• Laser & Optoelectronics Progress
  • Vol. 58, Issue 16, 1610002 (2021)
Qiongying Kong1、2, Bo Ye1、2、*, Weiquan Deng3, Chen Chen1、2, and Danhong Wang1、2
Author Affiliations
  • 1Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, Yunnan 650500, China
  • 2Yunnan Key Laboratory of Artificial Intelligence, Kunming, Yunnan 650500, China
  • 3Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming, Yunnan 650500, China
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    DOI: 10.3788/LOP202158.1610002 Cite this Article Set citation alerts
    Qiongying Kong, Bo Ye, Weiquan Deng, Chen Chen, Danhong Wang. Probability-Based Diagnostic Imaging Method of Fatigue Damage for Carbon Fiber Reinforced Plastic Based on ToF Damage Factor[J]. Laser & Optoelectronics Progress, 2021, 58(16): 1610002 Copy Citation Text show less

    Abstract

    The formation of carbon fiber reinforced plastic (CFRP) fatigue damage is complicated, and fatigue damage continues to expand over time and as the load increases. Focusing on the problems associated with existing probability-based diagnostic imaging methods, i.e., high misjudgment rate of damage location, low damage imaging clarity, and poor visualization effect, this paper proposes a CFRP fatigue damage-probability diagnostic imaging method based on a time-of-flight (ToF) damage factor. The method uses a new damage factor to improve existing probability-based diagnostic imaging methods, and studies the fatigue damage of CFRP plates under different fatigue loading cycles. Experimental results demonstrate that, compared with existing methods, the damage location error of the method is reduced by at least 49.85%, which provides a new method for the accurate quantitative analysis of CFRP fatigue damage.
    Qiongying Kong, Bo Ye, Weiquan Deng, Chen Chen, Danhong Wang. Probability-Based Diagnostic Imaging Method of Fatigue Damage for Carbon Fiber Reinforced Plastic Based on ToF Damage Factor[J]. Laser & Optoelectronics Progress, 2021, 58(16): 1610002
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