• DocumentCode
    3355601
  • Title

    Application of artificial neural networks in industrial technology

  • Author

    Uhrig, Robert E.

  • Author_Institution
    Tennessee Univ., Knoxville, TN, USA
  • fYear
    1994
  • fDate
    5-9 Dec 1994
  • Firstpage
    73
  • Lastpage
    77
  • Abstract
    The application of artificial neural networks to industrial technology is an area that has great potential for exploitation. Many of the applications developed at the University of Tennessee and Oak Ridge National Laboratory are related to equipment and facilities in nuclear power plants. However, the basic principles involved are the same whether the application is to a check valve, rotating machinery, inspection for wear in mechanical system or the evaluation of fatigue life. It makes little difference whether the component or system is part of a nuclear power plants, a manufacturing plant, or a chemical processing plant. Data are used to train a neural network to model the input-output relationships of the systems involved, and patterns associated with specific modes of behavior or characteristics are identified. The results from the artificial neural network must then be put in a form that is useful to the operators and/or engineers concerned with the system. This can involve a simple computer program, an expert system, a fuzzy system, or a human factors related methodology
  • Keywords
    industrial control; inspection; intelligent control; monitoring; neural nets; Oak Ridge National Laboratory; University of Tennessee; chemical processing plant; expert system; fuzzy system; human factors; industrial technology; inspection; manufacturing plant; monitoring; neural networks; nuclear power plants; Artificial neural networks; Chemical processes; Fatigue; Inspection; Laboratories; Machinery; Manufacturing processes; Mechanical systems; Power generation; Valves;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Technology, 1994., Proceedings of the IEEE International Conference on
  • Conference_Location
    Guangzhou
  • Print_ISBN
    0-7803-1978-8
  • Type

    conf

  • DOI
    10.1109/ICIT.1994.467182
  • Filename
    467182