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Instruments and Systems: Monitoring, Control, and Diagnostics

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Algorithms for Solving the Direct and Inverse Problem of Heat Conductivity Based on Data from Multi-Temporal Multispectral Images of the Earth from Unmanned Aerial Vehicles
YU.YU. GROMOV, I.N. ISHCHUK, YU.G. VESELOV, V.V. RODIONOV

The aim of the study is to develop effi cient algorithms for solving the coeffi cient inverse problem for a non-stationary heat fl ow using multispectral
observations of the Earth's surface layer made at specifi ed points in time from unmanned aerial vehicles. The proposed algorithms make it possible
to reconstruct the spatial distribution of thermal activity over the entire observed surface. The algorithms are intended for use in combination with
commercial calculation programs, such as Matrix Laboratory, which implements the fi nite element method (FEM). When implementing the FEM, both
linear and nonlinear fi nite elements are used. Unknown boundary conditions and non-stationary heat fl ow are approximated by step functions. Due to
the implementation of the FEM, the proposed method is applicable to complex-shaped objects with temperature-dependent thermophysical properties.
The paper presents numerical examples of identifying thermophysical properties for a simultaneous transient heat fl ow, including conductivity and
radiation. The developed algorithms can be used to recognize objects hidden under a soil layer during remote sensing of the Earth.
Keywords: aerospace monitoring, artifi cial neural network, background target environment, thermophysical properties, classifi cation, inverse
problem of heat conduction.


DOI: 10.25791/pribor.12.2024.1546

Pp. 31-47.

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