电子鼻在饮料识别中的应用研究

Electronic Nose and Its Application in Beverage Recognition

为解决传统的饮料检测所采用的理化分析方法烦琐而实时性差的问题 ,研制了一套能够实时、准确地检测饮料散发气味的电子鼻系统。该系统主要由气敏传感器阵列和数据处理软件组成 ,并采用氮气作为载气以减少测试环境因素的影响。为了提高信噪比 ,从每个传感器与气体反应曲线中提取了 4个特征值 ,然后用主成分分析法和BP神经网络对样本特征值进行处理。识别结果表明 ,这种检测方法快速、准确 ,识别正确率高达 95 .2 %。

The traditional chemical physical analyzing method for beverage inspection is troublesome and inefficient. Recently, a novel electronic nose system was developed, which can inspect the odorant from beverage quickly and accurately. This system is mainly composed of a gas sensor array and a data processing apparatus. In order to minimize the effect of inspecting environment, nitrogen was used as carrier gas, which could carry the odorant from the sample vessel into the sensor chamber. Four feature parameters were picked up from each sensor reacting curve to improve the rate of Signal to Noise. Moreover, the principal component analysis (PCA) and the back propagation(BP) neural network were used to identify beverage samples. The results demonstrate that this inspecting method is efficient and the recognition rate is up to 95.2%.