Your browser doesn't support javascript.
loading
Reconstruction of Water-Filled Pipe Ultrasonic Guided Wave Signals in the Distance Domain by Orthogonal Matching Pursuit Based on Dispersion and Multi-Mode.
Wang, Yuemin; Tang, Binghui; Gong, Ruqing; Zhou, Fan; Chen, Ang.
Afiliación
  • Wang Y; College of Power Engineering, Naval University of Engineering, Wuhan 430033, China.
  • Tang B; College of Power Engineering, Naval University of Engineering, Wuhan 430033, China.
  • Gong R; College of Power Engineering, Naval University of Engineering, Wuhan 430033, China.
  • Zhou F; College of Power Engineering, Naval University of Engineering, Wuhan 430033, China.
  • Chen A; College of Power Engineering, Naval University of Engineering, Wuhan 430033, China.
Sensors (Basel) ; 23(21)2023 Oct 24.
Article en En | MEDLINE | ID: mdl-37960382
ABSTRACT
Ultrasonic guided waves (UGWs) in water-filled pipes are subject to more severe dispersion and attenuation than vacant pipes, posing significant challenges for defect identification and localization. To this end, a novel sparse signal decomposition method called orthogonal matching pursuit based on dispersion and multi-mode (DMOMP) was proposed, which utilizes the second-order asymptotic solution of dispersion curves and the conversion characteristics of asymmetric UGWs in the defect contact stage to reconstruct the dispersive signals and converts the time-domain dispersive signals to distance-domain non-dispersive signals by dispersion compensated time-distance mapping. The synthesized simulation results indicate that DMOMP not only exhibits higher reconstruction accuracy compared to OMP, but also reveals more accurate and stable mode recognition and localization compared to DOMP, which only considers the dispersion under perturbation and noise. In addition, the UGW testing experimental results of water-filled pipes verify the effectiveness of DMOMP, the localization accuracies of three feature signals (defct 1, defct 2 and end echo) with DMOMP are 99.10%, 98.72% and 98.36%, respectively, and the average localization accuracy of DMOMP is as high as 98.73%.
Palabras clave

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2023 Tipo del documento: Article País de afiliación: China