Zhang Siquan
Department of Electrical and Automation, Shanghai Maritime University, Shanghai 201306, China.
Sensors (Basel). 2024 Dec 11;24(24):7931. doi: 10.3390/s24247931.
Multi-layer conductive structures, especially those with features like bolt holes, are vulnerable to hidden corrosion and cracking, posing a serious threat to equipment integrity. Early defect detection is vital for implementing effective maintenance strategies. However, the subtle signals produced by these defects necessitate highly sensitive non-destructive testing (NDT) techniques. Analytical modeling plays a critical role in both enhancing defect-detection capabilities and guiding the design of highly sensitive sensors for these complex structures. Compared to the finite element method (FEM), analytical approaches offer advantages, such as faster computation and high accuracy, enabling a comprehensive analysis of how sensor and material parameters influence defect detection outcomes. This paper introduces a novel T-core eddy current sensor featuring a central air gap. Utilizing the vector magnetic potential method and a truncated region eigenfunction expansion (TREE) method, an analytical model was developed to investigate the sensor's interaction with multi-layer conductive materials containing a hidden hole. The model yielded closed-form expressions for the induced eddy current density and coil impedance. A comparative study, implemented in Matlab, analyzed the eddy current distribution generated by T-core, E-core, I-core, and air core sensors under identical conditions. Furthermore, the study examined how the impedance of the T-core sensor changed at different excitation frequencies between 100 Hz and 10 kHz when positioned over a multi-layer conductor with a hidden air hole. These findings were then compared to those obtained from E-core, I-core, and air-core sensors. The analytical results were validated through finite element simulations and experimental measurements, exhibiting excellent agreement. The study further explored the influence of T-core design parameters, including the air gap radius, dome radius, core column height, and relative permeability of the T-core material, on the inspection sensitivity. Finally, the proposed T-core sensor was used to evaluate crack and hole defects in conductors, demonstrating its superior sensitivity compared to I-core and air core sensors. Although slightly less sensitive than the E-core sensor, the T-core sensor offers advantages, including a more compact design and reduced material requirements, making it well-suited for inspecting intricate and confined surfaces of the target object. This analytical model provides a valuable tool for designing advanced eddy current sensors, particularly for applications like detecting bolt hole defects or measuring the thickness of non-conductive coatings in multi-layer conductor structures.
多层导电结构，尤其是那些具有螺栓孔等特征的结构，容易受到隐藏腐蚀和开裂的影响，对设备完整性构成严重威胁。早期缺陷检测对于实施有效的维护策略至关重要。然而，这些缺陷产生的细微信号需要高度灵敏的无损检测（NDT）技术。分析建模在增强缺陷检测能力和指导针对这些复杂结构的高灵敏度传感器设计方面都起着关键作用。与有限元方法（FEM）相比，分析方法具有计算速度更快和精度更高等优势，能够全面分析传感器和材料参数如何影响缺陷检测结果。本文介绍了一种具有中心气隙的新型T型铁芯涡流传感器。利用矢量磁位法和截断区域本征函数展开（TREE）方法，开发了一个分析模型来研究该传感器与含有隐藏孔的多层导电材料之间的相互作用。该模型得出了感应涡流密度和线圈阻抗的闭式表达式。在Matlab中进行的一项对比研究，分析了在相同条件下T型铁芯、E型铁芯、I型铁芯和空心传感器产生的涡流分布。此外，该研究还考察了T型铁芯传感器在100 Hz至10 kHz不同激励频率下，放置在带有隐藏气孔的多层导体上方时其阻抗是如何变化的。然后将这些结果与从E型铁芯、I型铁芯和空心传感器获得的结果进行比较。分析结果通过有限元模拟和实验测量得到验证，显示出极好的一致性。该研究进一步探讨了T型铁芯设计参数，包括气隙半径、圆顶半径、铁芯柱高度以及T型铁芯材料的相对磁导率，对检测灵敏度的影响。最后，所提出的T型铁芯传感器用于评估导体中的裂纹和孔缺陷，证明了其与I型铁芯和空心传感器相比具有更高的灵敏度。虽然T型铁芯传感器的灵敏度略低于E型铁芯传感器，但它具有设计更紧凑和材料需求减少等优点，非常适合检测目标物体复杂且受限的表面。这种分析模型为设计先进的涡流传感器提供了一个有价值的工具，特别是对于检测螺栓孔缺陷或测量多层导体结构中非导电涂层厚度等应用。
