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The Application of Back Propagation Neural Network of Multi-channel Piezoelectric Quartz Crystal Sensor for Mixed Organic Vapours

並列摘要


A multi-channel piezoelectric quartz crystal sensor with a homemade computer interface was prepared and employed in the present study to detect mixture of organic molecules. Back propagation neural network (BPN) was used to distinguish the species in the mixture organic molecules and multivariate linear regression analysis (MLR) was used to compute the concentration of the species. A six-channel piezoelectric sensor detecting organic molecules in static system was investigated and discussed. Amine, carboxylic acid, alcohol and aromatic molecules can easily be distinguished by this system with back propagation neural network. Furthermore, the concentrations of the organic compounds were computed with an error of about 10% by multivariate linear regression analysis (MLR). Detection of organic mixture with amine, carboxylic acid, alcohol and aromatic molecules by this method also had good qualitative and quantitative results. In order to achieve better distinguishability, change of fault-tolerance in back propagation neural network was also investigated and discussed in this study.

被引用紀錄


申明智(2018)。表面聲波感測系統針對氣爆氣體辨識研究〔碩士論文,中原大學〕。華藝線上圖書館。https://doi.org/10.6840/cycu201800084
古佳琳(2007)。陣列式表面聲波感測器在有機氣體辨識之研究〔碩士論文,中原大學〕。華藝線上圖書館。https://doi.org/10.6840/cycu200700946

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