• DocumentCode
    3305633
  • Title

    Research on Fault Location of Large-Scale Mechanical Equipment Based on Improved Genetic Algorithm

  • Author

    Huang, Zhi-yong

  • fYear
    2010
  • fDate
    24-25 April 2010
  • Firstpage
    21
  • Lastpage
    24
  • Abstract
    Based on the analysis of shortcomings of commonly used mechanical equipment fault location methods, the paper brought out the method of applying Genetic Algorithm (GA) to solve fault probability of constitute components of mechanical equipments. Aiming at problems of easily local optimum and slow evolution that inherent by standard GA, the paper introduced energy entropy and pseudo-gradient into annealing selection and neighborhood search of GA, so as to take full advantage of effective information of current population and systems information to speed calculation. The material fault location example of some type mechanical equipment verifies that the improved GA can effectively solve the fault location problem of large scale mechanical equipments, the global optimization performance of which is superior to standard GA.
  • Keywords
    Annealing; Diagnostic expert systems; Entropy; Fault diagnosis; Fault location; Fuzzy reasoning; Genetic algorithms; Large-scale systems; Mathematical model; Neural networks; fault location; improved genetic algorithm; large scale mechanical equipments;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Vision and Human-Machine Interface (MVHI), 2010 International Conference on
  • Conference_Location
    Kaifeng, China
  • Print_ISBN
    978-1-4244-6595-8
  • Electronic_ISBN
    978-1-4244-6596-5
  • Type

    conf

  • DOI
    10.1109/MVHI.2010.78
  • Filename
    5532615