Ensemble empirical mode decomposition based fluorescence spectral noise reduction for low concentration PAHs

Shu-tao Wang , Xue-ying Yang , De-ming Kong , Yu-tian Wang

Optoelectronics Letters ›› : 432 -435.

PDF
Optoelectronics Letters ›› : 432 -435. DOI: 10.1007/s11801-017-7140-4
Article

Ensemble empirical mode decomposition based fluorescence spectral noise reduction for low concentration PAHs

Author information +
History +
PDF

Abstract

A new noise reduction method based on ensemble empirical mode decomposition (EEMD) is proposed to improve the detection effect for fluorescence spectra. Polycyclic aromatic hydrocarbons (PAHs) pollutants, as a kind of important current environmental pollution source, are highly oncogenic. Using the fluorescence spectroscopy method, the PAHs pollutants can be detected. However, instrument will produce noise in the experiment. Weak fluorescent signals can be affected by noise, so we propose a way to denoise and improve the detection effect. Firstly, we use fluorescence spectrometer to detect PAHs to obtain fluorescence spectra. Subsequently, noises are reduced by EEMD algorithm. Finally, the experiment results show the proposed method is feasible.

Cite this article

Download citation ▾
Shu-tao Wang, Xue-ying Yang, De-ming Kong, Yu-tian Wang. Ensemble empirical mode decomposition based fluorescence spectral noise reduction for low concentration PAHs. Optoelectronics Letters 432-435 DOI:10.1007/s11801-017-7140-4

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

ShenH, HuangY, WangR, ZhuD, LiW, ShenG, WangB, ZhangY, ChenY, LuY, ChenH, LiT, SunK, LiB, LiuW, LiuJ, TaoS. Environmental Science & Technology, 2013, 47: 6415

[2]

TopuzF, UyarT. Journal of Colloid & Interface Science, 2017, 497: 233

[3]

BixlerJN, ConeMT, HokrBH, MasonJD, FigueroaE, FryES, YakovlevVV, ScullyMO. Proceedings of the National Academy of Sciences of the United States of America, 2014, 111: 7208

[4]

SikorskaE, RomaniukA, KhmelinskiiI, SikorskiM, KoziołJ. Polish Journal of Food & Nutrition Sciences, 2003, 89: 217

[5]

LawaetzAJ, Kamstrup-NielsenM, ChristensenIJ, JørgensenLN, NielsenHJ. Metabolomics, 2012, 8: 122

[6]

Nguyen-NgocH, DurrieuC, Tran-MinhC. Ecotoxicology & Environmental Safety, 2009, 72: 316

[7]

TanH, LiR, ZhuY, ZhangY. Talanta, 2017, 167: 86

[8]

WANGS-t, LIM-m, LIP, LIUM-h, WANGL-y, ZENGQ-j. Acta Photonica Sinica, 2014, 43: 8

[9]

KedadoucheM, ThomasM, TahanAEmpirical Mode Decomposition of Acoustic Emission for Early Detection of Bearing DefectsAdvances in Condition Monitoring of Machinery in Non-Stationary Operations, 2014, 367

[10]

KedadoucheM, ThomasnM, TahanA. Mechanical Systems and Signal Processing, 2016, 81: 88

[11]

WuZ H, HuangN E. Advances in Adaptive Data Analysis, 2011, 1: 0980004

[12]

LIQ, WANGX, CHENL, LIUJ-g. Journal of Optoelectronics·Laser, 2016, 27: 1357

[13]

SONGD-r, ZHANGF-h, QIANGB-w. Journal of Optoelectronics·Laser, 2016, 27: 742

[14]

LiT, ChoiYH, ShinYB, KimHJ, KimMG. Chemosphere, 2016, 150: 407

AI Summary AI Mindmap
PDF

79

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/