Multivariate Discrimination Model for TNT and Gunpowder Using an Electronic Nose Prototype: A Proof of Concept
Conference paper
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Abstract
In this work a proof of concept for discriminating explosive substances is presented, where a discrimination model for the classification of TNT and gunpowder is developed. An electronic nose was designed for sensing volatile organic compounds present in TNT and gunpowder, and a model that combines Principal Component Analysis and Fisher Discriminant Analysis was built for enhancing class discrimination. The model was tested in two scenarios: discriminating among the two explosive substances and one non-explosive, and discriminating between explosives and non-explosives, obtaining better results in the second case. In order to test model confidence a permutation test was used proving an accuracy of 67% with a p-value <0.01 for the first scenario, and an accuracy of 86.6% for the second one. These results make us think that by enhancing the prototype characteristics in both hardware and software, we would be able to achieve better results.
Keywords
Electronic nose Explosive discrimination model Classification model Permutation testNotes
Acknowledgments
This work was founded by Universidad de las Fuerzas Armadas ESPE under the project 2016-pic-009.
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