Application of fractal theory on identification of near-surface defects in

doi:10.11772/j.issn.1001-9081.2014.11.3365

Journal of Computer Applications ›› 2014, Vol. 34 ›› Issue (11): 3365-3368.DOI: 10.11772/j.issn.1001-9081.2014.11.3365

Application of fractal theory on identification of near-surface defects in

CHEN Shili,HUANG Yuqiu,ZHANG Hui,YANG Xiaoxia,GUO Wei

State Key Laboratory of Precision Measurement Technology and Instrument (Tianjin University), Tianjin 300072, China

Received:2014-05-29 Revised:2014-07-01 Online:2014-12-01 Published:2014-11-01
Contact: CHEN Shili
Supported by:
A study on capacitive micromachined ultrasonic transducer with

分形理论在近表面缺陷超声A扫检测中的应用

陈世利,黄玉秋,张慧,杨晓霞,郭薇

精密测试技术及仪器国家重点实验室(天津大学),天津 300072

通讯作者: 陈世利
作者简介:
陈世利(1973-),男,湖北鄂州人,副教授,博士,主要研究方向:石油储运安全、智能传感器、超声无损检测;黄玉秋(1988-),女(壮族),广西钦州人,硕士研究生,主要研究方向:超声无损检测;张慧(1975-),女,吉林临江人,副教授,博士,主要研究方向: 岛型振动膜电容式微超声传感器、无损检测;杨晓霞(1986-),女,河北衡水人,博士研究生,主要研究方向:超声无损检测;郭薇(1989-),女,山西忻州人,硕士研究生,主要研究方向:碳纤维复合材料检测。
基金资助:
国家自然科学基金资助项目

Abstract

Abstract:

The near-surface defects are hard to identify in ultrasonic phased array Non-Destructive Testing (NDT), thus a new intelligent identification method based on fractal theory was proposed to solve this problem. A box-counting dimension algorithm based on linear interpolation was described to calculate the box-counting dimension of 140 groups of ultrasonic A-Scan time domain signals. Then the distribution of box-counting dimension was analyzed using the statistical method. The experimental results show that ultrasonic A-Scan signal is obviously fractal and it is effective to analyze the A-Scan signal with the fractal approach. This method has the potential to identify near-surface defects since the values of the box counting dimension of defective signals are different from those of defective signals. As a result, the detection rate of near-surface defects can be improved and the omission rate caused by man-made factors can be reduced in ultrasonic phased array automatic testing.

摘要：

针对超声相控阵无损检测(NDT)中近表面缺陷识别困难的问题,提出一种基于分形理论的近表面缺陷智能识别方法。运用基于线性插值的盒计数维数算法,计算140组超声A扫(A-Scan)信号的盒计数维数,并运用统计的方法详细分析其分布情况。实验结果表明超声A-scan信号具有分形特性,分形理论可应用于A-Scan信号分析;而且有无缺陷信号的盒维数分布区间差异明显,盒维数可作为A-Scan信号的特征识别近表面缺陷。在超声相控阵自动化检测中,运用分形理论能提高近表面缺陷的检出率，减少人为因素引起的漏检。

CLC Number:

TP391

CHEN Shili HUANG Yuqiu ZHANG Hui YANG Xiaoxia GUO Wei. Application of fractal theory on identification of near-surface defects in[J]. Journal of Computer Applications, 2014, 34(11): 3365-3368.

陈世利黄玉秋张慧杨晓霞郭薇. 分形理论在近表面缺陷超声A扫检测中的应用[J]. 计算机应用, 2014, 34(11): 3365-3368.

References

[1]DRINKWATER B W, WILCOX P D. Ultrasonic arrays for non-destructive evaluation: a review[J]. NDT and E International, 2006, 39(7): 525-541.
[2]YING C. Ultrasonic[M]. Beijing: Science Press, 1990:296-299.(应崇福. 超声学[M]. 北京: 科学出版社, 1990: 296-299.)
[3]XIA J. Study on embedded ultrasonic nondestructive testing system with high performance and its application[D]. Hangzhou: Zhejiang University, 2012.(夏军建. 高性能嵌入式超声无损检测系统及其应用的研究[D]. 杭州: 浙江大学, 2012.)
[4]PRADO V T, HIGUTI R T, KITANO C, et al. Lamb mode diversity imaging for non-destructive testing of plate-like structures[J]. NDT and E International, 2013, 59: 86-95.
[5]DONSKOY D, SUTIN A, EKIMOV A. Nonlinear acoustic interaction on contact interfaces and its use for nondestructive testing[J]. NDT and E International, 2001, 34(4): 231-238.
[6]VIEIRA A P, MOURA E P, GONCALVES L L, et al. Characterization of welding defects by fractal analysis of ultrasonic signals[J]. Chaos, Solitons and Fractals, 2008, 38(3): 748-754.
[7]ZHAN X, JIN S. A fractal-based flaw feature extraction method for ultrasonic phased array nondestructive testing[C]// ICMA 2009: Proceedings of the 2009 International Conference on Mechatronics and Automation. Piscataway: IEEE Press, 2009.
[8]BIANCIARDI G, BISOGNO S, BERTOLDI I, et al. Fractal dimension of bone texture in radiographs correlates to ultrasound broadband attenuation T-score[J]. Clinical and Experimental Rheumatology, 2013, 31(3): 389-393.
[9]de MOURA E P, NORMANDO P G, GONALVES L L, et al. Characterization of cast iron microstructure through the statistical fluctuation and fractal analysis of ultrasonic backscattered signal[J]. AIP Conference Proceedings, 2011, 1335(1): 1104-1111.
[10]ZHAO J, LEI L, PU X. Fractal theory and its application in signal processing[M]. Beijing: Tsinghua University Press, 2008: 1-21.(赵健, 雷蕾, 蒲小勤. 分形理论及其在信号处理中的应用[M]. 北京: 清华大学出版社, 2008: 1-21.)
[11]MANDDELBROT B. The fractal geometry of nature[M]. New York: W H Freeman and Company, 1982.
[12]RAISUTIS R, TUMSYS O, KAZYS R, et al. Application of time-frequency analysis in the case of ultrasonic imaging in a background of structural noise[J]. Insight — Non-Destructive Testing and Condition Monitoring, 2007, 49(11): 634-640.
[13]NI Z, NI L, YANG-GE Z. Application of fractal in case base maintenance[J]. Journal of Computer Applications, 2009, 29(6): 1598-1600, 1604.(倪志伟, 倪丽萍, 杨葛钟啸. 分形技术在案例库维护中的应用[J]. 计算机应用, 2009, 29(6): 1598-1600, 1604.)
[14]ZHU H, JI C. Fractal theory and its application[M]. Beijing: Science Press, 2011: 1-53.(朱华, 姬翠翠. 分形理论及其应用[M]. 北京: 科学出版社, 2011: 1-53.)

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Application of fractal theory on identification of near-surface defects in

分形理论在近表面缺陷超声A扫检测中的应用

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