小波
无损检测
降噪
混叠
超声波传感器
信号(编程语言)
小波变换
噪音(视频)
声学
导波测试
人工智能
计算机科学
时频分析
工程类
模式识别(心理学)
滤波器(信号处理)
计算机视觉
物理
图像(数学)
量子力学
程序设计语言
作者
Songling Huang,Hongyu Sun,Shen Wang,Kaifeng Qu,Wei Zhao,Lisha Peng
出处
期刊:IEEE Sensors Journal
[Institute of Electrical and Electronics Engineers]
日期:2021-01-14
卷期号:21 (13): 14709-14717
被引量:29
标识
DOI:10.1109/jsen.2021.3051658
摘要
Ultrasonic guided wave testing technology is currently widely used in industrial nondestructive testing (NDT), including defect detection in the floors of large tanks and oil pipelines. However, in addition to noise, practical scenarios of signal detection also present mode aliasing problems, which make it difficult to accurately identify and locate defects. In this paper, we propose an improved shear horizontal guided wave mode identification method using a variational mode decomposition (VMD) algorithm and a time-of-flight (TOF) extraction method using the synchrosqueezed wavelet transform (SSWT) algorithm. Moreover, we use the wavelet denoising method to denoise the original signal before applying VMD. The results show that the TOF errors obtained by the VMD method are all less than 5% and that the wavelet denoising of the original guided wave data can further reduce the errors (to less than 2%). In addition, the SSWT can modify the time-frequency analysis results of intrinsic mode functions obtained by the VMD method and provides accurate TOF data for different modes. Therefore, the proposed ultrasonic guided wave signal method is helpful for improving the defect detection sensitivity and accuracy of SH waves.
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