个人简介

成刘，男，汉族，工学博士，硕士生导师。对机器学习技术理论、监督学习/半监督学习/无监督学习/自监督学习/小样本学习/迁移学习/大模型/深度因果推理等深度学习技术理论，及其相关应用如非理想数据条件下旋转机械跨领域故障诊断、时间序列数据预测等具有较深入研究。曾在相关国际高水平期刊上发表SCI论文二十余篇，并担任IEEE TII、IEEE TIP、MSSP、ADEVI、KBS、Measurement等期刊审稿人，现任新疆大学机械工程学院机械工程系教师。

研究方向

机电装备数字孪生与智能运维、智慧水质预测、视觉缺陷检测

工作与教育经历

2026.08至今      新疆大学 机械工程学院 讲师

2025.11-2026.06   深圳市新凯来技术有限公司 算法工程师

2019.09-2025.09   东北大学 工学博士

2016.09-2019.01   东北大学 工学硕士

2012.09-2016.06   东北大学 工学学士

科研项目

（1）“航空发动机使用寿命及可靠性加速试验方法研究”，2021-01-30 至 2024-12-30，参与

（2）钢铁扁平材全流程智能化关键技术创新方法应用示范，2018-10-30 至 2021-09-30，参与

（3）多品种航空航天复杂锻件智能产线管控与集成技术，2019-12-12 至 2022-11-12，参与

（4）智能点检在线监测系统研发，2018-09-30至2022-03-30，参与

（5）烧结机智能远程漏风监测系统研发，2018-09至2022-03，参与

（6）水质-设备在线监测与远程自动加药智慧水务系统开发与研究，2024-08至2024.12，参与

（7）涡轮叶片用高温合金增材制造形性控制技术研发，参与

论文

1. R Duan, L. Cheng*, Z. Shen, et al. R3PTL: Refine, Reuse, and Remix - An Innovative Partial Transfer Learning Framework for Intelligent Machinery Fault Diagnosis with Sample Scarcity. Mechanical Systems and Signal Processing, 2025. (SCI, 中科院一区, IF= 10.2, 通讯)

2. Z. Liu, R. Wang, L. Cheng*, et al. Partial domain adaptation ProtoNet: A partial transfer meta-learning framework for cross-domain fault diagnosis with limited labeled data. Structural Health Monitoring-An International Journal, 2026. (SCI, 中科院二区, IF=5.9, 通讯)

3. L. Cheng, X. Kong*, Y. Zhang, et al. A Novel Causal Feature Learning-Based Domain Generalization Framework for Bearing Fault Diagnosis with A Mixture of Data From Multiple Working Conditions and Machines. Advanced Engineering Informatics, 2024. (SCI, 中科院一区, IF = 11.5)

4. L. Cheng, H. Qi, R. Ma, X. Kong*, et al. FS-PTL: A Unified Few-Shot Partial Transfer Learning Framework for Partial Cross-Domain Fault Diagnosis under Limited Data Scenarios. Knowledge-Based Systems, 2024. (SCI, 中科院一区, IF = 8.0)

5. L. Cheng, R. Wang, H. Qi, X. Kong*, et al. S3M: Two-Stage-Based Semi-Self-Supervised Method for Intelligent Bearing Fault Diagnosis. IEEE Transactions on Instrumentation and Measurement, 2023. (SCI, 中科院二区, IF = 7.0)

6. L. Cheng, X. Kong*, J. Zhang, M. Yu. A Novel Adversarial One-Shot Cross-Domain Network for Machinery Fault Diagnosis With Limited Source Data”. IEEE Transactions on Instrumentation and Measurement, 2022. (SCI, 中科院二区, IF = 7.0)

7. H. Qi, L. Cheng, X. Kong*, et al. WDLS: Deep Level-Set Learning for Weakly-Supervised Aeroengine Defect Segmentation. IEEE Transactions on Industrial Informatics, 2023. (SCI, 中科院一区, IF =12.3)

8. H. Qi, X. Kong*, Z. Liu, J. Gu, L. Cheng. SAIT: Harnessing Sparse Annotations and Intrinsic Tasks for Semi-Supervised Aeroengine Defect Segmentation. IEEE Transactions on Industrial Informatics, 2024. (SCI, 中科院一区, IF =12.3)

9. R. Ma, X. Kong, B. Wu, L. Cheng. Frequency-Enhanced AutoEncoding Decomposed Transformer (FEADformer) for Total Phosphorus Prediction in Industrial Recirculating Cooling Water Systems. Journal of Environmental Management, 2026. (SCI, 中科院二区, IF=9.2)

10. C. Jin, X. Kong*, L. Cheng, et al. Numerical Simulation of the Co-Combustion of Coke and Biochar Coupled with Methane Injection in Iron Ore Sintering Processes. International Journal of Hydrogen Energy, 2024. (SCI, 中科院二区, IF=8.1)

11. L. Ma, X. Kong, L. Cheng, et al. Fast scanning pattern selection in laser directed energy deposition via simulation data-driven based deep regression method. Journal of Manufacturing Processes, 2025. (SCI, 中科院一区, IF=7.8)

12. H. Qi, X. Kong*, Z. Wang, J. Gu, L. Cheng. AeroClick: An Advanced Single-Click Interactive Framework for Aeroengine Defect Segmentation. Expert Systems with Applications, 2024. (SCI, 中科院一区, IF=7.5)

13. H. Qi, X. Kong*, L. Cheng, et al. Addressing Fine-Grained Lake Water Body Extraction: A Hybrid Approach Combining Vision Transformer and Geodesic Active Contour. IEEE Transactions on Geoscience and Remote Sensing, 2024. (JCR 1区, 中科院 1区 TOP, IF=7.5)

14. C. Jin, X. Kong*, L. Cheng, et al. Mathematical Modeling and Characteristics Evaluation of Coke Replacing with Commercial Biochar in Iron Ore Sintering Process. Fuel, 2024. (JCR 1区, 中科院 1区TOP, IF=6.7)

15. J. Zhang, X. Kong*, X. Li, Z. Hu, L. Cheng, et al. Fault Diagnosis of Bearings Based on Deep Separable Convolutional Neural Network and Spatial Dropout. Chinese Journal of Aeronautics, 2022. (JCR 1区, 中科院 1区, IF=4.0)

16. Z. Shen, X. Kong*, L. Cheng, et al. Fault Diagnosis of the Rolling Bearing by a Multi-Task Deep Learning Method Based on a Classifier Generative Adversarial Network. Sensors, 2024. ( JCR 2区, IF=3.4)

17. J. Zhang, X. Kong*, L. Cheng, et al. Intelligent Fault Diagnosis of Rolling Bearings Based on Continuous Wavelet Transform-Multiscale Feature Fusion and Improved Channel Attention Mechanism. Eksploatacja i Niezawodnosc - Maintenance and Reliability, 2023. (SCI, JCR 1区, IF=2.5)

18. Z. Hu, T. Han, Z. Wang, L. Cheng, et al. A Deep Feature Extraction Approach for Bearing Fault Diagnosis Based on Multi-Scale Convolutional Autoencoder and Generative Adversarial Networks. Measurement Science and Technology, 2022. (JCR 1区, IF=2.39)

19. L. Kong, Z. Deng, L. Cheng, et al. Reaction Behaviors of Al-Killed Medium-Manganese Steel with Glazed MgO Refractory. Metallurgical and Materials Transactions B, 2018. ( JCR 2区, IF=1.95)

20. J. Guo, X. Kong*, L. Cheng, et al. Numerical Study of Rock-Breaking Performance of Cutters in Heterogeneous Sand-Cobble Ground. Journal of Mechanical Science and Technology, 2022. (JCR 3区, IF=1.81)

21. Z. Deng, L. Cheng, et al. Effect of Refractory on Nonmetallic Inclusions in Si–Mn‐Killed Steel. Steel Research International, 2019. (JCR 2区, IF=1.81)

专利

1.轴承复合故障诊断方法、装置、介质及设备

2.轴承故障信号的分析方法及装置、存储介质、计算机设备

3.基于跨尺度晶体塑性模型的叶片辊轧成形仿真方法及装置

4.图像去噪方法、装置、电子设备及计算机存储介质

5.一种用于生产含硫易切削钢的精炼渣及循环利用方法

主要奖励

第七届全国设备管理与技术创新成果（技术类）混合机智能点检在线监测系统

联系方式

邮箱：neustuchengliu@163.com

地址：新疆大学博达校区机械工程学院（乌鲁木齐市水磨沟区华瑞街777号）

欢迎对本人研究方向感兴趣，思想积极、勤奋负责的学生加入！