Application of improved threshold denoising based on wavelet transform to ultrasonic signal processing
-
摘要: 超声检测中回波信号信噪比低、易于被噪声淹没,小波变换是一种有效的提取缺陷回波的方法.建立了超声缺陷回波信号的数学模型,对基于小波变换的软、硬阈值消噪法作了改进,提出一种折中方法用于超声缺陷回波信号的去噪,同时以信噪比为目标函数对参数的选取也作了优化.仿真实验结果表明,改进方法非常适合用于超声信号的分析,能够很好地抑制噪声,它最大程度的发挥了小波软、硬阈值消噪法的优点,避免它们的缺点,使用该方法处理的信号相对于小波软、硬阈值消噪法在一定程度上改善了去噪的效果,提高了回波信号的信噪比.Abstract: The signal to noise ratio of ultrasonic echoes signal was low, the echoes signal was submerged easily in ultrasonic testing, and wavelet transforms was an effective method by which the flaw echoes can be extracted. The mathematics model of ultrasonic echoes signal was established, including the flaw echoes and the noise, the traditional soft and hard threshold denoising methods based on wavelet transform was ameliorated, and a middle course method was put forward for signal denoising in ultrasonic testing. At the same time the parameters selection was also optimized with the signal to noise ratio of ultrasonic flaw echoes signal as object function. The simulation experimental results showed that this method was fit for analyzing ultrasonic signal, and it can depress noises well. This method utilized the advantage of the soft and hard threshold denoising methods and avoided their disadvantage in the farthest. Compare to the traditional soft and hard threshold denoising methods, the denoising effect was improved in a certain extent, and the signal to noise ratio of ultrasonic flaw echoes signal was improved by using this method.
-
Key words:
- wavelet transforms /
- ultrasonic testing /
- signal to noise ratio /
- signal processing
-
[1] 崔锦泰. 小波分析导论[M]. 西安:西安交通大学出版社, 1995 Cui Jintai. Conspectus of wavelet analysis[M]. Xi’an:Xi’an Jiaotong University Press, 1995(in Chinese) [2] Mallat S. A theory for multiresolution signal decomposition:the wavelet representation[J]. IEEE Trans Pattern Anal and Machine Intell, 1989, 11(7):647~693 [3] Gustafsson M G, Stepinski T. Split spectrum algorithms rely on instantaneous phase information—a geometrical approach[J]. IEEE Trans UFFC, 1993, 40(6):659~665 [4] 张广明. 超声无损检测中的时频分析理论及应用研究 . 西安:西安交通大学机械工程学院, 1999 Zhang Guangming. The theory and application research of time-frequency analysis in ultrasonic nondestructive evaluation . Xi’an:School of Mechanical Engineering, Xi’an Jiaotong University, 1999(in Chinese) [5] Mallat S, Hwang W L. Singularity detection and processing with wavelets[J]. IEEE Trans on Information Theory, 1992, 38(2):617~643 [6] 范 中. 利用子波变换检测瞬时信号[J]. 电子学报, 1996, 24(1):79~82 Fan Zhong. Detect instantaneous signals using wavelet transform[J]. Journal of Electron, 1996, 24(1):79~82(in Chinese) [7] Donoho D L, Johnstone I M. Ideal spatial adaption by wavelet shrinkage[J]. Biometrika, 1994, 81:425~455 [8] Donoho D L, Johnstone I M. Adapting to unknown smoothness via wavelet shrinkage[J]. Journal of the American Statistical Association, 1995, 90:1200~ 1224 -
点击查看大图
计量
- 文章访问数: 3067
- HTML全文浏览量: 184
- PDF下载量: 944
- 被引次数: 0
下载:
