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分裂基算法在管道腐蚀超声内检测中的应用 被引量:2

The application of split-radix algorithm in pipeline corrosion ultrasonic inner inspection
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摘要 管道腐蚀内检测中超声回波信号具有周期性特点,功率谱估计是重要的数据处理方法之一。基于分裂基的FFT算法具有较小的乘法次数和加法次数,且算法结构较好。采用频率抽取分裂基2/4 FFT算法对管道腐蚀超声内检测回波信号进行了处理.得到管道壁厚数据,经分裂基FFT算法和基2 FFT算法比较,分裂基FFT算法明显减少了数据处理时间,提高了检测速度。理论分析和实验结果表明,该分裂基算法精度高,数据处理速度快,满足管道腐蚀内检测的实时性要求。 According to the periodic characteristic of the echo signal of the ultrasonic inner inspection on pipeline corrosion, the application of power spectrum estimation to digital ultrasonic thickness measurement has been researched. An effective method based on split radix FFT( Fast Fourier Transform) has been put forward. A frequency abstraction split radix-2/4 FFT algorithm is introduced. Comparison of split-radix FFT with radix-2 FFT is also made. The split-radix FFT algorithm can shorten the time of program executing and enhance the speed of inspection. The test shows that the method suitable for inner inspection of pipeline corrosion.
出处 《计算机与应用化学》 CAS CSCD 北大核心 2007年第4期515-518,共4页 Computers and Applied Chemistry
关键词 超声 管道检测 功率谱估计 分裂基算法 ultrasonic, pipeline inspection, power spectrum estimation, split-radix FFT
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  • 1陆俭伟,吕干霖,黎宗潼,杨松章.管材超声探伤中缺陷模糊模式识别方法研究[J].声学学报,1996,21(1):20-28. 被引量:7
  • 2Corts C, Vapnik V. Support Vector Networks[J]. Machine Learning. 1995, 20: 273- 297.
  • 3VAPNIC V. An Overview of Statistical Learning Theory[J].IEEEE Transaction on Neural Networks. 1999, 10(5): 988-999.
  • 4Scholkopf B, Sung K- K, Burges C et al. Comparing Support Vector Machines with Gaussian Kernels to Radial Basis Function Classifiers. IEEE Trans. on Signal Processing,1997, 45(11): 2758-2765.
  • 5Seungkoo Lee, George Vachtsevanos. An Application of Rough Set Theory to Defect Detection of Automotive glass[J]. Mathematics and Computers in Simulation, 2002, 60(3 - 5): 225 - 231.
  • 6Stanker, Rosenfeld. Hierarchical Representation of Waveform[J]. IEEE Trans on PAMI, 1998(1): 73 - 82.
  • 7K. Hwang, S. Mandayam, S.S. Udpa, et al. Characterization of Gas Pipeline Inspection Signals Using Wavelet Basis Function Neural Networks[ J]. NDT&E Intern Ational,2000,33(8):531-545.
  • 8Liu Z, Tsukada K, Hanasaki K. One- dimensional Eddy Current Mufti- Frequency Data Fusion: a Multi- resolution Analysis Approach[J]. INSIGHT, 1998, 40(4): 286-289.
  • 9Mina M, Udpa SS, Udpa I, et al. A New Approach for Practical Two Dimensional Data Fusion Utilizing a Single Eddy Current probe[J]. Review of Progress in Quantitative Nondestructive Evaluation, 1997, 16: 749-754.
  • 10Bartels KA, Fisher JL. Optimal Multidimensional Multifrequency Eddy Current Mixing Techniques [ J ]. Review of Progress in Quantitative Nondestructive Evaluation, 1996,15: 393 - 400.

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  • 1唐建,戴波.基于功率谱估计的管道超声测厚研究[J].北京石油化工学院学报,2005,13(1):18-22. 被引量:4
  • 2颜力,廖柯熹,蒙东英,王靖,曾润奇,王晓刚.管道最大腐蚀坑深的极值统计方法研究[J].石油工程建设,2007,33(3):1-4. 被引量:15
  • 3戴波,盛沙,唐建,田小平.改进的Burg最大熵法在管道检测中的应用[J].传感技术学报,2007,20(6):1416-1419. 被引量:6
  • 4WangZhongwci(q<,巍1.Research on key technology of Intelligentcontrol for autonomous subsea in-pipe robot [D]. Shanghai: Shanghai Jiao Tong University, 2010.
  • 5Campbell W, Swingler D N. Frequency estimation performance of several weighted burg algorithms [J]. 1EEE Trans on Signal Processing, 1993, 53(3): 1237-1247.
  • 6Demirli R, Saniie J. Model-based estimation of ultrasonic echoes( Ⅰ ): Analysis and algorithms [J]. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 2001, 48(3): 787-802.
  • 7Demirli R, Saniie J. Model-based estimation of ultrasonic echoes( II ): Non-destructive evaluation applications [J]. 1EEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 2001, 48(3): 803-811.
  • 8TangJian(唐建).Ultrasonic inner inspection technique research onlong distance pipeline[D]. Beijing: Beijing University of Chemical Technology, 2005.
  • 9Kay S M, Marple S L. Spectrum analysis-a modem perspective [J] Proc. IEEE, 1981, 68(11): 1380-1419.
  • 10Burg J E A new analysis technique for time series data[R] Netherlands: NATO, 1968.

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