中国机械工程 ›› 2023, Vol. 34 ›› Issue (19): 2327-2332.DOI: 10.3969/j.issn.1004-132X.2023.19.007

• 机械基础工程 • 上一篇    下一篇

碳纤维复合材料制孔结构超声无损检测及评价

杨亮;蔡桂喜;刘芳;李建奎   

  1. 中国科学院金属研究所,沈阳,110016
  • 出版日期:2023-10-10 发布日期:2023-11-02
  • 通讯作者: 蔡桂喜(通信作者),男,1965年生,研究员。研究方向为无损检测与评价。发表论文30余篇。E-mail:gxcai@imr.ac.cn。
  • 作者简介:杨亮 ,男,1992年生,硕士研究生。研究方向为材料无损检测与评价。E-mail:lyang@imr.ac.cn。

Ultrasonic Nondestructive Testing and Evaluation of CFRP Hole-making Structures

YANG Liang;CAI Guixi;LIU Fang;LI Jiankui   

  1. Institute of Metal Research,Chinese Academy of Sciences,Shenyang,110016
  • Online:2023-10-10 Published:2023-11-02

摘要: 为实现碳纤维复合材料制孔结构的无损检测与评价,基于超声波脉冲反射法原理,研制了便携式超声螺旋C扫描检测仪器,建立了制孔结构质量评价的数学模型。通过对人工试样和在役孔进行超声波检测试验,基于静矩原理确定了不规则超声C扫描图像形心,提取了图像中过形心的最长轴线,计算了最长轴线与孔的公称直径比值(RLN)以评价制孔质量。结果表明,该检测方法可大幅提高检测速度;分层缺陷测量值与实际值相当;检测结果与在役孔的实际形貌具有一致性;RLN因子可准确评价多种形式的分层缺陷。

关键词: 碳纤维复合材料, 制孔结构, 超声检测, 螺旋扫查, 评价因子模型

Abstract: In order to realize the nondestructive testing and evaluation of the hole-making structure of CFRP, a portable ultrasonic C-scan tester was developed based on the principle of ultrasonic pulse reflection method, a spiral scanning method was proposed, and a mathematical model for the quality evaluation of the hole-making structures was established. By performing ultrosonic inspection tests on artificial specimens and in-service pores, based on the static distance principle, the centroid of the irregular ultrasonic C-scan image was determined. The longest axis of the centroid was extracted, and the ratio of the longest axis to the nominal diameter of the hole(RLN) was calculated to evaluate the quality of the holes. The results show that the method may greatly improve the detection speed. The measured values of stratified defect are equivalent to the actual ones. The results are consistent with the actual morphologies of in-service pores. The RLN factor may accurately evaluate various types of stratification defects.

Key words:  , carbon fiber reinforced plastics(CFRP), hole-making structure, ultrasonic detection, spiral scan, evaluation factor model

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