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Jun Li
Jun Li
Professor & ARC Future Fellow, Curtin University, Australia
Bestätigte E-Mail-Adresse bei curtin.edu.au - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Structural damage identification based on autoencoder neural networks and deep learning
CSN Pathirage, J Li, L Li, H Hao, W Liu, P Ni
Engineering structures 172, 13-28, 2018
3852018
Micro-seismic event detection and location in underground mines by using Convolutional Neural Networks (CNN) and deep learning
L Huang, J Li, H Hao, X Li
Tunnelling and Underground Space Technology 81, 265-276, 2018
1642018
Towards next generation design of sustainable, durable, multi-hazard resistant, resilient, and smart civil engineering structures
H Hao, K Bi, W Chen, TM Pham, J Li
Engineering Structures 277, 115477, 2023
1582023
Substructure damage identification based on response reconstruction in frequency domain and model updating
J Li, SS Law, Y Ding
Engineering structures 41, 270-284, 2012
1512012
Lost data recovery for structural health monitoring based on convolutional neural networks
G Fan, J Li, H Hao
Structural Control and Health Monitoring 26 (10), e2433, 2019
1492019
Structural response reconstruction with transmissibility concept in frequency domain
SS Law, J Li, Y Ding
Mechanical Systems and Signal Processing 25 (3), 952-968, 2011
1462011
Development and application of a deep learning–based sparse autoencoder framework for structural damage identification
CSN Pathirage, J Li, L Li, H Hao, W Liu, R Wang
Structural Health Monitoring 18 (1), 103-122, 2019
1382019
Vibration signal denoising for structural health monitoring by residual convolutional neural networks
G Fan, J Li, H Hao
Measurement 157, 107651, 2020
1372020
Non-probabilistic method to consider uncertainties in frequency response function for vibration-based damage detection using Artificial Neural Network
KH Padil, N Bakhary, M Abdulkareem, J Li, H Hao
Journal of Sound and vibration 467, 115069, 2020
1142020
Data driven structural dynamic response reconstruction using segment based generative adversarial networks
G Fan, J Li, H Hao, Y Xin
Engineering Structures 234, 111970, 2021
1102021
Structural damage identification using improved Jaya algorithm based on sparse regularization and Bayesian inference
Z Ding, J Li, H Hao
Mechanical Systems and Signal Processing 132, 211-231, 2019
1102019
Dynamic response reconstruction for structural health monitoring using densely connected convolutional networks
G Fan, J Li, H Hao
Structural Health Monitoring 20 (4), 1373-1391, 2021
1012021
Time‐varying system identification using variational mode decomposition
P Ni, J Li, H Hao, Y Xia, X Wang, JM Lee, KH Jung
Structural Control and Health Monitoring 25 (6), e2175, 2018
952018
Reliability analysis and design optimization of nonlinear structures
P Ni, J Li, H Hao, W Yan, X Du, H Zhou
Reliability engineering & system safety 198, 106860, 2020
932020
Damage detection in bridge structures under moving loads with phase trajectory change of multi-type vibration measurements
W Zhang, J Li, H Hao, H Ma
Mechanical Systems and Signal Processing 87, 410-425, 2017
922017
Improved damage identification in bridge structures subject to moving loads: numerical and experimental studies
J Li, SS Law, H Hao
International Journal of Mechanical Sciences 74, 99-111, 2013
922013
Computer vision based target-free 3D vibration displacement measurement of structures
Y Shao, L Li, J Li, S An, H Hao
Engineering Structures 246, 113040, 2021
912021
Development and application of a relative displacement sensor for structural health monitoring of composite bridges
J Li, H Hao, K Fan, J Brownjohn
Structural Control and Health Monitoring 22 (4), 726-742, 2015
902015
Substructural response reconstruction in wavelet domain
J Li, SS Law
Journal of Applied Mechanics ASME 78 (4), 041010, 2011
892011
Fatigue reliability evaluation of deck-to-rib welded joints in OSD considering stochastic traffic load and welding residual stress
C Cui, Q Zhang, Y Luo, H Hao, J Li
International journal of fatigue 111, 151-160, 2018
882018
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