Abstract

This Paper presents the identification of mixed vapour using electronic nose system composed of Quartz Crystal Microbalance (QCM) sensor array and a partition column of gas chromatography. The polymer coated QCMs produced a specific frequency shift. The data set was processed by an Artificial Neural Network using Backpropagation algorithm as a pattern recognition. The result showed that this equipment was able to identify five types of vapours namely benzene, acetone, isopropyl alcohol, non-polar and polar mixture (i.e. benzene and acetone), and also polar and polar mixture (i.e. isopropyl alcohol and acetone) with the identification rate of 96%.

Original languageEnglish
Title of host publicationProceedings of 2016 International Conference on Information and Communication Technology and Systems, ICTS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages172-177
Number of pages6
ISBN (Electronic)9781509013791
DOIs
Publication statusPublished - 24 Apr 2017
Event2016 International Conference on Information and Communication Technology and Systems, ICTS 2016 - Surabaya, Indonesia
Duration: 12 Oct 2016 → …

Publication series

NameProceedings of 2016 International Conference on Information and Communication Technology and Systems, ICTS 2016

Conference

Conference2016 International Conference on Information and Communication Technology and Systems, ICTS 2016
Country/TerritoryIndonesia
CitySurabaya
Period12/10/16 → …

Keywords

  • Artificial Neural Network
  • Chromatography Column
  • Electronic Nose
  • Mixed Vapour
  • QCM Sensor

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