Non-Contact Measurement of Alcohol Content Based on Near Infrared Spectroscopy

Siying He; An Sun

doi:10.62051/ijcsit.v2n1.21

Authors

Siying He
An Sun

DOI:

https://doi.org/10.62051/ijcsit.v2n1.21

Keywords:

Near Infrared Spectrum; Alcoholic Strength; BP Neural Network; Intelligent Detection

Abstract

In order to solve the influence of other external factors on the measurement concentration of alcohol solution, a non-contact measurement method based on near-infrared spectroscopy and BP neural network temperature correction method was proposed in this paper. This method takes into account the influence of temperature on the light intensity of alcohol liquid solution in the detection process, and trains it together with the measurement data as the input of neural network. At the same time, it is compared with the index fitting algorithm, which proves that the method has a good effect on the non-contact measurement of alcohol content.

Downloads

Download data is not yet available.

References

HE C, LI Z G, REN Z M, et al. Research on the application of rapid and high precision determination method for liquor alcohol content[J]. Brewing Technology, 2019(07):40-42.

FU Y F, LIU D N, ZHOU Y L, et al. Uncertainty evaluation of alcohol content in glutinous rice wine by density bottle method[J]. Journal of Food Safety and Quality Inspection, 2019, 10(14):4726-4729.

WANG Zhifang, WANG Shutao, WANG Guichuan. Application of particle swarm optimization BP neural network in methane detection[J]. Acta Photonica Sinica, 2019, 48(4): 147-154.

Philip Antwi, LI Jianzheng, Portia Opoku Boadi, et al. Estimation of biogas and methane yields in an UASB treating potato starch processing waste water with backpropagation artificial neural network[J]. Bioresource Technology, 2017, 228: 106-115.

TONG Minming, ZHANG Yu, QI Meixing. Study on analysis method of combustible gas mixture based on BP neural network[J]. Acta Metrologica Sinica, 2006, 27(2): 169-171.

Hu Xiaobang, LV Jin, Liu Huijun, et al. Study on Alcohol and acidity detection Model of rice wine based on near infrared projection spectrum [J]. Optoelectronic Engineering, 2010,37 (10) : 122-127.

YU Songbai, ZHAO Xiaobo, Tian Min, ZOU Shengqiong, Liu Mengjie, Zhou Jun, ZHANG Suyi. Application of near infrared spectroscopy in rapid detection of fermented grains of liquor [J]. Brewing Technology,2021(02):59-64.

RAO Fangqiu, HE Cuirong, Lu Bin, LI Wanqun, LAN Xiaoqin, YUAN Songlin, GENG Dongxian. Application of portable near-infrared spectrometer in the analysis and detection of fermented grains [J]. Brewing Technology,2022(04):71-77.

Tian Yuhong, Wang Fengxian, Wu Qing. Rapid detection of key indexes in liquor based on near-infrared spectroscopy [J]. Wine Making,2019,46(05):93-96.

ZHOU Xinqi, Zheng Qiwei, Liu Yan, Ma Shuai, Guo Zhongyuan, Li Guang, Zhang Xiaodan. Online monitoring of distiller grains based on near-infrared spectroscopy [J]. Journal of Analytical and Testing, 2019,39(11):1358-1364.