EI、Scopus 收录
中文核心期刊
Quick Search Issue Search Advanced Search
Volume 50 Issue 3
Turn off MathJax
Article Contents
Abstract
References
Related Articles
Guan Xuexue, Chen Jianqiao, Zheng Yaochen, Zhang Xiaosheng. A COMBINED PARTICLE FILTER METHOD FOR PREDICTING STRUCTURAL PERFORMANCE DEGRADATION[J]. Chinese Journal of Theoretical and Applied Mechanics, 2018, 50(3): 677-687. DOI: 10.6052/0459-1879-18-014
Citation: Guan Xuexue, Chen Jianqiao, Zheng Yaochen, Zhang Xiaosheng. A COMBINED PARTICLE FILTER METHOD FOR PREDICTING STRUCTURAL PERFORMANCE DEGRADATION[J]. Chinese Journal of Theoretical and Applied Mechanics, 2018, 50(3): 677-687. DOI: 10.6052/0459-1879-18-014
shu

A COMBINED PARTICLE FILTER METHOD FOR PREDICTING STRUCTURAL PERFORMANCE DEGRADATION

  • Department of Mechanics, Huazhong University of Science and Technology, Wuhan 430074, China

  • Hubei Key Laboratory for Engineering Structural Analysis and Safety Assessment, Wuhan 430074, China

  • Received Date: January 07, 2018
    Graphical Abstract
    • Abstract
  • Structural performances will degrade with time due to the influence of loading, environmental and material factors. To assess the status of a structure in service, the structural deterioration process is usually described through physical models with uncertain model parameters. Prior distributions of model parameters are often determined by using the data collected from similar structures. To improve the accuracy of the model, Bayesian inference incorporated with available data is often used to update the distribution of the parameters. In this work, an effective Bayesian method PF-DREAM is proposed. In this approach, firstly, the mixing combination rule of the Dempster-shafer theory (DST) is utilized to get the prior distribution. Thereafter, for evaluating the complicated multidimensional integral in the Bayesian inference formula and obtaining the posterior distribution, a differential evolution adaptive Metropolis (DREAM) approach integrated with the particle filter (PF) is developed. As compared with the original PF method, the proposed PF-DREAM method can enhance the sample particles’ diversity and improve the quality of the model. To illustrate the efficiency and accuracy of the proposed method, a lithium-ion battery problem and a fatigue crack propagation problem are presented. Results demonstrated that the proposed method can provide more accurate results in parameters updating as well as response prediction. As more data is incorporated, the model’s variance becomes smaller, and the predicted mean trajectory is more reliable in terms of the actual deteriorate curves. It is pointed out that PF-DREAM method can be applied to high-dimensional problems and implicit function problems with the same algorithm presented in this paper, only accompanying more iteration numbers and greater computational load for obtaining convergent results.
    • FullText(HTML)
    • References (1)
  • [1] Tsai CC. Mis-specification analyses of gamma and Wiener degradation processes.Journal of Statistical Planning & Inference, 2011, 141(12): 3725-3735
    [2] Dan MF, Kallen MJ, Noortwijk JMV. Probabilistic models for life-cycle performance of deteriorating structures: Review and future directions.Progress in Structural Engineering & Materials, 2004, 6(4): 197-212
    [3] 刘海波, 姜潮, 郑静等. 含概率与区间混合不确定性的系统可靠性分析方法. 力学学报, 2017, 49(2): 456-466
    [3] (Liu Haibo, Jiang Chao, Zheng Jing, et al. A system reliability analysis method for structures with probability and interval mixed uncertainty.Chinese Journal of Theoretical and Applied Mechanics, 2017, 49(2): 456-466 (in Chinese))
    [4] Ge R, Chen J, Wei J. Reliability-based design of composites under the mixed uncertainties and the optimization algorithm.Acta Mechanica Solida Sinica, 2008, 21(1): 19-27
    [5] 李帅兵, 杨睿, 罗喜胜等. 气流作用下同轴带电射流的不稳定性研究. 力学学报, 2017, 49(5): 997-1007
    [5] (Li Shuaibing, Yang Rui, Luo Xisheng, et al. Instability study of an electrified coaxial jet in a coflowing gas stream.Chinese Journal of Theoretical and Applied Mechanics, 2017, 49(5): 997-1007 (in Chinese))
    [6] 周春晓,汪锐琼,聂肇坤等. 基于最大熵方法的水下航行体结构动力响应概率建模. 力学学报, 2018, 50(1): 114-123
    [6] (Zhou Chunxiao,Wang Ruiqiong, Nie Zhaokun, et al. Probabilistic modelling of dynamic response of underwater vehicle structure via maximum entropy method.Chinese Journal of Theoretical and Applied Mechanics, 2018, 50(1): 114-123 (in Chinese))
    [7] Huang X, Chen J. Time-dependent reliability model of deteriorating structures based on stochastic processes and Bayesian inference methods.Journal of Engineering Mechanics, 2015, 141(3): 04014123
    [8] Guan X, He J, Jha R, et al. An efficient analytical Bayesian method for reliability and system response updating based on Laplace and inverse first-order reliability computations.Reliability Engineering & System Safety, 2012, 97(1): 1-13
    [9] He W, Williard N, Osterman M, et al. Prognostics of lithium-ion batteries based on Dempster-Shafer theory and the Bayesian Monte Carlo method.Journal of Power Sources, 2011, 196(23): 10314-10321
    [10] Rebba R, Mahadevan S. Computational methods for model reliability assessment.Reliability Engineering & System Safety, 2008, 93(8): 1197-1207
    [11] Luke T, Joseph BK. Accurate Approximations for posterior moments and marginal densities.Journal of the American Statistical Association, 1986, 81(393): 82-86
    [12] 王宇. 贝叶斯参数更新在可靠性分析中的应用. [硕士论文]. 南京:南京航空航天大学, 2014
    [12] (Wang Yu. The application of Bayesian updating in reliability analysis. [Master Thesis]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2014 (in Chinese))
    [13] Cappé O, Moulines E, Rydén T. Inference in Hidden Markov Models. Springer, 2005: 574-575
    [14] Pitt MK, Silva RDS, Giordani P, et al. On some properties of Markov chain Monte Carlo simulation methods based on the particle filter.Journal of Econometrics, 2012, 171(2): 134-151
    [15] Fernándezvillaverde J, Rubioramrez JF. Estimating macroeconomic models: A likelihood approach.Review of Economic Studies, 2010, 74(4): 1059-1087
    [16] Christophe A, Arnaud D, Roman H. Particle Markov chain Monte Carlo methods.Journal of the Royal Statistical Society, 2010, 72(3): 269-342
    [17] Doucet A, Godsill S, Andrieu C. On sequential Monte Carlo sampling methods for Bayesian filtering.Statistics & Computing, 2000, 10(3):197-208
    [18] An D, Choi JH, Kim NH. Prognostics 101: A tutorial for particle filter-based prognostics algorithm using Matlab.Reliability Engineering & System Safety, 2013, 115(1): 161-169
    [19] 王鑫, 胡昌华, 暴飞虎. 基于贝叶斯原理的粒子滤波算法. 弹箭与制导学报, 2006, 26(s5): 269-271
    [19] (Wang Xin, Hu Changhua, Bao Feihu. Particle filtering method based on Bayesian theorem.Journal of Projectiles, Roktets, Missiles and Guidance, 2006, 26(s5): 269-271 (in Chinese))
    [20] Chen J, Yuan S, Qiu L, et al. On-line prognosis of fatigue crack propagation based on Gaussian weight-mixture proposal particle filter.Ultrasonics, 2017, 82: 134
    [21] Gordon NJ, Salmond DJ, Smith AFM. Novel approach to nonlinear/non-Gaussian Bayesian state estimation.IEE Proceedings F-Radar and Signal Processing, 2002, 140(2): 107-113
    [22] Djurić PM, Kotecha JH, Zhang J, et al. Particle filtering.Signal Processing Magazine IEEE, 2003, 20(5): 19-38
    [23] Zio E, Peloni G. Particle filtering prognostic estimation of the remaining useful life of nonlinear components.Reliability Engineering & System Safety, 2011, 96(3): 403-409
    [24] Bi H, Ma J, Wang F. An improved particle filter algorithm based on Ensemble Kalman filter and Markov Chain Monte Carlo method.IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing, 2015, 8(2): 447-459
    [25] Vrugt JA, Braak CJFT, Clark MP, et al. Treatment of input uncertainty in hydrologic modeling: Doing hydrology backward with Markov chain Monte Carlo simulation.Water Resources Research, 2008, 44(12): 5121-5127
    [26] Vrugt JA, Braak CJFT, Diks CGH, et al. Accelerating Markov chain Monte Carlo simulation by differential evolution with self-adaptive randomized subspace sampling.International Journal of Nonlinear Sciences & Numerical Simulation, 2009, 10(3): 273-290
    [27] Laloy E, Vrugt JA. High-dimensional posterior exploration of hydrologic models using multiple‐try DREAM(ZS) and high-performance computing.Water Resources Research, 2012, 50(3): 182-205
    [28] Vrugt J A. Markov chain Monte Carlo simulation using the DREAM software package: Theory, concepts, and MATLAB implementation.Environmental Modelling & Software, 2016, 75: 273-316
    [29] Wentworth MT, Smith RC, Williams B. Bayesian model calibration and uncertainty quantification for an HIV model using adaptive Metropolis algorithms.Inverse Problems in Science & Engineering, 2017, 26(2): 233-256
    [30] Post H, Vrugt JA, Fox A, et al. Estimation of community land model parameters for an improved assessment of net carbon fluxes at European sites.Journal of Geophysical Research Biogeosciences, 2017, 122(3): 661-689
    [31] Liang S, Jia H, Xu C, et al. A Bayesian approach for evaluation of the effect of water quality model parameter uncertainty on TMDLs: A case study of Miyun reservoir. Science of the Total Environment, 2016, s560-561: 44-54
    [32] Wu WF, Ni CC. A study of stochastic fatigue crack growth modeling through experimental data.Probabilistic Engineering Mechanics, 2003, 18(2): 107-118
    [33] Wu WF, Ni CC. Statistical aspects of some fatigue crack growth data.Engineering Fracture Mechanics, 2007, 74(18): 2952-2963
    • Related Articles

  • Related Articles

    [1]Zhang Linghai, Zhou Bin, Luo Yi, Feng Jun. AN ADAPTIVE COLLOCATION POINT ALGORITHM FOR PHYSICS-INFORMED NEURAL NETWORKS[J]. Chinese Journal of Theoretical and Applied Mechanics, 2024, 56(10): 3069-3083. DOI: 10.6052/0459-1879-24-244
    [2]Yuan Guoqiang*, Li Yinghui. ADAPTIVE FRONT ADVANCING ALGORITHM FOR COMPUTING TWO-DIMENSIONAL STABLE MANIFOLDS[J]. Chinese Journal of Theoretical and Applied Mechanics, 2018, 50(2): 405-414. DOI: 10.6052/0459-1879-17-353
    [3]Deng Kaiwen, Chen Haixin. HYBRID OPTIMIZATION ALGORITHM BASED ON DIFFERENTIAL EVOLUTION AND RBF RESPONSE SURFACE[J]. Chinese Journal of Theoretical and Applied Mechanics, 2017, 49(2): 441-455. DOI: 10.6052/0459-1879-16-285
    [4]Shao Yulong, Duan Qinglin, Gao Xin, Li Xikui, Zhang Hongwu. ADAPTIVE CONSISTENT HIGH ORDER ELEMENT-FREE GALERKIN METHOD[J]. Chinese Journal of Theoretical and Applied Mechanics, 2017, 49(1): 105-116. DOI: 10.6052/0459-1879-16-252
    [5]Dai Hongzhe, Xue Guofeng, Wang Wei. A WAVELET THRESHOLDING DENSITY-BASED ADAPTIVE IMPORTANCE SAMPING METHOD[J]. Chinese Journal of Theoretical and Applied Mechanics, 2014, 46(3): 480-484. DOI: 10.6052/0459-1879-13-303
    [6]Jiang Chao, Zhang Zhe, Han Xu, Bai Yingchun. AN EVIDENCE-THEORY-BASED RELIABILITY ANALYSIS METHOD FOR UNCERTAIN STRUCTURES[J]. Chinese Journal of Theoretical and Applied Mechanics, 2013, 45(1): 103-115. DOI: 10.6052/0459-1879-12-040
    [7]Zhang Renyong, Luo Jianjun, Cheng Yu, Tang Geshi, Cao Jing, Su Erlong, Feng Jinglang. THE GLOBAL OPTIMIZATION OF SPACE EXPLORATION TRAJECTORY DESIGN BASED ON DIFFERENTIAL EVOLUTION ALGORITHM[J]. Chinese Journal of Theoretical and Applied Mechanics, 2012, 44(6): 1079-1083. DOI: 10.6052/0459-1879-12-012
    [8]Xing Yufeng, Guo Jing. A SELF-ADAPTIVE NEWMARK METHOD WITH PARAMETERS DEPENDENT UPON STRUCTURAL DYNAMIC CHARACTERISTICS[J]. Chinese Journal of Theoretical and Applied Mechanics, 2012, 44(5): 904-911. DOI: 10.6052/0459-1879-12-033
    [9]Yan Chen, Shuliang Cao, Kaihong Liang, Baoshan Zhu. A new grid adaptive strategy combined characterized based split method[J]. Chinese Journal of Theoretical and Applied Mechanics, 2009, 41(5): 666-670. DOI: 10.6052/0459-1879-2009-5-2008-446
    [10]样条积分方程法分析弹塑性板弯曲[J]. Chinese Journal of Theoretical and Applied Mechanics, 1990, 22(2): 241-245. DOI: 10.6052/0459-1879-1990-2-1995-940

  • Cited by

    Periodical cited type(1)

    1. 王泓晖，房鑫，李德江，刘贵杰. 基于动态贝叶斯网络的变幅载荷下疲劳裂纹扩展预测方法. 浙江大学学报(工学版). 2021(02): 280-288 .

    Other cited types(3)

Catalog

    Get Citation
    PDF
    XML

    Article Metrics

    Article views (1310) PDF downloads (304) Cited by(4)
    Related

    Download Center

    Author Center

    Copyright © Editorial Office of the Chinese Journal of Mechanics   京ICP备05039218号-1

    Address：15 Beishihuan Xi Lu, Haidian District, Beijing, China   China Pos：100190

    Tel：010-62536271

    Email：lxxb@cstam.org.cn

    微信公众号
    RSS

    Supported by: Beijing Renhe Information Technology Co., Ltd.  Baidu Analytics

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return