Showing papers by "Tetsuya Uchimoto published in 2023"
TL;DR: In this article , a theoretical analysis of the magnetic Barkhausen noise energy (MBNenergy) is presented, showing that in standard characterization conditions, the magnetization variations associated with the domain wall motions are proportional to the square of the envelope of the MBN signal instead of its absolute value.
1 citations
30 Mar 2023
TL;DR: In this article , anisotropic Turing patterns (TPs) of an activator-inhibitor system were numerically studied by using the Finsler geometry (FG) modeling technique, where diffusion coefficients were dynamically generated to be direction dependent owing to an internal degree of freedom (IDOF) and its interaction with the activator and inhibitor under the presence of thermal fluctuations.
Abstract: We numerically study the anisotropic Turing patterns (TPs) of an activator-inhibitor system, focusing on anisotropic diffusion by using the Finsler geometry (FG) modeling technique. In the FG modeling prescription, the diffusion coefficients are dynamically generated to be direction dependent owing to an internal degree of freedom (IDOF) and its interaction with the activator and inhibitor under the presence of thermal fluctuations. In this sense, FG modeling contrasts sharply with the standard numerical technique, where direction-dependent diffusion coefficients are assumed in the reaction-diffusion (RD) equations of Turing. To find the solution of the RD equations, we use a hybrid numerical technique as a combination of the metropolis Monte Carlo method for IDOF updates and discrete RD equations for steady-state configurations of activator-inhibitor variables. We find that the newly introduced IDOF and its interaction are one possible origin of spontaneously emergent anisotropic patterns on living organisms such as zebra and fishes. Moreover, the IDOF makes TPs controllable by external conditions if the IDOF is identified with lipids on cells or cell mobility.
01 Apr 2023
TL;DR: In this paper , the thickness of 51 corrosion specimens was measured and compared with the true thickness obtained by 3D laser scanner, and it was confirmed that the estimation accuracy of this evaluated thickness was higher than that of the evaluated thickness by the DFT method.
Abstract: Electromagnetic acoustic resonance method (EMAR) is promising for online monitoring of pipes wall thinning with corrosion during operation. However, the improvement of measurement accuracy is one of issues to be solved, although some signal processing methods such as superposition of nth compression method (SNC) have been proposed in order to improve the accuracy of wall thickness estimation. In this study, for the purpose of highly accurate evaluation of the wall thickness, the thickness of 51 corrosion specimens was measured and compared with the true thickness obtained by 3D laser scanner. The fundamental resonance frequency of EMAR signal spectrum was evaluated by discrete Fourier transform method (DFT) and SNC method, and the wall thickness was calculated. As a result, evaluated thickness by EMAR almost corresponded to the average of true thickness. The accuracy of the evaluated thickness by the SNC method depends on the method to set the postulated thickness for determining the number of compressions. It was found that using the evaluated thickness by the DFT method for determining the number of compressions improved the estimation accuracy of the evaluated thickness by the SNC method. In addition, it was confirmed the estimation accuracy of this evaluated thickness was higher than that of the evaluated thickness by the DFT method.
TL;DR: In this article , an inversion scheme for profile reconstruction of a fatigue crack in rails from the motion-induced eddy current testing (MIECT) signals is proposed based on the conjugate gradient (CG) optimization method and the fast MIECT forward simulator developed by authors.
01 Mar 2023
TL;DR: In this article , the magnetization processes related to the domain wall kinetics were revealed to be more correlated to plastic strain, and the magnetic incremental permeability hysteresis area and maximal value were found to be the best plastic strain indicators.
Abstract: Electric steel is widely used for magnetic conversion of electrical energy such as in electric motors and power transformers. Electric steel sheets are cut using mechanical methods (such as punching) during manufacturing. These methods induce local plastic strains, which lead to overall degradation in magnetic performance. Plasticity and magnetic losses are physically related in electrical steel. It is impossible to measure the magnetic losses on the production line using standard methods. Non-destructive testing (NDT) based on magnetization mechanisms is a promising alternative, giving access to local plastic strains and indirectly to local magnetic losses. In this study, a setup was designed to stimulate the magnetization mechanisms separately while maintaining the same experimental conditions. The magnetization processes related to the domain wall kinetics were revealed to be more correlated to plastic strain. The magnetic incremental permeability hysteresis area and maximal value, and the coercivity associated with Barkhausen noise were found to be the best plastic strain indicators. Additional tests in an NDT context confirmed the correlations, the equal applicability of the proposed indicators, and their viability in predicting static hysteresis loss.
TL;DR: In this article , a new signal separation and extraction method is proposed for the hybrid detection signals in the PECT/EMAT nondestructive testing method based on wavelet analysis strategy.
Abstract: It is found that the electromagnetic acoustic testing (EMAT) signal itself contains part of the pulsed eddy current testing (PECT) signal. Therefore, if the pulsed eddy current signal embedded in the electromagnetic ultrasound signal can be effectively extracted and used, the hybrid nondestructive testing method of electromagnetic ultrasound and pulsed eddy current can be truly realized. Based on the above concept, the authors have obtained some preliminary results through simple signal processing try, and which gave us a promising hope of this hybrid method. To further verify the validity and strengthen the usability of the hybrid method, more effective signal separation and extraction way to the hybrid detection signals is expected, which is the core step. In this study, a new signal separation and extraction method is proposed for the hybrid detection signals in the PECT/EMAT nondestructive testing method based on wavelet analysis strategy. The effectiveness and merits of the proposed signal separation method compared to the previous way is verified through the numerical simulation as well as experiment.