基于离子选择电极和单片机技术的电子舌设计与试验

设计了一套基于离子选择电极和单片机技术的电子舌系统,并基于机器学习方法对饮用矿泉水及苹果汁进行了检测.使用离子选择电极组成传感器阵列,并通过单片机系统和串行A/D模块实现了高可靠性、低硬件成本的数据采集；在Matlab环境下实现了对实验数据的主成分分析、BP和PNN神经网络以及SVM分析,探讨了神经网络的优化设计方式.实验结果表明,该电子舌系统能够准确识别饮用水类别,并具有良好的可扩展性及成本低廉等优点.

Electronic Tongue Based on Ion-selective Electrode and MCU

Research was conducted to design an electronic tongue based on MCU and ion-selective electrodes, software based on machine learning technology. Ion-selective electrodes were used to compose a sensors-array. MCU and A/D chip were used to compose data acquisition system. In Matlab environment, principal component analysis (PCA), back propagation neural network (BPNN), probability neural network (PNN) and support vector machine (SVM) were used to achieve pattern recognition of four kinds of drinking water and five kinds of ciders. The results showed that this electronic tongue system displayed great application potential in drinking waters and ciders analysis and also had good expansibility.