具有不确定测量的非线性随机退化系统剩余寿命预测

摘要/Abstract

摘要：

摘要：提出了一类同时考虑不确定测量和非线性随机退化的退化建模方法，通过Kalman滤波技术对受不确定测量影响的潜在退化状态进行实时估计；基于此，通过首达时间的概念得到了同时考虑退化非线性特征、退化状态不确定性及测量不确定性的剩余寿命分布；此外，提出了一种基于极大似然方法的退化模型参数估计方法，并通过陀螺仪的退化测量数据验证了所提方法可以提高剩余寿命估计的准确性.

关键词: 预测与健康管理, 寿命预测, 退化建模, Kalman滤波, 不确定测量

Abstract:

Abstract： A class of degradation modeling approach was proposed, in which the nonlinear stochastic deterioration and uncertain measurements of the system were considered simultaneously, and the Kalman filtering technique was utilized to estimate the underlying degradation state. Based on the estimated degradation state, the analytical RUL distribution was derived according to the concept of the first passage time which accounted for the uncertainties in the estimated degradation state and measurements, and the effect of the degradation nonlinearity. Additionally, a parameter estimation method for the developed model was presented based on the maximum likelihood method. Finally, a case study of the gyros verified that the proposed method could improve the accuracy of the predicted RUL.

Key words: prognostics and health management, life prediction, degradation modeling, Kalman filter, uncertain measurements

中图分类号:

TP 273

司小胜1,胡昌华1,李娟2,孙国玺3,张琪1. 具有不确定测量的非线性随机退化系统剩余寿命预测[J]. 上海交通大学学报（自然版）, 2015, 49(06): 855-860.

SI Xiaosheng1,HU Changhua1,LI Juan2,SUN Guoxi3,ZHANG Qi1. Remaining Useful Life Prediction of Nonlinear Stochastic Degrading Systems Subject to Uncertain Measurements[J]. Journal of Shanghai Jiaotong University, 2015, 49(06): 855-860.

参考文献

［1］Si X S, Wang W, Hu C H, et al. Remaining useful life estimationA review on the statistical data driven approaches［J］. European Journal of Operational Research, 2011, 213(1): 114.

［2］周东华，魏慕恒，司小胜. 工业过程异常检测、寿命预测与维修决策的研究进展［J］. 自动化学报，2013, 39(5): 711722.

ZHOU Donghua, WEI Muheng, SI Xiaosheng. A survey on anomaly detection, life prediction and maintenance decision for industrial processes ［J］. Acta Automatica Sinica, 2013, 39(5): 711722.

［3］彭宝华，周经伦，冯静，等. 金属化膜脉冲电容器剩余寿命预测方法研究［J］. 电子学报，2011,39(11): 26742679.

PENG Baohua, ZHOU Jinglun, FENG Jing, et al. Residual lifetime prediction of metallized film pulse capacitors ［J］. Acta Electronica Sinica, 2011, 39(11): 26742679.

［4］Si X S, Wang W, Hu C H, et al. Estimating remaining useful life with threesource variability in degradation modelling［J］. IEEE Transactions on Reliability, 2014, 63(1): 167190.

［5］李志刚, 张菲菲, 李玲玲. 基于元器件初始信息的寿命评估方法［J］. 机械工程学报, 2014, 50(16): 4146.

LI Zhigang, ZHANG Feifei, LI Lingling. Lifetime evaluation approach based on initial information of components ［J］. Journal of Mechanical Engineering, 2014, 50(16): 4146.

［6］Si X S, Hu C H, Kong X Y, et al. A residual storage life prediction approach for systems with operation state switches［J］. IEEE Transactions on Industrial Electronics, 2014, 2014, 61(11): 63046315.

［7］Si X S, Wang W, Hu C H, et al. Remaining useful life estimation based on a nonlinear diffusion degradation process［J］. IEEE Transactions on Reliability, 2012, 61(1): 5067.

［8］Si X S, Wang W, Chen M Y, et al. A degradation pathdependent approach for remaining useful life estimation with an exact and closedform solution［J］. European Journal of Operational Research, 2013, 226(1): 5366.

［9］司小胜, 胡昌华, 张琪, 等. 不确定性退化测量数据下的剩余寿命估计［J］. 电子学报, 2015, 43(1): 3035.

SI Xiaosheng, HU Changhua, ZHANG Qi, et al. Remaining useful life estimation under uncertain degradation measurements ［J］. Acta Electronica Sinica, 2015, 43(1): 3035.

［10］王小林，郭波，程志君. 融合多源信息的维纳过程性能退化产品的可靠性评估［J］. 电子学报，2012, 40(5): 977982.

WANG Xiaoling, GUO Bo, CHENG Zhijun. Reliability assessment of products with Wiener process degradation by fusing multiple information ［J］. Acta Electronica Sinica, 2012, 40(5): 977982.

［11］司小胜, 胡昌华, 周东华. 带测量误差的非线性退化过程建模与剩余寿命估计［J］. 自动化学报, 2013, 39(5): 590601.

SI Xiaosheng, HU Changhua, ZHOU Donghua. Nonlinear degradation process modeling and remaining useful life estimation subject to measurement error ［J］. Acta Automatica Sinica, 2013, 39(5): 590601.

［12］冯磊, 王宏力, 周志杰, 等. 基于状态空间的惯性测量组合剩余寿命预测［J］. 清华大学学报:自然科学版, 2014, 54(4): 508514.

FENG Lei, WANG Hongli, ZHOU Zhijie, et al. Residual life prediction based on the state space for inertial measurement units ［J］. Journal of Tsinghua University: Science and Technology, 2014, 54(4): 508514.

[1]	孙志伟, 胡雄, 董凯, 孙德建, 刘洋. 基于LSTM-CAPF框架的岸桥起升减速箱轴承寿命预测方法[J]. 上海交通大学学报, 2024, 58(3): 352-360.
[2]	贺文选, 叶茂盛, 张雨, 张雅泰, 代晓辉, 张崎. 悬挂链在磨损条件下的极限强度评估[J]. 海洋工程装备与技术, 2024, 11(1): 23-29.
[3]	王汉禹, 陈震, 周笛, 陈兆祥, 潘尔顺. 基于核函数-Wiener过程的轧辊非线性退化建模与剩余寿命预测[J]. 上海交通大学学报, 2023, 57(8): 1037-1045.
[4]	钟智伟, 王誉翔, 黄亦翔, 肖登宇, 夏鹏程, 刘成良. 基于概率稀疏自注意力的IGBT模块剩余寿命跨工况预测[J]. 上海交通大学学报, 2023, 57(8): 1005-1015.
[5]	曹现刚1, 2，雷卓1，李彦川1，张梦园1，段欣宇1. 基于Self-Attention-LSTM神经网络的设备剩余寿命预测方法[J]. J Shanghai Jiaotong Univ Sci, 2023, 28(5): 652-664.
[6]	王者蓝, 赵宏杰, 赵凡, 沈晨晨, 吴佳伟. 基于卷积神经网络与滤波融合算法的某惯导系统剩余寿命预测模型建立[J]. 空天防御, 2023, 6(1): 70-77.
[7]	许勇, 蔡云泽, 宋林. 基于数据驱动的核电设备状态评估研究综述[J]. 上海交通大学学报, 2022, 56(3): 267-278.
[8]	杨世平, 董梦瑜, 李飞. 一种双悬臂梁柔性销轴的微动疲劳研究[J]. 上海交通大学学报, 2021, 55(3): 236-248.
[9]	王慧，井伟川，赵国超，金鑫. 基于灰色系统模型GM(1,1)改进Miner准则的液压支架底座疲劳寿命预测[J]. 上海交通大学学报, 2020, 54(1): 106-110.
[10]	刘健，陈自强，黄德扬，郑昌文，周诗尧，姜余. 基于等压差充电时间的锂离子电池寿命预测[J]. 上海交通大学学报, 2019, 53(9): 1058-1065.
[11]	廖欣, 朱莹, 史冉东, 郭正勇. 基于Kalman滤波的弹上陀螺零偏标定技术[J]. 空天防御, 2019, 2(1): 33-36.
[12]	杜党波a，胡昌华a，司小胜a，张正新a，张伟b. 一种混合退化系统剩余寿命预测方法[J]. 上海交通大学学报（自然版）, 2017, 51(7): 886-891.
[13]	王浩伟a,徐廷学a,周伟b. 综合退化数据与寿命数据的某型电连接器寿命预测方法[J]. 上海交通大学学报（自然版）, 2014, 48(05): 702-706.
[14]	胡友涛, 胡昌华. 一种基于遗传算法优化小波支持向量回归机的实时寿命预测方法[J]. 上海交通大学学报（自然版）, 2011, 45(08): 1216-1220.