基于贝叶斯理论的结构件健康状态评估方法研究

朱林1,陈敏2,贾民平3

振动与冲击 ›› 2020, Vol. 39 ›› Issue (6) : 59-63.

PDF(1389 KB)
PDF(1389 KB)
振动与冲击 ›› 2020, Vol. 39 ›› Issue (6) : 59-63.
论文

基于贝叶斯理论的结构件健康状态评估方法研究

  • 朱林1,陈敏2,贾民平3
作者信息 +

Approach for structural health assessment based on the Bayesian theory

  • ZHU Lin1,CHEN Min2,JIA Minping3
Author information +
文章历史 +

摘要

以结构件裂纹扩展过程中的健康状态评估为研究对象,针对结构件健康状态评估过程中广泛存在的Weibull型数据的特征,通过将Weibull型分布数据类型与贝叶斯理论相结合来提出了一种基于贝叶斯理论的结构件健康状态评估模型,并通过采用MCMC算法对复杂后验量的计算问题进行了求解。运用声发射手段对实例构件的健康状态数据进行了采集,基于贝叶斯理论的结构件健康状态评估模型对实例构件的健康状态进行了评估,评估结果表明5%与95%两个分位数构成了结构件健康状态评估参数的90%置信区间,后验参数的分布集中,且置信度达到90%,可以实现结构件健康状态的精确评估。

Abstract

The structural health assessment in the crack propagation process was studied.Considering the wide existence of Weilbull distribution data characteristics in the assessment process, an approach for structural health assessment based on the Bayesian theory was proposed through combining the data of the type of Weibull distribution with the Bayesian theory.The numerical solutions for the complex posterior problems were provided by using the MCMC algorithm.The acoustic emission approach was adopted to collect the health assessment data for an industrial component.The health result obtained by the proposed model shows that two fractile parameters of 5% and 95% constitute the 90% of confidence interval of the assessment parameter for structural health.The posterior parameters are centrally distributed and the confidence level is up to 90%, which verifies the accuracy of the health assessment method.

关键词

贝叶斯 / Weibull分布 / 裂纹扩展 / 结构件 / 健康状态评估

Key words

Bayesian / Weibull distribution / crack propagation / structural component / health assessment

引用本文

导出引用
朱林1,陈敏2,贾民平3. 基于贝叶斯理论的结构件健康状态评估方法研究[J]. 振动与冲击, 2020, 39(6): 59-63
ZHU Lin1,CHEN Min2,JIA Minping3. Approach for structural health assessment based on the Bayesian theory[J]. Journal of Vibration and Shock, 2020, 39(6): 59-63

参考文献

[1] SHI GL, ZHU L, WEI DB. A new prediction approach for the structural fatigue life based on multi-factor correction[J]. Surface Review & Letters, 2018, 25(5): 95-105.
[2] 朱林,贾民平,冯月贵等.考虑残余应力重分布情况下的裂纹扩展预测研究[J]. 机械工程学报,2017, 53(8): 43-49.
    ZHU Lin, JIA Minping, FENG Yuegui, et al. Prediction study of the crack propagation with consideration of the residual stress redistribution[J].Journal of mechanical engineering, 2017, 53(8): 43-49(in Chinese)
[3] UDWADIA F E. Methodology for optimum sensor locations for parameter identification in dynamic systems[J]. Journal of Engineering Mechanics, 1994, 120(2): 368-390.
[4] PAPADINITRIOU C. Optimal sensor placement methodology for parametric identification of structural systems[J].Journal of Sound and Vibration, 2004, 278: 923-947.
[5] 王宇. 贝叶斯参数更新在可靠性分析中的应用[D].南京航空航天大学, 2014.
WANG Yu. Bayesian parameter updating in the application of the reliability analysis[D]. Nanjing university of aeronautics and astronautics, 2014(in Chinese).
[6] TORREGOSA R F, HU W. Probabilistic risk analysis of fracture of aircraft structures using a Bayesian approach to update the distribution of the equivalent initial flaw sizes[J]. Fatigue & Fracture of Engineering Materials & Structures, 2013, 36(11): 1092-1101.
[7] STRAUB D, PAPAIOANNOU I. Bayesian updating with structural reliability methods[J]. Journal of Engineering Mechanics, 2014, 141(3): 04014134.
[8] 曹晋华, 程侃. 可靠性数学引论[M].高等教育出版社,2006:51-77.
CAO Jinhua, CHEN Kan. Introduction of reliability mathematics[M]. Higher Education Press, 2006: 51-77.
[9] BECK J L, AU S K. Bayesian updating of structural models and reliability using Markov chain Monte Carlo simulation[J]. Journal of Engineering Mechanics, 2002, 128(4): 380-391.
[10] GEBRAEEL N Z, LAWLEY M A, LI R, et al. Residual-life distributions from component degradation signals: A Bayesian approach[J]. IIE Transactions, 2005, 37(6): 543-557.
[11] MIESOWICZ K, STASZEWSKI W J, KORBIEL T. Analysis of Barkhausen noise using wavelet-based fractal signal processing for fatigue crack detection[J]. International Journal of Fatigue, 2016, 83: 109-116.
[12] GHOLIZADEH S, LEMAN Z, BAHARUDIN B. A review of the application of acoustic emission technique in engineering[J]. Structural Engineering and Mechanics, 2015, 54(6): 1075.
[13] ZHU L, JIA M P, JIANG C C, et al. Estimation of structure crack propagation based on multiple factors correction[J].Journal of Southeast University(English Edition), 2017, 33(1):39-45.

PDF(1389 KB)

Accesses

Citation

Detail

段落导航
相关文章

/