复合材料科学与工程 ›› 2023, Vol. 0 ›› Issue (2): 94-100.DOI: 10.19936/j.cnki.2096-8000.20230228.012

• 应用研究 • 上一篇    下一篇

含夹杂缺陷碳纤维复合材料层压板的无损检测与评估研究

胡业发1,2, 孟由1,2, 张锦光1,2*, 邓伟1,2, 徐胜风1,2   

  1. 1.武汉理工大学 机电工程学院,武汉 430070;
    2.武汉理工大学 先进材料制造装备与技术研究院,武汉 430070
  • 收稿日期:2022-01-18 出版日期:2023-02-28 发布日期:2023-04-28
  • 通讯作者: 张锦光(1966—),男,博士,教授,主要从事复合材料零部件设计与制造技术方面的研究,cfrp_204@163.com。
  • 作者简介:胡业发(1961—),男,博士,教授,主要从事磁悬浮技术、复合材料零部件设计与制造方面的研究。
  • 基金资助:
    国家自然科学基金资助项目(51975435)

Nondestructive testing and evaluation of carbon fiber reinforced polymer laminates with inclusions

HU Yefa1,2, MENG You1,2, ZHANG Jinguang1,2*, DENG Wei1,2, XU Shengfeng1,2   

  1. 1. School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China;
    2. Institute of Advanced Material and Manufacturing Technology, Wuhan University of Technology, Wuhan 430070, China
  • Received:2022-01-18 Online:2023-02-28 Published:2023-04-28

摘要: 针对复合材料无损检测与评估问题,本文采用超声相控阵探伤仪对预埋夹杂缺陷的碳纤维复合材料层压板试样进行定量定位检测,并利用小波包分析和神经网络对缺陷进行定性识别。首先,在层压板中埋入聚四氟乙烯薄膜、CFRP片和塑料纸制备夹杂缺陷试样;然后,对试样进行超声相控阵检测,对得到的B、C扫图像进行缺陷定量定位评估,对得到的A扫信号进行缺陷定性评估。结果表明:通过对B、C扫图像进行分析,能准确分辨出缺陷所在的位置、尺寸及形状。利用小波包分析和BP神经网络对聚四氟乙烯薄膜、CFRP片和塑料纸三种夹杂缺陷进行识别,正确率为90.9%,对CFRP片和塑料纸两种缺陷进行识别,正确率达到100%,为以后能快速、准确地识别更多种类的缺陷奠定了良好的基础。

关键词: 夹杂缺陷, 碳纤维复合材料, 超声相控阵

Abstract: In the field of nondestructive testing and evaluation(NDT&E)of carbon fiber reinforced polymer(CFRP), phased array ultrasonic testing technique(PAUT)was usually used to detect the size and location of defects. Furthermore, wavelet packet transform and BP neural network were used to identify the type of defects. In this paper, three different types of CFRP laminates which contain defects such as teflon, CFRP sheet and plastic paper were made. Then, PAUT was used to detect these CFRP laminates with inclusions. The size and location of defects were evaluated from B and C scanning images, and the type of defects were evaluated from the A scan signals. The recognition rate could reach 90.9% in three types of defects. However, if only CFRP sheet and plastic paper were recognized, and the recognition rate could reach 100%.

Key words: inclusion, carbon fiber reinforced polymer, phased array ultrasonic testing technique

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