Open AccessIdentification of soils, grounds and lands strata using the acoustic spectral analysis
Author(s) -
Sergey Evtushenko,
V A Lepikhova,
Nadezhda Lyashenko,
E V Skrinnikov
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/913/5/052043
Subject(s) - superposition principle , signal (programming language) , elemental analysis , spectral line , transformation (genetics) , fourier transform , fast fourier transform , acoustic emission , computer science , acoustics , algorithm , mathematics , physics , chemistry , mathematical analysis , biochemistry , organic chemistry , astronomy , programming language , gene
One of the important tasks of computer technology for the dispersed systems’ analysis of soils, grounds and lands strata is the determination of their qualitative (elemental) composition and quantitative ratio. Due to the complexity and cumbersomeness of traditional methods of chemical analysis, to solve such problems, modern technologies for the express analysis of the disperse systems under study, based on indirect measurements and computer calculation methods, are required. The developed computer technology for determining the elemental composition of the studied disperse systems is based on the acoustic emission signal (AE) Fourier spectrum analysis emitted by these systems as a result of vibro-acoustic exposure. The (AE) signal of the studied systems is recorded in the form of phonograms, which are converted to digital form and processed using the fast Fourier transform. The result of this transformation is the total (AE) signal spectrum, which is a superposition of the spectra belonging to the elements of the studied system. To determine the qualitative (elemental) composition of the studied system, signs are taken that uniquely identify the elements of the system. In the study of dispersed systems, the eigenfrequencies of the particle particles are taken as such signs. These frequencies make it possible to distinguish frequency sub-spectra corresponding to one or another element in the general signal spectrum (AE). Based on the sub-spectra analysis, the presence degree of these elements is considered. Thus, the task of determining the elemental composition is reduced to the selection and analysis in the (AE) total spectrum of the studied sub-spectra system corresponding to each element.