Publications
2025
Enhanced prognostic reliability for rotating machinery using neural networks with multi-scale vibration feature learning and uncertainty quantification
Zhao, K., Wen, Q., Li, H., Zhang, W., Xu, Z., & Feng, K. (2025). Enhanced prognostic reliability for rotating machinery using neural networks with multi-scale vibration feature learning and uncertainty quantification. Measurement Science and Technology, 36(6), 066102. doi:10.1088/1361-6501/add48e
Uncertainty-aware hourly load forecasting of hydrogen-blended natural gas with a hybrid deep learning model
Wang, L., Xie, Q., Wang, Z., Guo, J., Xu, Z., Kang, H. S., & Li, H. (2025). Uncertainty-aware hourly load forecasting of hydrogen-blended natural gas with a hybrid deep learning model. International Journal of Hydrogen Energy, 127, 541-563. doi:10.1016/j.ijhydene.2025.04.101
A Novel Bearing Remaining Useful Life Prediction Methodology With Slope-Based Change Point Detection and WOA-Attention-BiLSTM Model
Qiu, G., Ye, B., Gu, Y., Huang, P., Li, H., & Xu, Z. (2025). A Novel Bearing Remaining Useful Life Prediction Methodology With Slope-Based Change Point Detection and WOA-Attention-BiLSTM Model. IEEE Sensors Journal, 25(6), 10417-10431. doi:10.1109/jsen.2025.3530111
2024
Early anomaly detection of wind turbine gearbox based on SLFormer neural network
Wang, Z., Jiang, X., Xu, Z., Cai, C., Wang, X., Xu, J., . . . Li, Q. A. (2024). Early anomaly detection of wind turbine gearbox based on SLFormer neural network. Ocean Engineering, 311, 118925. doi:10.1016/j.oceaneng.2024.118925
Physics-informed probabilistic deep network with interpretable mechanism for trustworthy mechanical fault diagnosis
Xu, Z., Zhao, K., Wang, J., & Bashir, M. (2024). Physics-informed probabilistic deep network with interpretable mechanism for trustworthy mechanical fault diagnosis. Advanced Engineering Informatics, 62, 102806. doi:10.1016/j.aei.2024.102806
Rolling bearing fault diagnosis method using time-frequency information integration and multi-scale TransFusion network
Wang, Z., Xu, Z., Cai, C., Wang, X., Xu, J., Shi, K., . . . Li, Q. A. (2024). Rolling bearing fault diagnosis method using time-frequency information integration and multi-scale TransFusion network. Knowledge-Based Systems, 284, 111344. doi:10.1016/j.knosys.2023.111344
2023
Fault diagnosis of rolling bearing using CNN and PCA fractal based feature extraction
Zhao, K., Xiao, J., Li, C., Xu, Z., & Yue, M. (2023). Fault diagnosis of rolling bearing using CNN and PCA fractal based feature extraction. Measurement, 223, 113754. doi:10.1016/j.measurement.2023.113754
Optimized design of wind turbine airfoil aerodynamic performance and structural strength based on surrogate model
Zhang, Q., Miao, W., Liu, Q., Xu, Z., Li, C., Chang, L., & Yue, M. (2023). Optimized design of wind turbine airfoil aerodynamic performance and structural strength based on surrogate model. Ocean Engineering, 289, 116279. doi:10.1016/j.oceaneng.2023.116279
Dynamic response analysis of floating wind turbine platform in local fatigue of mooring
Sun, K., Xu, Z., Li, S., Jin, J., Wang, P., Yue, M., & Li, C. (2023). Dynamic response analysis of floating wind turbine platform in local fatigue of mooring. RENEWABLE ENERGY, 204, 733-749. doi:10.1016/j.renene.2022.12.117
A novel health indicator for intelligent prediction of rolling bearing remaining useful life based on unsupervised learning model
Xu, Z., Bashir, M., Liu, Q., Miao, Z., Wang, X., Wang, J., & Ekere, N. (2023). A novel health indicator for intelligent prediction of rolling bearing remaining useful life based on unsupervised learning model. COMPUTERS & INDUSTRIAL ENGINEERING, 176. doi:10.1016/j.cie.2023.108999
Recommendation for strut designs of vertical axis wind turbines: Effects of strut profiles and connecting configurations on the aerodynamic performance
Miao, W., Liu, Q., Zhang, Q., Xu, Z., Li, C., Yue, M., . . . Ye, Z. (2023). Recommendation for strut designs of vertical axis wind turbines: Effects of strut profiles and connecting configurations on the aerodynamic performance. ENERGY CONVERSION AND MANAGEMENT, 276. doi:10.1016/j.enconman.2022.116436
2022
Multisensory collaborative damage diagnosis of a 10 MW floating offshore wind turbine tendons using multi-scale convolutional neural network with attention mechanism
Xu, Z., Bashir, M., Yang, Y., Wang, X., Wang, J., Ekere, N., & Li, C. (2022). Multisensory collaborative damage diagnosis of a 10 MW floating offshore wind turbine tendons using multi-scale convolutional neural network with attention mechanism. RENEWABLE ENERGY, 199, 21-34. doi:10.1016/j.renene.2022.08.093
An intelligent fault diagnosis for machine maintenance using weighted soft-voting rule based multi-attention module with multi-scale information fusion
Xu, Z., Bashir, M., Zhang, W., Yang, Y., Wang, X., & Li, C. (2022). An intelligent fault diagnosis for machine maintenance using weighted soft-voting rule based multi-attention module with multi-scale information fusion. INFORMATION FUSION, 86-87, 17-29. doi:10.1016/j.inffus.2022.06.005
Research on Fault Diagnosis of Wind Turbine Rolling Bearing based on Improved Variational Mode Decomposition and Maximum Correlation Kurtosis Deconvolution
Xiao, J. Q., Jin, J. T., Li, C., & Xu, Z. F. (2022). Research on Fault Diagnosis of Wind Turbine Rolling Bearing based on Improved Variational Mode Decomposition and Maximum Correlation Kurtosis Deconvolution. Reneng Dongli Gongcheng Journal of Engineering for Thermal Energy and Power, 37(5), 165-173. doi:10.16146/j.cnki.rndlgc.2022.05.023
Bearing Fault Diagnosis Based on CEEMDAN Sample Entropy and Convolutional Neural Network
Xiao, J., Jin, J., Li, C., Xu, Z., & Sun, K. (2022). Bearing Fault Diagnosis Based on CEEMDAN Sample Entropy and Convolutional Neural Network. Dongli Gongcheng Xuebao Journal of Chinese Society of Power Engineering, 42(5), 429-436. doi:10.19805/j.cnki.jcspe.2022.05.006
Comparative Research on Load Characteristics and Bionic Fractal of Wind Turbine Blade with Pitch Fault and the Original Structure
Wang, Y. B., Zhang, Q., Li, C., & Xu, Z. F. (2022). Comparative Research on Load Characteristics and Bionic Fractal of Wind Turbine Blade with Pitch Fault and the Original Structure. Reneng Dongli Gongcheng Journal of Engineering for Thermal Energy and Power, 37(4), 144-151. doi:10.16146/j.cnki.rndlgc.2022.04.020
Research on Bearing Fault Diagnosis based on Optimized CEEMDAN-CNN
Xiao, J. Q., Jin, J. T., Li, C., & Xu, Z. F. (2022). Research on Bearing Fault Diagnosis based on Optimized CEEMDAN-CNN. Reneng Dongli Gongcheng Journal of Engineering for Thermal Energy and Power, 37(4), 166-174. doi:10.16146/j.cnki.rndlgc.2022.04.023
Application of convolutional neural network and chaos theory in fault diagnosis of rolling bearings
Jin, J., Xu, Z., Li, C., Miao, W., Zhang, W., & Li, G. (2022). Application of convolutional neural network and chaos theory in fault diagnosis of rolling bearings. Jixie Qiangdu Journal of Mechanical Strength, 44(2), 287-293. doi:10.16579/j.issn.1001.9669.2022.02.005
Nonlinear analysis of bearing signal based on improved variational modal decomposition and muti fractal
Jin, J., Xu, Z., Li, C., Miao, W., Zhang, W., & Li, G. (2022). Nonlinear analysis of bearing signal based on improved variational modal decomposition and muti fractal. Jixie Qiangdu Journal of Mechanical Strength, 44(1), 45-52. doi:10.16579/j.issn.1001.9669.2022.01.006
Research on dynamic response of super large floating wind turbine based on chaos theory
Wang, B., Liu, Q., Li, C., Xu, Z., Ding, Q., Zhang, L., & Li, S. (2022). Research on dynamic response of super large floating wind turbine based on chaos theory. Jixie Qiangdu Journal of Mechanical Strength, 44(1), 29-37. doi:10.16579/j.issn.1001.9669.2022.01.004
Tendon damage identification of 10 MW floating wind turbine based on CMS-CNN
Xu, Z., Yang, Y., Li, C., Miao, W., Zhang, W., Jin, J., & Wang, X. (2022). Tendon damage identification of 10 MW floating wind turbine based on CMS-CNN. Zhendong Yu Chongji Journal of Vibration and Shock, 41(3), 183-286. doi:10.13465/j.cnki.jvs.2022.03.022
A comprehensive analysis of blade tip for vertical axis wind turbine: Aerodynamics and the tip loss effect
Miao, W., Liu, Q., Xu, Z., Yue, M., Li, C., & Zhang, W. (2022). A comprehensive analysis of blade tip for vertical axis wind turbine: Aerodynamics and the tip loss effect. Energy Conversion and Management, 253, 115140. doi:10.1016/j.enconman.2021.115140
Fault diagnosis of wind turbine bearing using a multi-scale convolutional neural network with bidirectional long short term memory and weighted majority voting for multi-sensors
Xu, Z., Mei, X., Wang, X., Yue, M., Jin, J., Yang, Y., & Li, C. (2022). Fault diagnosis of wind turbine bearing using a multi-scale convolutional neural network with bidirectional long short term memory and weighted majority voting for multi-sensors. RENEWABLE ENERGY, 182, 615-626. doi:10.1016/j.renene.2021.10.024
Rolling bearing fault diagnosis based on deep learning and chaotic feature fusion
Jin, J. T., Xu, Z. F., Li, C., Miao, W. P., Xiao, J. Q., & Sun, K. (2022). Rolling bearing fault diagnosis based on deep learning and chaotic feature fusion. Kongzhi Lilun Yu Yingyong Control Theory and Applications, 39(1), 109-116. doi:10.7641/CTA.2021.10177
2021
New method for the fault diagnosis of rolling bearings based on a multiscale convolutional neural network
Xu, Z., Jin, J., & Li, C. (2021). New method for the fault diagnosis of rolling bearings based on a multiscale convolutional neural network. Zhendong Yu Chongji Journal of Vibration and Shock, 40(18), 212-220. doi:10.13465/j.cnki.jvs.2021.18.028
Bearing Fault Diagnosis Based on VMD Energy Entropy and Optimized Support Vector Machine
Jin, J. T., Xu, Z. F., Li, C., Miao, W. P., & Li, G. (2021). Bearing Fault Diagnosis Based on VMD Energy Entropy and Optimized Support Vector Machine. Jiliang Xuebao Acta Metrologica Sinica, 42(7), 898-905. doi:10.3969/j.issn.1000-1158.2021.07.11
Fault diagnosis of rolling bearings using an Improved Multi-Scale Convolutional Neural Network with Feature Attention mechanism
Xu, Z., Li, C., & Yang, Y. (2021). Fault diagnosis of rolling bearings using an Improved Multi-Scale Convolutional Neural Network with Feature Attention mechanism. ISA TRANSACTIONS, 110, 379-393. doi:10.1016/j.isatra.2020.10.054
Fault Diagnosis of Bearings based on Variational Mode Decomposition and Convolutional Neural Network
Xu, Z. F., Miao, W. P., Li, C., & Jin, J. T. (2021). Fault Diagnosis of Bearings based on Variational Mode Decomposition and Convolutional Neural Network. Reneng Dongli Gongcheng Journal of Engineering for Thermal Energy and Power, 36(3), 55-63. doi:10.16146/j.cnki.rndlgc.2021.03.008
Fault Diagnosis of Rolling Bearings Based on Variational Mode Decomposition and Optimized of Support Vector Machine
Jin, J., Xu, Z., Li, C., & Miao, W. (2021). Fault Diagnosis of Rolling Bearings Based on Variational Mode Decomposition and Optimized of Support Vector Machine. Dongli Gongcheng Xuebao Journal of Chinese Society of Power Engineering, 41(3), 214-243. doi:10.19805/j.cnki.jcspe.2021.03.007
2020
Nonlinear feature extraction and chaos analysis of flow field
Xu, Z. -F., Miao, W. -P., Li, C., Jin, J. -T., & Li, S. -J. (2020). Nonlinear feature extraction and chaos analysis of flow field. Acta Physica Sinica, 69(24), 249501. doi:10.7498/aps.69.20200625
Transient dynamics analysis of a large-scale jacket offshore wind turbine under seismic loading
Yan, Y., Xu, Z., Li, C., Deng, Y., & Wang, Y. (2020). Transient dynamics analysis of a large-scale jacket offshore wind turbine under seismic loading. Zhendong Yu Chongji Journal of Vibration and Shock, 39(22), 175-182. doi:10.13465/j.cnki.jvs.2020.22.024
Seismic Dynamic Response of Jacket Offshore Wind Turbines Under Different Wind Loads
Yan, Y., Yue, M., Li, C., Yang, Y., & Xu, Z. (2020). Seismic Dynamic Response of Jacket Offshore Wind Turbines Under Different Wind Loads. Dongli Gongcheng Xuebao Journal of Chinese Society of Power Engineering, 40(11), 915-923. doi:10.19805/j.cnki.jcspe.2020.11.008
Fault diagnosis of rolling bearing of wind turbines based on the Variational Mode Decomposition and Deep Convolutional Neural Networks
Xu, Z., Li, C., & Yang, Y. (2020). Fault diagnosis of rolling bearing of wind turbines based on the Variational Mode Decomposition and Deep Convolutional Neural Networks. APPLIED SOFT COMPUTING, 95. doi:10.1016/j.asoc.2020.106515
Hydrodynamic characteristics of forced oscillation of heave plate with fractal characteristics based on floating wind turbine platform
Wang, B., Xu, Z., Li, C., Wang, D., & Ding, Q. (2020). Hydrodynamic characteristics of forced oscillation of heave plate with fractal characteristics based on floating wind turbine platform. Ocean Engineering, 212, 107621. doi:10.1016/j.oceaneng.2020.107621
Research on Fault Diagnosis of Wind Turbine Bearing based on Optimized Variational Mode Decomposition and Fractal Method
Jin, J. T., Xu, Z. F., & Li, C. (2020). Research on Fault Diagnosis of Wind Turbine Bearing based on Optimized Variational Mode Decomposition and Fractal Method. Reneng Dongli Gongcheng Journal of Engineering for Thermal Energy and Power, 35(8), 142-150. doi:10.16146/j.cnki.rndlgc.2020.08.019
Fault Diagnosis and Analysis of Wind Turbine Bearing Chaotic Phase based on Convolutional Neural Network
Xu, Z. F., Yue, M. N., & Li, C. (2020). Fault Diagnosis and Analysis of Wind Turbine Bearing Chaotic Phase based on Convolutional Neural Network. Reneng Dongli Gongcheng Journal of Engineering for Thermal Energy and Power, 35(6), 243-256. doi:10.16146/j.cnki.rndlgc.2020.06.033
Nonlinear Characteristic Analysis of Wind Turbine Bearings by SVM based on Optimized Variational Mode Decomposition
Xu, Z. F., Yue, M. N., & Li, C. (2020). Nonlinear Characteristic Analysis of Wind Turbine Bearings by SVM based on Optimized Variational Mode Decomposition. Reneng Dongli Gongcheng Journal of Engineering for Thermal Energy and Power, 35(6), 233-242. doi:10.16146/j.cnki.rndlgc.2020.06.032
Rotating Machine Fault Diagnosis based on Manifold Learning and Neural Network
Xu, Z. F., Yue, M. N., & Li, C. (2020). Rotating Machine Fault Diagnosis based on Manifold Learning and Neural Network. Reneng Dongli Gongcheng Journal of Engineering for Thermal Energy and Power, 35(6), 224-232. doi:10.16146/j.cnki.rndlgc.2020.06.031
Bearing Fault Analysis based on Improved Variational Mode Decomposition Analysis and De-interference Envelope Factor
Han, X. H. Y., Xu, Z. F., Li, C., & Ye, K. H. (2020). Bearing Fault Analysis based on Improved Variational Mode Decomposition Analysis and De-interference Envelope Factor. Reneng Dongli Gongcheng Journal of Engineering for Thermal Energy and Power, 35(4), 52-61. doi:10.16146/j.cnki.rndlgc.2020.04.008
Comparison of Dynamic Response Among Three Offshore Wind Turbine Semi-submersible Platforms Under Extreme Sea Conditions
Wang, B., Xu, Z., Li, C., Deng, Y., & Liu, Q. (2020). Comparison of Dynamic Response Among Three Offshore Wind Turbine Semi-submersible Platforms Under Extreme Sea Conditions. Dongli Gongcheng Xuebao Journal of Chinese Society of Power Engineering, 40(1), 58-64. doi:10.19805/j.cnki.jcspe.2020.01.009
2019
Application of the proposed optimized recursive variational mode decomposition in nonlinear decomposition
Xu, Z. -F., Yue, M. -N., & Li, C. (2019). Application of the proposed optimized recursive variational mode decomposition in nonlinear decomposition. Acta Physica Sinica, 68(23), 238401. doi:10.7498/aps.68.20191005
Multifractal Spectrum Analysis of Bearing Failure of Wind Turbine based on Adaptive Variational Modal Decomposition
Xu, Z. F., Li, C., Zhang, W. F., & Deng, Y. H. (2019). Multifractal Spectrum Analysis of Bearing Failure of Wind Turbine based on Adaptive Variational Modal Decomposition. Reneng Dongli Gongcheng Journal of Engineering for Thermal Energy and Power, 34(9), 181-190. doi:10.16146/j.cnki.rndlgc.2019.09.021
Seismic Dynamic Response of Offshore Wind Turbine with Different Water Depths
Xu, Z. F., Zou, J. H., Li, C., & Yang, Y. (2019). Seismic Dynamic Response of Offshore Wind Turbine with Different Water Depths. Reneng Dongli Gongcheng Journal of Engineering for Thermal Energy and Power, 34(9), 83-90. doi:10.16146/j.cnki.rndlgc.2019.09.009
Structure Dynamic Response of Large Offshore Wind Turbine under Combined Action of Earthquake and Turbulent Wind
Yan, Y. T., Xu, Z. F., Li, C., & Yang, Y. (2019). Structure Dynamic Response of Large Offshore Wind Turbine under Combined Action of Earthquake and Turbulent Wind. Reneng Dongli Gongcheng Journal of Engineering for Thermal Energy and Power, 34(9), 132-140. doi:10.16146/j.cnki.rndlgc.2019.09.015
Study on the Vibration of Cone Structures of Offshore Wind Turbine based on Chaos Theory
Zou, J. H., Li, C., Ye, K. H., & Xu, Z. F. (2019). Study on the Vibration of Cone Structures of Offshore Wind Turbine based on Chaos Theory. Reneng Dongli Gongcheng Journal of Engineering for Thermal Energy and Power, 34(9), 173-180. doi:10.16146/j.cnki.rndlgc.2019.09.020
Vibration Signals Analysis of the Bearing of Wind Turbine based on Improved Threshold and Multi-Fractal
Xu, Z. F., Li, C., Yang, Y., & Musa. (2019). Vibration Signals Analysis of the Bearing of Wind Turbine based on Improved Threshold and Multi-Fractal. Reneng Dongli Gongcheng Journal of Engineering for Thermal Energy and Power, 34(9), 191-198. doi:10.16146/j.cnki.rndlgc.2019.09.022
R/S Analysis on Hurst Exponent of Wind Speed Time Series
Xu, Z., Zou, J., Li, C., & Yuan, Q. (2019). R/S Analysis on Hurst Exponent of Wind Speed Time Series. Dongli Gongcheng Xuebao Journal of Chinese Society of Power Engineering, 39(7), 585-604.
Research on influence of ice-induced vibration on offshore wind turbines
Ye, K., Li, C., Yang, Y., Zhang, W., & Xu, Z. (2019). Research on influence of ice-induced vibration on offshore wind turbines. Journal of Renewable and Sustainable Energy, 11(3). doi:10.1063/1.5079302
Comparative study of chaos identification methods for wind speed time series under different environmental measurement
Yu, K., Yuan, Q., Li, C., Yang, Y., & Xu, Z. (2019). Comparative study of chaos identification methods for wind speed time series under different environmental measurement. Ekoloji, 28(107), 3499-3503.
2018
Influences of the cone structure of a monopile offshore wind turbine on its dynamic responses under ice loading condition
Xu, Z., Ye, K., Li, C., Ding, Q., & Yang, Y. (2018). Influences of the cone structure of a monopile offshore wind turbine on its dynamic responses under ice loading condition. Zhendong Yu Chongji Journal of Vibration and Shock, 37(22), 225-254. doi:10.13465/j.cnki.jvs.2018.22.034
Vibration Reduction Analysis of Offshore Wind Turbine with TMD System
Xu, Z. F., Ye, K. H., Li, C., & Yang, Y. (2018). Vibration Reduction Analysis of Offshore Wind Turbine with TMD System. Reneng Dongli Gongcheng Journal of Engineering for Thermal Energy and Power, 33(10), 127-134. doi:10.16146/j.cnki.rndlgc.2018.10.019
Floating Ice Load Reduction of Offshore Wind Turbines by Two Approaches
Ye, K., Li, C., Chen, F., Xu, Z., Zhang, W., & Zhang, J. (2018). Floating Ice Load Reduction of Offshore Wind Turbines by Two Approaches. International Journal of Structural Stability and Dynamics, 18(10), 1850129. doi:10.1142/s0219455418501298
Vibration Analysis of Offshore Wind Turbine with Cone Structure
Xu, Z. F., Ye, K. H., Li, C., & Ding, Q. W. (2018). Vibration Analysis of Offshore Wind Turbine with Cone Structure. Reneng Dongli Gongcheng Journal of Engineering for Thermal Energy and Power, 33(9), 101-113. doi:10.16146/j.cnki.rndlgc.2018.09.015
Analysis on Anti-ice Performance of Offshore Wind Turbines with Ice Breaking Cone
Xu, Z., Ye, K., Li, C., & Yang, Y. (2018). Analysis on Anti-ice Performance of Offshore Wind Turbines with Ice Breaking Cone. Dongli Gongcheng Xuebao Journal of Chinese Society of Power Engineering, 38(9), 740-746.
Load Reduction Characteristic of Anti-ice Cone for Offshore Wind Turbine under Ice Loading Condition
Xu, Z. F., Li, C., Ye, K. H., & Yang, Y. (2018). Load Reduction Characteristic of Anti-ice Cone for Offshore Wind Turbine under Ice Loading Condition. Reneng Dongli Gongcheng Journal of Engineering for Thermal Energy and Power, 33(8), 121-128. doi:10.16146/j.cnki.rndlgc.2018.08.019