孙富强
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职???????称?????????讲师
行政职务?????????无
所在机构?????????可靠性与环境工程技术国家级重点实验室
座???????机?????????
办公地址?????????为民楼608
电子邮箱?????????sunfuqiang@buaa.edu.cn
个人主页????????

--> 研究方向
1、多退化过程与随机冲击竞争失效系统建模；2、多元相依加速退化模型；3、基于机器学习的退化建模与寿命预测；4、加速退化试验动态优化设计方法；5、耐久性仿真与试验验证。主持国家重点研发计划子课题、国家自然科学基金项目及多项横向课题。目前已发表SCI论文16篇，获批发明专利10余项，编写2部中国航空工业集团公司标准《QAVIC 05050-2018 航空电子产品可靠性强化试验》和《机载产品加速性能退化试验》。 教育背景
2006.9-2012.6 北京航空航天大学可靠性与系统工程学院，获系统工程专业工学博士学位 2002.9-2006.7 北京航空航天大学机械工程及自动化学院，获机械工程及自动化专业学士学位 2015.8-2016.8 美国阿肯色大学(University of Arkansas)工业工程系，访问 学术兼职
中国系统工程学会会员中国运筹学会会员INFORMS Member担任质量可靠性领域IEEE Transactions on Reliability, Reliability Engineering & System Safety, Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability、IEEE Access等国际高水平期刊的审稿人。 讲授课程
参与讲授研究生课程《加速试验技术》 奖励与荣誉
2012年北京航空航天大学“蓝天新秀”2018年北京航空航天大学优秀硕士学位论文指导教师指导的学生获北京市优秀毕业生、国家奖学金、北京航空航天大学优秀硕士学位论文等奖励与荣誉。 学术成果
1、主持/参与的纵向科研项目 （1）国家自然科学基金青年科学基金项目，相依情形下多退化过程与随机冲击竞争失效系统可靠性建模 方法（**），2017.01- 2019.12，项目负责人 （2）国家重点研发计划“新能源汽车”专项子课题：商用车集成控制器可靠性与寿命评测技术研究， 2018.07-2020.12，项目负责人 （3）某重点型号课题： 某型***通用质量特性试验与技术支撑，2017.01- 2019.12，参与 （4）973项目子课题：光纤陀螺寿命和精度长期保持的加速验证模型，2013.01- 2015.12，项目负责人 （5）中央高校基本科研业务费项目，基于支持向量机的性能退化建模与寿命预测技术研究，2013.03- 2013.12，项目负责人2、目前已发表的科研论文 （1）期刊论文[1] Li Xiaoyang, Chen Wenbin, Sun Fuqiang, Liao Haitao*, Kang Rui, Li Renqin. Bayesian accelerated acceptance sampling plans for a lognormal lifetime distribution under Type-I censoring [J]. Reliability Engineering & System Safety, 2018, 171: 78-86.[2] Fuqiang Sun, Ning Wang, Xiaoyang Li*, Yuanyuan Cheng. A Time-Varying Copula-based Prognostics Method for Bivariate Accelerated Degradation Testing. Journal of Intelligent and Fuzzy Systems, 2018, 34(6): 3707-3718.[3] Fuqiang Sun, Ning Wang, Xiaoyang Li, Wei Zhang*. Remaining Useful Life Prediction for a Machine With Multiple Dependent Features Based on Bayesian Dynamic Linear Model and Copulas [J]. IEEE Access, 2017, 5: 16277-16287.[4] Fuqiang Sun, Ning Wang, Jingjing He*, Xuefei Guan, Jinsong Yang. Lamb Wave Damage Quantification Using GA-Based LS-SVM [J]. Materials, 2017, 10(6): 648.[5] Li Xiaoyang, Yuqing Hu, Fuqiang Sun*, Rui Kang. A Bayesian Optimal Design for Sequential Accelerated Degradation Testing [J]. Entropy, 2017, 19(7): 325.[6] Fuqiang Sun, Xiaoyang Li, Haitao Liao*, Xiankun Zhang. A Bayesian least-squares support vector machine method for predicting the remaining useful life of a microwave component. Advances in Mechanical Engineering, 2017, 9(1): 1–9.[7] Wang Hongxun, Zhang Weifang, Sun Fuqiang, Zhang Wei*. A Comparison Study of Machine Learning Based Algorithms for Fatigue Crack Growth Calculation [J]. Materials, 2017, 10(5): 543.[8] Sun Fuqiang, Liu Le, Li Xiaoyang, Liao Haitao*. Stochastic Modeling and Analysis of Multiple Nonlinear Accelerated Degradation Processes through Information Fusion [J]. Sensors, 2016, 16(8): 1242.[9] Le Liu, Xiaoyang Li, Fuqiang Sun *, Ning Wang. A general accelerated degradation model based on Wiener process. Materials, 2016, 9(12): 981.[10] Fuqiang Sun, Jingcheng Liu, Xiaoyang Li, Haitao Liao*. Reliability analysis with multiple dependent features from a vibration-based accelerated degradation test. Shock and Vibration, 2016: **.[11] Fu-Qiang Sun*, Xiao-Yang Li, Tong-Min Jiang, Statistical analysis of constant-stress accelerated degradation testing with multiple performance parameters, Transactions of the Canadian Society for Mechanical Engineering, 2016, 40(4): 631-644.[12] Fuqiang Sun*, Jingcheng Liu, Ziqing Cao, Xiaoyang Li, Tongmin Jiang. Modified Norris-Landzberg Model and Optimum Design of Temperature Cycling ALT [J]. Strength of Materials, 2016, 48(1): 135-145[13] Le Liu, Xiao-Yang Li, Tong-Min Jiang and Fu-Qiang Sun. Utilizing Accelerated Degradation and Field Data for Life Prediction of Highly Reliable Products[J]. Quality and Reliability Engineering International, 2016, 32(7): 2281-2297.[14] Li Xiaoyang, Gao Pengfei, Sun Fuqiang. Acceptance sampling plan of accelerated life testing for lognormal distribution under time-censoring[J]. Chinese Journal of Aeronautics, 2015, 28(3): 814–821.[15] Xiaoyang Li, Tongmin Jiang, Fuqiang Sun, Jing Ma. Constant stress ADT for superluminescent diode and parameter sensitivity analysis. EKSPLOATACJA I Niezawodno?? - Maintenance and Reliability. 2010, 46(2): 21-26 （2）会议论文[1] Sun Fuqiang, Wang Ning, Li Xiaoyang, Jiang Tongmin. The temperature fluctuation modeling and compensation for the degradation data of super-luminescent diode [C]; proceedings of the 2017 Prognostics and System Health Management Conference (PHM-Harbin), 9-12 July 2017.[2] Dong Dong, Li Xiaoyang., Sun Fuqiang. Life prediction of jet engines based on LSTM-recurrent neural networks [C]; proceedings of the 2017 Prognostics and System Health Management Conference (PHM-Harbin), 9-12 July 2017. [3] Sun Fuqiang, Wang Ning, Fan Ye, Jiang Tongmin. An imputation method for missing degradation data based on regression analysis and RBF neural network [C]//?EPIN M, BRI? R. The 27th European Safety and Reliability Conference (ESREL 2017). Portoro?, Slovenia. pp. 3021–3026.[4] Fuqiang Sun, Xiaoyang Li, Tongmin Jiang. Life and reliability evaluation of tuner by constant-stress accelerated degradation testing method, Safety and Reliability: Methodology and Applications - Proceedings of the European Safety and Reliability Conference, ESREL 2014, p 837-841, 2015.[5] Li Xiao-Yang, Liu Le, Kang Rui, Xu Dan, Sun Fuqiang, Lee Jay. Experiments for PHM: Needs, developments and challenges. Safety and Reliability: Methodology and Applications - Proceedings of the European Safety and Reliability Conference, ESREL 2014, p569-576, 2015[6] Xiankun Zhang, Fuqiang Sun, Xiaoyang Li. A Degredation Interval Prediction Method Based on RBF Neural Network, Proceeding of 2014 International Conference on Reliability, Maintainability and Safety, Guangzhou, 6-8 Aug. 2014, pp.310- 315[7] Ye Fan, Fuqiang Sun, Tongmin Jiang. An improved RI for missing degradation data based on Brownian motion. RAMS, 2014 [8] Sun Fuqiang, Li Xiaoyang, Jiang Tongmin. A Performance Degradation Interval Prediction Method Based on Support Vector Machine and Fuzzy Information Granulation[M]//Engineering Asset Management- Systems, Professional Practices and Certification. Springer International Publishing, 2015: 363-374.[9] Fan Ye, Sun Fuqiang, Jiang Tongmin. Application and Comparison of Imputation Methods for Missing Degradation Data[M]//Engineering Asset Management-Systems, Professional Practices and Certification. Springer International Publishing, 2015: 1607-1614.[10] Sun Fuqiang, Jiang Tongmin, Li Xiaoyang, Fan Ye. An intelligent prognostic method for SSADT based on SVM. Chemical Engineering Transactions, v 33, p 103-108, 2013 (PHM 2013 - Milan)
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