Analysis of Water, Ethanol, and Fructose Mixtures Using Nondestructive Resonant Spectroscopy of Mechanical Vibrations and a Grouping Genetic Algorithm

A new haptic sensor that is based on vibration produced by mechanical excitation from a clock coupled to a resonant cavity is presented. This sensor is intended to determine the chemical composition of liquid mixtures in a completely non-destructive method. In this case, a set of 23 samples of water...

Full description

Bibliographic Details
Main Authors: Pilar García Díaz, Juan Antonio Martínez Rojas, Manuel Utrilla Manso, Leticia Monasterio Expósito
Format: Article
Language:English
Published: MDPI AG 2018-08-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/18/8/2695
Description
Summary:A new haptic sensor that is based on vibration produced by mechanical excitation from a clock coupled to a resonant cavity is presented. This sensor is intended to determine the chemical composition of liquid mixtures in a completely non-destructive method. In this case, a set of 23 samples of water, ethanol, and fructose mixtures has been used to simulate different kinds of alcoholic beverage. The spectral information from the vibrational absorption bands of liquid samples is analyzed by a Grouping Genetic Algorithm. An Extreme Learning Machine implements the fitness function that is able to classify the mixtures according to the concentration of ethanol and fructose. The 23 samples range from 0%–13% by volume of ethanol and from 0–3 g/L of fructose, all of them with different concentration. The new technique achieves an average classification accuracy of 96%.
ISSN:1424-8220