Fuzzy Evaluation Output of Taste Information for Liquor Using Electronic Tongue Based on Cloud Model

Sensors - Tập 20 Số 3 - Trang 686
Jingjing Liu1,2,3, Mingxu Zuo2, Sze Shin Low1, Ning Xu2, Zhiqing Chen2, Chuang Lv2, Ying Cui2, Yan Shi2, Hong Men2
1Biosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China
2College of Automation Engineering, Northeast Electric Power University, Jilin 132012, China
3Department of Computer Science and Bioimaging Research Center, University of Georgia, Athens, GA 30602, USA

Tóm tắt

As a taste bionic system, electronic tongues can be used to derive taste information for different types of food. On this basis, we have carried forward the work by making it, in addition to the ability of accurately distinguish samples, be more expressive by speaking evaluative language like human beings. Thus, this paper demonstrates the correlation between the qualitative digital output of the taste bionic system and the fuzzy evaluation language that conform to the human perception mode. First, through principal component analysis (PCA), backward cloud generator and forward cloud generator, two-dimensional cloud droplet groups of different flavor information were established by using liquor taste data collected by electronic tongue. Second, the frequency and order of the evaluation words for different flavor of liquor were obtained by counting and analyzing the data appeared in the artificial sensory evaluation experiment. According to the frequency and order of words, the cloud droplet range corresponding to each word was calculated in the cloud drop group. Finally, the fuzzy evaluations that originated from the eight groups of liquor data with different flavor were compared with the artificial sense, and the results indicated that the model developed in this work is capable of outputting fuzzy evaluation that is consistent with human perception rather than digital output. To sum up, this method enabled the electronic tongue system to generate an output, which conforms to human’s descriptive language, making food detection technology a step closer to human perception.

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