Juanjuan Shi
Juanjuan Shi
Подтвержден адрес электронной почты в домене suda.edu.cn
Stacked sparse autoencoder-based deep network for fault diagnosis of rotating machinery
Y Qi, C Shen, D Wang, J Shi, X Jiang, Z Zhu
Ieee Access 5, 15066-15079, 2017
A coarse-to-fine decomposing strategy of VMD for extraction of weak repetitive transients in fault diagnosis of rotating machines
X Jiang, J Wang, J Shi, C Shen, W Huang, Z Zhu
Mechanical Systems and Signal Processing 116, 668-692, 2019
Initial center frequency-guided VMD for fault diagnosis of rotating machines
X Jiang, C Shen, J Shi, Z Zhu
Journal of Sound and Vibration 435, 36-55, 2018
Generalized stepwise demodulation transform and synchrosqueezing for time–frequency analysis and bearing fault diagnosis
J Shi, M Liang, DS Necsulescu, Y Guan
Journal of Sound and Vibration 368, 202-222, 2016
Bearing fault diagnosis under variable rotational speed via the joint application of windowed fractal dimension transform and generalized demodulation: A method free from …
J Shi, M Liang, Y Guan
Mechanical Systems and Signal Processing 68, 15-33, 2016
Bearing fault diagnosis via generalized logarithm sparse regularization
Z Zhang, W Huang, Y Liao, Z Song, J Shi, X Jiang, C Shen, Z Zhu
Mechanical Systems and Signal Processing 167, 108576, 2022
A new l0-norm embedded MED method for roller element bearing fault diagnosis at early stage of damage
X Jiang, X Cheng, J Shi, W Huang, C Shen, Z Zhu
Measurement 127, 414-424, 2018
Transient extraction based on minimax concave regularized sparse representation for gear fault diagnosis
W Huang, S Li, X Fu, C Zhang, J Shi, Z Zhu
Measurement 151, 107273, 2020
Modeling method of the grey GM (1, 1) model with interval grey action quantity and its application
B Zeng, X Ma, J Shi
Complexity 2020, 1-10, 2020
Intelligent bearing fault signature extraction via iterative oscillatory behavior based signal decomposition (IOBSD)
J Shi, M Liang
Expert Systems with Applications 45, 40-55, 2016
Nonconvex group sparsity signal decomposition via convex optimization for bearing fault diagnosis
W Huang, N Li, I Selesnick, J Shi, J Wang, L Mao, X Jiang, Z Zhu
IEEE Transactions on Instrumentation and Measurement 69 (7), 4863-4872, 2019
Multi-source fidelity sparse representation via convex optimization for gearbox compound fault diagnosis
W Huang, Z Song, C Zhang, J Wang, J Shi, X Jiang, Z Zhu
Journal of Sound and vibration 496, 115879, 2021
A hybrid technique based on convolutional neural network and support vector regression for intelligent diagnosis of rotating machinery
W You, C Shen, X Guo, X Jiang, J Shi, Z Zhu
Advances in Mechanical Engineering 9 (6), 1687814017704146, 2017
An adaptive and efficient variational mode decomposition and its application for bearing fault diagnosis
X Jiang, J Wang, C Shen, J Shi, W Huang, Z Zhu, Q Wang
Structural Health Monitoring 20 (5), 2708-2725, 2021
Machinery health monitoring based on unsupervised feature learning via generative adversarial networks
J Dai, J Wang, W Huang, J Shi, Z Zhu
IEEE/ASME Transactions on Mechatronics 25 (5), 2252-2263, 2020
Improved hierarchical adaptive deep belief network for bearing fault diagnosis
C Shen, J Xie, D Wang, X Jiang, J Shi, Z Zhu
Applied Sciences 9 (16), 3374, 2019
Non-dominated solution set based on time–frequency infograms for local damage detection of rotating machines
X Jiang, J Shi, W Huang, Z Zhu
ISA transactions 92, 213-227, 2019
Iterative matching synchrosqueezing transform and application to rotating machinery fault diagnosis under nonstationary conditions
Z Hua, J Shi, Y Luo, W Huang, J Wang, Z Zhu
Measurement 173, 108592, 2021
A coarse TF ridge-guided multi-band feature extraction method for bearing fault diagnosis under varying speed conditions
W Guo, X Jiang, N Li, J Shi, Z Zhu
IEEE Access 7, 18293-18310, 2019
An enhanced VMD with the guidance of envelope negentropy spectrum for bearing fault diagnosis
H Wang, X Jiang, W Guo, J Shi, Z Zhu
Complexity 2020, 1-23, 2020
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Статьи 1–20