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首页> 外文期刊>Journal of Nondestructive Evaluation >Weldment Nondestructive Testing Using Magneto-optical Imaging Induced by Alternating Magnetic Field
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Weldment Nondestructive Testing Using Magneto-optical Imaging Induced by Alternating Magnetic Field

机译:使用交替磁场引起的磁光成像焊接无损检测

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摘要

This paper introduces an innovative Nondestructive testing (NDT) approach by using dynamic magneto-optical imaging (MOI) system to diagnose weld defects. MOI mechanism was explained by Faraday magneto-optical effect and magnetic domain theory. Two Q235 specimen MOI experiments based on excitation of permanent magnet and alternating electromagnet (alternating current driven electromagnet) were performed, thus the feasibility of MOI system for weld defects detection was verified and the relation between alternating magnetic field (AMF) and dynamic MO images was discussed as well. In this research, AMF of welded high-strength steel (HSS) weldment was excited by an alternating electromagnet, and dynamic MO images of HSS seam were acquired for weldment NDT. Finally, a pattern recognition method including three steps was proposed. Dynamic MO images were fused periodically and the features of fused images were extracted by principal component analysis. A classifier based on error back propagation (BP) neural network was established to identify these weld features. It proved that typical weld features such as incomplete penetration, sag, crack and no defect can be classified by the proposed method with an accuracy of 93.5%.
机译:本文介绍了一种通过使用动态磁光成像(MOI)系统来诊断焊接缺陷的创新无损检测(NDT)方法。由法拉第磁光效应和磁畴理论解释了MOI机制。进行基于永磁体和交替电磁铁(交流驱动电磁铁)激发的两个Q235样本MOI实验,因此验证了用于焊接缺陷检测的MOI系统的可行性,交替磁场(AMF)和动态MO图像之间的关系讨论也是如此。在本研究中,通过交替的电磁铁激发焊接的高强度钢(HSS)焊缝的AMF,并获得HSS接缝的动态MO图像用于焊接NDT。最后,提出了一种模式识别方法,包括三个步骤。动态MO图像定期融合,并通过主成分分析提取融合图像的特征。建立了基于错误反向传播(BP)神经网络的分类器以识别这些焊接功能。事实证明,典型的焊接特征如不完全穿透,下垂,裂缝,没有缺陷,可以通过提出的方法进行分类,精度为93.5%。

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