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Author:

Li, X. (Li, X..) | Liu, H. (Liu, H..) | Chen, X. (Chen, X..) | Lyu, Y. (Lyu, Y..) | Liu, Z. (Liu, Z..)

Indexed by:

EI Scopus SCIE

Abstract:

The prediction of the initial stress in composites is essential for the non-destructive testing (NDT) and structural health monitoring (SHM) of carbon fibre reinforced polymer (CFRP). This paper examines the potential of Lamb waves in the inverse of initial stress by calculating the influence of initial stress on the dispersion characteristics of Lamb waves propagating in multilayered CFRP laminates. By introducing the mechanics of incremental deformation into the linear three-dimensional elasticity theory, the Legendre orthogonal polynomial expansion (LOPE) method is used to mathematically model the Lamb wave propagating in multilayered CFRP laminates subjected to horizontal and vertical homogeneous initial stresses. Then, a three-hidden-layers Feed Forward Deep Neural Network (DNN) with Back Propagation (BP) algorithm is constructed to invert the magnitude and direction of the initial stresses. The input features are the phase velocities of fundamental Lamb wave A0 mode at five different frequencies. Both training and testing samples are obtained by LOPE forward calculation. An ablation experiment is presented to compare the two different activation functions. Finally, the accuracy of the inverse is verified by comparing with the available outcomes of LOPE forward calculation. © 2023 Elsevier B.V.

Keyword:

Lamb wave Carbon fiber reinforced polymer laminates Legendre orthogonal polynomial Deep Neural Network Initial stress

Author Community:

  • [ 1 ] [Li X.]School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Jungong Road 580, Shanghai, 200093, China
  • [ 2 ] [Liu H.]School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Jungong Road 580, Shanghai, 200093, China
  • [ 3 ] [Chen X.]Mechanical Engineering Division, Southwest Research Institute, 6220 Culebra Road, San Antonio, 78238, TX, United States
  • [ 4 ] [Lyu Y.]Faculty of Materials and Manufacturing, Beijing University of Technology, Beijing, 100124, China
  • [ 5 ] [Liu Z.]Faculty of Materials and Manufacturing, Beijing University of Technology, Beijing, 100124, China

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Source :

Ultrasonics

ISSN: 0041-624X

Year: 2023

Volume: 132

4 . 2 0 0

JCR@2022

ESI Discipline: CLINICAL MEDICINE;

ESI HC Threshold:14

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 2

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 3

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