Wei Zhang
Cited by
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A deep convolutional neural network with new training methods for bearing fault diagnosis under noisy environment and different working load
W Zhang, C Li, G Peng, Y Chen, Z Zhang
Mechanical Systems and Signal Processing 100, 439-453, 2018
A new deep learning model for fault diagnosis with good anti-noise and domain adaptation ability on raw vibration signals
W Zhang, G Peng, C Li, Y Chen, Z Zhang
Sensors 17 (2), 425, 2017
Bearing fault diagnosis using fully-connected winner-take-all autoencoder
C Li, WEI Zhang, G Peng, S Liu
IEEE Access 6, 6103-6115, 2017
ACDIN: Bridging the gap between artificial and real bearing damages for bearing fault diagnosis
Y Chen, G Peng, C Xie, W Zhang, C Li, S Liu
Neurocomputing 294, 61-71, 2018
Bearings fault diagnosis based on convolutional neural networks with 2-D representation of vibration signals as input
W Zhang, G Peng, C Li
MATEC web of conferences 95, 13001, 2017
Rolling element bearings fault intelligent diagnosis based on convolutional neural networks using raw sensing signal
W Zhang, G Peng, C Li
Advances in Intelligent Information Hiding and Multimedia Signal Processing …, 2017
Map-less navigation: A single drl-based controller for robots with varied dimensions
W Zhang, Y Zhang, N Liu
arXiv preprint arXiv:2002.06320, 2020
Danger-aware adaptive composition of DRL agents for self-navigation
W Zhang, Y Zhang, N Liu
Unmanned Systems 9 (01), 1-9, 2021
Learn to Navigate Maplessly With Varied LiDAR configurations: a support point-based approach
W Zhang, N Liu, Y Zhang
IEEE Robotics and Automation Letters 6 (2), 1918-1925, 2021
Behavior Switch for DRL-based Robot Navigation
W Zhang, YF Zhang
2019 IEEE 15th International Conference on Control and Automation (ICCA …, 2019
An Evolutional Algorithm for Automatic 2D Layer Segmentation in Laser-aided Additive Manufacturing
N Liu, K Ren, W Zhang, YF Zhang, YX Chew, GJ Bi, JYH Fuh
Additive Manufacturing, 102342, 2021
IPAPRec: A promising tool for learning high-performance mapless navigation skills with deep reinforcement learning
W Zhang, Y Zhang, N Liu, K Ren, P Wang
arXiv preprint arXiv:2103.11686, 2021
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