》 Research Fields
Methodologies:
· Machine and statistical learning
· Nonlinear system modelling and analysis
· Sparse representation
· Dynamic-based digital twin
Applications
· Advanced manufacturing
· Condition monitoring and fault detection
· Structural Health Monitoring
Smart devices
· Hardware and software design
》 Courses
》 Projects
》 Publications
Journal Papers:
[J1] ZP,Zhu, Z.Liu*, ZQ.Lang, and H.Laalej, " Uncertainties of Data-driven Models: Theory and Application to Condition Monitoring." IEEE Transactions on Instrumentation & Measurement, vol. 74, pp. 1-11, 2025. [IF:5.9]
[J2] Y.Zhao, Z.Liu*, Z.Yang, Q.Kai and, H.Ma, "Machinery Fault Diagnosis-Oriented Regularization for Nonlinear System Identification: Framework and Applications." Applied Acoustics, 231, pp.110537, 2024. [IF: 3.4]
[J3] Y,Zhao, T.Liu, Z.Liu*, YP.Zhu, Q.Kai and H.Ma, "Lifelong monitoring of bearing-rotor systems over whole life cycle: an emerging paradigm." IEEE Transactions on Industrial Informatics, Accept/inpress. [IF:11.7]
[J4] Z Liu, ZQ Lang, Y,Gui and YP Zhu, "Digital Twin-Based Anomaly Detection for Real-time Tool Condition Monitoring in Machining." Journal of Manufacturing Systems, 75, pp.163-173, 2024. [IF: 12.1]
[J1] Y.Gui, X.Tang and Z.Liu*, "Local Regularization Assisted Split Augmented Lagrangian Shrinkage Algorithm for Feature Selection in Condition Monitoring." Control Engineering Practice, 147, pp.105923, 2024. [IF: 4.9]
[J2] Z Liu, "A Nonlinear AutoRegression-Based Noise Cancellation Method for Real-time Fault Diagnosis of Rolling Bearings." IEEE Transactions on Instrumentation & Measurement, 73, pp.1-12, 2024. [IF: 5.9]
[J3] Y.Zhao, Z.Liu*, H.Zhang, Q.Kai, Y.Liu, and X.Wang, "On-line Condition Monitoring for Rotor Systems based on Nonlinear Data-driven Modelling and Model Frequency Analysis." Nonlinear Dynamics, 112, pp. 5229–5245, 2024. [IF: 5.6]
[J4] Y.Zhu, Z.Liu*, W.Zhang and B.Zhang, " Fast Evaluation of Generalized Associated Linear Equations (GALEs) for Nonlinear Systems Characterization and Compensation." Journal of the Franklin Institute, 361(2), pp.944-957, 2023. [IF: 4.1]
[J5] Z.Liu, Z Q.Lang, Y.Gui, Y.Zhu, H.Laalej, and D.Curtis, " Vibration Signal-based Tool Condition Monitoring Using Regularized Sensor Data Modelling and Model Frequency Analysis." IEEE Transactions on Instrumentation and Measurement, 2023. [IF: 5.6]
[J6] Z.Liu, Z Q.Lang, Y.Zhu, Y.Gui, H.Laalej, and J.Stammers, "Sensor Data Modelling and Model Frequency Analysis for Detecting Cutting Tool Anomalies in Machining." IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022. [IF: 8.6]
[J7] X.Qin, W.Huang, X.Wang, Z.Tang and Z.Liu*, "Real-time Remaining Useful Life Prediction of Cutting Tools Using Sparse Augmented Lagrangian Analysis and Gaussian Process Regression." Sensors, 23(1), pp.413, 2023 [IF: 3.85]
[J8] Y.Zhao, Z.Liu*, J.Lin, Q.Han* and Y.Liu, "Real-time Remaining Useful Life Prediction of Cutting Tools Using Sparse Augmented Lagrangian Analysis and Gaussian Process Regression." Measurement, 221, pp.113497, 2023 [IF: 5.6]
[J9] Y.Gui, Z.Lang, Z.Liu, and H.Laalej, " Tool Condition Monitoring Based on Nonlinear Output Frequency Response Functions and Multivariate Control Chart." Journal of Dynamics Monitoring and Diagnostics, 2023.
[J10] C.Zhang, Z.Liu,and L.Zhang, "Wind Turbine Blade Bearing Fault Detection with Bayesian and Adaptive Kalman Augmented Lagrangian Algorithm." Renewable Energy, 199 (2022): 1016-1023. [IF: 8.162].
[J11] Y.Zhu, Y.Zhao,Z Q.Lang and Z.Liu and Yang Liu, "On-line Rotor Systems Condition Monitoring Using Nonlinear Output Frequency Response Functions under Harmonic Excitations." IEEE Transactions on Industrial Informatics, 18.10 (2022): 6798-6808. [IF: 11.7]
[J12] Z.Liu, X.Tang, X.Wang, J.Mugica and L.Zhang, "Wind Turbine Blade Bearing Fault Diagnosis Under Fluctuating Speed Operations via Bayesian Augmented Lagrangian Analysis." IEEE Transactions on Industrial Informatics, 17(7), pp.4613-4623, July 2021. [IF: 11.648]
[J13] Z.Liu, B.Yang, X.Wang, and L.Zhang, "Wind Turbine Blade Bearing Fault Detection Under Low Speed and Heavy Load Conditions Us- ing Sparse Augmented Lagrangian Analysis." IEEE Transactions on Industry Applications, 57(3), pp.2791-2800, May-June 2021. [IF: 4.079]
[J14] Z.Liu, X.Wang, and L.Zhang, "Fault Diagnosis of Industrial Wind Turbine Blade Bearing using Acoustic Emission Analysis." IEEE Transactions on Instrumentation and Measurement, 69(9), pp. 6630-6639, Sept. 2020. [IF: 5.332]
[J15] Z.Liu, L.Zhang, and J.Carrasco, "Vibration analysis for large-scale wind turbine blade bearing fault detection with an empirical wavelet thresholding method." Renewable Energy, 146, pp.99-110, 2020. [IF: 8.634, ESI highly cited article]
[J16] Z.Liu and L.Zhang,"Naturally Damaged Wind Turbine Blade Bearing Fault Detection Using Novel Iterative Nonlinear Filter and Morphological Analysis." IEEE Transactions on Industrial Electronics, 67(10), pp. 8713-8722, Oct. 2020 (2019). [IF: 7.7]
[J17] Z.Liu, and L.Zhang, "A review of failure modes, condition monitoring and fault diagnosis methods for large-scale wind turbine bearings." Measurement, p.107002, 2019. [IF: 5.131, ESI highly cited article]
