Affiliations: State Key Laboratory of Power System, Department of Electrical Engineering, Tsinghua University, Beijing 100084, China
Correspondence:
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Corresponding author: Shen Wang, State Key Laboratory of Power System, Department of Electrical Engineering, Tsinghua University, Beijing 100084, China. E-mail: wangshen@mail.tsinghua.edu.cn.
Abstract: Electromagnetic acoustic transducers (EMATs) are non-contact ultrasonic transducers used to generate ultrasonic waves directly in the tested metal samples, suitable for special situations like testing moving or hot metal solids. EMATs rely on electromagnetic coupling, and the transduction efficiency of EMATs is relatively low, so it’s crucial to improve their performance through building accurate models and implementing structural optimisations. Modern evolutionary optimization algorithms involve a number of evaluations of the objective function of the optimization problem, so it’s necessary to explore surrogate models to reduce the time consumption during evaluation of the computationally expensive objective function, especially when the function corresponds to complex numerical models, like the EMAT model. We focused on the application of Kriging surrogate model (DACE) in EMAT modeling in this work. The formulations of the DACE model were reviewed, then the model of an omnidirectional EMAT was introduced. Three methods to calculate the amplitudes of the displacement components were discussed and compared, including the time-domain method, the multifrequency method (with FFT/IFFT processing), and the single frequency method applying directly the phasors. The DACE model of the EMAT was then built to predict outputs on a discrete grid of the design variables. Finally the obtained DACE model was used as the surrogate model in the optimization of the EMAT driven by the simulated annealing algorithm. With the DACE model, the total time consumption of optimization of the EMAT was reduced greatly.
