Abstract
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%.
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