题目：Condition Monitoring, Control, and Diagnostic Technologies and their Application in Aerospace engineering and Renewable systems

报告人：岑朝辉 博士

时间：2018年8月28日上午9:00

地点：动力与机械学院报告厅

欢迎各位师生踊跃参加！

摘要：

Condition monitoring, diagnostics, prognostics and health management are effective means to reduce the downtime and the maintenance cost, and to improve the reliability, capacity factor, and lifespan of industrial systems. These issues have drawn more and more attention because of complexities of modern industrial systems, and significant research effort is being taken by both the academia and the industry to advance the technologies within the framework of Industry 4.0.

In this talk, Dr Zhaohui will present several demonstration applications about condition monitoring, control and diagnostic technologies applied in Spacecraft, UAV, smart grid systems, and Energy storage systems, which based on his prior R&D experience in China, UK and GCC. Related test and diagnostics tools/instrument/facilities for condition monitoring will be shown in this presentation, and Key methodologies of fault detection and diagnosis such as Adaptive observer, Grey-box neural network model will be introduced.  Also, Fault-tolerant Control and nonlinear control methods such as Nonlinear Dynamics Inversion Control in aerospace engineering will be discussed.

主讲人介绍：

Dr. Zhaohui Cen is now a Research Engineer/Scientist of Electronics at Qatar Environment and Energy Research Institute (QEERI), member of Qatar foundation. He got his PhD degree from Department of Electronic and information engineering, Huazhong University of Science and technology (HUST) in 2011. Prior to join QEERI, he worked as research associates at Lincoln school of engineering, the University of Lincoln, UK, the department of Automatic Control and system engineering, the University of Sheffield, UK, and department of electrical engineering, UAE university, UAE. His background and skills mainly involves measurement & control, modeling & simulation, condition monitoring & fault diagnosis, data analysis & artificial intelligence for industrial systems such as Energy storage systems, Smart grid, aircrafts, UAVs, Spacecraft. He also specializes in SCADA/HMI, power electronics, embedded systems, as well as rapid control prototype tools such as dSPACE, eMegaSim and NI compact RIO to automate field demonstrations. He have extensive research/engineering project experiences and also published nearly 40 peer-reviewed papers in renowned journals such as 《International Journal of Neural Systems》, 《IEEE Trans. on Reliability》, 《Journal of Power Source》and 《Solar Energy Materials and Solar Cells》. He is also an owner of three patents and one copyright of software.

报告摘要：

状态监测、故障诊断/预诊断及健康管理是减少工业系统宕机时间及维护成本，并提升可靠性、容限因素及寿命长度的有效手段。鉴于现代工业系统变得日趋复杂，尤其是航天飞行器等关键工业系统凸显的可靠性问题也更具挑战性，对可靠性保障技术演化的需求进一步提高。同时，当下工业4.0及工业物联网等一系列新型技术需求及概念的流行也促进了工业界和学术界在该领域仍不遗余力进行技术研究及开发。

在此报告中，岑朝辉博士将基于其先前在卡塔尔、英国、阿联酋及中国的科研工作经历，以航天器、无人机、智能微电网/电池储能系统等工业系统为研究对象，重点汇报状态监测、控制及诊断技术在上述工业系统的技术开发及应用验证工作。本报告将介绍状态监测与诊断所涉及的仪器及实验设施开发工作，同时也对自适应模型观测器、灰盒神经网络模型等故障检测与诊断先进方法在电子电路系统/航天器/无人机/锂电池中的应用进行重点阐述。另外，还会对航空航天飞行器中涉及的故障容错控制及非线性控制等控制方面研究工作进行讨论。

个人简介：

岑朝辉博士，现就职于卡塔尔环境与能源究院智能电网研究组，任职研究工程师/科学家。分别于2005年、2007年、2011年获得华中科技大学电子与信息工程系本科、硕士与博士学位，图像识别与人工智能研究所博士后，2012-2013先后在阿联酋大学、英国谢菲尔德大学、英国林肯大学任助理研究员。研究兴趣与专长领域涵盖复杂工业设备及设施故障预诊断与健康管理,物联网工业自动化等智能系统相关技术，从事航空航天无人自主系统、无人飞行器、人工智能、储能系统、光伏及智能电网等方面的研究及开发工作，具备丰富的国内外学术届研究及工业届研发经验，目前已拥有授权专利3 项及1 项软件著作权，在国际期刊及会议发表论文约40篇（一作及通信作者期刊论文13篇，其中SCI索引 10篇）。