可视化仿生鼻对五小香型白酒的识别

建立了一种有潜力的人工仿生鼻方法，用于分析典型的中国五小香型白酒。为减少误差、去除冗余数据，采用阈值限定结合平方和均值方根的方法对原始RGB数据进行预处理；在可视化区分的基础上采用分层聚类分析（HCA）、主成分分析（PCA）以及支持向量机（SVM）的分析方法，对预处理后的数据进行分析。聚类分析方法依据香型衍生的不同可以实现正确的归类；利用主成分分析得到的前3个主成分包含了白酒80.79%信息量，可以将不同香型白酒正确区分；支持向量机的可视化仿生鼻能对白酒香型进行有效区分，其识别的准确率达到了100%。研究结果表明，基于可视化传感技术的可视化仿生鼻可以用于五小香型白酒的识别。

Identification of different aromatic Chinese liquors by colorimetric artificial nose

A potential instrument, the colorimetric nose, is developed to identify the fragrances of five different Chinese liquors. Firstly, in order to minimize error, the RGB values of the raw data are preprocessed using a threshold before further analysis. The output of the artificial nose is then analyzed by hierarchical routing cluster analysis (HCA), principal component analysis (PCA) and support vector machine (SVM). It is found that HCA can perform correctly classify fragrances into five different classes. However, using the first three components identified by PCA analysis, representing 80.79% of the variance, the five individual fragrances can be reliably distinguished. Finally, it also shows that the five constituent fragrant liquors can also be reliably classified with 100% accuracy by SVM. These results show that the colorimetric artificial nose, a simple and efficient detection and identification tool, has great potential to identify different constituent fragrant liquors reliably well.