Artificial neural network based multi-parameter inversion for the characterization of transversely isotropic composite lamina using velocity measurements of Lamb waves

被引:4
|
作者
Ramadas, C. [1 ,2 ,3 ]
Harshe, Rahul [3 ]
Balasubramaniam, Krishnan [1 ,2 ]
Joshi, Makarand [3 ]
机构
[1] Indian Inst Technol Madras, Ctr Nondestruct Evaluat, Madras 600036, Tamil Nadu, India
[2] Indian Inst Technol Madras, Dept Mech Engn, Madras 600036, Tamil Nadu, India
[3] DRDO, Composite Res Ctr, Res & Dev Estab, Pune, Maharashtra, India
关键词
Composite lamina; lamb wave; lamina properties; artificial neural network; RECONSTRUCTION; ALGORITHM;
D O I
10.1177/0021998311414217
中图分类号
TB33 [复合材料];
学科分类号
摘要
Artificial neural network (ANN) based multi-parameter inversion method is proposed to characterize transversely isotropic composite lamina using Lamb wave group velocity measurements. The ANN is first trained using numerical simulations and known micromechanics based formulae before being deployed on experimental samples. The group velocities obtained from the experiments were fed to the trained network. The network so trained, predicted the elastic properties, fiber volume fraction, and density.
引用
收藏
页码:517 / 525
页数:9
相关论文
共 18 条
  • [1] Multi-Parameter Inversion of AIEM by Using Bi-Directional Deep Neural Network
    Wang, Yu
    He, Zi
    Yang, Ying
    Ding, Dazhi
    Ding, Fan
    Dang, Xun-Wang
    REMOTE SENSING, 2022, 14 (14)
  • [2] Multi-Parameter Inversion of AIEM by Using Multi-layer and Multi-Channel Convolutional Neural Network
    Wang, Yu
    He, Zi
    Ding, Dazhi
    2022 INTERNATIONAL CONFERENCE ON MICROWAVE AND MILLIMETER WAVE TECHNOLOGY (ICMMT), 2022,
  • [3] Multi-parameter reconstruction of velocity and density using ultrasonic tomography based on full waveform inversion
    Rao, Jing
    Yang, Jizhong
    Ratassepp, Madis
    Fan, Zheng
    ULTRASONICS, 2020, 101 (101)
  • [4] Damage Localization in Composite Structures Using a Guided Waves Based Multi-Parameter Approach
    Memmolo, Vittorio
    Boffa, Natalino D.
    Maio, Leandro
    Monaco, Ernesto
    Ricci, Fabrizio
    AEROSPACE, 2018, 5 (04)
  • [5] Insulating fault diagnosis of XLPE power cables using multi-parameter based on artificial neural networks
    Chen, XL
    Cheng, YH
    Zhu, ZL
    Yue, B
    Xie, XJ
    ADVANCES IN NEURAL NETWORKS - ISNN 2005, PT 3, PROCEEDINGS, 2005, 3498 : 609 - 615
  • [6] Locating Low Velocity Impacts on a Composite Plate Using Multi-Frequency Image Fusion and Artificial Neural Network
    Feng, Bo
    Ribeiro, Artur Lopes
    Pasadas, Dario J.
    Ramos, Helena Geirinhas
    JOURNAL OF NONDESTRUCTIVE EVALUATION, 2022, 41 (02)
  • [7] Locating Low Velocity Impacts on a Composite Plate Using Multi-Frequency Image Fusion and Artificial Neural Network
    Bo Feng
    Artur Lopes Ribeiro
    Dario J. Pasadas
    Helena Geirinhas Ramos
    Journal of Nondestructive Evaluation, 2022, 41
  • [8] Assessment of degree of internal carotid artery stenosis based on duplex velocity measurements using an artificial neural network
    Mofidi, R
    Brabazon, A
    Powell, T
    Hurson, C
    Sheehan, S
    Mehigan, D
    MacErlaine, D
    Keaveny, TV
    BRITISH JOURNAL OF SURGERY, 2001, 88 (04) : 600 - 600
  • [9] Assessment of degree of Internal Carotid Artery stenosis based on duplex ultrasound velocity measurements using an artificial neural network
    Mofidi, R
    Powell, TI
    Brabazon, A
    Sheehan, S
    Keaveny, TV
    MacErlaine, DP
    RADIOLOGY, 2001, 221 : 591 - 592
  • [10] Prediction of the exact degree of internal carotid artery stenosis using an artificial neural network based on duplex velocity measurements
    Mofidi, R
    Powell, TI
    Brabazon, A
    Mehigan, D
    Sheehan, SJ
    MacErlaine, DP
    Keaveny, TV
    ANNALS OF VASCULAR SURGERY, 2005, 19 (06) : 829 - 837