Application Potential of artificial neural Networks in the Prognosis and Analysis of technical Reliability

被引：0
|
作者：
Fink, Olga [1 ]
Weidmann, Ulrich [1 ]
Hofmann, Daniel [2 ]
Krolo, Anna [2 ]
机构：
[1] Swiss Fed Inst Technol, Inst Verkehrsplanung & Transportsyst, Zurich, Switzerland
[2] Univ Stuttgart, Inst Maschinenelemente, Stuttgart, Germany
来源：
TECHNISCHE ZUVERLASSIGKEIT 2011: ENTWICKLUNG UN BETRIEB ZUVERLASSIGER PRODUKTE | 2011年 / 2146卷
关键词：
SYSTEMS RELIABILITY; PREDICTION;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
This paper elaborates prerequisites, strengths and limitations of the application of artificial neural networks (in the following only "neural networks") in reliability engineering. The applications of reliability forecasting and analysis, which are particularly suitable for the application of neural networks, are investigated. This will be evaluated in comparison to other state of the art methods. Application areas are identified, in which neural networks are already implemented. Other potential fields of application are evaluated based on the comparison results of different methods. Railway applications, as one of the possible fields of application, are in special focus of this article.
引用
收藏
页码：183 / 196
页数：14
相关论文
共 50 条
  • [1] RELIABILITY-ANALYSIS OF ARTIFICIAL NEURAL NETWORKS
    DUGAN, JB
    WATTERSON, JW
    PROCEEDINGS ANNUAL RELIABILITY AND MAINTAINABILITY SYMPOSIUM, 1991, (SYM): : 598 - 603
  • [2] Review and application of Artificial Neural Networks models in reliability analysis of steel structures
    Chojaczyk, A. A.
    Teixeira, A. P.
    Neves, L. C.
    Cardoso, J. B.
    Guedes Soares, C.
    STRUCTURAL SAFETY, 2015, 52 : 78 - 89
  • [3] Application of artificial neural networks for Zeta potential of copolymer
    Tekeli, F. Noyan
    BULGARIAN CHEMICAL COMMUNICATIONS, 2017, 49 : 146 - 150
  • [4] Application of Artificial Neural Networks to stylometric analysis
    Stanczyk, Urszula
    Cyran, Krzysztof A.
    PROCEEDINGS OF THE 8TH WSEAS INTERNATIONAL CONFERENCE ON SYSTEMS THEORY AND SCIENTIFIC COMPUTATION (ISTAC'08): NEW ASPECTS OF SYSTEMS THEORY AND SCIENTIFIC COMPUTATION, 2008, : 25 - 30
  • [5] Shallow and Deep Artificial Neural Networks for Structural Reliability Analysis
    de Santana Gomes, Wellison Jose
    ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING, 2020, 6 (04):
  • [6] Structural Reliability Analysis Using Adaptive Artificial Neural Networks
    de Santana Gomes, Wellison Jose
    ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING, 2019, 5 (04):
  • [7] Application of artificial neural networks in the analysis of LIBS spectra
    Philip, T
    Panda, M
    Singh, JP
    Yueh, FY
    Zhang, H
    INTERNATIONAL SOCIETY FOR COMPUTERS AND THEIR APPLICATIONS 11TH INTERNATIONAL CONFERENCE ON COMPUTER APPLICATIONS IN INDUSTRY AND ENGINEERING, 1998, : 17 - 20
  • [8] Application of Artificial Neural Networks to Downhole Fluid Analysis
    Hegeman, Peter
    Dong, Chengli
    Varotsis, Nikos
    Gaganis, Vassilis
    SPE RESERVOIR EVALUATION & ENGINEERING, 2009, 12 (01) : 8 - 13
  • [9] Artificial Neural Networks Application in Modal Analysis of Tires
    Kostial, P.
    Jancikova, Z.
    Bakosova, D.
    Valicek, J.
    Harnicarova, M.
    Spicka, I.
    MEASUREMENT SCIENCE REVIEW, 2013, 13 (05): : 273 - 278
  • [10] Application of artificial neural networks for the analysis of multispectral images
    Alies, M. Yu
    Antonov, E. A.
    Kalugin, A., I
    Zaripov, M. R.
    JOURNAL OF OPTICAL TECHNOLOGY, 2021, 88 (08) : 441 - 444
12345