Calibration Model Building for Online Monitoring of the Granule Moisture Content during Fluidized Bed Drying by NIR Spectroscopy

被引:21
作者
Mu, Guoqing [1 ]
Liu, Tao [1 ]
Liu, Jingxiang [1 ]
Xia, Liangzhi [2 ]
Yu, Caiyuan [3 ]
机构
[1] Dalian Univ Technol, Inst Adv Control Technol, Dalian 116024, Peoples R China
[2] Dalian Univ Technol, Sch Chem Machinery & Safety Engn, Dalian 116024, Peoples R China
[3] Dalian Univ Technol, Sch Chem Engn, Dalian 116024, Peoples R China
关键词
NEAR-INFRARED SPECTROSCOPY; IN-LINE; PARTICLES;
D O I
10.1021/acs.iecr.8b05043
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
For monitoring the granule moisture content during a fluidized bed drying (FBD) process, a calibration model building method is proposed for in situ measurement using the near-infrared (NIR) spectroscopy. It is found that the FBD operating conditions such as the chamber temperature and heating power have a nonnegligible impact on the NIR model prediction of granule moisture. By combining these operating variables with the measured NIR spectra for model calibration, the prediction accuracy for online measurement of the granule moisture content under different process conditions could be evidently improved compared to only using the measured NIR spectra for model calibration. To determine the optimal number of factors for establishing a partial-least-squares (PLS) regression model for predicting the granule moisture content, it is proposed to combine the leave-one-out cross validation (LOOCV) approach with the median absolute percentage error (MdAPE) index to deal with measurement outliers often involved with practical applications, based on a comparative study with the well-known K-fold cross validation (KCV) and Monte Carlo cross validation (MCCV) methods. Experimental results on monitoring the silica gel granule moisture under different FBD operating conditions demonstrate the effectiveness of the proposed spectral calibration method.
引用
收藏
页码:6476 / 6485
页数:10
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