Premium
Multilayer thermal object identification in frequency domain using IR thermography and vector fitting
Author(s) -
Strakowska Maria,
Chatzipanagiotou Panagiotis,
De Mey Gilbert,
Chatziathanasiou Vasilis,
Więcek Bogusław
Publication year - 2020
Publication title -
international journal of circuit theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.364
H-Index - 52
eISSN - 1097-007X
pISSN - 0098-9886
DOI - 10.1002/cta.2845
Subject(s) - thermography , laplace transform , electrical impedance , thermal , frequency domain , algorithm , acoustics , computer science , electronic engineering , mathematical analysis , infrared , mathematics , optics , physics , engineering , electrical engineering , meteorology
Summary This paper deals with the identification of the thermal parameters of multilayer objects using the concept of thermal impedance. In order to perform such identification, temperature evolution in time is obtained by an infrared camera after power excitation is applied in the investigated structure. Infrared thermography offers the advantage of being a noncontact temperature detection and measurement method. In many practical cases, it is impossible to use contact temperature measurements. Typically, the power in the form of a step function is applied. In order to calculate the thermal impedance of an object, temperature and power are converted into the frequency domain using the Laplace transform for s = jω. Then, the poles of the thermal impedance are identified using vector fitting, which allows calculating the thermal impedance as a sum of partial fractions. This corresponds directly to the Foster network of a thermal object. In addition, the vector fitting method offers much better convergence in comparison with other methods using the polynomial rational approximation of thermal impedance. A considerable improvement of the numerical Laplace transform in high frequency range is proposed. In this approach, the variable s = jω is replaced by s ~ = α + j ω , and then, the integration result is corrected by the Taylor series. It leads to a kind of filtering of the temperature signal.