Abstract

The paper presents a prototype of a measurement system with a hot probe based on a transient line heat source method, designed for testing the thermal parameters of heat insulation materials. The proposition is to use an auxiliary thermometer (dual needle probe) and a trained artificial neural network to determine the parameters of thermal insulation materials. The data extracted from the simulation of a nonstationary two-dimensional heat conduction model inside a sample of material with a dual needle probe trained the artificial neural network (ANN). The significant heat capacity of the needle probe is taken into account in the model. To solve the system of partial differential equations describing the model, the finite element method (FEM) was applied. The ANN is used to estimate the coefficients of the inverse heat conduction problem for a solid. The network determines the values of the effective thermal conductivity and effective thermal diffusivity on the basis of the temperature increases of the hot probe and the auxiliary thermometer. All calculations, such as FEM, and training and testing processes of the ANN, were carried out in the Matlab environment. The results of the experiment are also presented. The proposed measurement system for testing the parameters is suitable for temporary measurements in a building site or factory.

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