Design of Non-contact Measurement of Alcohol Concentration Based on the Lambert-beer Law
DOI:
https://doi.org/10.54097/qtfsxr74Keywords:
Alcohol Concentration, Non-contact, Spectral Analysis, Lambert-beer LawAbstract
This paper is based on the lambert-beer law, measuring the transmission rate of infrared light through alcohol to determine its concentration in a non-contact manner. Compared to traditional measurement methods, non-contact measurement minimizes the risk of alcohol contamination, while being simple and efficient. The design section includes mechanical structure, sensor filtering and sampling circuits, main control systems, and human-computer interaction programs. A high-order fitting algorithm was employed to establish a mathematical model relating alcohol concentration to voltage values, followed by data processing of the measured voltage values for different alcohol concentrations. Using this model, the corresponding alcohol concentrations were obtained. The relative error between measured values and calibrated values was found to be within 2.12%, demonstrating the accuracy of the experimental apparatus. Additionally, to address the impact of temperature variations on voltage values, a water calibration method was implemented to further reduce experimental errors. This achieved high-precision measurement of alcohol concentration and validated the rationality of the experimental system design.
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[1] Wang Zhenzuo, Lv Jiahui, Guo Weiliang, etc. Determination of ethanol content in distilled spirits using short-wave near infrared spectroscopy with partial least square regression model [J]. Science and Technology of Food Industry, 2005, (11): 158-160.
[2] Bu Guijun, He Xiaosong, Zheng Xiaojiang, et al. Study on the Characteristics of Three-Dimensional Fluorescence Excitation-Emission Spectra of Methanol and Ethanol [J]. Spectroscopy and Spectral Analysis, 2012, 32 (02): 420-424.
[3] WANG Hongbin; WANG Weihua; FANG Ye. Design of Non-Contact Measurement System for Alcohol Concentration [J]. Journal of Lanzhou Institute of Technology, 2024,31(06):81-85.
[4] Zhong Zhiqiang. The research of university physics experiment data processing method based on Python language [J]. Journal of Anshan Normal University,2016,18(02):77-81.
[5] YAN Feng YANG Jun-Jie SHI Jiu-Lin. Detection of edible alcohol and industrial alcohol by spectral technique [J]. Journal of Food Safety and Quality,2016,7(07):2828-2834. DOI:10. 19812/j.cnki.jfsq11-5956/ts.2016.07.043.
[6] Zhouweiwei. Non-destructive Test Alcohol content of Driver Earlobe Based on Near infrared Spectrum [D]. Shandong university, 2014.
[7] ZHOU Ying; LI Dong-yun. Advantages and Application Development of Near Infrared Spectroscopy in Screening of Illegal Chemical Additives in Health Food and Chinese Patent Medicine [J]. GuangZhou Chemical Industry, 2023,51(05): 135-138.
[8] Xia Y, Zou S ,Xie P , et al.A kind of multi-dot ensemble regression AI detector for lubricating oil additive content based on lambert-beer law[J].Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy,2024,318124436-.
[9] ZHOU yang, LIU jie, Wang jiyuan. Absorption mechanism and application of infrared spectra of ethanol [J]. China Brewing, 2013, 32(12):128-130.
[10] Luo Zhangcheng, Zuo Shizhu, Huang Qiang, et al. Three-port voltage stabilizing circuit with high reliable start and low voltage difference [J/OL]. Microelectronics,1-9[2025-03-28]. https:// doi.org/10.13911/j.cnki.1004-3365.240030.
[11] Zheng Lixia, Wu Jin, Zhang Xiuchuan, etc.Sensing detection and quenching method for InGaAs single-photon detector [J]. Acta Physica Sinica, 2014,63(10):222-230.
[12] Zhouweiwei. Non-destructive Test Alcohol Content of Driver Earlobe Based on Near-infrared Spectrum[D]. Shandong University, 2014.
[13] Zhu Hengjun, Wang Fazhi, Yao Zhongmin. Analysis and Implementation of digital filter algorithm based on MCU [J]. Journal of Qiqihar University(Natural Science Edition),2008, (06):53-54+57.
[14] Wang Zhenzuo, Lv Jiahui, Guo Weiliang, etc.. Determination of ethanol content in distilled spirits using short-wave near infrared spectroscopy with partial least square regression model [J]. Science and Technology of Food Industry, 2005, (11):158-160.
[15] A high-bandwidth low current transimpedance amplification circuit[J]. Liu Hao;Dong Chunhui;Yang XinYing;Cheng Feng; Zhang Qingxian;Liao Kaiyong;Lu Zhigang;Gao Zhiyu;Luo Tingfang; Huang Qichang;Li Weilan.Journal of Instrumentation, 2021.
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