首页 > 论文 > 中国激光 > 47卷 > 1期(pp:111001--1)

温度对水泥生料近红外光谱检测的影响及补偿方法

Effect of Temperature on Near-Infrared Spectrum Detection of Cement Raw Meal and Compensation Method

  • 摘要
  • 论文信息
  • 参考文献
  • 被引情况
  • PDF全文
分享:

摘要

通过建立校正集样本不同的模型Ⅰ与模型Ⅱ来研究温度对水泥生料近红外光谱模型的影响,其中模型Ⅰ中的建模样本为温度一致的样本,模型Ⅱ中的建模样本为温度变化的样本,建模方法采用偏最小二乘法。对比两组模型的预测结果可知,模型Ⅱ中SiO2、Al2O3、Fe2O3、CaCO3的预测方均根误差与模型Ⅰ相比分别减小了78.3%、26.4%、42.9%、60.4%。实验结果表明:温度变化会导致预测结果产生一定的误差。在校正集中加入温度不同的样本进行建模,可以降低预测误差,使近红外光谱模型更好地应用于生产现场。

Abstract

In this paper, the effect of temperature on the near-infrared spectroscopy model of cement raw meal was investigated by developing two models (model I and model II) with different calibration sets. Model I and model II were developed by applying the partial least squares method using same-temperature and different-temperature samples, respectively. In comparison with model I, the root mean square error of prediction (RMSEP) of SiO2, AlO3, Fe2O3, and CaCO3 in model II was reduced by 78.3%, 26.4%, 42.9%, and 60.4%, respectively. Experimental results show that the temperature of the cement raw meal sample has a certain influence on the prediction results of the near-infrared spectroscopy model. The influence of temperature on the prediction results can be effectively reduced by modeling with temperature gradient samples in the calibration set, and thus the infrared spectroscopy model can better be applied to production site.

Newport宣传-MKS新实验室计划
补充资料

中图分类号:O657.33

DOI:10.3788/CJL202047.0111001

所属栏目:光谱学

基金项目:山东省重点研发计划;

收稿日期:2019-08-08

修改稿日期:2019-09-16

网络出版日期:2020-01-01

作者单位    点击查看

肖航:山东大学控制科学与工程学院, 山东 济南 250061
杨振发:山东大学控制科学与工程学院, 山东 济南 250061
张雷:山东大学控制科学与工程学院, 山东 济南 250061
张法业:山东大学控制科学与工程学院, 山东 济南 250061
隋青美:山东大学控制科学与工程学院, 山东 济南 250061
贾磊:山东大学控制科学与工程学院, 山东 济南 250061
姜明顺:山东大学控制科学与工程学院, 山东 济南 250061

联系人作者:张雷(drleizhang@sdu.edu.cn)

备注:山东省重点研发计划;

【1】Ali M B, Saidur R, Hossain M S. A review on emission analysis in cement industries [J]. Renewable and Sustainable Energy Reviews. 2011, 15(5): 2252-2261.

【2】Yu H L, Wan X, Lian G D, et al. Intelligent control system for cement raw meal quality based on online analysis . [C]∥2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER), June 8-12, 2015, Shenyang, China. New York: IEEE. 2015, 1704-1707.

【3】Tyopine A A, Wangum A J, Idoko E A. Impact of different grinding aids on standard deviation in X-ray fluorescence analysis of cement raw meal [J]. American Journal of Analytical Chemistry. 2015, 6(5): 492-494.

【4】Wang L J, Yang Y Y. Purification and noise elimination of near infrared spectrum in rapid detection of milk components concentration by using principal component weight resetting [J]. Acta Optica Sinica. 2017, 37(10): 1030003.
王丽杰, 杨羽翼. 利用主成分权重重置实现牛奶成分浓度快速检测中近红外光谱的净化去噪 [J]. 光学学报. 2017, 37(10): 1030003.

【5】Zhang H, Liu G H, Jiang H, et al. Quantitative detection of ethanol solid-state fermentation process parameters based on near infrared spectroscopy [J]. Laser & Optoelectronics Progress. 2017, 54(2): 023002.
张航, 刘国海, 江辉, 等. 基于近红外光谱技术的乙醇固态发酵过程参数定量检测 [J]. 激光与光电子学进展. 2017, 54(2): 023002.

【6】Machado J C. Jr, Faria M A, Ferreira I M P L V O, et al. Varietal discrimination of hop pellets by near and mid infrared spectroscopy [J]. Talanta. 2018, 180: 69-75.

【7】Schlegel L B, Schubert-Zsilavecz M, Abdel-Tawab M. Quantification of active ingredients in semi-solid pharmaceutical formulations by near infrared spectroscopy [J]. Journal of Pharmaceutical and Biomedical Analysis. 2017, 142: 178-189.

【8】Rebou?as J P. Rohwedder J J R, Pasquini C. Near infrared emission spectroscopy for rapid compositional analysis of Portland cements [J]. Analytica Chimica Acta. 2018, 1024: 136-144.

【9】Xiao H, Yang Z F, Zhang L, spectroscopy[J/OL]. Analytical Letters, et al. 2019-08-07] . https:∥www_tandfonline.gg363.site/doi/full/10.1080/00032719.2019.1628248?scroll=top&needAccess=true. 2019.

【10】Yang Z F, Xiao H, Zhang L, et al. Fast determination of oxides content in cement raw meal using NIR-spectroscopy and backward interval PLS with genetic algorithm [J]. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy. 2019, 223: 117327.

【11】Wang D, Xiong Y M, Huang R, et al. Influence of temperature on near-infrared spectroscopic quantitative analysis models of compound emulsifiable concentrate [J]. Chinese Journal of Analytical Chemistry. 2010, 38(9): 1311-1315.
王冬, 熊艳梅, 黄蓉, 等. 温度对复配乳油的近红外光谱定量分析模型的影响 [J]. 分析化学. 2010, 38(9): 1311-1315.

【12】Chen T, Martin E. The impact of temperature variations on spectroscopic calibration modelling: a comparative study [J]. Journal of Chemometrics. 2007, 21(5/6): 198-207.

【13】Campos M I, Antolin G, Debán L, et al. Assessing the influence of temperature on NIRS prediction models for the determination of sodium content in dry-cured ham slices [J]. Food Chemistry. 2018, 257: 237-242.

【14】Chu X L, Yuan H F, Wang Y B, et al. Developing robust near infrared calibration models [J]. Spectroscopy and Spectral Analysis. 2004, 24(6): 666-671.
褚小立, 袁洪福, 王艳斌, 等. 近红外稳健分析校正模型的建立(Ⅰ): 样品温度的影响 [J]. 光谱学与光谱分析. 2004, 24(6): 666-671.

【15】Shi X Z, Wang Z G, Du W, et al. On-line quantitative monitoring and control of tobacco flavors by near infrared spectroscopy combined with advanced calibration transfer method [J]. Chinese Journal of Analytical Chemistry. 2014, 42(11): 1673-1678.
史新珍, 王志国, 杜文, 等. 近红外光谱结合新型模型传递方法用于糖料的在线质量监控 [J]. 分析化学. 2014, 42(11): 1673-1678.

【16】Wülfert F. Kok W T, de Noord O E, et al. Linear techniques to correct for temperature-induced spectral variation in multivariate calibration [J]. Chemometrics and Intelligent Laboratory Systems. 2000, 51(2): 189-200.

【17】Guo Z W, Sun L X, Zhang P, et al. On-line component analysis of cement powder using LIBS technology [J]. Spectroscopy and Spectral Analysis. 2019, 39(1): 278-285.
郭志卫, 孙兰香, 张鹏, 等. 基于LIBS技术的水泥粉末在线成分分析 [J]. 光谱学与光谱分析. 2019, 39(1): 278-285.

引用该论文

Xiao Hang,Yang Zhenfa,Zhang Lei,Zhang Faye,Sui Qingmei,Jia Lei,Jiang Mingshun. Effect of Temperature on Near-Infrared Spectrum Detection of Cement Raw Meal and Compensation Method[J]. Chinese Journal of Lasers, 2020, 47(1): 0111001

肖航,杨振发,张雷,张法业,隋青美,贾磊,姜明顺. 温度对水泥生料近红外光谱检测的影响及补偿方法[J]. 中国激光, 2020, 47(1): 0111001

您的浏览器不支持PDF插件,请使用最新的(Chrome/Fire Fox等)浏览器.或者您还可以点击此处下载该论文PDF