Efficient Numerical Solver for Simulation of Pulsed Eddy-Current Testing Signals

ArticleinIEEE Transactions on Magnetics 47(11):4582 - 4591 · December 2011with19 Reads
DOI: 10.1109/TMAG.2011.2151872 · Source: IEEE Xplore
The pulsed eddy-current testing (PECT) method has the promising capabilities for detecting defects and evaluating material properties. It achieves this through its rich variety of frequency components and large driving electric current. Efficient numerical simulation of PECT signals plays an important role in probe optimization and quantitative signal processing. This study primarily focuses on the development of an efficient numerical solver for PECT signals, and its validation via the consideration of the nondestructive testing problems of wall thinning defects in pipes of nuclear power plants. A frequency domain summation method combined with an interpolation strategy was proposed and implemented. It is based on the finite element method with edge elements. The number of total frequencies used in signal summation and the number of selected frequencies for interpolation were thoroughly discussed. In addition, a code using the time domain integration method was also developed for the signal prediction of a transient PECT problem. It was used for comparison with the frequency domain summation method. A comparison of numerical results of the two proposed simulation methods and experimental results indicates that both of these simulation methods can model PECT signals with high precision. However, the frequency domain summation method combined with an interpolation strategy is much more efficient in its use of simulation time.
    • "Pulsed eddy current (PEC) has recently become an important alternative nondestructive testing (NDT) and evaluation technique [1,2]. There has been an increasing interest in the use of NDT of defects from metal forming procedures [3], fatigue cracks of aerospace structure [4,5], as well as defects of pressure vessels [6] and petroleum tubes [7] due to its high sensitivity, robustness, and wide range of frequencies. Previous defect classification works have concentrated on transient analysis in the time domain [8] and spectral analysis in the frequency domain though Fourier transform (FT) [9]. "
    [Show abstract] [Hide abstract] ABSTRACT: The defect classification is investigated by using features-based giant-magnetoresistive pulsed eddy current (GMR-PEC) sensor. The power spectrum density of the intrinsic mode functions (IMFs) is extracted as the classification feature, considering the disadvantage of selecting a wavelet base determined in previous work on spectral analysis combined with wavelet-decomposition. The IMFs are derived through empirical mode decomposition (EMD) and ensemble EMD. Principal component analysis, linear discriminant analysis, and Bayesian classifier are employed for defect classification algorithm. The proposed approach is validated by experiments, and results indicate that the cracks and cavities in the surface and subsurface can be classified satisfactorily.
    Article · Nov 2015
    • "Then, the permeability distribution of carbon steel specimen can be predicted according to the B-H curve of the targeted material.Figure 3 shows the permeability distribution of surface of carbon steel specimen where we can see that the permeability of the area saturated by the yoke can be dramatically reduced. Finally, the PECT forward simulation tool for carbon steel under magnetic saturation environment is developed based on the A r (reduced A) method and Fourier series strategy [3].Figure 4 shows the preliminary results of the comparison of ECT signals under different permeability. It can be found that the defect signal becomes larger when the permeability of specimen becomes smaller, which demonstrates that the promising efficiency of the magnetic saturation PECT approach. "
    [Show abstract] [Hide abstract] ABSTRACT: Quantitative non-destructive evaluation of wall thinning in carbon steel piping is a difficult and urgent issue for safety of nuclear power plants. In this study, a magnetic saturation PECT (pulsed eddy current testing) method is proposed for this purpose, where a magnetic yoke is utilized to generate strong static magnetic field to saturate the piping material and to increase the skin depth, and the PECT is applied then in the magnetic saturation environment. The feasibility of the magnetic saturation PECT method for wall thinning detection in carbon steel piping is validated through numerical simulations. Firstly, the simulated polarization approach is adopted for the calculation of the static magnetic field distribution generated by the electromagnetic magnet, then the material permeability distribution is predicted according to the B-H curve of the targeted material. Finally the efficient PECT forward simulation tool is updated for the carbon steel based on the Ar (reduced A) method and the Fourier series strategy to validate the wall thinning detection in carbon steel material.
    Full-text · Article · Jan 2014
    • "It is clear that most of the energy of the excitation pulse concentrates on the odd harmonics of the excitation frequency (0.2 kHz). in other words, the spectrum of the excitation pulse is composed of 0.2 kHz, 0.6 kHz, 1.0 kHz, 1.4 kHz, and so on, which agrees well with [25]. Since the PEC problem primarily has linear property [16], the response signal from a PEC is also composed of the odd harmonics. So training and operating the model with odd harmonics is reasonable. "
    [Show abstract] [Hide abstract] ABSTRACT: This paper reports fast crack profile reconstruction methods using transient slices and spectral components of pulsed eddy current (PEC) signals after a review of the state-of-the-art and current challenges. These methods provide initial approximate profiles for crack shape reconstruction, and have potential to reduce the computing time. Experimental samples, results, and reconstructions have been presented and discussed. Comparative studies of different profile reconstructions using different PEC signals such as amplitude, phase, real and imaginary values of spectral components, transient slices, have also been conducted using reconstruction Mean Square Errors (MSE). The results show that the profiles estimation using the imaginary values of spectral components is more stable and accurate than the others.
    Full-text · Article · Mar 2013
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