• DocumentCode
    3215158
  • Title

    Full Measuring System for Copper Electrowinning Processes Using Optibar® Inter-Cell Bars

  • Author

    Wiechmann, Eduardo P. ; Morales, Anibal S. ; Aqueveque, Pablo E.

  • Author_Institution
    Dept. of Electr. Eng., Univ. of Concepcion, Concepcion
  • fYear
    2008
  • fDate
    5-9 Oct. 2008
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    An evolved Optibar inter-cell bar for copper EW processes with current sensing capabilities is presented. This technology upgrades the advantages of the conventional Optibar by providing a complete measuring system using magnetic sensors inside the capping board. To enhance reliability and simplicity, only half of the intercell currents are physically measured. This is accomplished using Adaptive Neuro-Fuzzy Inference System networks to calculate the current flowing through non-sensored connecting Optibar segments using virtual sensors. This way, process cathode currents are available on-line enabling a myriad of key process computations; i.e. cathode harvest time, weight at harvest, current dispersion among cathodes, energy consumption and process efficiency, and on-line setting of optimum process current level based on the ability to detect and locate metallurgical short-circuits events. In this work, this task is accomplished using a short-circuit diagnosis algorithm based on the recognition of current distribution patterns that characterizes the phenomena using Artificial Neural Networks. The technology employed to implement the system is completely embedded in the bar to ensure compatibility with the process environment. From the outside Optibar add ons are hidden and do not disrupt the operation. On site industrial data proved that cathode currents measurements exhibit an average absolute error lower than 2% with a dispersion lower than 1.6%. Finally, the algorithm developed for short circuit diagnosis exhibits a success rate of 98% or better.
  • Keywords
    cathodes; copper; electric current measurement; fuzzy neural nets; fuzzy reasoning; magnetic sensors; power engineering computing; short-circuit currents; Optibar; adaptive neuro-fuzzy inference system; artificial neural networks; cathode harvest time; copper electrowinning processes; current dispersion; currents measurements; energy consumption; intercell bars; magnetic sensors; short circuit diagnosis; virtual sensors; Adaptive systems; Bars; Cathodes; Copper; Current measurement; Energy consumption; Event detection; Joining processes; Magnetic sensors; Sensor systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industry Applications Society Annual Meeting, 2008. IAS '08. IEEE
  • Conference_Location
    Edmonton, Alta.
  • ISSN
    0197-2618
  • Print_ISBN
    978-1-4244-2278-4
  • Electronic_ISBN
    0197-2618
  • Type

    conf

  • DOI
    10.1109/08IAS.2008.338
  • Filename
    4659126