An Idea of a Measurement System for Determining Thermal Parameters of Heat Insulation Materials
The article presents the prototype of a measurement system with a hot probe, designed for testing thermal parameters of heat insulation materials. The idea is to determine parameters of thermal insulation materials using a hot probe with an auxiliary thermometer and a trained artificial neural network. The network is trained on data extracted from a nonstationary two-dimensional model of heat conduction inside a sample of material with the hot probe and the auxiliary thermometer. The significant heat capacity of the probe handle is taken into account in the model. The finite element method (FEM) is applied to solve the system of partial differential equations describing the model. An 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. Experimental results are also presented. The proposed measurement system for parameter testing is suitable for temporary measurements in a building site or factory.
Al-Homoud, M. (2005). Performance characteristics and practical applications of common building thermal insulation materials. Building and Environment, 40, 353-366.
Chudzik, S., Minkina, W. Method for determining thermal parameters, patent PL Nr 193596 B1, Int. Cl.8 G 01N 25/18, G 01K 17/00. (in Polish).
Minkina, W., Chudzik, S. (2004). Measurement of Thermal Parameters of Thermoinsulating Materials - Instrumentation and Methods. Publishing House of Czestochowa University of Technology. Czestochowa. (in Polish)
Beck, J.V. (1985). Inverse Heat Conduction. A Wiley-Interscience Publisher.
Alifanov, O., Artyukhin, E., Rumyantsev, S. (1995). Extreme Methods for solving Ill-Posed Problems with Applications to Inverse Heat Transfer Problems. New York.
Blackwell, J.H. (1953). Radial-axial heat flow in regions bounded internally by circular cylinders. Canadian Journal of Physics, 31(4), 472-479.
Boer, J., Butter, J., Grosskopf, B., Jeschke, P. (1980). Hot wire technique for determining high thermal conductivities. Refractories Journal, 55, 22-28.
Sylos Cintra, J., Santos, W. (2000). Numerical analysis of sample dimensions in hot wire thermal conductivity measurements. Journal of the European Ceramic Society, 20, 1871-1875.
Ventkaesan, G., Guang-Pu Jin. (2001). Measurement of thermophysical properties of poliurethane foam insulation during transient method. Int. J. Therm. Sci., 40, 133-144.
Xin-Gang Liang. (1995). The bounduary induced error on the measurement of thermal conductivity by transient hot wire method. Measurement Science and Technology, 6(5), 467-471.
Huaqing Xie, Shuxia Cheng. (2001). A fine needle probe for determining the thermal conductivity of penetrable materials. Measurement Science and Technology, 12(1), 58-62.
Hammerschmidt, U., Sabuga, W. (2000). Transient hot wire (THW) method: uncertainty assessment. International Journal of Thermophysics, 21(6), 1255-1278.
Tavman, I.H., Tavman, S. (1999). Measurement of thermal conductivity of dairy products. Journal of Food Engineering, 41, 109-114.
ASTM D 5334-00. (2000). Standard test methods for determination of thermal conductivity of soil and soft rock by thermal needle probe procedure. ASTM, 100 Barr-Harbor Dr. West Conshocken. PA 19428-2059, 04.08.
ASTM D 5930-01. (2001). Standard test method for thermal conductivity of plastics by means of a transient line source technique. ASTM, 100 Barr-Harbor Dr., West Conshocken, PA 19428-2059, 14.02.
IEEE STD 442-1981 IEEE guide for Thermal Resistivity Measurements. The Institute of Electrical and Electronics Engineers, Inc. 345 East 47 Street, New York, NY 10017
Chudzik, S., Gryś, S., Minkina, W. (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. Proc. of IEEE International Conference on Industrial Technology ICIT. Melbourne, 1-6.
Chudzik, S. (2009). The idea of using artificial neural network in measurement system with hot probe for testing parameters of heat-insulating materials. Measurement, 42, 764-770.
Chudzik, S., Minkina, W., Gryś, S. (2009). The application of the artificial neural network and hot probe method in thermal parameters determination of heat insulation materials. Part 2 - application of the neural network. Proc. of IEEE International Conference on Industrial Technology ICIT. Melbourne, 1-5.
Daponde, P., Grimaldi, D. (1998). Artifical neural networks in measurements. Measurement, 23, 93-115.
Gajda, J. (2002). Uncertainty of an identification process. Metrology and Measurement Systems, 9(2), 89-101.
Gajda, J., Szyper, M. (1998). Modelling and simulation of measurement systems. AGH. Firma Jartek s.c. Krakow. (in Polish)
Taler, J. (1995). Theory and practice of identifications heat transfer processes. Ossolineum, Wroclaw. (in Polish)
Terpiłowski, J. (1991). Measurements of thermal diffusivity of solids. Scientific Papers of the Technical University of Lodz, 101(606), 161-191. (in Polish).
Minkina, W., Chudzik, S. (2003). Determination of thermal parameters of heat-insulating materials using artifical neural networks. Metrology and Measurement Systems, 10(1), 34-49.
Chudzik, S., Gryś, S., Minkina, W. (2009). Artificial neural networks in solution of inverse problem of heat diffusion. PAK, 55(2), 83-88. (in Polish).
Chudzik, S., Minkina, W. Method for determining thermal parameters. patent application P 382918. (in Polish).