Volume 39 Issue 8
Aug.  2024
Turn off MathJax
Article Contents
XU Xianxin, LI Juan, SUN Xiuhui, et al. RUL prediction for aero-engines based on Copula similarity[J]. Journal of Aerospace Power, 2023, 39(X):20220576 doi: 10.13224/j.cnki.jasp.20220576
Citation: XU Xianxin, LI Juan, SUN Xiuhui, et al. RUL prediction for aero-engines based on Copula similarity[J]. Journal of Aerospace Power, 2023, 39(X):20220576 doi: 10.13224/j.cnki.jasp.20220576

RUL prediction for aero-engines based on Copula similarity

doi: 10.13224/j.cnki.jasp.20220576
  • Received Date: 2022-08-08
    Available Online: 2023-11-20
  • In view of many degradation features of aero-engine performance and their mutual influence, the RUL(remaining useful life) prediction method of aero-engine based on Copula similarity was proposed considering the nonlinear correlations of the degradation features. The working state of the aero-engine was classified through K-means clustering, and a degradation model was established to select three sets of sensors with the most obvious degradation performance trend. Based on the Copula function, the correlation modeling and analysis of the selected three sets of sensors were carried out to build the Copula structure between engine sensors. The prediction of the remaining life of aero-engine was realized based on Copula similarity. The results showed that compared with traditional methods, the prediction errors of the aero-engine RUL based on Copula similarity were reduced by 13.053%, 31.328% and 74.602% respectively, and the prediction accuracy was improved.

     

  • loading
  • [1]
    XIONG Minglan,WANG Huawei,FU Qiang,et al. Digital twin-driven aero-engine intelligent predictive maintenance[J]. The International Journal of Advanced Manufacturing Technology,2021,114(11/12): 3751-3761.
    [2]
    XU Jiuping,WANG Yusheng,XU Lei. PHM-oriented integrated fusion prognostics for aircraft engines based on sensor data[J]. IEEE Sensors Journal,2014,14(4): 1124-1132.
    [3]
    LIAO Linxia,KÖTTIG F. Review of hybrid prognostics approaches for remaining useful life prediction of engineered systems,and an application to battery life prediction[J]. IEEE Transactions on Reliability,2014,63(1): 191-207.
    [4]
    LI Yiguang,NILKITSARANONT P. Gas turbine performance prognostic for condition-based maintenance[J]. Applied Energy,2009,86(10): 2152-2161.
    [5]
    王华伟,吴海桥. 基于信息融合的航空发动机剩余寿命预测[J]. 航空动力学报,2012,27(12): 2749-2755. WANG Huawei,WU Haiqiao. Residual useful life prediction for aircraft engine based on information fusion[J]. Journal of Aerospace Power,2012,27(12): 2749-2755. (in Chinese doi: 10.13224/j.cnki.jasp.2012.12.018

    WANG Huawei, WU Haiqiao. Residual useful life prediction for aircraft engine based on information fusion[J]. Journal of Aerospace Power, 2012, 27(12): 2749-2755. (in Chinese) doi: 10.13224/j.cnki.jasp.2012.12.018
    [6]
    SON K L,FOULADIRAD M,BARROS A,et al. Remaining useful life estimation based on stochastic deterioration models: a comparative study[J]. Reliability Engineering & System Safety,2013,112: 165-175.
    [7]
    GIANTOMASSI A,FERRACUTI F,BENINI A,et al. Hidden Markov model for health estimation and prognosis of turbofan engines[C]// International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Washington: ASME,2011: 681-689.
    [8]
    XIANG Sheng,QIN Yi,LUO Jun,et al. Multicellular LSTM-based deep learning model for aero-engine remaining useful life prediction[J]. Reliability Engineering & System Safety,2021,216: 107927.
    [9]
    MALINOWSKI S,CHEBEL-MORELLO B,ZERHOUNI N. Remaining useful life estimation based on discriminating shapelet extraction[J]. Reliability Engineering & System Safety,2015,142: 279-288.
    [10]
    LAM J,SANKARARAMAN S,STEWART B. Enhanced trajectory based similarity prediction with uncertainty quantification[C]//Annual Conference of the PHM Society. Texas: IJPHM,2014: 2513.1-2513.12.
    [11]
    KHELIF R,MALINOWSKI S,CHEBEL-MORELLO B,et al. RUL prediction based on a new similarity-instance based approach[C]//2014 IEEE 23rd International Symposium on Industrial Electronics. Piscataway,US: IEEE,2014: 2463-2468.
    [12]
    LIU Yingchao,HU Xiaofeng,ZHANG Wenjuan. Remaining useful life prediction based on health index similarity[J]. Reliability Engineering & System Safety,2019,185: 502-510.
    [13]
    YU Wennian,KIM I Y,MECHEFSKE C. An improved similarity-based prognostic algorithm for RUL estimation using an RNN autoencoder scheme[J]. Reliability Engineering & System Safety,2020,199: 106926.
    [14]
    PAN Zhengqiang,BALAKRISHNAN N. Reliability modeling of degradation of products with multiple performance characteristics based on gamma processes[J]. Reliability Engineering & System Safety,2011,96(8): 949-957.
    [15]
    ZHENG Jianfei,SI Xiaosheng,HU Changhua,et al. A nonlinear prognostic model for degrading systems with three-source variability[J]. IEEE Transactions on Reliability,2016,65(2): 736-750. doi: 10.1109/TR.2015.2513044
    [16]
    RASMEKOMEN N,PARLIKAD A K. Condition-based maintenance of multi-component systems with degradation state-rate interactions[J]. Reliability Engineering & System Safety,2016,148: 1-10.
    [17]
    SUN Fuqiang,WANG Ning,LI Xiaoyang,et al. 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. doi: 10.1109/ACCESS.2017.2735966
    [18]
    YANG Zhiyuan,ZHAO Jianmin,CHENG Zhonghua,et al. Reliability modeling of two-component system with degradation interaction based on copulas[C]//2018 Prognostics and System Health Management Conference. Piscataway,US: IEEE,2019: 138-143.
    [19]
    XI Zhimin,WANG Pingfeng. A Copula based sampling method for residual life prediction of engineering systems under uncertainty[C]//2012 IEEE Conference on Prognostics and Health Management. Piscataway,US: IEEE,2012: 1-9.
    [20]
    宋仁旺,张岩,石慧. 基于Copula函数的齿轮箱剩余寿命预测方法[J]. 系统工程理论与实践,2020,40(9): 2466-2474. SONG Renwang,ZHANG Yan,SHI Hui. Prediction method for the remaining useful life of gearbox based on copula function[J]. Systems Engineering-Theory & Practice,2020,40(9): 2466-2474. (in Chinese doi: 10.12011/1000-6788-2019-0307-09

    SONG Renwang, ZHANG Yan, SHI Hui. Prediction method for the remaining useful life of gearbox based on copula function[J]. Systems Engineering-Theory & Practice, 2020, 40(9): 2466-2474. (in Chinese) doi: 10.12011/1000-6788-2019-0307-09
    [21]
    SUKHANOVA E M. A test for independence of two multivariate samples[J]. Mathematical Methods of Statistics,2008,17(1): 74-86. doi: 10.3103/S1066530708010067
    [22]
    蔡菲,严正,赵静波,等. 基于Copula理论的风电场间风速及输出功率相依结构建模[J]. 电力系统自动化,2013,37(17): 9-16. CAI Fei,YAN Zheng,ZHAO Jingbo,et al. Dependence structure models for wind speed and wind power among different wind farms based on copula theory[J]. Automation of Electric Power Systems,2013,37(17): 9-16. (in Chinese doi: 10.7500/AEPS201207293

    CAI Fei, YAN Zheng, ZHAO Jingbo, et al. Dependence structure models for wind speed and wind power among different wind farms based on copula theory[J]. Automation of Electric Power Systems, 2013, 37(17): 9-16. (in Chinese) doi: 10.7500/AEPS201207293
    [23]
    ATIQUE F,ATTOH-OKINE N. Using copula method for pipe data analysis[J]. Construction and Building Materials,2016,106: 140-148. doi: 10.1016/j.conbuildmat.2015.12.027
    [24]
    SAXENA A,GOEBEL K,SIMON D,et al. Damage propagation modeling for aircraft engine run-to-failure simulation[C]//2008 International Conference on Prognostics and Health Management. Piscataway,US: IEEE,2008: 1-9.
    [25]
    WANG Tianyi,YU Jianbo,SIEGEL D,et al. A similarity-based prognostics approach for Remaining Useful Life estimation of engineered systems[C]//2008 International Conference on Prognostics and Health Management. Piscataway,US: IEEE,2008: 1-6.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (631) PDF downloads(57) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return