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Rapid Online Determination of Feed Concentration in Nitroguanidine Spray Drying Process by Near Infrared Spectroscopy
Infrared Physics & Technology ( IF 3.1 ) Pub Date : 2020-09-01 , DOI: 10.1016/j.infrared.2020.103432
Gaofeng Zhang , Yunyun Wang , Weibin Wang , Guodong Deng

Abstract This work investigated the feasibility of using near-infrared (NIR) spectroscopy to rapidly online detect the feed concentration of nitroguanidine (NQ) in order to ensure the uniformity and stability of the NQ feed during the spray drying process. A Fourier transform NIR spectrometer with a detector installed on the NQ slurry pipeline was used to collect original spectra of NQ samples with different concentrations. Standard normal variate was used to preprocess the original spectra, and a quantitative model with 7 factors of feed concentration was established by partial least squares regression in the spectral wavenumber ranges of 6890–6444 cm−1 and 5126–4236 cm−1. The determination coefficients of calibration and prediction ( R c 2 , R p 2 ) were 0.9945 and 0.9880, the root mean square errors of calibration and prediction (RMSEC, RMSEP) were 0.111 and 0.157, and the residual predictive deviation (RPD) values of calibration and prediction were 13.5 and 9.18, respectively. The established model was applied to detect the feed concentration of 8 other samples, and the difference between the near-infrared prediction values and the traditional measured values was only 0.29%. The results indicate the excellent predictive performance and repeatability of the model and provide new insights into the NIR spectroscopy rapid online detection of the feed concentration of NQ during spray drying process.

中文翻译:

近红外光谱法快速在线测定硝基胍喷雾干燥过程中的饲料浓度

摘要 本工作研究了利用近红外(NIR)光谱快速在线检测硝基胍(NQ)进料浓度的可行性,以确保NQ进料在喷雾干燥过程中的均匀性和稳定性。傅里叶变换近红外光谱仪在 NQ 浆液管道上安装了一个检测器,用于收集不同浓度 NQ 样品的原始光谱。采用标准正态变量对原始光谱进行预处理,在6890-6444 cm-1和5126-4236 cm-1光谱波数范围内通过偏最小二乘回归建立了7个进料浓度因子的定量模型。校准和预测的决定系数(R c 2 ,R p 2 )分别为0.9945和0.9880,校准和预测的均方根误差(RMSEC,RMSEP) 分别为 0.111 和 0.157,校准和预测的残余预测偏差 (RPD) 值分别为 13.5 和 9.18。将建立的模型应用于其他8个样品的进料浓度检测,近红外预测值与传统测量值的差异仅为0.29%。结果表明该模型具有出色的预测性能和可重复性,并为 NIR 光谱快速在线检测喷雾干燥过程中 NQ 进料浓度提供了新的见解。近红外预测值与传统实测值的差异仅为0.29%。结果表明该模型具有出色的预测性能和可重复性,并为 NIR 光谱快速在线检测喷雾干燥过程中 NQ 进料浓度提供了新的见解。近红外预测值与传统实测值的差异仅为0.29%。结果表明该模型具有出色的预测性能和可重复性,并为 NIR 光谱快速在线检测喷雾干燥过程中 NQ 进料浓度提供了新的见解。
更新日期:2020-09-01
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