Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/54438
Title: Pattern classification of odour for electronic nose
Authors: Tong, Wee Chin.
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Electronic circuits
Issue Date: 2013
Abstract: This project is based on the architecture of Electronic Nose. The Electronic Nose comprises of Figaro sensors, data acquisition and pattern classification. The main part revolves around the development of the pattern classification, as this is the main objective for this project. The understanding of data acquisition is important as it is required to carry out tests on the odour. Different classification network has been considered and eventually comes to Probabilistic Neural Network (PNN). The data acquisition is makeup of different equipment and software. This includes the hardware from National Instrument such as SCB-68 and PCI-6071E. Together with the software LabVIEW as well as a excel sheet for data record and the training data excel sheet forms the entire data acquisition. With the understanding of data acquisition, several experiments have been carried out to familiarise the process and obtain the training data. With a strong training data and the understanding of PNN, a program is developed to perform the classification function. This program is compiled based on the programming language, VB.Net. Further improvement has been made to the program to provide integration. The program has become multi-interface software. The importing of training data, which is part of the data acquisition has been added in. Together with other editing features, forms the admin interface. The pattern classification will become the user interface. The whole program is named Electronic Nose.
URI: http://hdl.handle.net/10356/54438
Schools: School of Electrical and Electronic Engineering 
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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