A novel Bayesian approach to acoustic emission data analysis

被引:25
|
作者
Agletdinov, E. [1 ]
Pomponi, E. [2 ]
Merson, D. [1 ]
Vinogradov, A. [1 ,3 ]
机构
[1] Togliatti State Univ, Inst Adv Technol, Tolyatti 445667, Russia
[2] CGnal Spa, Dept Data Sci & Analyt, Via Carducci 38, I-20122 Milan, Italy
[3] Norwegian Univ Sci & Technol NTNU, Dept Engn Design & Mat, N-7491 Trondheim, Norway
关键词
Bayesian probability; Signal processing; Random time-series; Acoustic emission; CORRODED GALVANIZED STEEL; TIME-DELAY ESTIMATION; TIN COATINGS; PATTERN-RECOGNITION; NEURAL-NETWORKS; AE SIGNALS; SCRATCH; MECHANISMS; IDENTIFICATION; DEFORMATION;
D O I
10.1016/j.ultras.2016.07.014
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
Acoustic emission (AE) technique is a popular tool for materials characterization and non-destructive testing. Originating from the stochastic motion of defects in solids, AE is a random process by nature. The challenging problem arises whenever an attempt is made to identify specific points corresponding to the changes in the trends in the fluctuating AE time series. A general Bayesian framework is proposed for the analysis of AE time series, aiming at automated finding the breakpoints signaling a crossover in the dynamics of underlying AE sources. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:89 / 94
页数:6
相关论文
共 50 条
  • [41] A Bayesian approach for the analysis of triadic data in cognitive social structures
    Swartz, Tim B.
    Gill, Paramjit S.
    Muthukumarana, Saman
    JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS, 2015, 64 (04) : 593 - 610
  • [42] A Bayesian approach for semiparametric regression analysis of panel count data
    Jianhong Wang
    Xiaoyan Lin
    Lifetime Data Analysis, 2020, 26 : 402 - 420
  • [43] Analysis and packaging of radiochemical solar neutrino data: A Bayesian approach
    Sturrock, P. A.
    Wheatland, M. S.
    SOLAR PHYSICS, 2008, 247 (02) : 217 - 224
  • [44] FMRI data analysis with nonstationary noise models: A Bayesian approach
    Luo, Huaien
    Puthusserypady, Sadasivan
    IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2007, 54 (09) : 1621 - 1630
  • [45] A Bayesian approach for semiparametric regression analysis of panel count data
    Wang, Jianhong
    Lin, Xiaoyan
    LIFETIME DATA ANALYSIS, 2020, 26 (02) : 402 - 420
  • [46] AEdata Analysis of Acoustic Emission Testing Data using Neural Networks
    Hill, Eric v. K.
    Dorfman, Michele D.
    MATERIALS EVALUATION, 2013, 71 (08) : 937 - 946
  • [47] A Novel Bayesian Linear Regression Model for the Analysis of Neuroimaging Data
    Belenguer-Llorens, Albert
    Sevilla-Salcedo, Carlos
    Desco, Manuel
    Soto-Montenegro, Maria Luisa
    Gomez-Verdejo, Vanessa
    APPLIED SCIENCES-BASEL, 2022, 12 (05):
  • [48] A Bayesian Approach to the Analysis of Gauge R&R Data
    Weaver, Brian P.
    Hamada, Michael S.
    Vardeman, Stephen B.
    Wilson, Alyson G.
    QUALITY ENGINEERING, 2012, 24 (04) : 486 - 500
  • [49] A Bayesian semiparametric approach for the differential analysis of sequence counts data
    Guindani, Michele
    Sepulveda, Nuno
    Paulino, Carlos Daniel
    Mueller, Peter
    JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS, 2014, 63 (03) : 385 - 404
  • [50] A Bayesian Approach for the Multifractal Analysis of Spatio-Temporal Data
    Combrexelle, S.
    Wendt, H.
    Tourneret, J. -Y.
    Altmann, Y.
    McLaughlin, S.
    Abry, P.
    PROCEEDINGS OF THE 23RD INTERNATIONAL CONFERENCE ON SYSTEMS, SIGNALS AND IMAGE PROCESSING, (IWSSIP 2016), 2016, : 331 - 334