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    YANG Huimin, LI Chunpeng, YUAN Xin'an, YANG Tao, YANG Jianlong, LIU Ziqi, LIANG Dengbo. Defects intelligent recognition method of ACFM based on SSD[J]. Nondestructive Testing, 2022, 44(8): 25-30. DOI: 10.11973/wsjc202208005
    Citation: YANG Huimin, LI Chunpeng, YUAN Xin'an, YANG Tao, YANG Jianlong, LIU Ziqi, LIANG Dengbo. Defects intelligent recognition method of ACFM based on SSD[J]. Nondestructive Testing, 2022, 44(8): 25-30. DOI: 10.11973/wsjc202208005

    Defects intelligent recognition method of ACFM based on SSD

    • Aiming at the problems of difficulty in defect identification and low level of intelligence in traditional alternating current field measuremen (ACFM), this paper proposes a method for defects intelligent identification of ACFM based on single shot multibox detector (SSD). Different types of defect visualization imaging databases were established through simulation models and experiment, and data enhancement algorithms was used to expand the database to improve the generalization ability of the database. Defects intelligent identification method of ACFM based on SSD may lay a foundation for defects intelligent evaluation and defects judgment. Different types of defect testing experiments were carried out to verify the efficiency of the defects intelligent recognition method of ACFM based on SSD. The experimental results showed that the defects intelligent identification method of ACFM based on SSD could correctly identify different types of defects. The accuracy of the recognition was 98%, and the confidence of detecting the defects was above 90%. The method can provide support for the intelligent identification and evaluation of structural defects.
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