• DocumentCode
    3092230
  • Title

    Coal quality analysis techniques using artificial neural network techniques

  • Author

    Salehfar, H.

  • Author_Institution
    Dept. of Electr. Eng., North Dakota Univ., Grand Forks, ND, USA
  • Volume
    2
  • fYear
    1999
  • fDate
    1999
  • Abstract
    Summary form only given. The paper describes the design and development of an online hybrid intelligent system from which coal quality can be determined interactively as an aid to steam power plant operators. The hybrid model combines neural networks with expert systems. The neural net module predicts the online performance of a boiler and its health for various coal blends and load conditions. The expert system deciphers the neural network model results and then diagnoses the situation. If coal quality conditions change, then the expert system alerts the operator and reports any impending consequences and performance degradation. The system then suggests one or more corrective actions to the steam power plant operator
  • Keywords
    boilers; coal; combustion; expert systems; neural nets; power station control; steam power stations; artificial neural network; boiler health; boiler performance; coal quality analysis techniques; corrective actions; expert systems; online hybrid intelligent system; performance degradation; steam power plant; Artificial neural networks; Ash; Availability; Boilers; Diagnostic expert systems; Hybrid intelligent systems; Impurities; Neodymium; Neural networks; Power generation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering Society Summer Meeting, 1999. IEEE
  • Conference_Location
    Edmonton, Alta.
  • Print_ISBN
    0-7803-5569-5
  • Type

    conf

  • DOI
    10.1109/PESS.1999.787502
  • Filename
    787502