Technology for determining the elemental composition of soils by acoustic signals

Summary. The article presents the results of determining the humus content in the studied soil samples. Obtaining the results was based on processing phonograms with subsequent decomposition of the acoustic signal into a Fourier spectrum. The obtained spectrum was processed by the method of pattern recognition with division into classes corresponding to the proportion of humus content in the soil.

Introduction. Obtaining a stable harvest in agricultural fields of the agroindustrial complex is inextricably linked with the annual agrochemical analysis of soils. One of the indicators of soil quality is the content of humus in the arable layer. The development of an express analysis to determine the humus content in the analyzed layers of soils is the purpose of this research. At this stage of research, the task is to analyze the acoustic absorption signal and select the necessary number of factors that allow recognizing the structure of an object according to the accepted classification scale.

Object. The object of research is samples of soil layers in order to determine the humus content in the soil.

Materials and methods. The studies were carried out by analyzing and decomposing the acoustic signal transmitted by an electromechanical transducer to the surface of a vibrator in contact with the analyzed soil, where the acoustic absorption signal is received by a sensor installed on the object.

Results and conclusions. In order to diagnose soil samples by humus content, the acoustic signal is decomposed into natural components corresponding to various signal sources, therefore, by decomposing the complete signal into orthogonal components - the main and timbre harmonics, it is possible to isolate the informative part of the signal, freeing it from noise interference. The informative signal prepared in this way is subjected to mathematical processing. After restrictions, filtering in the information frequency band and pre-amplification, the time series of signals is decomposed into the acoustic Fourier spectrum and analyzed by the fundamental frequency and highest timbre harmonics of the diagnostic spectrum. The signal is decrypted using the method of potential functions from the theory of pattern recognition into classes of elemental composition of soils. In an experiment with known (reference) classes of objects, the spectra lead to their own central axes, replacing each spectrum with an equivalent application point found by the method of static moments. After obtaining the dividing boundaries, all experimentally obtained pairs of samples with coordinates f₁ – frequency and f₂ – amplitude are plotted on the graph.

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