Szulczyński Bartosz, Gębicki Jacek
Department of Process Engineering and Chemical Technology, Chemical Faculty, Gdansk University of Technology, 11/12 G. Narutowicza Str., 80-233 Gdańsk, Poland.
Sensors (Basel). 2019 Aug 8;19(16):3473. doi: 10.3390/s19163473.
Measurement and monitoring of air quality in terms of odor nuisance is an important problem. From a practical point of view, it would be most valuable to directly link the odor intensity with the results of analytical air monitoring. Such a solution is offered by electronic noses, which thanks to the possibility of holistic analysis of the gas sample, allow estimation of the odor intensity of the gas mixture. The biggest problem is the occurrence of odor interactions between the mixture components. For this reason, methods that can take into account the interaction between components of the mixture are used to analyze data from the e-nose. In the presented study, the fuzzy logic algorithm was proposed for determination of odor intensity of binary mixtures of eight odorants: n-Hexane, cyclohexane, toluene, o-xylene, trimethylamine, triethylamine, α-pinene, and β-pinene. The proposed algorithm was compared with four theoretical perceptual models: Euclidean additivity, vectorial additivity, U model, and UPL model.
从气味滋扰角度对空气质量进行测量和监测是一个重要问题。从实际角度来看，将气味强度与空气分析监测结果直接联系起来将非常有价值。电子鼻提供了这样一种解决方案，由于其能够对气体样本进行整体分析，从而可以估计气体混合物的气味强度。最大的问题是混合物各成分之间会出现气味相互作用。因此，在分析来自电子鼻的数据时，会使用能够考虑混合物各成分之间相互作用的方法。在本研究中，提出了模糊逻辑算法来确定八种气味物质二元混合物的气味强度，这八种气味物质分别是：正己烷、环己烷、甲苯、邻二甲苯、三甲胺、三乙胺、α-蒎烯和β-蒎烯。将所提出的算法与四种理论感知模型进行了比较：欧几里得加和性、矢量加和性、U模型和UPL模型。
