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Article

Zhang, Ming, Amiri, Amirpiran, Xu, Yuchun, Bastin, Lucy and Clark, Tony (2024). Self-adaptive digital twin of fuel cell for remaining useful lifetime prediction. International Journal of Hydrogen Energy, 89 , pp. 634-647.

Amaitik, Nasser, Buckingham, Christopher, Zhang, Ming and Xu, Yuchun (2024). A Fuzzy Synthesis Approach for Hierarchical Decision Analysis to Select Optimum Repair Technique. Procedia CIRP, 126 , pp. 52-57.

Hu, Youxi, Liu, Chao, Zhang, Ming, Lu, Yuqian, Jia, Yu and Xu, Yuchun (2024). An ontology and rule-based method for human–robot collaborative disassembly planning in smart remanufacturing. Robotics and Computer-Integrated Manufacturing, 89 ,

Lyu, Pin, Cheng, Yihong, Zhang, Ming, Yu, Wenbing, Xia, Liqiao and Liu, Chao (2024). GPSC-GAN: A Data Enhanced Model for Intelligent Fault Diagnosis. IEEE Transactions on Instrumentation and Measurement, 73 ,

Zhang, Ying, Zhang, Ming, Liu, Chao, Feng, Zhipeng and Xu, Yuchun (2024). Reliability enhancement of state of health assessment model of lithium-ion battery considering the uncertainty with quantile distribution of deep features. Reliability Engineering and System Safety, 245 ,

Zhang, Ying, Li, Yan-Fu, Zhang, Ming and Wang, Huan (2024). A novel health indicator by dominant invariant subspace on Grassmann manifold for state of health assessment of lithium-ion battery. Engineering Applications of Artificial Intelligence, 130 ,

Amaitik, Nasser, Zhang, Ming, Xu, Yuchun, Thomson, Gareth A., Kolokas, Nikolaos, Maisuradze, Alexander, Peschl, Michael and Tzovaras, Dimitrios (2023). Towards sustainable manufacturing by enabling optimum selection of life extension strategy for industrial equipment based on cost modelling. Journal of Remanufacturing, 13 (3), pp. 263-282.

Liang, Xiaoxia, Zhang, Ming, Feng, Guojin, Wang, Duo, Xu, Yuchun and Gu, Fengshou (2023). Few-Shot Learning Approaches for Fault Diagnosis Using Vibration Data: A Comprehensive Review. Sustainability, 15 (20),

Zhang, Ming, Sharma, Vikas, Wang, Zezhong, Jia, Yu, Hossain, Abul Kalam and Xu, Yuchun (2023). Online Big-Data Monitoring and Assessment Framework for Internal Combustion Engine with Various Biofuels. International Journal of Automotive Manufacturing and Materials, 2 (2),

Lv, Chunpu, Huang, Jingwei, Zhang, Ming, Wang, Huangang and Zhang, Tao (2023). Semi-Supervised Deep Kernel Active Learning for Material Removal Rate Prediction in Chemical Mechanical Planarization. Sensors, 23 (9),

Liang, Xiaoxia, Zhang, Ming, Feng, Guojin, Xu, Yuchun, Zhen, Dong and Gu, Fengshou (2023). A Novel Deep Model with Meta-learning for Rolling Bearing Few-shot Fault Diagnosis. Journal of Dynamics, Monitoring and Diagnostics, 2 (2), 102–114.

Zhang, Ming, Sharma, Vikas, Jia, Yu, Hossain, A K and Xu, Yuchun (2023). Data-driven Approach for Condition Assessment of a Diesel Engine Powered with Various Biodiesels. SAE Technical Papers, 2023-0 ,

Hu, Youxi, Liu, Chao, Zhang, Ming, Jia, Yu and Xu, Yuchun (2023). A Novel Simulated Annealing-Based Hyper-Heuristic Algorithm for Stochastic Parallel Disassembly Line Balancing in Smart Remanufacturing. Sensors, 23 (3),

Zhang, Ming, Wang, Duo, Amaitik, Nasser and Xu, Yuchun (2022). A Distributional Perspective on Remaining Useful Life Prediction with Deep Learning and Quantile Regression. IEEE Open Journal of Instrumentation and Measurement, 1 ,

Zhang, Ming, Lu, Yang, Hu, Youxi, Amaitik, Nasser and Xu, Yuchun (2022). Dynamic Scheduling Method for Job-Shop Manufacturing Systems by Deep Reinforcement Learning with Proximal Policy Optimization. Sustainability, 14 (9),

Zhang, Ming, Amaitik, Nasser, Wang, Zezhong, Xu, Yuchun, Maisuradze, Alexander, Peschl, Michael and Tzovaras, Dimitrios (2022). Predictive Maintenance for Remanufacturing Based on Hybrid-Driven Remaining Useful Life Prediction. Applied Sciences, 12 (7),

Amaitik, Nasser, Zhang, Ming, Wang, Zezhong, Xu, Yuchun, Thomson, Gareth A., Xiao, Yiyong, Kolokas, Nikolaos, Maisuradze, Alexander, Garcia, Oscar, Peschl, Michael and Tzovaras, Dimitrios (2022). Cost Modelling to Support Optimum Selection of Life Extension Strategy for Industrial Equipment in Smart Manufacturing. Circular Economy and Sustainability ,

Wang, Duo, Zhang, Ming, Xu, Yuchun, Lu, Weining, Yang, Jun and Zhang, Tao (2021). Metric-based meta-learning model for few-shot fault diagnosis under multiple limited data conditions. Mechanical Systems and Signal Processing, 155 ,

Zhang, Ming, Amaitik, Nasser, Xu, Yuchun, Rossini, Rosaria, Bosi, Ilaria and Cedola, Ariel Pablo (2021). A New Implementation of Digital Twins for Fault Diagnosis of Large Industrial Equipment. Journal of Robotics and Mechanical Engineering Research, 1 (1),

Zhang, Ming, Wang, Duo, Lu, Weining, Yang, Jun, Li, Zhiheng and Liang, Bin (2019). A Deep Transfer Model With Wasserstein Distance Guided Multi-Adversarial Networks for Bearing Fault Diagnosis Under Different Working Conditions. IEEE Access, 7 , 65303 - 65318.

Zhang, Ming, Jiang, Zhinong and Gao, Jinji (2016). Dynamic analysis of integrally geared compressors with varying workloads. Shock and Vibration, 2016 ,

Book Section

Amaitik, Nasser, Zhang, Ming, Xu, Yuchun, Clark, Tony and Bastin, Lucy (2024). Utilising Digital Twins for Smart Maintenance Planning of Fuel Cell in Electric Vehicles. IN: MATEC Web of Conferences. GBR: EDP Sciences.

Ma, Qianxia, Zhang, Ming, Xu, Yuchun, Song, Jingyan and Zhang, Tao (2021). Remaining Useful Life Estimation for Turbofan Engine with Transformer-based Deep Architecture. IN: 2021 26th International Conference on Automation and Computing (ICAC). IEEE.