Publications
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). 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). 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). 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).
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). 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). 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