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Weihua Li
Weihua Li
Prof. with School of Mechanical & Automotive Engineering, South China University of Technology
Verified email at scut.edu.cn
Title
Cited by
Cited by
Year
Multisensor feature fusion for bearing fault diagnosis using sparse autoencoder and deep belief network
Z Chen, W Li
IEEE Transactions on instrumentation and measurement 66 (7), 1693-1702, 2017
8462017
A perspective survey on deep transfer learning for fault diagnosis in industrial scenarios: Theories, applications and challenges
W Li, R Huang, J Li, Y Liao, Z Chen, G He, R Yan, K Gryllias
Mechanical Systems and Signal Processing 167, 108487, 2022
4862022
State-of-charge estimation of lithium-ion batteries based on gated recurrent neural network
F Yang, W Li, C Li, Q Miao
Energy 175, 66-75, 2019
4062019
A deep learning method for bearing fault diagnosis based on cyclic spectral coherence and convolutional neural networks
Z Chen, A Mauricio, W Li, K Gryllias
Mechanical Systems and Signal Processing 140, 106683, 2020
3592020
Active droplet sorting in microfluidics: a review
HD Xi, H Zheng, W Guo, AM Gañán-Calvo, Y Ai, CW Tsao, J Zhou, W Li, ...
Lab on a Chip 17 (5), 751-771, 2017
3292017
Mechanical fault diagnosis using convolutional neural networks and extreme learning machine
Z Chen, K Gryllias, W Li
Mechanical systems and signal processing 133, 106272, 2019
3072019
State-of-charge estimation of lithium-ion batteries using LSTM and UKF
F Yang, S Zhang, W Li, Q Miao
Energy 201, 117664, 2020
3032020
Bearing performance degradation assessment using long short-term memory recurrent network
B Zhang, S Zhang, W Li
Computers in Industry 106, 14-29, 2019
2942019
Intelligent fault diagnosis for rotary machinery using transferable convolutional neural network
Z Chen, K Gryllias, W Li
IEEE Transactions on Industrial Informatics 16 (1), 339-349, 2019
2602019
Domain adversarial transfer network for cross-domain fault diagnosis of rotary machinery
Z Chen, G He, J Li, Y Liao, K Gryllias, W Li
IEEE Transactions on Instrumentation and Measurement 69 (11), 8702-8712, 2020
2232020
Energy, exergy, exergoeconomic and environmental (4E) analysis of a distributed generation solar-assisted CCHP (combined cooling, heating and power) gas turbine system
J Wang, Z Lu, M Li, N Lior, W Li
Energy 175, 1246-1258, 2019
1902019
Deep decoupling convolutional neural network for intelligent compound fault diagnosis
R Huang, Y Liao, S Zhang, W Li
Ieee Access 7, 1848-1858, 2018
1832018
A two-stage transfer adversarial network for intelligent fault diagnosis of rotating machinery with multiple new faults
J Li, R Huang, G He, Y Liao, Z Wang, W Li
IEEE/ASME Transactions on Mechatronics 26 (3), 1591-1601, 2020
1532020
Deep semisupervised domain generalization network for rotary machinery fault diagnosis under variable speed
Y Liao, R Huang, J Li, Z Chen, W Li
IEEE Transactions on Instrumentation and Measurement 69 (10), 8064-8075, 2020
1492020
Deep adversarial capsule network for compound fault diagnosis of machinery toward multidomain generalization task
R Huang, J Li, Y Liao, J Chen, Z Wang, W Li
IEEE Transactions on Instrumentation and Measurement 70, 1-11, 2020
1462020
A novel weighted adversarial transfer network for partial domain fault diagnosis of machinery
W Li, Z Chen, G He
IEEE Transactions on Industrial Informatics 17 (3), 1753-1762, 2020
1392020
Semisupervised distance-preserving self-organizing map for machine-defect detection and classification
W Li, S Zhang, G He
IEEE Transactions on Instrumentation and Measurement 62 (5), 869-879, 2013
1102013
A deep adversarial transfer learning network for machinery emerging fault detection
J Li, R Huang, G He, S Wang, G Li, W Li
IEEE Sensors Journal 20 (15), 8413-8422, 2020
1052020
A liquid metal artificial muscle
J Shu, DA Ge, E Wang, H Ren, T Cole, SY Tang, X Li, X Zhou, R Li, H Jin, ...
Advanced Materials 33 (43), 2103062, 2021
1042021
A novel order tracking method for wind turbine planetary gearbox vibration analysis based on discrete spectrum correction technique
G He, K Ding, W Li, X Jiao
Renewable Energy 87, 364-375, 2016
1032016
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Articles 1–20