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首页> 外文会议>Industrial Technology, 2009. ICIT 2009 >The application of the artificial neural network and hot probe method in thermal parameters determination of heat insulation materials Part 1 - thermal model consideration
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The application of the artificial neural network and hot probe method in thermal parameters determination of heat insulation materials Part 1 - thermal model consideration

机译：人工神经网络和热探针法在隔热材料热参数确定中的应用第1部分-热模型考虑

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摘要

The article presents an idea of a measurement system with hot probe for testing thermal parameters of heat insulation materials. In comparison to the classical method of the line heat source (LHS) numerous assumptions about model of heat flow in the sample of material are not needed. The model of a nonstationary heat flow process in the sample of material with hot probe and an auxiliary thermometer is based on a two-dimensional heat-conduction model and includes heat capacity of probe handle. For solving the system of partial differential equations describing the model, the finite element method (FEM) was applied. Simulations of heat flow process were carried out in the Matlab environment and the results are presented in part 1 of the paper. Part 2 is concentrated on the usability of the artificial neural network in solving the inverse heat transfer problem in a sample of heat insulation material. The proposed method is suitable for immediate measurement in building site or factory.
机译：本文提出了一种带有热探头的测量系统，用于测试隔热材料的热参数。与线热源（LHS）的经典方法相比，无需对材料样本中的热流模型进行大量假设。具有热探针和辅助温度计的材料样品中的非平稳热流过程模型基于二维热传导模型，并且包括探针手柄的热容量。为了求解描述模型的偏微分方程组，应用了有限元方法（FEM）。在Matlab环境中进行了热流过程的仿真，结果在论文的第1部分中进行了介绍。第2部分集中讨论了人工神经网络在解决隔热材料样本中逆热传递问题方面的可用性。该方法适用于建筑工地或工厂的即时测量。

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