文章摘要
郑善朴,陆铭慧,王俊东,罗艺,董俊冬.多层结构中脱粘缺陷的超声检测方法[J].,2019,38(1):134-144
多层结构中脱粘缺陷的超声检测方法
Ultrasonic testing method for debonding defects in multilayer structures
投稿时间:2018-04-28  修订日期:2018-12-26
中文摘要:
      固体火箭发动机多层装药结构中的脱粘类型、位置和尺寸决定了其对整体安全性能构成的威胁程度。该文研究了多层结构中脱粘缺陷的超声检测方法,通过对不同脱粘缺陷超声脉冲回波的特征分析与统计,实现缺陷的定性、定位和定量。首先,采集含有多类脱粘缺陷的粘接结构的超声脉冲回波信号,分析信号中主能量波包所代表的声程,提取五种声程的波峰时刻和幅值作为特征值,组建已知脱粘类型训练样本并输入至 BP神经网络,实现特征值域到类别域的非线性映射,即脱粘类型分类;其次,采用阈值法确定缺陷的界面位置;最后,提出分段线性插值 -相关性定量法将待检测缺陷的定量结果缩小到 ±2 mm 以内。该文利用 COMSOL 有限元仿真和实验操作验证了多层粘接结构中脱粘缺陷的定性、定位和定量方法的可行性和可靠性。
英文摘要:
      The type, location and size of the debonding defects in a multi-layer charge structure of a solid rocket motor determines its threat degree to overall safety performance. In this paper, the ultrasonic detection method of debonding defects in multilayer structure is studied. According to the analysis and statistics of ultrasonic pulse echoes of different debonding defects, the judge of type, position and area of defects is realized. Firstly, the ultrasonic pulse echo signals of the bonding structure containing multiple types of debonding defects are acquired, the sound paths represented by the main energy wave packet in the signal are analyzed, and the peak moments and amplitudes of the five sound paths are extracted as the eigenvalues to construct the known debonding defects’ training samples and input the samples into the BP neural network to realize the nonlinear mapping from the eigenvalue domain to the category domain, equivalent to the classification of debonding defects. Secondly, the threshold method is used to determine the interface position of the defect. Finally, the segmented linear interpolation-correlation is proposed to reduce the quantitative result of defects to be detected to within ±2 mm. In this paper, the feasibility and reliability of the judge method of type, position and area for debonding defects in multilayer bonded structures are verified by COMSOL finite element simulation and experimental operations.
DOI:10.11684/j.issn.1000-310X.2019.01.018
中文关键词: 脱粘缺陷,BP神经网络,超声检测,阈值定位,线性插值
英文关键词: Debonding defect, BP neural network, Ultrasonic testing, Threshold positioning, Linear interpolation
基金项目:
作者单位E-mail
郑善朴 南昌航空大学无损检测重点实验室 1569729328@qq.com 
陆铭慧 无损检测教育部重点实验室(南昌航空大学) lumara@163.com 
王俊东 天津市交通科学研究院天津 270679481@qq.com 
罗艺 无损检测教育部重点实验室(南昌航空大学) 1298656327@qq.com 
董俊冬 无损检测教育部重点实验室(南昌航空大学) 1905035220@qq.com 
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