Rapid Detection of Sesame Oil Flavoring Based on the Gas Sensor Array

Author

Ma Lihui ; Gao Yongyang ; Sun Hui ; Qi Mingjun ; Zhang Ting ; Hou Xiaohua

Author_Institution

Coll. of Quality & Tech. Supervision, Hebei Univ., Baoding, China

fYear

2013

fDate

16-17 Jan. 2013

Firstpage

841

Lastpage

844

Abstract

For the rapid detection of sesame oil flavoring, a real-time and accurate detection of sesame oil flavoring system is developed. The system mainly consists of the data acquisition part and data processing components. The data acquisition parts include gas sensor and the host computer. Data processing part include a three-layer BP neural network which is trained in MATLAB. During the experiment, the preparations of sesame oil flavoring samples have eight different proportions, and the standard samples are for the neural network training and test samples are verified. The system provides a basis method for the rapid detection of sesame oil flavoring.

Keywords

backpropagation; data acquisition; food additives; food safety; gas sensors; learning (artificial intelligence); mathematics computing; production engineering computing; vegetable oils; Matlab; data acquisition; data processing part; gas sensor array; sesame oil flavoring rapid detection; three-layer BP neural network training; Automation; Mechatronics; Artificial Neural Network (BP-ANN); Electronic Nose; Sesame Oil Flavoring;

fLanguage

English

Publisher

ieee

Conference_Titel

Measuring Technology and Mechatronics Automation (ICMTMA), 2013 Fifth International Conference on

Conference_Location

Hong Kong

Print_ISBN

978-1-4673-5652-7

Type

conf

DOI

10.1109/ICMTMA.2013.211

Filename

6493862