毛磊 特任研究员 博士生导师
办公电话：0551-63607985
个人简介：
主要研究包括系统动态检测和数据处理技术、人工智能方法如深度学习、迁移学习等在新能源电池系统、智能制造设备中的应用。此外，还包括采用无损检测方法，对新能源电池在复杂运行条件下的性能衰减机理进行监测和分析。
研究方向：
新能源电池系统测试、智能诊断与控制；
智能制造设备运行可靠性分析及预测性维护；
信号处理、无损检测方法；
学习经历：
2012.11 英国爱丁堡大学 基础设施与环境 博士
2007.07 中国科学技术大学 机械电子工程 硕士
2004.07 合肥工业大学 交通工程 学士
工作经历：
2018.05-至今 中国科学技术大学精密机械与精密仪器系 特任研究员
2013.11-2018.03 英国拉夫堡大学 航天与汽车工程系 助理研究员
2012.01-2013.10 英国朴次茅斯大学 土木工程与测量系 助理研究员
学术任职：
国际工程师协会（International Association of Engineers）会员
国际预测与健康管理组织（Prognostics and Health Management Society）会员
中国振动工程协会故障诊断专业委员会理事
主要讲授课程：
研究生课程《机电控制系统分析与设计》；
研究生课程《机械振动理论》
招生信息：
发表文章：
近五年论文发表情况：
1、Mao, L., Jackson, L., Huang, W., Li, Z., Ben, D. (2020). Polymer electrolyte membrane fuel cell fault diagnosis and sensor abnormality identification using sensor selection method, Journal of Power Sources, 447, 227394.
2、Huang, W., Li, N., Selesnick, I., Shi, J., Wang, J., Mao, L., Jiang, X., Zhu, Z. (2020). Non-convex group sparsity signal decomposition via convex optimization for bearing fault diagnosis. IEEE Transactions on Instrumentation and Measurement, Early Access.
3、Abuker, Y. Y. A., Liu, Z., Mao, L. (2019). Fault classification of polymer electrolyte membrane fuel cell system based on empirical mode decomposition. 2nd World Congress on Condition Monitoring, WCCM 2019, December 2-5, Singapore.
3、Liu, Z., Abuker, Y. Y. A., Mao, L. (2019). A novel method of PEM fuel cell fault diagnosis based on signal-to-image conversion. 2nd World Congress on Condition Monitoring, WCCM 2019, December 2-5, Singapore.
4、Pan, W. T., Abuker, Y. Y. A., Mao, L. (2019). Investigation of feature effectiveness in fault diagnosis of PEM fuel cell system. The 10th IEEE Prognostics and System Health Management Conference. PHM-2019, October 25-27, Qingdao, China.
5、Mao, L., Jackson, L. (2018). Effect of sensor set size on polymer electrolyte membrane fuel cell fault diagnosis. Sensors, 18, 2777.
6、Mao, L., Jackson, L., Davies, B. (2018). Effectiveness of a novel sensor selection algorithm in PEM fuel cell on-line diagnosis. IEEE Transactions on Industrial Electronics. 65, 7301-7310.
7、Mao, L.,Jackson, L., Davies, B. (2018). Investigation of PEMFC fault diagnosis with consideration of sensor reliability. International Journal of Hydrogen Energy. 43, 16941-16948.
8、Mao, L., Goodall, P., Jackson, L., West, A. (2018). Enhanced condition monitoring of the machining process using wavelet packet transform, European Safety and Reliability Conference 2018, 17-21 June, 2018, Trondheim, Norway.
9、Vasilyev, A., Mao, L., Jackson, L., Andrews, J. (2018). The use of bond graph modelling in polymer electrolyte membrane fuel cell fault diagnosis, European Safety and Reliability Conference 2018, 17-21 June, 2018, Trondheim, Norway
10、Lisa Jackson, Melanie-Jane Stoneman, Heather Callaghan, Hanjing Zhang, Cristina Latsou, Sarah Dunnett, Lei Mao.(2018). Influencing Operational Policing Strategy by Predictive Service Analytics. 51st Hawaii International Conference on System Sciences, 03-06 January, 2018, Waikoloa Village, HI, United States.
11、Eleni Tsalapati, Thomas W. Jackson, William Johnson, Lisa Jackson, Andrey Vasilyev, Andrew West, Lei Mao, Ben Davies (2018). The Role of Sematic Technologies in Diagnostic and Decision Support for Service Systems. 51st Hawaii International Conference on System Sciences, 03-06 January, 2018, Waikoloa Village, HI, United States.
12、Mao, L., Lu, Y. (2017). Experimental study of sensitivity-aided application of artificial boundary condition frequencies for damage identification. Engineering Structures, 134, 253-261.
13、Mao, L., Barnett, S.J. (2017). Investigation of toughness of ultra high performance fibre reinforced concrete (UHPFRC) beam under impact loading. International Journal of Impact Engineering, 99, 26-38.
14、Mao, L. *,Jackson, L., Dunnett, S.J. (2017). Fault diagnosis of practical polymer electrolyte membrane (PEM) fuel cell system with data-driven approaches. Fuel Cells, 17, 247-258.
15、Mao, L., Jackson, L. (2016). Selection of optimal sensors for predicting performance polymer electrolyte membrane fuel cell. Journal of Power Sources, 328, 151-160.
16、Mao, L., Jackson, L. (2016). Comparative study on prediction of fuel cell performance using machine learning approaches. Lecture Notes in Engineering and Computer Science. 1, 52-57.
17、Mao, L., Lu, Y. (2016). Selection of optimal artificial boundary condition (ABC) frequencies for structural damage identification. Journal of Sound and Vibration, 374, 245-259.
承担科研项目：
国家自然科学基金面上项目，不完备数据下车用燃料电池电堆故障诊断的迁移学习方法研究，2020.1-2023.12，主持；
安徽省自然科学基金面上项目，基于深度学习和逻辑推理的燃料电池故障诊断关键技术研究，2019.7-2022.6，主持；
上海交通大学机械系统与振动国家重点实验室开放课题，多源数据下车用燃料电池实时故障诊断深度学习方法研究，2020.1-2021.12，主持；
中国科学院人才计划项目，2018-2020，主持；
中国科学技术大学人才引进启动经费，2018-2021，主持