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Improvement of minimum paint film thickness for THz paint meters by multiple-regression analysis
Takashi Yasuda1, Tetsuo Iwata, Tsutomu Araki
1Graduate School of Engineering Science, Osaka University, Japan.
Abstract:
We propose a numerical parameter fitting method to determine the time delay between two temporally overlapped echo pulses in terahertz (THz) tomography measurements. The method is based on multiple-regression analysis with the least-squares method and is applied to decrease the minimum paint film thickness for THz paint meters. Applying multiple-regression analysis to paint thickness measurements is five times more sensitive with regard to the minimum thickness than numerical Fourier deconvolution. We apply the proposed method to determine the optical thickness, geometrical thickness, and group refractive index of dry paint film and wet paint film. The proposed method is useful for decreasing the minimum thickness for a THz paint meter and other THz tomography measurements.

