Fire hazard analysis of alcohol aqueous solution and Chinese liquor based on flash point

Chen, Qinpei; Kang, Guoting; Zhou, Ting

doi:10.1088/1757-899x/241/1/012036

Cited by 2 publications

(1 citation statement)

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“…Alcohols cannot be distinguished visually because they are 100% liquid and colorless liquids, and they are in a small group of chemicals that can spontaneously ignite (Q. Chen, Kang, Zhou, & Wang, 2017). The flash point of alcohol-water solutions diluted with water will increase and as the flash point value of flammable liquids increases, the risk of fire hazards decreases (Cheremisinoff, 1999), However, these liquids, besides their flammable properties, also contain toxic substances and endanger human health.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Parameters that Affect the Measurements of Reflection Coefficients and Evaluation of the Effects of Parameters for K Nearest Neighbors-Based Liquid Classification

Efeoglu¹,

Tuna²

2021

Journal of Intelligent Systems: Theory and Applications

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In this study, microwave spectroscopy method has been used in liquid measurements and K nearest neighbors algorithm has been used for classifying liquids. For this aim, firstly an experimental setup consisting of a vector network analyzer, a patch antenna and a bottle have been built to measure the reflection parameter of each liquid used in classification experiments. The aim of this study is to examine both the parameters that may affect the measurements taken with the proposed system and the algorithm parameters that may affect the performance in the classification of liquids and the effects of these parameters. Measurements have been taken by leaving different distances between the antenna and the liquid in order to examine whether the distance of the liquids to the antenna affects the measurement result, and if so, what effect. For examining the parameters of K nearest neighbors algorithm that may affect the classification, the scattering parameters of different liquids measured using the patch antenna have been used as microwave dataset. In addition, the effect of container type has been analyzed. Performance tests have been conducted by weighting and without weighting the algorithm, by measuring the accuracy rate when different numbers of nearest neighbors and different distance metrics have been used. The results reveal that the classification made by applying weighting is more successful than the classification made without weighting regardless of the number of nearest neighbors and used distance metrics.

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Section: Introductionmentioning

confidence: 99%