Combining near infrared spectroscopy with predictive model and expertise to monitor herb extraction processes

Suo, Tongchuan; Wang, Haixia; Shi, Xianqing; Feng, Linlin; Cai, Jiayou; Duan, Yu; Bao, Huimin; Wu, Xiaolin; Zhang, Yue; Yu, Heshui; Li, Zheng

doi:10.1016/j.jpba.2017.10.004

Cited by 12 publications

(3 citation statements)

References 15 publications

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“…With new analytical techniques, near-infrared (NIR) spectroscopy has been widely developed in many fields due to its unique features of noninvasiveness, less pollution, and being suitable for online analysis [17][18][19][20]. Essentially, a vibrational spectroscopy technique allows the probing of overtones and combination bands of the fundamental frequencies, mainly hydrogen bonds, such as -OH, -NH, and -CH [21].…”

Section: Introductionmentioning

confidence: 99%

Fault Isolation for Desalting Processes Using Near-Infrared Measurements

Wang

Gao

et al. 2021

Mathematical Problems in Engineering

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Due to the important role of crude oil desalting for the whole petroleum refining process, the near-infrared spectroscopy resulting from molecular vibration is used to detect and isolate potential faults of the desalting process in this paper. With the molecular spectral data reflected by the near-infrared spectroscopy, the principal component analysis is adopted to monitor the process to see if it is in a normal operating condition or not. Considering the feature that the dimension of near-infrared spectroscopy is much larger than the sample size, the least absolute shrinkage and selection operator is employed to achieve an automatic variable selection procedure of the observed spectral data. Simultaneously, if some faults occur, the least absolute shrinkage and selection operator can be used to locate the spectral region affected by the failure. In such a way, the roots of faults can be tracked according to the change of the wavelength numbers. Performances of the proposed fault detection and isolation approaches are evaluated based on the near-infrared spectroscopy sampled for the crude oil desalting process to show the effectiveness.

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Section: Introductionmentioning

confidence: 99%

Fault Isolation for Desalting Processes Using Near-Infrared Measurements

Wang

Gao

et al. 2021

Mathematical Problems in Engineering

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Section: Introductionmentioning

confidence: 99%

“…Due to its noninvasiveness, little or no sample preparation, and rapid measurements, NIR has been widely used in many fields for process monitoring. 18,19 For instance, in the food industry, Santos et al 20 used NIR as a real-time and in situ analytical tool to predict two of the most relevant coffee parameters during the roasting process and proved the suitability; in the pharmaceutical industry, Liu et al 21 investigated the application of NIR to monitor and control fluidized bed granulation and coating processes; in the chemical industry, Sales et al 22 monitored the transesterification reactions for biodiesel based on NIR. However, to the authors' best knowledge, few studies applied NIR for the FD of the oil desalting process.…”

Section: Introductionmentioning

confidence: 99%

Fault Detection Based on Near-Infrared Spectra for the Oil Desalting Process

2018

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The fault detection problem of the oil desalting process is investigated in this paper. Different from the traditional fault detection approaches based on measurable process variables, near-infrared (NIR) spectroscopy is applied to acquire the process fault information from the molecular vibrational signal. With the molecular spectra data, principal component analysis was explored to calculate the Hotelling T and squared prediction error, which act as fault indicators. Compared with the traditional fault detection approach based on measurable process variables, NIR spectra-based fault detection illustrates more sensitivity to early failure because of the fact that the changes in the molecular level can be identified earlier than the physical appearances on the process. The application results show that the detection time of the proposed method is earlier than the traditional method by about 200 min.

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