费成巍
近期热点
资料介绍
个人简历
学习/工作经历:2018/10至今复旦大学航空航天系青年研究员2017/12-2018/09 香港科技大学机械与航空航天工程系,研究员(Research Fellow)2015/12-2017/12 香港理工大学机械工程系,博士后研究员2014/09-2015/11 香港理工大学机械工程系,副研究员(Research Associate)2010/09-2014/07 北京航空航天大学航空宇航推进理论与工程专业,工学博士开设课程:本科生:《航空发动机原理》、《航空燃气涡轮机结构设计》研究生:《系统可靠性设计》、《现代燃气涡轮发动机结构设计》、《航空发动机状态监视与故障诊断》主要科研项目:(1)两机专项项目子课题,XXXX多失效模式与多构件相关性的可靠性设计及验证,负责人;(2)民机专项项目子课题,基于XXXX 的运行可靠性分析与反馈技术研究,在研,负责人;(3)航天科学技术基金项目,在研,负责人(4)国家自然科学基金面上项目,基于矢量代理模型的工程系统优化与可靠性设计方法,2020.01-2023.12, 60万,在研,负责人;(5)复旦大学引进人才启动经费,涡轮叶尖间隙分解协调全局优化与验证,2018.10-202021.09,100万,在研,负责人;(6)国家自然科学基金青年项目,工程优化与可靠性设计的分布式协同代理模型方法,2017.01-2019.12,20万,已结,负责人;(7)“香江学者”计划资助项目,2015.12-2017.12, 60万,已完成,负责人;(8)中国博士后科学基金项目(一等),8万,负责人;(9)国家自然科学基金面上项目,叶轮机械颤振稳定性的不确定性预测方法研究,84万,在研,主要参与人;(10)国家自然科学基金面上项目,机械动态装配可靠性设计方法研究,63万,主要完成人;(11)香港教育研究基金,基于流固耦合分析技术的叶片振动分析与抑制,60万,主要完成人;(12)国家自然科学基金面上项目,机械动态装配关系的稳健协同优化设计方法研究,65万,主要完成人;奖项与荣誉:1)沈阳市自然科学学术成果三等奖(排名第3),20182)航空宇航科学与技术学科全国优秀博士学位论文(全国5篇/年),20163)香江学者奖,20154)北京航空航天大学优秀博士学位论文,20155)教育部博士生学术新人奖,2012研究成果:已出版学术论文100余篇(SCI检索80余篇(一作/通讯近70篇),1区top期刊30余篇),学术专著2本和会议文章若干.出版专著:[1]费成巍,艾延廷,田晶. 基于信息融合的航空发动机整机振动故障诊断技术[M]. 科学出版社, 2020.[2]Fei CW, Sun D. Experimental Investigation on Rotordynamic Characteristics and Rotor System Stability of a Novel Negative Dislocated Seal (Chapter)[M]. Top 5 Contributions in Shock and Vibration, 2019, 1-29.[3]费成巍,复杂机械动态装配可靠性设计理论与方法研究[D],博士学位论文,2014. 航空宇航科学与技术学科全国优秀博士学位论文(2016年,5篇/年).本课题组主要从事飞机/发动机(转子)故障诊断、性能与可靠性评估、疲劳失效分析、结构概率设计与多学科优化等方面研究。欢迎有志于从事航空航天(特别是航空发动机)事业、且具有航空航天工程、机械工程、力学、大数据、智能学习等相关学科背景的本科生、研究生和博士后加入本课题组。有意者请联系研究领域
航空燃气涡轮发动机结构可靠性与健康监测,主要包括:(1)航空发动机结构优化与可靠性设计(2)航空发动机性能与健康评估(3)转子/轴承故障检测、诊断与预测技术(4)多学科仿真与建模、模型修正与验证(5)机器学习与智能算法在可靠性与健康监测方面的应用等""近期论文
发表文章(2016-,*通讯作者):[1]Fei CW, Li H, Zhu ZZ, Lu C*, An LQ, Li SL. Whole-process design and experimental validation of landing gear lower drag stay with global/local linked driven optimization strategy [J]. Chinese Journal of Aeronautics, accepted.[2]Fei CW, Li H, Liu HT, Lu C*, Keshtegar B*. Multilevel nested reliability-based design optimization with hybrid intelligent regression for operating assembly relationship [J]. Aerospace Science and Technology, 2020, 103: 105906.[3]Sun D, Zhou M, Zhao H, Lu J, Fei CW*, Li H. Numerical and experimental investigations on windage heating characteristics of labyrinth seals [J]. Journal of Aerospace Engineering. 2020, 33(5): 04020057.[4]Lu C, Feng YW, Fei CW*, Bu SQ. Improved decomposed-coordinated Kriging modeling strategy for dynamic probabilistic analysis of multi-component structures [J]. IEEE Transactions on Reliability. 2020,69(2): 440-457.[5]Lu C, Feng YW, Fei CW*, Bu SQ. Decomposed-coordinated framework with enhanced extremum Kriging for multi-component dynamic probabilistic failure analyses[J]. IEEE Access, 2019, 7(1): 163287-163300.[6]Fei CW*, Lu C, Liem R.P. Decomposed-coordinated surrogate modelling strategy for compound function approximation and a turbine blisk reliability evaluation [J]. Aerospace Science and Technology, 2019, 95:105466.[7]Song LK, Bai GC, Fei CW*, Tang WZ. Multi-failure probabilistic design for turbine bladed disks using neural network regression with distributed collaborative strategy [J], Aerospace Science and Technology, 2019, 92: 464-477.[8]Tian J, Ai YT, Fei CW*, Zhang FL. Dynamic modeling and simulation of inter-shaft bearings with localized defects excited by time-varying displacement [J]. Journal of Vibration and Control, 2019, 25(8): 1436-1446.[9]Song LK, Bai GC, Fei CW*, Wen J. Probabilistic LCF life assessment of turbine discs using DC-based wavelet neural network regression [J]. International Journal of Fatigue 2019, 119: 204-219.[10]Lu C, Feng YW,Rhea. P Liem, Fei CW*. Improved kriging with extremum response surface method for structural dynamic reliability and sensitivity analyses [J].Aerospace Science and Technology, 2018, 76:164-175.[11]Fei CW, Choy YS, Tang WZ*, Bai GC. Multi-feature entropy distance approach with vibration and AE signals for process feature extraction and diagnosis of rolling bearing faults[J]. Structural Health Monitoring-An International Journal, 2018, 17(2):156-168.[12]Song LK, Wen J, Fei CW, Bai GC, Distributed collaborative probabilistic design of multi-failure structure with fliud-structure internaction using fuzzy neural network of regression [J]. Mechanical Systems and Signal Processing, 2018, 104: 72-84.[13]Gao HF*, Wang AJ, Bai GC, Wei CM, Fei CW. Substructure-based distributed collaborative probabilistic analysis method for low-cycle fatigue damage assessment of turbine bladed-disk[J]. Aerospace Science and Technology, 2018, 79:636-646.[14]Zhai X, Fei CW*, Wang JJ, Choy YS. A stochastic model updating strategy-based improved response surface model and advanced Monte Carlo simulation[J]. Mechanical Systems and Signal Processing, 2017, 82(1): 323-338.[15]Song LK, Fei CW*, Bai GC, Yu LC. Dynamic neural network method-based improved PSO and BR algorithms for transient probabilistic analysis of flexible mechanism [J]. Advanced Engineering Informatics, 2017, 33: 144-153.[16]Song LK, Fei CW*, Wen J, Bai GC. Multi-objective reliability-based design optimization approach of complex structure with multi-failure modes[J]. Aerospace Science and Technology, 2017, 64:52-62.[17]Fei CW*, Choy YS, Hu DY, Bai GC, Tang WZ. Dynamic probabilistic design approach of high-pressure turbine blade-tip radial running clearance [J]. Nonlinear Dynamics, 2016, 86(1):205-223.[18]Fei CW*, Choy YS, Hu DY, Bai GC, Tang WZ.Transient probabilistic analysis for turbine blade-tip radial clearance with multiple components and multi-physics fields based on DCERSM[J].Aerospace Science and Technology, 2016, 50: 62-70.[19]Sun D, N Liu N, Fei CW*, Hu GY, Ai YT and Choy YS. Theoretical and numerical investigation on the leakage flow characteristics of brush seals based on fluid-structure interaction[J]. Aerospace Science and Technology, 2016, 58:207-216[20]Zhang CY, Song LK, Fei CW*, Lu C, Xie YM. Advanced multiple response surface method for reliability sensitivity analysis of turbine blisk with multi-physics coupling[J]. Chinese Journal of Aeronautics, 2016, 29(4):962-971.会议文章:[1]Fei CW*, Lu C, Tang WT, An Enhanced Network Learning Method for Dynamic Probabilistic LCF Evaluation of Turbine Blisk [C]. 2019 Prognostics & System Health Management Conference (PHM-2019), Qingdao, China, Oct. 26-29, 2019.[2]Lu C, Feng YW, Fei CW*. An enhanced weighted regression model for compressor blisk safety analysis regarding dynamics and uncertainty [C]. 2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE 2019). August 06-09, 2019, Zhangjiajie, Hunan, China;中国振动工程学会会员中国振动工程学会转子动力学分会理事美国航空航天协会(AIAA)会员中国航空协会(动力专业分会)(CSAA)会员美国机械工程学会(ASME)会员国际期刊Aerospace Engineering: An International Journal编委国际期刊Journal of dynamics of Machines编委国际期刊Advances in Acoustics and Vibration客座主编(Lead Guest Editor)国际期刊Advances in Mechanical Engineering客座主编(Lead Guest Editor)国际期刊审稿人:AIAA JournalJournal of Power and PropulsionMechanical System and Signal ProcessingNonlinear DynamicsAerospace Science and TechnologyJournal of Aerospace EngineeringChinese Journal of AeronauticsInternational Journal for Numerical Methods in EngineeringEnergyInternational Journal of FatigueJournal of Engineering for Gas Turbine and Power等20余个国际期刊 相关热点