基于多向扫描的涡流检测空腔和裂纹识别

IF 4.3 2区综合性期刊 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Sensors Journal Pub Date : 2025-08-04 DOI:10.1109/JSEN.2025.3593368

Zhengya Guo;Kok-Meng Lee;Yiwen Zhu;Zhenhua Xiong

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引用次数: 0

摘要

针对空腔缺陷和裂纹缺陷长径比存在显著差异的问题，本文通过分析扰动涡流缺陷及其相应磁通密度场的特征，提出了一种基于多向扫描的涡流检测策略，以区分空腔缺陷和裂纹缺陷。为了实现有效的仿真和验证策略，分布式电流源（DCS）方法通过纳入解域旋转来增强，允许在任意方向上精确建模缺陷。为了减少所需的模拟次数，还讨论了扫描图像之间的对称关系。通过与有限元分析结果的比较，验证了改进数值模型的有效性。然后使用各种缺陷方向的模拟扫描图像来确定能够进行可靠分类的关键参数。最后，利用安装在伺服定位平台上的试验台对所提出的策略进行了实验验证，即使应用于与仿真中使用的不同的工件（WP）材料，也证实了其有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Multidirectional Scanning-Based Eddy Current Testing for Cavity and Crack Discrimination

Motivated by the significant disparity in the aspect ratio of cavity and crack defects, this article proposes a multidirectional scanning-based eddy current (EC) testing strategy for distinguishing between these two types by analyzing the characteristics of the perturbed EC and the corresponding magnetic flux density (MFD) fields. To enable efficient simulation and verification of the strategy, the distributed current source (DCS) method is enhanced by incorporating solution domain rotation, allowing accurate modeling of defects at arbitrary orientations. A symmetrical relationship among scanning images is also discussed to reduce the number of required simulations. The validity of the improved numerical model is demonstrated by comparing it with finite element analysis (FEA) results. Simulated scanning images for various defect orientations are then used to identify a key parameter that enables reliable classification. Finally, the proposed strategy is experimentally validated using a testbed mounted on a servo-positioning platform, confirming its effectiveness even when applied to workpiece (WP) materials different from those used in the simulations.

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来源期刊

IEEE Sensors Journal 工程技术-工程：电子与电气

CiteScore

7.70

自引率

14.00%

发文量

2058

审稿时长

5.2 months

期刊介绍： The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following: -Sensor Phenomenology, Modelling, and Evaluation -Sensor Materials, Processing, and Fabrication -Chemical and Gas Sensors -Microfluidics and Biosensors -Optical Sensors -Physical Sensors: Temperature, Mechanical, Magnetic, and others -Acoustic and Ultrasonic Sensors -Sensor Packaging -Sensor Networks -Sensor Applications -Sensor Systems: Signals, Processing, and Interfaces -Actuators and Sensor Power Systems -Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting -Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data) -Sensors in Industrial Practice