郑祥豪

2024-03-12阅读

 姓名:郑祥豪
 性别:
 职称:讲师,硕导
 学位:博士
 电子邮件: xianghao.zheng@foxmail.com

教育工作经历

2012.09~2016.06 华北电力大学(北京) 能源与动力工程 学士

2016.09~2022.06 华北电力大学(北京) 动力工程及工程热物理 硕士、博士

2023~至今 bat365app官网入口登录 bat365app官网入口登录 讲师

研究方向

1. 水泵水轮机(抽水蓄能机组)运行状态监测、智能流态识别、故障诊断

2. 信号处理算法、深度学习算法、大数据技术

科研简介

参与国家自然科学基金项目(雅砻江联合基金)、国家自然科学基金面上项目、国家重点研发计划等项目

代表性论著

[1] Zheng, X., Zhang, S., Zhang, Y.*, et al. Dynamic characteristic analysis of pressure pulsations of a pump turbine in turbine mode utilizing variational mode decomposition combined with Hilbert transform [J]. Energy, 2023, 280, p.128148.

[2] Zheng, X., Li, H., Zhang, S., et al. Hydrodynamic feature extraction and intelligent identification of flow regimes in vaneless space of a pump turbine using improved empirical wavelet transform and Bayesian optimized convolutional neural network [J]. Energy, 2023, 282, p.128705.

[3] Zheng, X., Lu, M., Li, H., et al. Dynamic feature extraction and recognition of flow states in vaneless space of a prototype reversible pump turbine in generating mode based on variational mode decomposition and energy index [J]. Journal of Energy Storage, 2022, 55, p.105821.

[4] Zheng, X., Zhang, Y.*, Li, J., et al. Influences of rotational speed variations on the flow-induced vibrational performance of a prototype reversible pump turbine in spin-no-load mode [J]. ASME Journal of Fluids Engineering, 2020, 142(1), p.011106.

[5] Zheng, X. and Zhang, Y*. De-noising of radiation pressure signal generated by bubble oscillation based on ensemble empirical mode decomposition [J]. Journal of Hydrodynamics, 2022, 34(5), pp.849-863.

[6] Zheng, X., Zhang, S., Zhang, Y.*, et al. Investigation on operational stability of main shaft of a prototype reversible pump turbine in generating mode based on ensemble empirical mode decomposition and permutation entropy [J]. Journal of Mechanical Science and Technology, 2022, 36(12), pp.6093-6105.

[7] Zheng, X., Zhang, Y.*, Zhang, Y. et al. Flow-Induced Instabilities of Reversible Pump Turbines [M]. Springer Cham, Switzerland, 2022. (ISBN: 978-3-031-18057-6)

[8] 张苏祺, 李浩, 张宇宁, 郑祥豪*等. 水泵水轮机复杂振动信号特征提取与智能识别 [J]. 水力发电学报, 2023, 42(12): 70-78.

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