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Author:

Hua, Jiadong (Hua, Jiadong.) | Zeng, Liang (Zeng, Liang.) | Lin, Jing (Lin, Jing.)

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Abstract:

Sparse decomposition is a promising approach for Lamb wave structural health monitoring. In Lamb wave sparse decomposition, designing an appropriate dictionary is of vital importance, which should be as accurate to actual wave packet as possible. Dispersion and multi-mode characteristics have been used for dictionary design. However, none of the previous research considered amplitude modulation in dictionary design, which limits the performance of sparse decomposition. To solve this issue, modified dictionary design for Lamb wave sparse decomposition is proposed in this study. First, frequency-dependent amplitude modulation curve is obtained based on the prior information of plate thickness, the type of mode, and the transducer size. Second, amplitude modulation is placed on the Lamb wave propagation model to redesign the dictionary. An experiment is given to validate the effectiveness of Lamb wave sparse decomposition with the modified dictionary design. © APWSHM 2018. All rights reserved.

Keyword:

Amplitude modulation Structural health monitoring Surface waves Ultrasonic waves Wave propagation

Author Community:

  • [ 1 ] [Hua, Jiadong]School of Reliability and Systems Engineering, Beihang University, Beijing, China
  • [ 2 ] [Zeng, Liang]School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China
  • [ 3 ] [Lin, Jing]School of Reliability and Systems Engineering, Beihang University, Beijing, China
  • [ 4 ] [Lin, Jing]School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China

Reprint Author's Address:

  • [Lin, Jing]School of Reliability and Systems Engineering, Beihang University, Beijing, China;;[Lin, Jing]School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China;;

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Source :

Year: 2018

Page: 1159-1164

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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