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多应力耦合条件下氧气浓缩器退化建模

潘晋新 景博 焦晓璇 王生龙 黄崧琳 方玲

潘晋新,景博,焦晓璇,等. 多应力耦合条件下氧气浓缩器退化建模[J]. 北京航空航天大学学报,2023,49(2):472-481 doi: 10.13700/j.bh.1001-5965.2021.0260
引用本文: 潘晋新,景博,焦晓璇,等. 多应力耦合条件下氧气浓缩器退化建模[J]. 北京航空航天大学学报,2023,49(2):472-481 doi: 10.13700/j.bh.1001-5965.2021.0260
PAN J X,JING B,JIAO X X,et al. Degradation modeling of oxygen concentrator in multiple stress coupling[J]. Journal of Beijing University of Aeronautics and Astronautics,2023,49(2):472-481 (in Chinese) doi: 10.13700/j.bh.1001-5965.2021.0260
Citation: PAN J X,JING B,JIAO X X,et al. Degradation modeling of oxygen concentrator in multiple stress coupling[J]. Journal of Beijing University of Aeronautics and Astronautics,2023,49(2):472-481 (in Chinese) doi: 10.13700/j.bh.1001-5965.2021.0260

多应力耦合条件下氧气浓缩器退化建模

doi: 10.13700/j.bh.1001-5965.2021.0260
基金项目: 航空科学基金(20200033096001);陕西省自然科学基金(2022JQ-586)
详细信息
    作者简介:

    潘晋新:男,硕士研究生。主要研究方向:装备可靠性评估与数据智能分析

    景博:女,博士,教授,博士生导师。主要研究方向:飞机故障预测与健康管理

    焦晓璇:男,博士,讲师。主要研究方向:装备智能检测

    通讯作者:

    E-mail:1091313541@qq.com

  • 中图分类号: V245.3

Degradation modeling of oxygen concentrator in multiple stress coupling

Funds: Aeronautical Science Foundation of China (20200033096001); Nature Science Foundation of Shaanxi Province (2022JQ-586)
More Information
  • 摘要:

    耦合应力条件下的建模是故障预测与健康管理领域的难点问题。以氧气浓缩器地面试验退化建模为例,针对试验中2种应力线性相关且耦合作用于氧气浓缩器退化的问题,提出了一种机理模型与数据驱动联合的偏微分方程建模方法。基于退化机理分析建立偏微分方程的基本形式,利用数据驱动的方法确定方程具体参数。通过偏微分方程建模,对2种应力进行解耦分析,确定引气湿度的增加会加快氧气浓缩器的退化速率,发现随着氧气浓缩器工作性能的退化,氧气浓缩器氧分压对引气压力的敏感性减弱,确定氧分压随引气压力变化斜率为健康因子。通过卡尔曼滤波器模式识别,确定氧气浓缩器退化可分为平稳阶段与退化阶段,与实际服役环境下氧气浓缩器退化数据对比,验证了氧气浓缩器两阶段退化特性。

     

  • 图 1  氧气浓缩器原理

    Figure 1.  Schematic diagram of oxygen concentrator

    图 2  分子筛床工作流程

    Figure 2.  Workflow of screen bed

    图 3  分子筛结构

    Figure 3.  Molecular sieve structure

    图 4  氧气浓缩器退化试验硬件连接图

    Figure 4.  Diagram of hardware connection for oxygen concentrator degradation test

    图 5  氧气浓缩器全寿命周期退化数据

    Figure 5.  Life cycle degradation data of oxygen concentrator

    图 6  x=0.14时的退化数据

    Figure 6.  Degeneration data (x=0.14)

    图 7  x=0.3时的退化数据

    Figure 7.  Degeneration data (x=0.3)

    图 8  x=0.7时的退化数据

    Figure 8.  Degeneration data (x=0.7)

    图 9  x=1时的退化数据

    Figure 9.  Degeneration data (x=1)

    图 10  联合参数x与氧分压关系随时间的变化

    Figure 10.  Relationship between x and oxygen partial pressure over time

    图 11  全寿命周期内氧分压与引气压力比值变化

    Figure 11.  Variation of ratio of oxygen partial pressure to bleed air pressure over lifespan

    图 12  Switching卡尔曼滤波原理[18]

    Figure 12.  Principle of Switching Kalman filter[18]

    图 13  退化数据拟合

    Figure 13.  Degradation data fitting

    图 14  退化模式识别

    Figure 14.  Degeneration pattern recognition

    图 15  实际服役环境下氧气浓缩器退化数据

    Figure 15.  Degradation data of oxygen concentrator in actual service environment

    图 16  环境因素限制条件下氧气浓缩器退化数据

    Figure 16.  Degradation data of oxygen concentrator under restriction of environmental factors

    表  1  氧气浓缩器退化试验数据记录

    Table  1.   Oxygen concentrator degradation test data

    引气压力/MPa引气湿度/(g·L−1)引气温度/℃氧浓度/%氧分压/kPa
    0.1432.847038.134.9
    0.361.786959.857.5
    0.780.636963.961.8
    1.094.477164.363.5
    0.774.38716563.3
    0.354.006964.462.4
    0.1434.026938.337.9
    下载: 导出CSV

    表  2  健康因子性能指标

    Table  2.   Health factor performance indicators

    指标HI
    本文0.14MPa0.3MPa0.7MPa1MPa
    Corr0.9680.7180.8520.9030.877
    Mon0.7960.5820.6030.6160.573
    下载: 导出CSV
  • [1] 彭宇, 刘大同. 数据驱动故障预测和健康管理综述[J]. 仪器仪表学报, 2014, 35(3): 481-495. doi: 10.19650/j.cnki.cjsi.2014.03.001

    PENG Y, LIU D T. Overview of data-driven fault prediction and health management[J]. Chinese Journal of Scientific Instrument, 2014, 35(3): 481-495(in Chinese). doi: 10.19650/j.cnki.cjsi.2014.03.001
    [2] 张景元, 何玉珠, 崔唯佳. 基于多应力退化模型的智能电表可靠寿命预估[J]. 北京航空航天大学学报, 2017, 43(8): 1662-1669. doi: 10.13700/j.bh.1001-5965.2016.0582

    ZHANG J Y, HE Y Z, CUI W J. Reliability life prediction of smart electricity meter based on multi-stress degradation model[J]. Journal of Beijing University of Aeronautics and Astronautics, 2017, 43(8): 1662-1669(in Chinese). doi: 10.13700/j.bh.1001-5965.2016.0582
    [3] 张振华, 史建新, 李小龙, 等. 增压锅炉冷态启动过程中耦合应力及疲劳分析[J]. 哈尔滨工程大学学报, 2021, 42(7): 997-1002. doi: 10.11990/jheu.201911066

    ZHANG Z H, SHI J X, LI X L, et al. Coupling stress and fatigue analysis of pressurized boiler during cold start-up of the supercharged boiler[J]. Journal of Harbin Engineering University, 2021, 42(7): 997-1002(in Chinese). doi: 10.11990/jheu.201911066
    [4] 李超, 刘竞中, 王海宏, 等. 多载荷耦合作用下涡旋压缩机动涡旋盘的应力应变分析[J]. 流体机械, 2020, 48(10): 30-35. doi: 10.3969/j.issn.1005-0329.2020.10.006

    LI C, LIU J Z, WANG H H, et al. Stress and strain analysis of orbiting scroll of scroll compressor under coupled action of multiple loads[J]. Fluid Machinery, 2020, 48(10): 30-35(in Chinese). doi: 10.3969/j.issn.1005-0329.2020.10.006
    [5] WU J Y. A geometrically regularized gradient-damage model with energetic equivalence[J]. Computer Methods in Applied Mechanics and Engineering, 2018, 328(1): 612-637.
    [6] RAHI A. Vibration analysis of multiple-layer microbeams based on the modified couple stress theory: Analytical approach[J]. Archive of Applied Mechanics, 2020, 91(12): 1-10.
    [7] WILEMAN A, PERINPANAYAGAM S, ASLAM S. Physics of failure (PoF) based lifetime prediction of power electronics at the printed circuit board level[J]. Applied Sciences, 2021, 11(6): 23-34.
    [8] SUN B, LI Y, WANG Z L. A combined physics of failure and Bayesian network reliability analysis method for complex electronic systems[J]. Process Safety and Environmental Protection, 2021, 148(2): 698-710.
    [9] 柳小伟, 宋辉, 郭美卿, 等. 基于电化学-应力耦合模型的锂离子电池硅/碳核壳结构的模拟与优化[J]. 物理学报, 2021, 70(17): 178201.

    LIU X W, SONG H, GUO M Q, et al. Simulation and optimization of silicon/carbon core-shell structures in lithium-ion batteries based on electrochemical-mechanical coupling model[J]. Acta Physica Sinica, 2021, 70(17): 178201(in Chinese).
    [10] 齐琦, 宋月. 带有测量误差的自适应维纳模型研究[J]. 统计与决策, 2020, 36(12): 55-58. doi: 10.13546/j.cnki.tjyjc.2020.12.011

    QI Q, SONG Y. Study on adaptive Wiener model with measurement errors[J]. Statistics and Decision, 2020, 36(12): 55-58(in Chinese). doi: 10.13546/j.cnki.tjyjc.2020.12.011
    [11] PARADIS K C, NAHEEDY K W, MATUSZAK M M, et al. The fusion of incident learning and failure mode and effects analysis for data-driven patient safety improvements[J]. Practical Radiation Oncology, 2021, 11(1): 106-113. doi: 10.1016/j.prro.2020.02.015
    [12] FINEGAN D P, ZHU J, FENG X, et al. The application of data-driven methods and physics-based learning for improving battery safety[J]. Joule, 2020, 5(2): 316-329.
    [13] CHEN Y Z, WANG Z X. Solution of multiple crack problem in a finite plate using coupled integral equations[J]. International Journal of Solids & Structures, 2012, 49(1): 87-94.
    [14] 叶振华. 化工吸附分离过程[M]. 北京: 中国石化出版社, 1992: 108-136.

    YE Z H. Adsorption separation process in chemical industry[M]. Beijing: China Petrochemical Press, 1992: 108-136 (in Chinese).
    [15] 张燕平, 赵宏韬. 测控技术在分子筛机载制氧领域的应用研究[C]//航空试验测试技术学术交流会, 2015: 297-299.

    ZHANG Y P, ZHAO H T. Application of measurement and control technology in molecular sieve airborne oxygen production field[C]//Aeronautical Test and Test Technology Academic Exchange Conference, 2015: 297-299(in Chinese).
    [16] 王世和, 卢灿, 许育林, 等. 分子筛氧气浓缩监控器可靠性技术及管理研究[J]. 兵器装备工程学报, 2017, 38(4): 105-108. doi: 10.11809/scbgxb2017.04.023

    WANG S H, LU C, XU Y L, et al. The reliability technique and management study of molecular sieve oxygen concentrator controller[J]. Journal of Ordnance and Equipment Engineering, 2017, 38(4): 105-108(in Chinese). doi: 10.11809/scbgxb2017.04.023
    [17] 田利梅, 龚梦彤, 唐荻音, 等. 基于功耗残差的航天器CMG退化特征提取方法[J]. 北京航空航天大学学报, 2022, 48(10): 1899-1905. doi: 10.13700/j.bh.1001-5965.2021.0060

    TIAN L M, GONG M T, TANG D Y, et al. Degradation indicator extraction for aerospace CMG based on power consumption analysis[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(10): 1899-1905(in Chinese). doi: 10.13700/j.bh.1001-5965.2021.0060
    [18] BOKER, G, LUNZE J. Stability and performance of switching Kalman filters[J]. International Journal of Control, 2002, 75(16-17): 1269-1281. doi: 10.1080/0020717021000023708
    [19] 李娟, 景博, 焦晓璇, 等. 基于LSTAR的机载燃油泵多阶段退化建模[J]. 北京航空航天大学学报, 2017, 43(5): 880-886. doi: 10.13700/j.bh.1001-5965.2016.0347

    LI J, JING B, JIAO X X, et al. Multi-stage degradation modeling for airborne fuel pump based on LSTAR[J]. Journal of Beijing University of Aeronautics and Astronautics, 2017, 43(5): 880-886(in Chinese). doi: 10.13700/j.bh.1001-5965.2016.0347
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出版历程
  • 收稿日期:  2021-05-18
  • 录用日期:  2021-07-30
  • 网络出版日期:  2021-08-27
  • 整期出版日期:  2023-02-28

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