• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2021, Vol. 57 ›› Issue (14): 177-187.doi: 10.3901/JME.2021.14.177

• 仪器科学与技术 • 上一篇    下一篇

扫码分享

基于PCA-WHMM的超声漏表面波频域合成孔径成像研究

胡宏伟1,2, 周刚1, 沈晓炜1, 徐晓强1,2   

  1. 1. 长沙理工大学汽车与机械工程学院 长沙 410114;
    2. 机械装备高性能智能制造关键技术湖南省重点实验室 长沙 410114
  • 收稿日期:2020-08-25 修回日期:2021-03-05 出版日期:2021-09-15 发布日期:2021-09-15
  • 通讯作者: 胡宏伟(通信作者),男,1980年出生,博士,教授。主要研究方向为无损检测及信号处理、机电装备智能测控技术。E-mail:hu_hongwei@foxmail.com
  • 作者简介:周刚,男,1997年出生。主要研究方向为超声无损检测。E-mail:adjustrun@foxmail.com
  • 基金资助:
    国家自然科学基金(52075049)和湖南省自然科学杰出青年基金(2020JJ2028)资助项目

PCA-WHMM-based Frequency-domain Synthetic Aperture Focusing Imaging Using Ultrasonic Leaky Rayleigh Waves

HU Hongwei1,2, ZHOU Gang1, SHEN Xiaowei1, XU Xiaoqiang1,2   

  1. 1. College of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha 410114;
    2. Hunan Provincial Key Laboratory of Intelligent Manufacturing Technology forHigh-Performance Mechanical Equipment, Changsha 410114
  • Received:2020-08-25 Revised:2021-03-05 Online:2021-09-15 Published:2021-09-15

摘要: 超声漏表面波可用于检测表面或近表面缺陷,其非接触检测的优点易于实现自动化检测。但由于波型转换与传播衰减,漏表面波的回波幅值较小,不利于缺陷检测和成像。仿真分析了漏表面波的传播特性及缺陷回波特征,应用主成分分析分离回波信号中的干扰波,再利用小波域隐马尔可夫模型算法分离整段信号的系统噪声,联合两种方法提取漏表面波信号中的缺陷信息,最后通过频域合成孔径算法对漏表面波扫查数据进行了高分辨率图像重建。结果表明,相比于传统B扫成像,基于PCA-WHMM的超声漏表面波F-SAFT方法在回波信号平均信噪比上提高了10.05 dB,平均成像误差降低了26.3%,为金属表面及近表面缺陷检测提供了一种有效方法。

关键词: 超声无损检测, 漏表面波, 主成分分析, 小波域隐马尔可夫模型, 频域合成孔径

Abstract: Ultrasonic leaky Rayleigh waves can be used to detect surface and sub-surface defects. The advantage of non-contact detection makes it easy to realize automatic inspection. However, due to the waveform conversion and propagation attenuation, the echo amplitude of leaky Rayleigh waves is quite small, which is not conducive for defect detection and imaging. It simulates and analyzes the propagation characteristics and defect echo characteristics of the leaky Rayleigh waves, applies principal component analysis (PCA) to separate the interference waves from the echo signal, then uses the Wavelet-based hidden Markov models (WHMM) algorithm to separate the systematic noise from the whole signal, combines the two methods to extract the defect information in the leaky Rayleigh waves signal, and finally uses the frequency-domain synthetic aperture focusing technology(F-SAFT) to conduct a high resolution ratio reconstruction for the data of the leaky Rayleigh waves scanning. The results show that compared with the conventional B-scan imaging, the PCA-WHMM-based ultrasonic leaky Rayleigh waves F-SAFT imaging method improves the SNR of the echo signal by 10.05 dB and reduces the average imaging error by 26.3%,which provides an effective method for the detection of metal surface and sub-surface defects.

Key words: ultrasonic nondestructive testing, leaky Rayleigh waves, principal component analysis, wavelet-based hidden Markov models, frequency-domain synthetic aperture focusing

中图分类号: