张九思

个人信息Personal Information

硕士生导师

性别：男

毕业院校：哈尔滨工业大学

学历：博士研究生毕业

学位：工学博士学位

在职信息：在职人员

所在单位：自动化工程学院

学科：仪器科学与技术

办公地点：电子科技大学清水河校区成电国际创新中心D311

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部分代表性论文

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[1] J. Zhang, K. Qian, H. Luo, Y. Liu, X. Qiao, X. Xu, J. Tian. Process monitoring for tower pumping units under variable operational conditions: From an integrated multitasking perspective. Control Engineering Practice, 2025, 156: 106229.

[2] J. Zhang, K. Zhang, Y. An, H. Luo, S. Yin. An Integrated Multitasking Intelligent Bearing Fault Diagnosis Scheme Based on Representation Learning Under Imbalanced Sample Condition. IEEE Transactions on Neural Networks and Learning Systems, 2024, 35(5): 6231-6242.（ESI热点论文，ESI 高被引论文）

[3] J. Zhang, C. Huang, M.Y. Chow, X. Li, J. Tian, H. Luo, S. Yin. A Data-model Interactive Remaining Useful Life Prediction Approach of Lithium-ion Batteries Based on PF-BiGRU-TSAM. IEEE Transactions on Industrial Informatics, 2024, 20(2): 1144-1154.（ESI 高被引论文）

[4] J. Zhang, J. Tian, H. Luo, S. Wu, S. Yin, O. Kaynak. Prognostics for the Sustainability of Industrial Cyber-Physical Systems: From an Artificial Intelligence Perspective. IEEE Transactions on Industrial Cyber-Physical Systems, 2024, 2: 495-507.

[5] J. Zhang, J. Tian, P. Yan, S. Wu, H. Luo, S. Yin. Multi-hop graph pooling adversarial network for cross-domain remaining useful life prediction: A distributed federated learning perspective. Reliability Engineering & System Safety, 2024, 244: 109950.（ESI 高被引论文）

[6] J. Zhang, J. Tian, A. M. Alcaide, J. I. Leon, S. Vazquez, L. G. Franquelo, H. Luo, S. Yin. Lifetime Extension Approach Based on Levenberg-arquardt Neural Network and Power Routing of DC-DC Converters. IEEE Transactions on Power Electronics, 2023, 38(3): 10280-10291.（ESI 高被引论文）

[7] J. Zhang, X. Li, J. Tian, H. Luo, S. Yin. An integrated multi-head dual sparse self-attention network for remaining useful life prediction. Reliability Engineering & System Safety, 2023, 233: 109096.（ESI 热点论文，ESI 高被引论文）

[8] J. Zhang, X. Li, J. Tian, Y. Jiang, H. Luo, S. Yin. A variational local weighted deep sub-domain adaptation network for remaining useful life prediction facing cross-domain condition. Reliability Engineering & System Safety, 2023, 231: 108986.（ESI 热点论文，ESI 高被引论文）

[9] J. Zhang, J. Tian, M. Li, J. I. Leon, L. G. Franquelo, H. Luo, S. Yin. A Parallel Hybrid Neural Network with Integration of Spatial and Temporal Features for Remaining Useful Life Prediction in Prognostics. IEEE Transactions on Instrumentation and Measurement, 2023, 72: 1-12. （ESI 高被引论文）

[10] J. Zhang, Y. Jiang, X. Li, H. Luo, S. Yin, O. Kaynak. Remaining Useful Life Prediction of Lithium-ion Battery with Adaptive Noise Estimation and Capacity Regeneration Detection. IEEE/ASME Transactions on Mechatronics, 2023, 28(2): 632-643.（ESI 高被引论文）

[11] J. Zhang, Y. Jiang, X. Li, M. Huo, H. Luo, S. Yin. An adaptive remaining useful life prediction approach for single battery with unlabeled small sample data and parameter uncertainty. Reliability Engineering & System Safety, 2022, 222: 108357.（ESI 高被引论文）

[12] J. Zhang, Y. Jiang, S. Wu, X. Li, H. Luo, S. Yin. Prediction of remaining useful life based on bidirectional gated recurrent unit with temporal self-attention mechanism. Reliability Engineering & System Safety, 2022, 221: 108297.（ESI 热点论文，ESI 高被引论文）