Adulteration detection of mild aromatic Chinese spirits on electronic tongue combined with VMD-IMG composite model
In view of the problems of long analysis process and complex instrument operation with the traditional liquor adulteration detection methods,a method based on the electronic tongue combined with Variational mode decomposition(VMD)and Improved Multichannel Ghostnet(IMG)was proposed to realize the rapid detection of liquor adulteration.The Bayesian optimized VMD was used to perform adaptive mode decomposition of the signal,and the original signal was decomposed into multiple intrinsic mode functions(IMFs).Based on the traditional GhostNet network,the bottleneck attention module and dilated convolution were introduced and extended to multi-channel GhostNet,which was then constructed as a combined VMD-IMG model to realize the effective extraction of electronic tongue signal features and classification recognition.The experimental results show that the VMD-IMG combined model proposed has a better performance in liquor adulteration discrimination,and its tested accuracy,precision,and F1-Score are 98.33%,98.43%,and 98.34%,respectively.This study provides a fast and low-cost detection method for liquor adulteration detection,and can provide a new technical means for other liquor or beverage adulteration detection.
国家科技期刊平台
NSTL
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