超声C扫描的碳纤维复合材料缺陷检测及分析
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摘要
研究了动车转向架中碳纤维复合材料连接结构的超声扫描检测方法。采用超声C扫描方法采集缺陷信息,针对碳纤维复合材料连接构件建立手动超声成像检测系统,避免了常规超声自动扫描成像对不规则曲面结构适应性差的技术弊端,使检测过程实时、快速、柔性;在KSW熵方法基础上,基于几何建模,对三维模型建立二值化图像,编制计算程序得到缺陷覆盖面积和缺陷覆盖率,实现了构件三维图像中缺陷的可视化检测,避免了常规肉眼观测,提高了检测结果可信度。
In this paper,the ultrasonic scanning detection method of carbon fiber reinforced composite(CFRP) joints in the bogies of electric vehicles is studied. The defect information is collected by ultrasonic C-scan method,and a manual ultrasonic imaging detection system is established for carbon fiber reinforced composite connectors,which avoids the technical drawbacks of poor adaptability of conventional ultrasonic automatic scanning imaging to irregular surface structures,and makes the detection process real-time,fast and flexible. Based on the KSW entropy method,a geometric model is established and two three-dimensional models are built. The defect coverage area and the defect coverage rate are obtained by the computed program. The visualized defect detection in the three-dimensional image of the component is realized,which avoids the naked eye observation in the conventional method and improves the reliability of the detection results.
In this paper,the ultrasonic scanning detection method of carbon fiber reinforced composite(CFRP) joints in the bogies of electric vehicles is studied. The defect information is collected by ultrasonic C-scan method,and a manual ultrasonic imaging detection system is established for carbon fiber reinforced composite connectors,which avoids the technical drawbacks of poor adaptability of conventional ultrasonic automatic scanning imaging to irregular surface structures,and makes the detection process real-time,fast and flexible. Based on the KSW entropy method,a geometric model is established and two three-dimensional models are built. The defect coverage area and the defect coverage rate are obtained by the computed program. The visualized defect detection in the three-dimensional image of the component is realized,which avoids the naked eye observation in the conventional method and improves the reliability of the detection results.
引文
[1]沈真.轨道交通复合材料产业化之路——六论国产碳纤维产业化之路[J].新材料产业,2019(03):34-40.
[2]滕国阳,周晓军,杨辰龙,等.厚截面碳纤维复合材料远表面微缺陷超声检测[J].光学精密工程,2018,26(12):3108-3117.
[3]刘元林,赵国金,高帅帅,等.碳纤维复合材料缺陷无损检测方法研究[J].煤矿机械,2017,38(12):64-66.
[4]魏莹莹,安庆龙,蔡晓江,等.碳纤维复合材料超声扫描分层检测及评价方法[J].航空学报,2016,37(11):3512-3519.
[5]周正干,孙广开,李洋.先进无损检测技术在复合材料缺陷检测中的应用[J].航空制造技术,2016(04):30-35.
[2]滕国阳,周晓军,杨辰龙,等.厚截面碳纤维复合材料远表面微缺陷超声检测[J].光学精密工程,2018,26(12):3108-3117.
[3]刘元林,赵国金,高帅帅,等.碳纤维复合材料缺陷无损检测方法研究[J].煤矿机械,2017,38(12):64-66.
[4]魏莹莹,安庆龙,蔡晓江,等.碳纤维复合材料超声扫描分层检测及评价方法[J].航空学报,2016,37(11):3512-3519.
[5]周正干,孙广开,李洋.先进无损检测技术在复合材料缺陷检测中的应用[J].航空制造技术,2016(04):30-35.