Study on steam detection method of Chinese spirits steamer-filling operation based on support vector machine

Authors

TIAN Wan-chun, Artificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science & Engineering,Yibin, Sichuan 644000 , China ；School of Automation & Information Engineering, Sichuan University ofScience & Engineering, Yibin, Sichuan 644000 , China
ZHANG Gui-yu, Artificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science & Engineering,Yibin, Sichuan 644000 , China ；School of Automation & Information Engineering, Sichuan University ofScience & Engineering, Yibin, Sichuan 644000 , China ；School of Information Engineering, SouthwestUniversity of Science and Technology, Mianyang, Sichuan 621010 , China
TUO Xian-guo, Artificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science & Engineering,Yibin, Sichuan 644000 , China ；School of Automation & Information Engineering, Sichuan University ofScience & Engineering, Yibin, Sichuan 644000 , China
WU Hao-han, Artificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science & Engineering,Yibin, Sichuan 644000 , China ；School of Automation & Information Engineering, Sichuan University ofScience & Engineering, Yibin, Sichuan 644000 , China
SHI Xiao-shi, Artificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science & Engineering,Yibin, Sichuan 644000 , China ；School of Automation & Information Engineering, Sichuan University ofScience & Engineering, Yibin, Sichuan 644000 , China

Abstract

Aiming at the problem of low accuracy of steam detection in the process of automation of "steam detection and steaming" of Chinese spirits. This paper proposes a steam detection method based on support vector machine (SVM) to improve the accuracy of automatic steam detection. First, the infrared thermal imager is used to collect the infrared grayscale image of the surface of the wine cellar in the barrel and perform histogram processing, then extract histogram’s multiple features. Combined with the engineering experience to add tags to form the training set, and through the support vector machine training to obtain the exploration model in the process of the captain. Through testing, the method has a high detection accuracy of 96%, which can meet the requirements of Chinese spirits production process.

Publication Date

1-28-2020

First Page

79

Last Page

83,103

DOI

10.13652/j.issn.1003-5788.2020.01.012

Recommended Citation

Wan-chun, TIAN; Gui-yu, ZHANG; Xian-guo, TUO; Hao-han, WU; and Xiao-shi, SHI (2020) "Study on steam detection method of Chinese spirits steamer-filling operation based on support vector machine," Food and Machinery: Vol. 36: Iss. 1, Article 12.
DOI: 10.13652/j.issn.1003-5788.2020.01.012
Available at: https://www.ifoodmm.cn/journal/vol36/iss1/12

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