基于超声背散射信号递归定量分析的CFRP局部孔隙缺陷识别方法

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摘要以碳纤维复合材料（Carbon Fiber Reinforced Plastics, CFRP）的超声背散射信号为研究对象，创新性地提出运用递归定量分析（Recursive Quantitative Analysis,RQA）方法获得其信号特征，实现对材料局部孔隙缺陷的识别及评估。首先，对含有孔隙率为0.2%～5.92%的标准试块的超声背散射信号分别进行递归图分析和递归定量分析。结果表明，不同孔隙率试块所对应的递归图特征表现出明显差异，同时，RQA的特征量参数——递归率与递归熵均随孔隙率的增大而增大。然后，运用RQA方法对某未知孔隙率试块进行局部孔隙缺陷评估，基于上述结论，识别得到该试块中最有可能含有局部孔隙缺陷的区域。最后，剖开该未知孔隙率试块作微观形貌观察实验，实验发现该试块实际孔隙缺陷区域与RQA识别得到的结果相同，从而验证了递归定量分析方法用于CFRP局部孔隙缺陷识别的有效性。

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	王喆
	杨辰龙
	周晓军
	滕国阳

关键词 ： CFRP, 超声检测, 递归定量分析, 孔隙缺陷识别

Abstract：Taking ultrasonic backscattering signal of carbon fiber reinforced plastics (CFRP) as the study object, a new method called the recursive quantitative analysis (RQA) was proposed to analyze this signal’s features, and then realize CFRP local pore defect identification and evaluation.Firstly, recursive plot analysis (RPA) and RQA were performed for ultrasonic backscattering signals of 5 standard CFRP specimens with the porosity of 0.2%-5.94%, respectively.The results showed that feature parameters of RQA including recursive rate and recursive entropy increase with increase in porosity.Then, RQA was performed for another CFRP specimen with unknown porosity to evaluate local pore defects, and identify regions most probably containing local pore defects.Finally, a destructive test was performed for the unknown porosity specimen to do microscopic morphology observation.It was shown that the actual pore defect regions agree well with the results identified using RQA to verify the effectiveness of RQA for identifying CFRP local pore defects.

Key words： CFRP ultrasonic backscattered signal recursive quantitative analysis experiment

收稿日期: 2018-05-03 出版日期: 2019-10-28

引用本文:

王喆，杨辰龙，周晓军，滕国阳. 基于超声背散射信号递归定量分析的CFRP局部孔隙缺陷识别方法[J]. 振动与冲击, 2019, 38(21): 229-235.
WANG Zhe,YANG Chenlong, ZHOU Xiao Jun, TENG Guoyang. Identification method for CFRP local pore defects based on recursive quantitative analysis of ultrasonic backscattering signal. JOURNAL OF VIBRATION AND SHOCK, 2019, 38(21): 229-235.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2019/V38/I21/229

[1] 刘玲,张博明,王殿富,等. 聚合物基复合材料中孔隙率及层间剪切性能的实验表征[J]. 航空材料学报, 2006, 26(4): 115-118.
LIU Ling, ZHANG Bo Ming, WANG Dian Fu, et al. Experimental Characterization of Porosity and Interlaminar Shear Strength in Polymeric Matrix Composites[J]. Journal of Aeronautical Materials, 2006, 26(4):115-118.
[2] JEONG H, HSU D K. Experimental Analysis of Porosity Induced Ultrasonic Attenuation and Velocity Change in Carbon Composites[J].Ultrasonics, 1995, 33(3):195-203.
[3] MARTIN B G. Ultrasonic wave propagation in fiber-reinforced solids containing voids [J]. Journal of Applied Physics, 1977, 48(8): 3368-3373.
[4] 林莉，罗明，郭广平，等. 碳纤维复合材料孔隙率超声声阻抗法检测[J].复合材料学报，2009, 26(3): 105-110.
LIN Li, LUO Ming, GUO Guang Ping, et al. Ultrasonic Determination of Carbon Fiber Composite Porosity Using Acoustic impedance [J]. Acta Materiae Compositae Sinica, 2009, 26(3): 105-110.
[5] SMITH R A, NELSON L J, MIENCZAKOWSKI M J. Automated analysis and advanced defect characterisation from ultrasonic scans of composites [J]. Insight-Non-Destructive Testing and Condition Monitoring, 2009, 51(2): 82-87.
[6] 陈越超，杨辰龙，周晓军，等.基于反射系数建模的层状CFRP超声共振特性研究[J]. 振动与冲击, 2016, 35(12): 147-154.
CHEN Yue Chao, YANG Chen Long, ZHOU Xiao Jun,et al. Research of layered CFRP ultrasonic resonance characteristics based on reflection coefficient modeling [J]. Journal of Vibration and Shock, 2016, 35(12): 147-154.
[7] CHEN Y C, ZHOU X J, YANG C L. The ultrasonic evaluation method for the porosity of variable-thickness curved CFRP workpiece: using a numerical wavelet transform[J]. Nondestructive Testing & Evaluation, 2014, 29(3):195-207.
[8] KIM KB, HSU DK, DANIEL JB. Estimation of porosity content of composite materials by applying discrete wavelet transform to ultrasonic backscattered signal. NDT&E International. 2013;56(10):10 – 16.
[9] KARABUTOV A A, PODYMOVA N B. Nondestructive Porosity Assessment of CFRP Composites with Spectral Analysis of Backscattered Laserinduced Ultrasonic Pulses[J]. Journal of Nondestructive Evaluation,2013, 32: 315-324.
[10] ECKMANN J P, KAMPHORST S O, RUELLE D. Recurrence Plots of Dynamical Systems[J]. Europhysics Letters, 1987, 4(9):973-977.
[11] IOANA C, DIGULESCU A, SERBANESCU A. Recent Advances in Non-stationary Signal Processing Based on the Concept of Recurrence Plot Analysis [M]. Translational Recurrences. Springer International Publishing, 2014:75-93.
[12] 陈静,李亚安,王东海. 基于递归分析的水声信号处理[J]. 哈尔滨工程大学学报,2006,27(05):649-652.
CHEN Jing, LI Ya An, WANG Dong Hai. Underwater acoustic signal processing based on recurrence plot[J]. Journal of Harbin Engineering University, 2006, 27(5):649-652.
[13] LIANG Q Z, GUO X M, ZHANG W Y. Identification of Heart Sounds with Arrhythmia based on Recurrence Quantification Analysis and Kolmogorov Entropy[J]. Journal of Medical and Biological Engineering, 2015, 35(2):209-217.
[14] 肖涵,李友荣,吕勇. 基于递归定量分析与高斯混合模型的齿轮故障识别[J]. 振动工程学报,2011, 24(01):84-88.
XIAO Han, LI You Rong, LV Yong. Gear fault recognition based on recurrence quantification analysis and Gaussian mixture model[J]. Journal of Vibration Engineering, 2011, 24(1):84-88.
[15] BRANDT C. Recurrence Quantification Analysis for Non-Destructive Evaluation with an Application in Aeronautic Industry[C].World Conference on Non-Destructive Testing, 2016.
[16] BRANDT C. Recurrence Quantification Analysis as an Approach for Ultrasonic Testing of Porous Carbon Fibre Reinforced Polymers [M] Recurrence Plots and Their Quantifications: Expanding Horizons. Springer International Publishing, 2016.
[17] CARRIÓN A, MIRALLES R, LARA G. Measuring predictability in ultrasonic signals: an application to scattering material characterization [J]. Ultrasonics, 2014, 54(7):1904-11.
[18] 何晓晨，金士杰，林莉. 超声背散射信号递归定量分析无损表征CFRP孔隙分布仿真[J]. 复合材料学报，2018，35.
HE Xiao Chen, JIN Shi Jie, LIN Li. Simulation on non-destructive evaluation of CFRP void distribution with recurrence quantification analysis of ultrasonic back-scatter signals[J]. Acta Materiae Compositae Sinica, 2018, 35.
[19] TAKENS, F. Detecting strange attractors in turbulence [J]. Lecture Notes Mathematics, 1981:366-381.
[20] MARWAN N, ROMANO M C, THIEL M. Recurrence plots for the analysis of complex systems[J]. Physics Reports, 2007, 438(5):237-329.
[21] JR W C, ZBILUT J P. Dynamical assessment of physiological systems and states using recurrence plot strategies [J]. Journal of Applied Physiology, 1994, 76(2):965-73.
[22] KENNEL M B, BROWN R, ABARBANEL HDI. Determining embedding dimension for phase-space reconstruction using a geometrical construction [J].Physical Review A, 1992, 45: 3403–3411.
[23] FRASER A M, SWINNEY H L. Independent coordinates for strange attractors from mutual information [J]. Physical Review A, 1986,33:1134–1140
[24] BRANDT C. A State Space Approach for the Non-Destructive Evaluation of CFRP with Ultrasonic Testing [J], International Symposium on NDT in Aerospace, 2015.
[25]陈越超, 周晓军, 杨辰龙. 厚截面复合材料局域孔隙超声检测方法[J]. 农业机械学报, 2015, 46(6):372-378.
CHEN Yue Chao, ZHOU Xiao Jun, YANG Chen Long. Ultrasonic testing method for localized void defect identification in thick section composites[J]. Transactions of the Chinese Society for Agricultural Machinery, 2015, 46(6):372-378.