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PL
W artykule przedstawiono koncepcję podręcznego systemu pomiarowego wykorzystującego odpowiednią sondę cieplną do doraźnej kontroli parametrów cieplnych materiałów termoizolacyjnych. Przedstawiony system pomiarowy wykorzystuje sztuczne sieci neuronowe do rozwiązania współczynnikowego zagadnienia odwrotnego dyfuzji ciepła w materiale. Symulacje zjawiska dyfuzji ciepła oraz proces uczenia sieci neuronowej przeprowadzono w środowisku programowym MATLAB. Otrzymane wyniki przeprowadzonego eksperymentu wskazują, że istnieje możliwość wykorzystania w praktyce przedstawianej koncepcji systemu pomiarowego wykorzystującego do rozwiązania zagadnienia odwrotnego sieć neuronową. Koncepcja ta pozwala zbudować system pomiarowy na bazie prostego mikrokontrolera, w którego programie można zaimplementować strukturę nauczonej sieci.
EN
The article presents a prototype of a measurement system with a hot probe, designed for testing thermal parameters of heat insulation materials. The proposition is to use a hot probe with an auxiliary thermometer and a trained artificial neural network to determine parameters of thermal insulation materials. The network is trained on data extracted from a nonstationary two-dimensional heat conduction model inside a sample of material with a hot probe and an auxiliary thermometer. The significant heat capacity of the probe handle 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 artificial neural network (ANN) is used to estimate coefficients of the inverse heat conduction problem for a solid. The network determines values of the effective thermal conductivity and effective thermal diffusivity on the basis of temperature responses of the hot probe and the auxiliary thermometer. All calculations, like FEM, training and testing processes, were conducted in the MATLAB environment. The results of the experiment are also presented. The proposed measurement system for parameters testing is suitable for temporary measurements in a building site or factory.
EN
An analytical method for determining temperature of the fluid affecting a thick walled component based on an inverse heat conduction problem is presented in this paper. Effectiveness of the method is illustrated by following examples: one of a temperature sensor attached to the outer surface of a thick-walled pipe or placed inside a pipe wall heated by a flow of steam from inside and another of a cylindrical thermometer quickly submerged in boiling water.
3
Content available remote Identification of internal heat source capacity in the heterogeneous domain
EN
The heterogeneous domain Ωbeing the composition of two domains (Ω1, Ω2) is considered. It is assumed that in the first domain Ω1 the internal volumetric heat sources act. On the basis of knowledge of heating (cooling) curves at the selected set of Ω2 the capacity of internal heat sources in Ω1 is identified. The inverse problem formulated in this way is interesting from the practical point of view. For example, a such situation takes place during the casting solidification. The evolution of latent heat in the casting domain causes that in Ω1 the internal heat sources appear, while in the mould domain this component of energy equation is equal to 0. Additionally the measurements of temperature in the mould are essentially simpler from the technical view-point. In the paper the theoretical base of the problem and the examples of numerical realization are discussed.
EN
In the paper the inverse heat conduction problem consisting in the estimation of surface heat flux from transient temperature measurements in 2D solid body is presented. In order to solve the problem the sequential function specification method using future temperature information and the boundary element method have been applied. The theoretical considerations are supplemented by the example of computations.
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