孙单勋，中共党员、副教授、硕士研究生导师。2020年毕业于华北电力大学控制科学与工程学科检测技术与自动化装置专业。现任暨南大学能源电力研究中心/国际能源学院副教授。作为负责人主持国家级项目1项、省部级项目3项、中央高校项目1项；作为技术骨干参与国家国家自然科学基金重点及面上项目、教育部“111引智基地”项目及多项横向课题。近五年在相关领域发表各类学术期刊三十余篇，申请及授权专利多项；受邀担任多个国内外能源领域权威期刊审稿人。主要研究兴趣及方向包括：风电场重建预测与优化布置、海上风-浪耦合检测、风机故障检测、工业层析成像等。

2015/9-2020/8     华北电力大学（北京） 检测技术与自动化装置 工学博士

2011/9-2015/6     华北电力大学（北京） 测控技术与仪器           本科

2025/10 -  至今       暨南大学 国际能源学院/能源电力研究中心   副教授

2020/12-2025/10    暨南大学 国际能源学院/能源电力研究中心  讲师  

1. 多源信息融合及处理

2. 风电场信息重建及预测

3. 复杂浪涌检测技术

4. 海上风浪耦合机制模拟及研究

5. 风机故障监测及预警

6. 工业层析成像技术改进

[1] Sun S X, Xu Z J, Wang Z H, Cui S S, He T, Cai Y. Hierarchical learning method for array flow field prediction integrated with a deep neural network[J]. Journal of Zhejiang University-SCIENCE A, 2026: 1‑15.  

[2] Sun S X, Yang Z C, Cai Z H, Ye L F, Kou Y N, He T. Fusing SWAN priors with tucker decomposition: A training‑free framework for sparse wave field reconstruction[J]. Ocean Engineering, 2026, 353: 124786.  DOI: 10.1016/j.oceaneng.2026.124786

[3] 孙单勋,杨智聪,王卓恒,等.基于SWAN模型的波浪能发电站选址研究[J].太阳能学报,2026,47(01):730-737.DOI:10.19912/j.0254-0096.tynxb.2024-1593.

[4] Peng X Q, Zhuo H S, Peng S B, Li Y H, Hu S Q, Sun S X*. The fault diagnosis method for overall wind turbine systems with an integrated feature extraction method[J]. Wind Engineering, 2025, 49(1): 57‑70.  DOI: 10.1177/0309524X241307586

[5] Yan R Z, Li H, Chen M, Deng H, Sun S X*. Wind farm resolution enhancing through meso‑microscale coupled method with complex terrain[J]. Wind Engineering, 2025. DOI: 10.1177/0309524X251387838

[6] Zheng Y S, Ying X H, Jian W H, Wang Z, Wang H T, Sun S X*, Cai Y*, Zhao F Y. Functional ventilation building envelope integrated photovoltaic modules and phrase change material in subtropical climate: An in‑depth numerical investigation[J]. Energy, 2024, 307: 132579.  DOI: 10.1016/j.energy.2024.132579

[7] Sun S X, Cui S S, He T, Yao Q. An integrated deep neural network framework for predicting the wake flow in the wind field[J]. Energy, 2024, 291: 130400. DOI: 10.1016/j.energy.2024.130400

[8] Yao Q, Zhang Y M, Sun S X, Hu Y, Liu J Z, Fang F. Optimization of energy efficiency for offshore wind farms via wake modeling‑free NMPC[J]. Ocean Engineering, 2024, 305: 117923. DOI: 10.1016/j.oceaneng.2024.117923

[9] Zhang Y M, Luo B, Zhang Y Q, Sun S X. Model‑free compensation learning control of asymmetric hysteretic systems with initial state learning[J]. Journal of Sound and Vibration, 2024, 584: 118451. DOI: 10.1016/j.jsv.2024.118451

[10] Guan Y P, Xiao Y T, Qin L, Sun S X, Liu X, Yao Q. An admittance modeling method of grid‑tied converter in αβ‑frame under voltage sag[J]. IEEE Transactions on Transportation Electrification, 2023, 10(2): 3613‑3629.  DOI: 10.1109/TTE.2023.3312528

[11] Yao Q, Hu Y, Liu J Z, Zhao T Y, Qi X, Sun S X*. Power curve modeling for wind turbine using hybrid‑driven outlier detection method[J]. Journal of Modern Power Systems and Clean Energy, 2022, 11(4): 1115‑1125.  DOI: 10.35833/MPCE.2021.000769

[12] 崔双双,孙单勋*.分工况下风电机组各变量相关性研究[J].综合智慧能源,2022,44(12):49-55.

[13] 陈敏鑫,刘石,孙单勋,等.基于主成分分析的温度分布重建优化算法[J].仪表技术与传感器,2021,(03):102-105.

[14] Sun S X, Zhao Q, Liu S, Zhu H X, Ju Y, Zhang M, Liu J. Sensitivity guided image fusion for electrical capacitance tomography[J]. IEEE Transactions on Instrumentation and Measurement, 2020, 70: 1‑12.  DOI: 10.1109/TIM.2020.3043501

[15] Guo H B, Liu S, Cheng H Y, Sun S X, Ding J K, Guo H Q. Iterative computational imaging method for flow pattern reconstruction based on electrical capacitance tomography[J]. Chemical Engineering Science, 2020, 214: 115432.  DOI: 10.1016/j.ces.2019.115432

[16] Chen M X, Liu S, Sun S X, Liu Z Y, Zhao Y. Rapid reconstruction of simulated and experimental temperature fields based on proper orthogonal decomposition[J]. Applied Sciences, 2020, 10(11): 3729.  DOI: 10.3390/app10113729

[17] Sun S X, Liu S, Chen M X, Guo H B. An optimized sensing arrangement in wind field reconstruction using CFD and POD[J]. IEEE Transactions on Sustainable Energy, 2019, 11(4): 2449‑2456.  DOI: 10.1109/TSTE.2019.2961381

[18] Sun S X, Liu S, Zhang G C. The rapid establishment of large wind fields via an inverse process[J]. Applied Sciences, 2019, 9(14): 2847.  DOI: 10.3390/app9142847

[19] Liu J, Liu S, Sun S X, Wang M, Schlaberg I H I, Lu G. Data fusion for integrated planar and cylindrical tomographic flame sensing[J]. Flow Measurement and Instrumentation, 2018, 62: 213‑222.  DOI: 10.1016/j.flowmeasinst.2017.09.006

[20] Sun S X, Liu S, Liu J, Schlaberg H I. Wind field reconstruction using inverse process with optimal sensor placement[J]. IEEE Transactions on Sustainable Energy, 2018, 10(3): 1290‑1299.  DOI: 10.1109/TSTE.2018.2865512

1. 国家自然科学基金青年项目，62201226，多维信息耦合驱动的海上风场层析成像研究，结题，主持

2. 广东省基础与应用基础研究基金海上风电联合基金-面上项目，2022A1515240021，在研，主持

3. 广东省基础与应用基础研究基金青年项目，2021A1515110665，结题，主持

4. 南方海上风电联合开发有限公司企业委托项目，在研，主持

5. 中国博士后科学基金面上项目，2022M711344，结题，主持

6. 中央高校基本科研业务费专项资金资助项目，21621042，结题，主持

7. 国家自然科学基金面上项目，61871181, 结题, 参与

8. 国家自然科学基金面上项目，61571189，结题，参与

9. 教育部高等学校学科创新111引智计划项目，结题，参与

本科生基础必修课《信号与系统》《信号与系统实验》

本科生专业选修课《检测技术》 《自动化专业英语》

硕士研究生学位课《机器学习》