ZHANG Yubin, LIU Pengqian, CHEN Lina, HAN Yage, LIU Rui, XIE Jing, XU Changhang. YOLO v5-based Intelligent Detection for Eddy Current Pulse Thermography of Subsurface Defects in Coated Steel Structures[J]. Infrared Technology , 2023, 45(10): 1029-1037.
Citation: ZHANG Yubin, LIU Pengqian, CHEN Lina, HAN Yage, LIU Rui, XIE Jing, XU Changhang. YOLO v5-based Intelligent Detection for Eddy Current Pulse Thermography of Subsurface Defects in Coated Steel Structures[J]. Infrared Technology , 2023, 45(10): 1029-1037.

YOLO v5-based Intelligent Detection for Eddy Current Pulse Thermography of Subsurface Defects in Coated Steel Structures

  • Subsurface defects in coated steel structures, such as corrosion, steel matrix cracks, and coating debonding, affect the overall structural performance and accelerate the degradation of coating systems. Therefore, this study proposes a YOLO v5-based intelligent detection method for pulsed eddy current thermography of subsurface defects in coated steel structures. This method can automatically detect subsurface defects in coated steel structures without removing the coating, which is of significant importance for engineering applications. The proposed method intelligently detects subsurface defects such as corrosion, cracks, and debonding in coated steel structures without removing the coating. The detection results show that the proposed method can accurately identify and classify four types of subsurface defects in coated steel structures: cracks in the steel matrix, debonding, severe quality loss (corrosion pits and corrosion abrasion), and slight quality loss (thin corrosion layers); the four defect types can be detected with accuracies of 96%, 97%, 95%, and 93%, respectively, while meeting real-time inspection requirements.
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