Portable Electronic Nose System for Aroma Classification of Black Tea

Santi Sankar Chowdhury, B. Tudu, R. Bandyopadhyay, N. Bhattacharyya
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引用次数: 12

Abstract

A portable electronic nose system has been developed with an array of five commercially available Metal Oxide Semiconductor (MOS) sensors, where a microcontroller (muc) is used for the pattern recognition. The classification of black tea aroma is carried out in the muc (PIC18F4520) and is based on feed forward multilayer perceptron (FF-MLP) algorithm. With the samples collected from the different gardens of north-east and eastern India, the MLP is trained first using the back-propagation algorithm with the fingerprint from the sensor array and the corresponding tea tasters' mark in a PC to obtain the optimum architecture and weights and biases of the neurons. Once it is trained, the computed weights and biases of the neurons are programmed in the muc and it then becomes a portable instrument, which gives the aroma index directly for new unknown tea samples. It is observed from the results that the performance of the muc-based electronic nose is at par with that of the PC-based electronic nose system when compared with unknown finished black tea samples.
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便携式电子鼻系统用于红茶香气分类
一种便携式电子鼻系统已开发与五个市售金属氧化物半导体(MOS)传感器阵列,其中微控制器(muc)用于模式识别。红茶香气的分类在muc (PIC18F4520)中进行,基于前馈多层感知器(FF-MLP)算法。从印度东北部和东部不同的花园收集样本,首先使用反向传播算法对MLP进行训练,并使用传感器阵列中的指纹和PC中相应的品茶者标记,以获得神经元的最佳结构,权重和偏差。一旦它被训练,神经元的计算权重和偏差就会被编程到机器中,然后它就变成了一种便携式仪器,可以直接为新的未知茶叶样品提供香气指数。从结果中可以观察到,与未知成品红茶样品相比,基于pc的电子鼻系统的性能与基于pc的电子鼻系统的性能相当。
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