Multilayer thermal object identification in frequency domain using IR thermography and vector fitting

Abstract

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 trues~=()α+jω, and then, the integration result is corrected by the Taylor series. It leads to a kind of filtering of the temperature signal.

Identification of the Thermal Constants of the DPL Heat Transfer Model of a Single Layer Porous Material

“…Figures 5 and 7 present recovered temperature evolution versus time using Frequency domain Thermal Object Identification (FredTOI) methodology. It is based on the Vector Fitting and the Laplace transform with correction for high-frequency range [4].…”

“…The solution of 1D Fourier-Kirchhoff differential equation [1,2] in frequency domain for a sourceless object takes a form [3][4][5]. (1) where A and B are the integration constants.…”

Minimal seven‐element series‐parallel realizability of a certain positive‐real biquadratic impedance

“…During recent years, there are many new results on the minimal network realizations of low-order positive-real functions, 4,5,8,[24][25][26][27][28][29][30][31][32][33][34] and some other problems in network synthesis. [35][36][37][38][39][40] In addition to inerter-based mechanical control, passive network synthesis can provide a long-term impact on many other related fields, such as passive systems, 10,41,42 self-assembling circuit design, 43 thermal object identification, 44 biomedical engineering, 45 and negative imaginary systems. 46 The biquadratic function is the biproper real-rational function whose McMillan degree is two, and the impedances of many mechanical networks in vibration control systems can be expressed in the biquadratic form.…”

“…During recent years, there are many new results on the minimal network realizations of low‐order positive‐real functions, 4,5,8,24–34 and some other problems in network synthesis 35–40 . In addition to inerter‐based mechanical control, passive network synthesis can provide a long‐term impact on many other related fields, such as passive systems, 10,41,42 self‐assembling circuit design, 43 thermal object identification, 44 biomedical engineering, 45 and negative imaginary systems 46 …”

Thermal Time Constant CNN-Based Spectrometry for Biomedical Applications

“…It uses built-in transfer function estimation (TFEST) [ 13 , 14 ]. Recently, a new approach has been implemented using the Vector Fitting algorithm for inverse heat transfer problem solution [ 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 ]. It is important to mention that in the biomedical sciences, screening and diagnostic procedures must be non-invasive and, in many cases, contactless.…”