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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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

Received: 03 May 2018 Published: 28 October 2019

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	WANG Zhe
	YANG Chenlong
	ZHOU Xiao Jun
	TENG Guoyang

Cite this article:

WANG Zhe,YANG Chenlong,ZHOU Xiao Jun, et al. Identification method for CFRP local pore defects based on recursive quantitative analysis of ultrasonic backscattering signal[J]. JOURNAL OF VIBRATION AND SHOCK, 2019, 38(21): 229-235.

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http://jvs.sjtu.edu.cn/EN/ OR http://jvs.sjtu.edu.cn/EN/Y2019/V38/I21/229

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