The present study explores the capability of COMSOL Multiphysics, as a finite element modelling (FEM) tool, to model the interaction between a split-D differential surface eddy current (ECT) probe and semi-elliptical surface electrical discharge machined (EDM) notches. The effect of the small probe’s lift-off and tilt on its signal is investigated through modelling and subsequently, the simulation outcomes are validated using the probe’s impedance measurements. In the next stage, an adaptive neuro-fuzzy inference system (ANFIS) is designed to take the signal features as inputs and consequently, provide the length of the scanned notch as the system’s output. The system is trained by extracted features of thirty model-generated signals obtained from scanning of the same number of semi-elliptical notches by means of the split-D probe. The trained ANFIS is tested afterwards using the measured signals of 3 calibration EDM notches together with 5 model-based ones. A very low average estimation error is observed with regard to the length estimation of the test notches and the accuracy of the length estimation is found to be quite reasonable.

中文翻译：

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自适应神经模糊推理系统训练用于确定涡流扫描的半椭圆槽口的尺寸

本研究探索了 COMSOL Multiphysics 作为有限元建模 (FEM) 工具的能力，以模拟分裂 D 差分表面涡流 (ECT) 探头和半椭圆表面放电加工 (EDM) 凹口之间的相互作用。通过建模研究了小探针的提升和倾斜对其信号的影响，随后，使用探针的阻抗测量来验证仿真结果。在下一阶段，自适应神经模糊推理系统 (ANFIS) 被设计为将信号特征作为输入，从而提供扫描陷波的长度作为系统的输出。该系统通过使用分裂 D 探针扫描相同数量的半椭圆凹口获得的 30 个模型生成信号的提取特征进行训练。随后使用 3 个校准 EDM 凹口和 5 个基于模型的凹口的测量信号对经过训练的 ANFIS 进行测试。在测试槽口的长度估计方面观察到非常低的平均估计误差，并且发现长度估计的准确度是相当合理的。