Silk is a natural animal protein with special odour. Polyester yarns, similar in appearance to silk, are oftenused in silk production. Electronic nose (e-nose) technology can distinguish different gases by different patternrecognition methods. In this paper, e-nose technology was applied to obtain data sets of silk/polyester yarnswith different mixing ratios, and cluster analysis was carried out for silk samples. The experimental resultsshow that the results of e-nose response are related to the headspace, sample quality, and headspacegeneration time etc.; as the response time increases, the relative standard deviation of each sensor turns tobe smaller, and the response value is more stable. There are significant differences in the fluctuationsbetween the ten metal sensors, and different samples have significant effects on the response of sensors No.2, 7, and. 9. The e-nose sensor has a higher prediction accuracy when identifying different ratios ofsilk/polyester yarns at the accuracy rate up to 90.286%.
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