主题：【求助】哪位朋友有此类近红外数据

自然科学 >> 化学 >> 分析化学 >> 摘要
小波系数压缩用于柴油十六烷值近红外光谱分析建模评论推荐             
                     
熊智新[1] 徐广通[2] 胡上序[3]
[1]南京林业大学化学工程学院自动化教研室,南京市龙蟠路159号210037 [2]中国石油化工科学研究院,北京市海淀区学院路18号100083 [3]浙江大学材料与化学工程学院,杭州市浙大路38号310027

《光谱实验室》
2006年第23卷第2期
论文发表速发快发（点击进入）

核心期刊论文快速发表（点击进入）
摘　　要:近红外光谱分析建模中存在多变量高维数据处理问题,导致计算量大,不利于过程控制中应用.为此提出利用小波变换压缩近红外光谱数据的算法与准则,并结合柴油十六烷值定量分析研究压缩数据的建模效果.研究表明,经小波方法处理后,变量维数压缩30倍左右,光谱主要信息基本保留,而模型的预测精度和常规预处理方法分析相比有明显提高.光谱数据压缩的同时包含了噪声滤除和基线校正,简化数据处理步骤,有利于NIRS实际应用时提高建模效率. (共6页)
 
关 键 词:近红外光谱 小波变换 数据压缩 十六烷值.
学科分类:O65[数理科学和化学 > 化学 > 分析化学]
相关文章:主题相关 参考文献(7篇)　被引情况(1篇)　耦合文献(211篇)

你把这篇文章下载后看看

http://www.osti.gov/energycitations/product.biblio.jsp?osti_id=6847857
Home  •  Basic Search  •  Fielded Search  •  Alerts  •  Document Availability Bibliographic Citation 
Download as EndNote Return to Search Results Return to Original Search Page 
Document
For copies of Journal Articles, please contact the Publisher or your local public or university library and refer to the information in the Resource Relation field.
For copies of other documents, please see the Availability, Publisher, Research Organization, Resource Relation and/or Author (affiliation information) fields and/or Document Availability. 
Title On-line NIR analysis and advanced control improve gasoline blending
Creator/Author Espinosa, A. ; Sanchez, M. ; Osta, S. ; Boniface, C. ; Gil, J. (BP, Lavera (France)) ; Martens, A. ; Descales, B. ; Lambert, D. (BP Chemicals, Lavera (France)) ; Valleur, M. (Technip, Paris (France)) 
Publication Date 1994 Oct 17
OSTI Identifier OSTI ID: 6847857
Other Number(s) Journal ID: ISSN 0030-1388; CODEN: OIGJAV
Resource Type Journal Article
Resource Relation Journal Name: Oil and Gas Journal; (United States); Journal Volume: 92:42
Subject 02 PETROLEUM; FRANCE; PETROLEUM REFINERIES; GASOLINE; MIXING; ON-LINE CONTROL SYSTEMS; ON-LINE MEASUREMENT SYSTEMS; ABSORPTION SPECTROSCOPY; DATA ANALYSIS; FLOWSHEETS; NEAR INFRARED RADIATION; PROCESS CONTROL; CONTROL; CONTROL SYSTEMS; DEVELOPED COUNTRIES; DIAGRAMS; ELECTROMAGNETIC RADIATION; EUROPE; FUELS; INDUSTRIAL PLANTS; INFRARED RADIATION; LIQUID FUELS; ON-LINE SYSTEMS; PETROLEUM PRODUCTS; RADIATIONS; SPECTROSCOPY; WESTERN EUROPE
Description/Abstract A near-infrared (NIR), advanced control system has been controlling the gasoline blender at BP France's Lavera refinery for more than 2 years. The blender produces 1 million metric tons/year gasoline (about 21,000 b/d) using multivariable blend-control software in a closed-loop mode. BP's system uses a centralized NIR spectrometer fitted with optical fibers that carry NIR radiation between the instrument and process streams. The analyzer monitors the product stream from the blender and transmits data to the control software, which adjusts the component flow rates to meet target specifications. The system computes blending indices using an innovative approach based on the NIR response of the individual basestocks. The paper discusses NIR analysis, blending optimization, the Lavera project, BP methodology, data treatment, system assessment, and benefits.
Country of Publication United States
Language English
Format Medium: X; Size: Pages: 49-56
System Entry Date 2008 Feb 08

你再看看这篇文章

http://pubs.acs.org/doi/abs/10.1021/ci000447r
这篇也相关的

Multivariate Analysis of Near-Infrared Spectra Using the G-Programming Language
Abstract
Olusola O. Soyemi, Marianna A. Busch, and Kenneth W. Busch*
Center for Analytical Spectroscopy, Baylor University, P.O. Box 97348, Waco, Texas 76798-7348

J. Chem. Inf. Comput. Sci., 2000, 40 (5), pp 1093–1100
DOI: 10.1021/ci000447r
Publication Date (Web): July 6, 2000
Copyright © 2000 American Chemical Society
* In papers with more than one author, the asterisk indicates the name of the author to whom inquiries about the paper should be addressed.

Abstract“Real-time” chemometrics as envisioned by the union of instrument control, data acquisition, and chemometric analysis with a single software platform can provide substantial benefits to manufacturing concerns that require process control. Some of these benefits include faster generation of information and improved quality control. This paper describes a series of chemometric routines written in LabVIEW and demonstrates their use in predicting six properties of diesel fuel. In particular, near-infrared spectral data were used to predict the boiling point at 50% recovery, cetane number, density, freezing temperature, total aromatics, and viscosity for a series of diesel fuels.

谢谢上面两位，不过我不是需要这方面的文章，而是用仪器检测出来的数据。

原文由 wandouhua100 发表:
谢谢上面两位，不过我不是需要这方面的文章，而是用仪器检测出来的数据。

什么数据？光谱图和实验室检测的数据一般不会给你的。