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Jiangxi Nonferrous Metals Society
ISSN：1674-9669
CN：36-1311/TF
CODEN YJKYA9
Volume 4 Issue 5
Oct.  2013
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LIU Fei-fei, LIU Hui-hui, LI Jun-rong. Soft measurement modeling of WO3 leaching rate based on artificial neural network[J]. Nonferrous Metals Science and Engineering, 2013, 4(5): 117-121. DOI: 10.13264/j.cnki.ysjskx.2013.05.004
Citation: LIU Fei-fei, LIU Hui-hui, LI Jun-rong. Soft measurement modeling of WO3 leaching rate based on artificial neural network[J]. Nonferrous Metals Science and Engineering, 2013, 4(5): 117-121. DOI: 10.13264/j.cnki.ysjskx.2013.05.004
shu

Soft measurement modeling of WO3 leaching rate based on artificial neural network

  • 1.

    School of Electrical Engineering and Automation, Jiangxi University of Science and Technology, Ganzhou 341000, China

  • 2.

    Ganzhou Huaxing Tungsten Products Co.Ltd., Ganzhou 341000, China

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  • Received Date: March 10, 2013
  • Published Date: October 30, 2013
    Graphical Abstract
    • Abstract
  • The online detection of WO3 Leaching Rate in tungsten hydrometallurgy is difficult to accomplish. A soft measurement plan with a convenient and fast detecting soft measurement model is devised by using MATLAB and the data collected from industrial field train neural network according to the chemical reaction mechanism of tungsten alkali hot leaching and the factors which influenced the leaching rate. Simulation results manifested the soft measurement model could well reflect actual reaction situation. The measuring relative error is less than 0.5 %. The model fit the industrial requirement. This research provides a new method for onl ine detection of tungsten leaching rate.
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    • References (17)
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