Mode Identification of Denoised SH Guided Waves Using Variational Mode Decomposition Method

被引:3
|
作者
Sun, Hongyu
Peng, Lisha
Huang, Songling [1 ]
Wang, Shen
Wang, Qing
Zhao, Wei
机构
[1] Tsinghua Univ, Dept Elect Engn, Beijing, Peoples R China
来源
2020 IEEE SENSORS | 2020年
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
Signal processing algorithms; acoustic waves; acoustic sensors; wavelet transforms; SIGNALS; EMAT;
D O I
10.1109/sensors47125.2020.9278659
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In the non-destructive testing (NDT) for large tank floors and oil pipelines, in addition to noise, the practical detection signal also has mode aliasing problems, which makes it difficult to identify and locate defects accurately. Therefore, in this work, we propose an improved shear horizontal guided wave mode identification method by using a variational mode decomposition (VMD) algorithm. Besides, we use the wavelet denoising method to denoise the original signal before using VMD for mode decomposition. Results show that compared with the traditional EMD method, the VMD algorithm is more effective for identifying aliased mode ultrasonic guided waves, and the wavelet denoising of the original guided wave data can further reduce the errors. Therefore, the proposed ultrasonic guided wave signal method is helpful to improve the defect detection sensitivity and accuracy of the SH EMAT.
引用
收藏
页数:3
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