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基于时间反转算法和归一化小波能量熵的套筒灌浆缺陷检测
          
Defect detection for grouting sleeve based on time reversal algorithm and normalized wavelet energy entropy

摘    要
灌浆套筒灌浆缺陷严重削弱预制装配式结构性能,需要发展有效的检测方法。在灌浆套筒表面黏贴压电陶瓷传感器,对直接接收信号进行时间反转处理,得到具有高信噪比的超声聚焦信号,借助快速傅里叶变换和归一化小波能量熵算法,对水平连接和竖向连接形式的套筒不同灌浆程度的聚焦信号进行频谱及能量分析。结果表明,相对于直接接收信号,经过时间反转算法处理的聚焦信号将幅值提高了25. 4 dB,聚焦信号更适用于复杂连接环境下的套筒灌浆缺陷检测;基于归一化小波能量熵的缺陷评价指标可以定量反映灌浆套筒内部缺陷程度。
标    签 灌浆套筒   缺陷检测   时间反转   小波能量熵   压电陶瓷   grouting sleeve   defect detection   time reversal   wavelet energy entropy   piezoelectric ceramic  
 
Abstract
Grouting defects of grouting sleeve reduce the seismic performance of prefabricated assembled structures and effective detection methods need to be developed. Piezoelectric ceramic transducers are pasted on the surface of the grouting sleeve, and the directly received signals are processed by the time-reversal algorithm to obtain high signal to noise ratio ultrasonic focused signals. Quantitative analysis of the spectral characteristics and energy of the focused signals with different grouting degrees of horizontal and vertical connection sleeves are carried out using the fast Fourier transform and normalized wavelet energy entropy algorithm. The results showed that: compared to the directly received signal, the time-reversed focused signal increases the amplitude by 25. 4 dB, indicating that the focused signal is more suitable for defect detection in the complex connection environment of grouting sleeves. The defect evaluation index based on the normalized wavelet energy entropy method can quantitatively reveal the degree of grouting defects.

中图分类号 P375 TG115.28   DOI 10.11973/wsjc202308001

 
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所属栏目 混凝土无损检测专题

基金项目 教育部重点实验室开放基金(CPCSME2022-02)

收稿日期 2023/4/25

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备注陈冬冬(1992-),男,博士,副教授,主要从事结构健康监测的相关工作

引用该论文: CHEN Dongdong,ZHANG Zihang,WANG Ying,SUN Yu,DONG Zhiqiang,ZHU Hong. Defect detection for grouting sleeve based on time reversal algorithm and normalized wavelet energy entropy[J]. Nondestructive Testing, 2023, 45(8): 1~7
陈冬冬,张子航,汪莹,孙瑜,董志强,朱虹. 基于时间反转算法和归一化小波能量熵的套筒灌浆缺陷检测[J]. 无损检测, 2023, 45(8): 1~7


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