Loader Boom Reliability Analysis with Artificial Neural Network Method

被引:1
|
作者
Sha, Lirong [1 ]
Yang, Yue [1 ]
机构
[1] Jilin Jianzhu Univ, Changchun 130118, Peoples R China
关键词
Reliability; Artificial neural network; Fatigue; Response method;
D O I
10.4028/www.scientific.net/AMR.838-841.250
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The artificial neural network is used to solve the reliability analysis of the engineering structure. When the limit state function of structure is highly complex or with nonlinearity, it is time-consuming or cumbersome to carry out reliability analysis with traditional methods. The artificial neural network response surface method is adopted to analyze the fatigue reliability of loader boom, the working process of loader machine is analyzed with FEM software and analytical method, the stress-time history and strain-tithe history of loader boom are schematized with rain-flow algorithm, consequently the fatigue life analysis on the structure can be carried out with local stress-strain method. The artificial neural network method is used to fit the performance function as well as its derivatives, so as to calculate the reliability of the structure. The numerical example results show that the proposed method has capability of solving industrial-scale reliability problems.
引用
收藏
页码:250 / 253
页数:4
相关论文
共 50 条
  • [41] Seismic reliability assessment of structures using artificial neural network
    Vazirizade, Sayyed Mohsen
    Nozhati, Saeed
    Zadeh, Mostafa Allameh
    JOURNAL OF BUILDING ENGINEERING, 2017, 11 : 230 - 235
  • [42] Estimation on the Reliability of Farm Vehicle Based on Artificial Neural Network
    WANG Jinwu Engineering College
    JournalofNortheastAgriculturalUniversity(EnglishEdition), 2008, 15 (04) : 45 - 48
  • [43] Reliability and performance-based design by artificial neural network
    Chau, K. W.
    ADVANCES IN ENGINEERING SOFTWARE, 2007, 38 (03) : 145 - 149
  • [44] Artificial neural network based on time series prediction of reliability
    Xu, Kai
    Zhu, Meilin
    Hou, Guoxiang
    Gao, Jun
    Huazhong Ligong Daxue Xuebao/Journal Huazhong (Central China) University of Science and Technology, 2000, 28 (08): : 35 - 37
  • [45] Structural Reliability Optimization Design based on Artificial Neural Network
    Sha, Lirong
    Yue, Yang
    RESEARCH IN MATERIALS AND MANUFACTURING TECHNOLOGIES, PTS 1-3, 2014, 835-836 : 1877 - 1880
  • [46] Method of spectrogram recognition by artificial neural network
    Orlikov, NL
    Petrakov, RS
    MODERN COMMUNICATION TECHNOLOGIES SIBCOM-2001, PROCEEDINGS, 2001, : 55 - 57
  • [47] Artificial Neural Network Intelligent Method for Prediction
    Trifonov, Roumen
    Yoshinov, Radoslav
    Pavlova, Galya
    Tsochev, Georgi
    MATHEMATICAL METHODS & COMPUTATIONAL TECHNIQUES IN SCIENCE & ENGINEERING, 2017, 1872
  • [48] An artificial neural network method for map correction
    Chai, Y
    Guo, MY
    Li, SF
    Zhang, ZF
    Feng, DL
    ADVANCES IN NEURAL NETWORKS - ISNN 2005, PT 3, PROCEEDINGS, 2005, 3498 : 1004 - 1009
  • [49] Estimation of all-terminal network reliability using an artificial neural network
    Srivaree-Ratana, C
    Konak, A
    Smith, AE
    COMPUTERS & OPERATIONS RESEARCH, 2002, 29 (07) : 849 - 868
  • [50] Artificial neural network method in acoustical simulation
    Zhang, Qiong
    Shi, Jiao-ying
    Ruan Jian Xue Bao/Journal of Software, 1998, 9 (01): : 7 - 13