CIESC Journal ›› 2014, Vol. 65 ›› Issue (4): 1327-1332.DOI: 10.3969/j.issn.0438-1157.2014.04.024

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Multi-parameter correlation analysis based on mixed Copula model for aluminum reduction cell

YI Jun1, LI Taifu1,2, ZHANG Yuantao1, ZHOU Wei1, TIAN Yingfu3   

  1. 1 School of Electronic & Information Engineering, Chongqing University of Science and Technology, Chongqing 401331, China;
    2 School of Automation, Chongqing University, Chongqing 400044, China;
    3 Chongqing Tiantai Aluminum Corporation Ltd., Chongqing 401328, China
  • Received:2013-08-19 Revised:2013-11-28 Online:2013-12-02 Published:2014-04-05
  • Supported by:

    supported by the National Natural Science Foundation of China (51374268, 51075418, 61174015), the Natural Science Foundation of Chongqing (cstc2012jjB40006, cstc2013jjB40007, cstc2012jjA90011) and the Campus Research Foundation of Chongqing University of Science and Technology (CK2011B04, CK2013Z10).

基于混合Copula模型的铝电解槽多参数相关性分析

易军1, 李太福1,2, 张元涛1, 周伟1, 田应甫3   

  1. 1 重庆科技学院电气与信息工程学院, 重庆 401331;
    2 重庆大学自动化学院, 重庆 400044;
    3 重庆天泰铝业有限公司, 重庆 401328
  • 通讯作者: 易军(1973—),男,博士,副教授。
  • 作者简介:易军(1973—),男,博士,副教授。
  • 基金资助:

    国家自然科学基金项目(51374268,51075418,61174015);重庆市自然科学基金项目(cstc2012jjB40006,cstc2013jjB40007,cstc2012jjA90011);重庆市教委科学技术研究项目(KJ121410);重庆科技学院校内科研基金项目(CK2011B04,CK2013Z10)。

Abstract: It is difficult to accurately describe probability distribution and to do correlation analysis of operating multiple parameters in aluminum reduction cells. A correlation analysis method based on mixed Copula model was proposed to resolve the problem. First of all, non-parametric kernel density estimation method was used to establish edge density function of variables in the case of unknown distribution type. Secondly, proportion of contribution of different Copula functions could be adjusted by weight parameters in the joint distribution function of multiple parameters. Finally, the maximum likelihood method was used to estimate the mixed model parameters. By using 1824 groups real data of 170 kA operating aluminum smelter from a factory, test results showed that this method was better than other single Copula function because three distance indicators were 0.3169, 0.6239 and 0.9276. It was an effective way under super-low-voltage condition to do multi-parameter correlation analysis with non-steady-state and non-uniform features.

Key words: correlation analysis, Copula, model, distributions, electrolysis

摘要: 针对铝电解大型预焙槽操作参数较多且彼此耦合性强,难以进行准确的概率分布描述和相关性分析问题,提出一种基于混合Copula模型的铝电解槽多参数相关性分析方法。在铝电解槽参数分布类型未知的情况下,首先利用非参数核密度函数估计建立变量的边缘密度函数;再构建基于混合Copula模型的多变量联合分布函数,并通过权重参数调节不同类型Copula函数的贡献比重;最后利用极大似然法对模型参数进行估计。对取自某厂170 kA铝电解槽的1824组真实样本数据进行实验,结果得到的3种距离指标分别是0.3169、0.6239和0.9276,均优于其他单一Copula函数,表明本方法是对超低电压下具有非稳态非均一特征的多参数进行相关性分析的一种有效途径。

关键词: 相关性分析, Copula, 模型, 分布, 电解

CLC Number: