Study on the Noise Reduction of Vehicle Exhaust NOX Spectra Based on Adaptive EEMD Algorithm

doi:10.1155/2017/3290420

CORC > 合肥物质科学研究院 > 中国科学院合肥物质科学研究院 > 中科院安徽光学精密机械研究所

	Study on the Noise Reduction of Vehicle Exhaust NOX Spectra Based on Adaptive EEMD Algorithm
	Zhang, Kai 1,2,3; Zhang, Yujun 1; You, Kun 1; He, Ying 1,2; Gao, Qiankun 1,2; Liu, Guohua 1,2; He, Chungui 1,2; Lu, Yibing 1,2; Fan, Boqiang 1,2; Tang, Qixing 1,2
刊名	JOURNAL OF SPECTROSCOPY
	2017
期号	无页码:1-7
DOI	10.1155/2017/3290420
文献子类	Article
英文摘要	It becomes a key technology to measure the concentration of the vehicle exhaust components with the transmission spectra. But in the conventional methods for noise reduction and baseline correction, such as wavelet transform, derivative, interpolation, polynomial fitting, and so forth, the basic functions of these algorithms, the number of decomposition layers, and the way to reconstruct the signal have to be adjusted according to the characteristics of different components in the transmission spectra. The parameter settings of the algorithms above are not transcendental, so with them, it is difficult to achieve the best noise reduction effect for the vehicle exhaust spectra which are sharp and drastic in the waveform. In this paper, an adaptive ensemble empirical mode decomposition (EEMD) denoising model based on a special normalized index optimization is proposed and used in the spectral noise reduction of vehicle exhaust NOX. It is shown with the experimental results that the method can effectively improve the accuracy of the spectral noise reduction and simplify the denoising process and its operation difficulty.
WOS研究方向	Biochemistry & Molecular Biology ; Spectroscopy
语种	英语
WOS记录号	WOS:000404413900001
资助机构	National Key Research and Development Program of China(2016YFC0201003) ; National Key Research and Development Program of China(2016YFC0201003) ; National Key Research and Development Program of China(2016YFC0201003) ; National Key Research and Development Program of China(2016YFC0201003) ; National Key Research and Development Program of China(2016YFC0201003) ; National Key Research and Development Program of China(2016YFC0201003) ; National Key Research and Development Program of China(2016YFC0201003) ; National Key Research and Development Program of China(2016YFC0201003) ; 863 National High Technology Research and Development Program of China(2014AA06A503) ; 863 National High Technology Research and Development Program of China(2014AA06A503) ; 863 National High Technology Research and Development Program of China(2014AA06A503) ; 863 National High Technology Research and Development Program of China(2014AA06A503) ; 863 National High Technology Research and Development Program of China(2014AA06A503) ; 863 National High Technology Research and Development Program of China(2014AA06A503) ; 863 National High Technology Research and Development Program of China(2014AA06A503) ; 863 National High Technology Research and Development Program of China(2014AA06A503) ; National Key Research and Development Program of China(2016YFC0201003) ; National Key Research and Development Program of China(2016YFC0201003) ; National Key Research and Development Program of China(2016YFC0201003) ; National Key Research and Development Program of China(2016YFC0201003) ; National Key Research and Development Program of China(2016YFC0201003) ; National Key Research and Development Program of China(2016YFC0201003) ; National Key Research and Development Program of China(2016YFC0201003) ; National Key Research and Development Program of China(2016YFC0201003) ; 863 National High Technology Research and Development Program of China(2014AA06A503) ; 863 National High Technology Research and Development Program of China(2014AA06A503) ; 863 National High Technology Research and Development Program of China(2014AA06A503) ; 863 National High Technology Research and Development Program of China(2014AA06A503) ; 863 National High Technology Research and Development Program of China(2014AA06A503) ; 863 National High Technology Research and Development Program of China(2014AA06A503) ; 863 National High Technology Research and Development Program of China(2014AA06A503) ; 863 National High Technology Research and Development Program of China(2014AA06A503)
内容类型	期刊论文
源URL	[http://ir.hfcas.ac.cn:8080/handle/334002/31999]
专题	合肥物质科学研究院_中科院安徽光学精密机械研究所
作者单位	1.Chinese Acad Sci, Anhui Inst Opt & Fine Mech, Key Lab Environm Opt & Technol, Hefei 230031, Anhui, Peoples R China 2.Univ Sci & Technol China, Hefei 230026, Anhui, Peoples R China 3.Key Lab Opt Monitoring Technol Environm, Hefei 230031, Anhui, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Kai,Zhang, Yujun,You, Kun,et al. Study on the Noise Reduction of Vehicle Exhaust NOX Spectra Based on Adaptive EEMD Algorithm[J]. JOURNAL OF SPECTROSCOPY,2017(无):1-7.
APA	Zhang, Kai.,Zhang, Yujun.,You, Kun.,He, Ying.,Gao, Qiankun.,...&Liu, Wenqing.(2017).Study on the Noise Reduction of Vehicle Exhaust NOX Spectra Based on Adaptive EEMD Algorithm.JOURNAL OF SPECTROSCOPY(无),1-7.
MLA	Zhang, Kai,et al."Study on the Noise Reduction of Vehicle Exhaust NOX Spectra Based on Adaptive EEMD Algorithm".JOURNAL OF SPECTROSCOPY .无(2017):1-7.