<listing id="l9bhj"><var id="l9bhj"></var></listing>
<var id="l9bhj"><strike id="l9bhj"></strike></var>
<menuitem id="l9bhj"></menuitem>
<cite id="l9bhj"><strike id="l9bhj"></strike></cite>
<cite id="l9bhj"><strike id="l9bhj"></strike></cite>
<var id="l9bhj"></var><cite id="l9bhj"><video id="l9bhj"></video></cite>
<menuitem id="l9bhj"></menuitem>
<cite id="l9bhj"><strike id="l9bhj"><listing id="l9bhj"></listing></strike></cite><cite id="l9bhj"><span id="l9bhj"><menuitem id="l9bhj"></menuitem></span></cite>
<var id="l9bhj"></var>
<var id="l9bhj"></var>
<var id="l9bhj"></var>
<var id="l9bhj"><strike id="l9bhj"></strike></var>
<ins id="l9bhj"><span id="l9bhj"></span></ins>
Volume 36 Issue S1
Jul.  2021
Turn off MathJax
Article Contents
HE Dong-feng, HE Fei, XU An-jun, TIAN Nai-yuan. On-line liquid steel temperature control for the steelmaking-continuous casting process[J]. Chinese Journal of Engineering, 2014, 36(S1): 200-206. doi: 10.13374/j.issn1001-053x.2014.s1.037
Citation: HE Dong-feng, HE Fei, XU An-jun, TIAN Nai-yuan. On-line liquid steel temperature control for the steelmaking-continuous casting process[J]. Chinese Journal of Engineering, 2014, 36(S1): 200-206. doi: 10.13374/j.issn1001-053x.2014.s1.037

On-line liquid steel temperature control for the steelmaking-continuous casting process

doi: 10.13374/j.issn1001-053x.2014.s1.037
  • Received Date: 2013-11-18
    Available Online: 2021-07-19
  • In order to control liquid steel temperature accurately,forward and backward prediction models for liquid steel temperature in key strategic points of steelmaking process were proposed,based on the analysis of the main influencing factors and the control state of liquid steel temperature in actual steelmaking process. At the same time,to overcome the disadvantages of traditional prediction methods,a hybrid model method based ladle heat status and BP neural network was proposed. The method is based on the ladle heat status tracking model,and gives full consideration to the effects of ladle heat status on molten steel temperature,and combines with BP neural network,which can effectively improve the prediction precision.

     

  • loading
  • 加載中

Catalog

    通訊作者: 陳斌, bchen63@163.com
    • 1. 

      沈陽化工大學材料科學與工程學院 沈陽 110142

    1. 本站搜索
    2. 百度學術搜索
    3. 萬方數據庫搜索
    4. CNKI搜索
    Article views (318) PDF downloads(11) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return
    久色视频