（1）个人信息
许凡，男，湖北仙桃人，2017年博士毕业于武汉大学机械电子工程专业，2017年7月至2020年9月在香港城市大学进行博士后研究工作，师从Kwok-Leung Tsui教授（数理统计领域知名专家，美国弗吉尼亚理工学院Professor，曾是香港城市大学Chair Professor, 美国佐治亚理工学院教授）。现为bet356体育亚洲版在线官网智能制造系副研究员与硕士研究生导师。（联系邮箱：xufanfanxu@163.com或xufanfanxu@whut.edu.cn）
（2）主要研究方向：
1.旋转机械设备振动信号分析、故障诊断、寿命预测；
2.数据挖掘聚类分析在故障诊断寿命预测中的应用；
3. 基于无监督深度学习的故障敏感特征选择与识别；
4. 水泥回转窑机械设备状态在线状态监测与诊断（长期研究方向）。
（3）招生条件与期望
学生勤奋，认真，性格活泼。
（4）主持、在研与参与项目：
[1]2023.01-2025.12,无监督深度学习动态自适应列车轮对轴承健康状态诊断研究，国家自然科学青年基金项目(编号:52205168)，30万,项目主持人；
[2]2022.03-2023.10，无监督深度学习动态自适应轴承诊断研究，学校自主创新基金项目(编号:223104001)，5万,在研，项目主持人；
[3] 2016.01-2020.12,Safety， Reliablity and Disruption Management of High-Speed Rail and Metro Systems(高速铁路和地铁系统的安全、可靠性和中断管理), 香港研究资助局重大专项项目(编号:T32-101/15-R), 4462万元(港币),已结题,作为核心成员参与；
[4]2019.01-2023.12,Enhancing safety,punctualityand ride comfortof railway transportations:From local metro to global high-speed rail network(提高铁路运输的安全性、准时性和乘坐舒适性：从本地地铁到全球高速铁路网络)香港研究资助局专项项目(编号: R-5020-18),589万元(港币),在研，作为核心成员主要参与；
[5] 2018.01-2020.12, Reliablity and Degradation Modeling for Rechargeable Battery(可再充电电池的可靠性和退化建模),香港研究资助局专项项目(编号:CityU 11206417), 58万元(港币), 结题, 作为核心成员参与；
[6]2010.01-2012.12,基于动态关联规则元规则的通信客户流失预测模型的研究,甘肃省科技厅甘肃省科技支撑计划项目(编号:1011GKCA040),10万元, 结题,作为核心成员参与；
（5）部分代表作（第一作者与通信SCI论文，*为通信作者）
1.Fan Xu, Lei Wang. Constructing a health indicator for bearing degradation assessment via an unsupervised and enhanced stacked autoencoder. Advanced Engineering Informatics. (2022) 53:101708. (SCI收录，JCR一区, IF: 7.862).
2.Fan Xu, Zhelin Huang, Fangfang Yang, Dong Wang, KwokLeung Tsui. Constructing a health indicator for roller bearings by using a stacked auto-encoder with an exponential function to eliminate concussion. Applied Soft Computing. (2020) 89: 106119. (SCI收录，JCR一区, IF:8.263).
3.Fan Xu, Peter Wai Tat TSE, Yiu, Lun Tse. Roller bearing fault diagnosis using stacked denoising autoencoder in deep learning and Gath–Geva clustering algorithm without principal component analysis and data label. Applied Soft Computing. (2018) 73: 898-913. (SCI收录，JCR一区, IF: 8.263).
4.Fan Xu, Fangfang Yang, Zhelin Huang, Kwok Leung Tsui. Life prediction of lithium-ion batteries based on stacked denoising autoencoders. Reliability Engineering & System Safety. (2021) 208: 107396. (SCI收录，JCR一区, IF: 7.427).
5.Fangfang Yang, Dong Wang, Fan Xu*, Zhelin Huang, Kwok Leung Tsui. Lifespan Prediction of Lithium-ion Batteries based on Various Extracted Features and Gradient Boosting Regression Tree Model. Journal of Power Sources. (2020) 476: 228654. (SCI收录，JCR一区, IF: 9.794).
6.Fan Xu, Xin Shu, Ruoli Tang, Xin Li, Health indicator construction for roller bearing based on an unsupervised deep belief network with a novel sigmoid zero local minimum point model. Structural Health Monitoring-An International Journal, (2020) 1-14. (SCI收录，JCR一区, IF:5.710). https://doi.org/10.1177/1475921720963951
7.Fan Xu, Fangfang Yang, Xiaomao Fan, Zhelin Huang, KwokLeung Tsui. Extracting degradation trends for roller bearings by using a moving-average stacked auto-encoder and a novel exponential function. Measurement. (2020). 152:107371. (SCI收录，JCR一区, IF: 5.131).
8.Fan Xu, Zhou Fang, Ruoli Tang, Xin Li, KwokLeung Tsui. An unsupervised and enhanced deep belief network for bearing performance degradation assessment. Measurement. (2020) 162: 107902 (SCI收录，JCR一区, IF: 5.131).
9.Yang Zhao, Fan Xu*, Xiaomao Fan, Hailiang Wang, Kwok-Leung Tsui, Yurong Guan. Prediction of Wellness Condition for Community-Dwelling Elderly via ECG Signals Data-Based Feature Construction and Modeling. Int. J. Environ. Res. Public Health (2022), 191, 1136. https://doi.org/10.3390/ijerph191711136(SCI). (SCI收录，JCR一区, IF: 3.364).
10.Fan Xu, W Tse Peter. Automatic roller bearings fault diagnosis using DSAE in deep learning and CFS algorithm. Soft Computing. (2019) 23(13): 5117-5128. (SCI收录，JCR二区).