IFA和FA聯(lián)合方法在化工過(guò)程監(jiān)控中的應(yīng)用
發(fā)布時(shí)間：2018-10-11 09:46
【摘要】：工業(yè)過(guò)程數(shù)據(jù)具有高斯和非高斯混合分布的特點(diǎn)。獨(dú)立因子分析(IFA)采用一維高斯混合模型擬合任意的因子分布,因此可以處理高斯和非高斯混合的問(wèn)題。雖然在給定因子數(shù)的前提下變分IFA算法可以有效地縮短建模時(shí)間,但是獨(dú)立因子數(shù)的選擇仍然需要較長(zhǎng)的計(jì)算時(shí)間。此外,若IFA的因子數(shù)選擇不當(dāng),會(huì)造成部分因子的信息遺留在觀察變量的殘差中,導(dǎo)致GSPE監(jiān)控指標(biāo)的監(jiān)控性能變差。為了解決IFA在實(shí)際應(yīng)用中存在的問(wèn)題,本文結(jié)合了IFA和FA方法。首先使用FA輔助IFA選取獨(dú)立因子數(shù),以進(jìn)一步減小IFA建模時(shí)間;其次使用FA對(duì)IFA的殘差進(jìn)行再處理,以解決由于獨(dú)立因子數(shù)選擇不當(dāng)造成的問(wèn)題。最后將該方法應(yīng)用于田納西-伊斯曼(TE)過(guò)程和乙烯裂解爐過(guò)程的監(jiān)控中,實(shí)驗(yàn)結(jié)果驗(yàn)證了該聯(lián)合方法的有效性。
[Abstract]:Industrial process data have the characteristics of mixed distribution of Gao Si and non-Gao Si. Independent factor analysis (IFA) uses a one-dimensional Gao Si mixed model to fit arbitrary factor distributions, so it can deal with the mixed problem of Gao Si and non-Gao Si. Although the variable IFA algorithm can effectively shorten the modeling time under the condition of given factor number, the selection of independent factor number still needs a long calculation time. In addition, if the factor number of IFA is not selected properly, the information of some factors will be left in the residual of observation variables, which will lead to the deterioration of monitoring performance of GSPE monitoring index. In order to solve the problem of IFA in practical application, this paper combines IFA and FA methods. In order to further reduce the modeling time of IFA, the FA aided IFA is used to select the independent factor number, and the FA is used to reprocess the IFA residuals to solve the problem caused by improper selection of independent factor numbers. Finally, the method is applied to the monitoring of Tennessee Eastman (TE) process and ethylene cracking furnace process. The experimental results show the effectiveness of the combined method.
【作者單位】： 華東理工大學(xué)化工過(guò)程先進(jìn)控制和優(yōu)化技術(shù)教育部重點(diǎn)實(shí)驗(yàn)室;
【基金】：國(guó)家自然科學(xué)基金(61134007,21376077,21303102) 上海市研發(fā)平臺(tái)建設(shè)項(xiàng)目(13DZ2295300) 上海市自然科學(xué)基金(16ZR1407300)
【分類號(hào)】：TP277;TQ06
本文編號(hào)：2263746
[Abstract]:Industrial process data have the characteristics of mixed distribution of Gao Si and non-Gao Si. Independent factor analysis (IFA) uses a one-dimensional Gao Si mixed model to fit arbitrary factor distributions, so it can deal with the mixed problem of Gao Si and non-Gao Si. Although the variable IFA algorithm can effectively shorten the modeling time under the condition of given factor number, the selection of independent factor number still needs a long calculation time. In addition, if the factor number of IFA is not selected properly, the information of some factors will be left in the residual of observation variables, which will lead to the deterioration of monitoring performance of GSPE monitoring index. In order to solve the problem of IFA in practical application, this paper combines IFA and FA methods. In order to further reduce the modeling time of IFA, the FA aided IFA is used to select the independent factor number, and the FA is used to reprocess the IFA residuals to solve the problem caused by improper selection of independent factor numbers. Finally, the method is applied to the monitoring of Tennessee Eastman (TE) process and ethylene cracking furnace process. The experimental results show the effectiveness of the combined method.
【作者單位】： 華東理工大學(xué)化工過(guò)程先進(jìn)控制和優(yōu)化技術(shù)教育部重點(diǎn)實(shí)驗(yàn)室;
【基金】：國(guó)家自然科學(xué)基金(61134007,21376077,21303102) 上海市研發(fā)平臺(tái)建設(shè)項(xiàng)目(13DZ2295300) 上海市自然科學(xué)基金(16ZR1407300)
【分類號(hào)】：TP277;TQ06
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1 黃蕾;;IFA秘書(shū)長(zhǎng)支招中國(guó)化肥業(yè)[J];中國(guó)科技財(cái)富;2006年04期
2 ;第68屆IFA年會(huì)引發(fā)的思考[J];農(nóng)資科技;2000年04期
3 Changkyoo Yoo;Minhan Kim;Sunjin Hwang;Yongmin Jo;Jongmin Oh;;非高斯建模方法的間歇過(guò)程的在線預(yù)測(cè)監(jiān)控和預(yù)測(cè)模型(英文)[J];Chinese Journal of Chemical Engineering;2008年01期
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