Four kinds of Chinese liquors were detected by the colorimetric sensor array, which was composed of thirty chemoresponsive sensors. Principal component analysis (PCA), cluster analysis (CA) and back-propagation artificial neural network (BP-ANN) were used in the data analysis and pattern recognition. With principal component analysis, not only Chinese liquors could be identified according to alcoholicity, but also bouquet. Cluster analysis further proved the result of PCA, but some samples could not be classified by using this method. Finally, BP neural network was employed to identify the Chinese liquors, and the accuracy of recognition was 100%. This research shows the potential applications of the olfaction visualization technology for analyzing and identifying Chinese liquors.