基于近红外波长组合快速检测油页岩含油率

王智宏; 张福东; 滕飞; 王炳建; 孙玉洋; 刘杰

doi:10.3788/OPE.20152302.0371

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基于近红外波长组合快速检测油页岩含油率

现代应用光学 | 更新时间：2020-08-13

- 基于近红外波长组合快速检测油页岩含油率
- Rapid detection of oil yield of oil shale by combination of wavelengths in near infrared spectroscopy
- 光学精密工程 2015年23卷第2期页码：371-377
- 作者机构：
  
  吉林大学仪器科学与电气工程学院,吉林长春,130026
- 作者简介：
- 基金信息：
  
  吉林省科技发展计划资助项目(No.20116014)();国家潜在油气资源(油页岩勘探开发利用)产学研用合作创新项目(No.OSR-02-04)()
- DOI：10.3788/OPE.20152302.0371
  中图分类号： TE122;O657.33
- 收稿日期：2014-06-19，
  
  修回日期：2014-08-15，
  
  纸质出版日期：2015-02-25
- 稿件说明：
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王智宏, 张福东, 滕飞等. 基于近红外波长组合快速检测油页岩含油率[J]. 光学精密工程, 2015,23(2): 371-377

WANG Zhi-hong, ZHANG Fu-dong, TENG Fei etc. Rapid detection of oil yield of oil shale by combination of wavelengths in near infrared spectroscopy[J]. Editorial Office of Optics and Precision Engineering, 2015,23(2): 371-377
王智宏, 张福东, 滕飞等. 基于近红外波长组合快速检测油页岩含油率[J]. 光学精密工程, 2015,23(2): 371-377 DOI： 10.3788/OPE.20152302.0371.

WANG Zhi-hong, ZHANG Fu-dong, TENG Fei etc. Rapid detection of oil yield of oil shale by combination of wavelengths in near infrared spectroscopy[J]. Editorial Office of Optics and Precision Engineering, 2015,23(2): 371-377 DOI： 10.3788/OPE.20152302.0371.

摘要

为实现油页岩含油率的快速单点测量

研究了基于近红外波长组合的油页岩含油率快速检测方法。以高岭土与机油混合的模拟样品为研究对象

利用便携式近红外光谱分析技术

研究了近红外波长组合选择方法。该方法采用自制的便携式光谱仪获得全光谱反射率数据

结合微分和多元散射校正数据处理及相关系数法进行波长初步筛选

将组合生成算法与留一交互校验多元线性回归(MLR)建模相结合

确定最佳波长组合

并用MLR建模对单点测量获得的最佳波长组合光谱数据进行了实验验证。结果表明:最佳波长组合为1 644

1 720

2 210

2 260 nm

30个建模样品的校正集和预测集的决定系数为0.995 4和0.997 7

11个验证样品的验证集的决定系数为0.990 1。该方法为研制基于单点测量的油页岩含油率快速检测光谱仪提供了基础。

Abstract

To detect rapidly the oil yield of an oil shale on a single point measurement

a detection method was proposed based on combination of wavelengths by a portable near infrared spectroscopy. By taking the kaolin mixed with oil simulating samples as the research object

how to select the combination of wavelengths by near infrared spectroscopy was performed. With proposed method

the full spectral reflectivity data were firstly acquired by the developed portable spectrometer. Then the preliminary selection for the combination of wavelengths was implemented by differential multiplicative scatter correction method and correlation coefficient method

and the optimum combination of wavelengths was determined by combination generation method and leave one cross validation Multiple Linear Regression (MLR). Finally

the data for the optimum combination of wavelengths were verified by MLR modeling. The results show that the optimum combination of wavelengths is 1 644

1 720

2 210 and 2 260 nm

and the determination coefficients for calibration set (

)

prediction set (

) of 30 modeling samples and validation (

) of 11 validation samples are 0.995 4

0.997 7 and 0.990 1

respectively. The method provides a basis for design of a rapid detecting spectrometer in oil yields of oil shapes.

关键词

Keywords

references

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