Citation: | LIU Junqiang, HU Dongbin, PAN Chunlu, et al. Remaining useful life prediction of multi-stage aero-engine based on super statistics[J]. Journal of Beijing University of Aeronautics and Astronautics, 2021, 47(1): 56-64. doi: 10.13700/j.bh.1001-5965.2019.0647(in Chinese) |
Traditional aero-engine Remaining Useful Life (RUL) model cannot objectively describe the multi-stage degeneration process, and the accuracy of RUL prediction is low. To solve this problem, a new multi-stage RUL prediction model for RUL prediction is proposed, including super statistics theory, mutation point detection, Unscented Kalman Filter (UKF) and nonlinear prediction. In the paper, a Multi-stage Segmentation Filtering based on Super statistics (BS-MSF) theory algorithm is proposed. In this algorithm, first, super statistics theory is used to conduct mutation point detection and divide the health data of aero-engine into multiple degradation phases. Then, UKF is used to filter the fused time-varying parameters. Finally, the real RUL of the aero-engine is estimated by nonlinear fitting. nonlinear fitting, and the aero-engine data was released by National Aeronautics and Space Administration. Simulation results show that the presented method has better adaptability in predicting engine performance degradation, smaller fitting error, and more accurate prediction of RUL. The prediction accuracy is 5.5% higher than that of single-stage method.
[1] |
ALFORD L D.The problem with aviation COTS[J].IEEE Aerospace and Electronic Systems Magazine, 2001, 16(2):33-37. doi: 10.1109/62.904242
|
[2] |
李军, 杨旭.航空发动机健康管理系统功能架构[J].航空动力学报, 2019(1):71-74. https://www.cnki.com.cn/Article/CJFDTOTAL-HKDL201901019.htm
LI J, YANG X.Functional framework of aero engine health management system[J].Journal of Aerospace Power, 2019(1):71-74(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-HKDL201901019.htm
|
[3] |
郑金涛, 邓四二, 张文虎, 等.航空发动机主轴滚子轴承非典型失效机理[J].航空学报, 2019, 41(5):305-317. https://www.cnki.com.cn/Article/CJFDTOTAL-HKXB202005022.htm
ZHENG J T, DENG S E, ZHANG W H, et al.A typical failure mechanism of aeroengine spindle roller bearing[J].Acta Aeronauticaet Astronautica Sinica, 2019, 41(5):305-317(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-HKXB202005022.htm
|
[4] |
GARCÍA NIETO P J, GARCÍA-GONZALO E, SÁNCHEZ LASHERAS F, et al.Hybrid PSO-SVM-based method for forecasting of the remaining useful life for aircraft engines and evaluation of its reliability[J].Reliability Engineering and System Safety, 2015, 138:219-231. doi: 10.1016/j.ress.2015.02.001
|
[5] |
CAVARZERE A, VENTURINI M.Application of forecasting methodologies to predict gas turbine behavior over time[C]//ASME 2011 Turbo Expo: Turbine Technical Conference and Exposition, 2011.
|
[6] |
任淑红, 左洪福.基于性能衰退的航空发动机剩余寿命组合预测方法[J].机械科学与技术, 2011, 30(1):23-29. https://www.cnki.com.cn/Article/CJFDTOTAL-JXKX201101006.htm
REN S H, ZUO H F.A Combined prediction method for the residual-life of civil aviation engines based on performance degradation[J].Mechanical Science and Technology for Aerospace Engineering, 2011, 30(1):23-29(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JXKX201101006.htm
|
[7] |
赵广社, 吴思思, 荣海军.多源统计数据驱动的航空发动机剩余寿命预测方法[J].西安交通大学学报, 2017, 51(11):150-155, 172. https://www.cnki.com.cn/Article/CJFDTOTAL-XAJT201711021.htm
ZHAO G S, WU S S, RONG H J.A multi-source statistics data-driven method for remaining for remaining useful life prediction of aircraft engine[J].Journal of Xi'an Jiaotong University, 2017, 51(11):150-155, 172(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-XAJT201711021.htm
|
[8] |
张马兰.基于空地数据链的航空发动机剩余寿命预测研究[D].南京: 南京航空航天大学, 2015: 38-48.
ZHANG M L.Research on remaining useful life prognostics for aero-engine based on ACARS[D].Nanjing: Nanjing University of Aeronautics and Astronautics, 2015: 38-48(in Chinese).
|
[9] |
RAMIN M, MING J Z.An integrated framework for online diagnostic and prognostic health monitoring using a multistate deterioration process[J].Reliability Engineering and System Safety, 2014, 124(C):92-104. http://www.sciencedirect.com/science/article/pii/S0951832013003037
|
[10] |
BARALDI P, MANGILI F, ZIO E.A Kalman filter-based ensemble approach with application to turbine creep prognostics[J].IEEE Transactions on Reliability, 2012, 61(4):966-977. doi: 10.1109/TR.2012.2221037
|
[11] |
AN D, CHOI J H, KIM N H.Prognostics 101:A tutorial for particle filter-based prognostics algorithm using Matlab[J].Reliability Engineering and System Safety, 2013, 115(1):161-169. http://www.sciencedirect.com/science/article/pii/S0951832013000549
|
[12] |
张马兰.基于分阶段非线性融合的粒子滤波预测算法[J].武汉理工大学学报(交通科学与工程版), 2016, 40(6):1106-1110. doi: 10.3963/j.issn.2095-3844.2016.06.032
ZHANG M L.Particle filter prognostics algorithm based on multi-phase and non-linear fusion[J].Journal of Wuhan University of Technology (Transportation Science and Engineering), 2016, 40(6):1106-1110(in Chinese). doi: 10.3963/j.issn.2095-3844.2016.06.032
|
[13] |
黄亮, 刘君强, 贡英杰.基于Wiener过程的发动机多阶段剩余寿命预测[J].北京航空航天大学学报, 2018, 44(5):1081-1087. doi: 10.13700/j.bh.1001-5965.2017.0383
HUAGN L, LIU J Q, GONG Y J.Multi-phase residual life prediction of engines based on Wiener process[J].Journal of Beijing University of Aeronautics and Astronautics, 2018, 44(5):1081-1087(in Chinese). doi: 10.13700/j.bh.1001-5965.2017.0383
|
[14] |
BECK C, COHEN E G D.Superstatistics[J].Physica A:Statistical Mechanics and its Applications, 2003, 322:267-275. doi: 10.1016/S0378-4371(03)00019-0
|
[15] |
李天梅, 邱静, 刘冠军.基于故障率的测试性验证试验故障样本分配方案[J].航空学报, 2009, 30(9):1661-1665. doi: 10.3321/j.issn:1000-6893.2009.09.017
LI T M, QIU J, LIU G J.Allocation plan of failure samples based on failure rate in testability[J].Acta Aeronautica et Astronautica Sinica, 2009, 30(9):1661-1665(in Chinese). doi: 10.3321/j.issn:1000-6893.2009.09.017
|
[16] |
JULIER S J.The spherical simplex unscented transformation[C]//Proceedings of the IEEE American Control Conference.Piscataway: IEEE Press, 2003, 3: 2430-2433.
|
[17] |
黄小平, 王岩.卡尔曼滤波原理及应用:MATLAB仿真[M].北京:电子工业出版社, 2015:103-107.
HUANG X P, WANG Y.Kalman filter principle and application:MATLAB simulation[M].Beijing:Electronic Industry Press, 2015:103-107(in Chinese).
|
[18] |
邱恺, 黄国荣, 陈天如, 等.卡尔曼滤波过程的稳定性研究[J].系统工程与电子技术, 2005, 27(1):33-35. doi: 10.3321/j.issn:1001-506X.2005.01.010
QIU K, HUANG G R, CHEN T R, et al.Study of the stability of Kalman filtering process[J].Journal of Systems Engineering and Electronics, 2005, 27(1):33-35(in Chinese). doi: 10.3321/j.issn:1001-506X.2005.01.010
|
[19] |
陈晶, 李波, 高智, 等.航空发动机气路系统故障机理分析[J].长春工业大学学报, 2017, 38(4):402-409. https://www.cnki.com.cn/Article/CJFDTOTAL-JLGX201704015.htm
CHEN J, LI B, GAO Z, et al.Fault mechanism analysis of aero-engine gas-path system[J].Journal of Changchun University, 2017, 38(4):402-409(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JLGX201704015.htm
|
[20] |
熊耀刚.基于贝叶斯网络的可靠性概率风险评价方法研究[D].赣州: 江西理工大学, 2013: 45-49.
XIONG Y G.Reliability probability risk evaluation method Based on bayesian network[D].Ganzhou: Jiangxi University of Science and Technology, 2013: 45-49(in Chinese).
|