摘要
针对孔隙率接近0的小孔隙率碳纤维复合材料(Carbon Fiber Reinforced Composite,CFRP)的富树脂检测需求,提出富树脂超声检测技术。对超声检测信号中的噪声消除方法、衰减抑制方法和富树脂检测的多视图成像技术进行研究,并开发小孔隙率CFRP富树脂超声检测软件。首先提出共振频率估计方法,通过低通滤波抑制高频随机噪声。其次根据频率差异,应用变分模态分解算法分离并消除共振结构噪声,提取低频成分。该低频成分包括表面回波、底面回波、富树脂反射信号和由层间反射信号、材料散射噪声等构成的相干噪声。再次,引入瞬时幅值比修正低频成分的幅值衰减并描述被检测小孔隙率CFRP的局部反射能力。最后,应用Otsu多阈值方法自适应获得富树脂识别的阈值,消除相干噪声的影响,完成富树脂识别。进一步对小孔隙率CFRP的超声检测结果进行多视图成像,在三维视图、C扫描视图和B扫描视图内识别富树脂。结果表明:变分模态分解的分量数为2,Otsu多阈值的类别数为3时,能够准确识别小孔隙率CFRP超声检测信号中的富树脂反射信号;采用0.15作为多视图成像的阈值,可简洁有效地描述富树脂在小孔隙率CFRP中的分布。
To satisfy the demand of rich-resin defect detection in the so-called low-porosity carbon fiber reinforced composite(CFRP)with porosity close to zero,an ultrasonic testing methodology was proposed in this article.The denoising methods,attenuation suppression method,and3D imaging technology for rich-resin identification are investigated,and low-porosity CFRP rich-resin detection software was developed.The rich resin was detected in four steps.First,the resonant frequency was estimated,and the high-frequency stochastic noise was suppressed.Second,variational mode decomposition(VMD)was used to separate the resonant structure noise and extract the low-frequency component.The low-frequency component consisted of the front-wall echo,back-wall echo,rich-resin reflection signal,and remaining coherent noise made up of the interlayer reflection signals and material scattering noise.Third,the instant amplitude ratio was introduced to correct the envelop attenuation of the low-frequency component and describe the local reflectivity of the low-porosity CFRP.Finally,the multi-threshold Otsu method was used to search the threshold of the rich-resin detection,resulting in the elimination of interference and finishing the detection of rich resin.Further,multi-view imaging was performed on the test results,and the rich resin was identified in the3D,C-scan,and B-scan imaging processes.The experimental results show that when the VMD mode was set to two and the classes in the multi-threshold Otsu method are set to three,a rich-resin reflection signal can be detected.When the threshold in the multi-view imaging is set to0.15,the rich resin can be effectively characterized.
作者
曾祥
杨辰龙
周晓军
滕国阳
ZENG Xiang;YANG Chen-long;ZHOU Xiao-jun;TENG Guo-yang(State Key Lab of Fluid Power and Mechatronic Systems, College of Mechanical Engineering,Zhejiang University, Hangzhou 310027, China;CRRC Zhuzhou Institute Co. Ltd., Zhuzhou 412001, China)
出处
《光学精密工程》
EI
CAS
CSCD
北大核心
2018年第11期2732-2743,共12页
Optics and Precision Engineering
基金
浙江省自然科学基金资助项目(No.LY18E050002)
中央高校基本科研基金资助项目(No.2018QNA4001)
关键词
小孔隙率碳纤维复合材料
富树脂
变分模态分解
Otsu多阈值
多视图成像
软件开发
low-porosity Carbon Fiber Reinforced Plastic(CFRP)
rich-resin
variational mode decomposition
multi-threshold Otsu method
multi-view imaging
software development