Gao Xiangdong, Li Guohua, Chen Ziqin, Lan Chongzhou, Li Yanfeng, Gao Perry P
Appl Opt. 2018 Jul 20;57(21):6110-6119. doi: 10.1364/AO.57.006110.
A magneto-optical (MO) imaging nondestructive testing (NDT) method for ferromagnetic weldments has been proposed. The mechanism of MO imaging was analyzed by the Faraday MO effect, magnetic domain theory, and magnetic hysteresis loops. Then, the relation between MO images and their corresponding excitation voltages was investigated. To explain the MO imaging system, magnetic domain distribution models of various welding states were established. These models are excited by two kinds of magnetic fields. One is the external magnetic field (H), and the other is a weldment remanence field (M) after H is removed. Relations of magnetic field excitation voltages, thickness of the spacer plate, and the corresponding MO images were also researched, which indicates the proposed NDT method can be used to detect incomplete penetration defect. Then, an experiment that uses MO imaging to detect the defects of high-strength steel (HSS) weldment was performed. Experimental results proved this method can detect crack, sag, and incomplete penetration of weldment effectively. Finally, a series of welded joint MO images of the HSS weldment were captured, which are used as the input data of the defect classification model established by using principal component analysis and an error backpropagation neural network, and the accuracy of this classification model can achieve 92.8%.
提出了一种用于铁磁焊件的磁光（MO）成像无损检测（NDT）方法。通过法拉第磁光效应、磁畴理论和磁滞回线分析了磁光成像的机理。然后，研究了磁光图像与其相应激励电压之间的关系。为了解释磁光成像系统，建立了各种焊接状态的磁畴分布模型。这些模型由两种磁场激发。一种是外部磁场（H），另一种是去除H后的焊件剩磁场（M）。还研究了磁场激励电压、隔板厚度与相应磁光图像之间的关系，这表明所提出的无损检测方法可用于检测未焊透缺陷。然后，进行了使用磁光成像检测高强度钢（HSS）焊件缺陷的实验。实验结果证明该方法能够有效检测焊件的裂纹、凹陷和未焊透。最后，采集了一系列高强度钢焊件的焊接接头磁光图像，将其作为利用主成分分析和误差反向传播神经网络建立的缺陷分类模型的输入数据，该分类模型的准确率可达92.8%。
