Study of the Optimal Waveforms for Non-Destructive Spectral Analysis of Aqueous Solutions by Means of Audible Sound and Optimization Algorithms

• Published in: Applied sciences Vol. 11; no. 16; p. 7301
• Main Authors: García Díaz, Pilar, Utrilla Manso, Manuel, Alpuente Hermosilla, Jesús, Martínez Rojas, Juan A.
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-08-2021
• Subjects: Accuracy; acoustic chemical analysis; Acoustics; Algorithms; Anechoic chambers; Aqueous solutions; automatic classification; Biomimetics; Computer engineering; feature extraction; Gels; Genetic algorithms; Learning algorithms; non-destructive analysis; Nondestructive testing; Optimization; Particle size; Penetration depth; Sound; Spectral analysis; Spectrum analysis; Ultrasonic imaging; Velocity; Waveforms
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app11167301

Acoustic analysis of materials is a common non-destructive technique, but most efforts are focused on the ultrasonic range. In the audible range, such studies are generally devoted to audio engineering applications. Ultrasonic sound has evident advantages, but also severe limitations, like penetration depth and the use of coupling gels. We propose a biomimetic approach in the audible range to overcome some of these limitations. A total of 364 samples of water and fructose solutions with 28 concentrations between 0 g/L and 9 g/L have been analyzed inside an anechoic chamber using audible sound configurations. The spectral information from the scattered sound is used to identify and discriminate the concentration with the help of an improved grouping genetic algorithm that extracts a set of frequencies as a classifier. The fitness function of the optimization algorithm implements an extreme learning machine. The classifier obtained with this new technique is composed only by nine frequencies in the (3–15) kHz range. The results have been obtained over 20,000 independent random iterations, achieving an average classification accuracy of 98.65% for concentrations with a difference of ±0.01 g/L.