconstructed, at last, cross-correlation is used to estimate the length Compared with the traditional denoise method, the above method is better to remove measurement noise and estimate the length

引用

页码：627 / +

页数：2

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