Study on Applied Technology with Soft Measurement for Lance Position Based on MLR and PCR

Abstract:

Because the lance position of oxygen-enriched air and top-blown furnace is affected by lance pressure, melt temperature, melt furface,the type of slag and other factors, it is difficult accurately measured. Firstly, processing informations(excluding data,analysis correlation) to the production data.Then identified the main auxiliary variables of soft measurement model and established MLR and PCR soft prediction model of the lance position.Secondly,according to production data,through fitting and forecasting of these models, the results show that the PCR model's forecasting ability is better than the MLR model.Finally, the obtained model is embedded in WinCC software platform and further verify the feasibility of the model.The research may guide the production and lay theoretical foundations for the lance position control

• Periodical: Advanced Materials Research (Volume 859)
• Pages: 379-383
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.859.379
• Online since: December 2013
• Authors: Kai Fen Wen, Ying Dong Liao, Li Hui Feng, Qiang Hua Shen
• Keywords: Data Process, MLR, Oxygen-Enriched Air and Top-Blown Furnace, PCR, Soft Measurement

References

[1] Wifeng Li, Zhuhong Jia．Lead sulfide concentrate oxygen rich-low blow and oxygen-enriched top-blown smelting technology[M]．Changsha: Central South University Press, (2010).

[2] Ye Chen．Implementation of integrated automatic control system of copper smelter based on bath smelting technique[J]．International Journal of Manufacturing Technology and Management, August 2012 , pp.224-236.

DOI: 10.1504/ijmtm.2012.048706

[3] Chuan Ye, Chuanhui WU, Jiayi Zhang. Measurement and Testing of abnormal data rejection method[J]．Measurement and test technology，2007，34（7）: 26—27.

[4] Min Zhang, Hui Yuan. The Rajda criterion and rejecting the abnormal value[J]．Journal of Zhengzhou University of Technology，1997，18(1): 84—88.

[5] Tsekouras, G.J. A non-linear multivariable regression model for midterm energy forecasting of power systems[J]． Electric Power Systems Research, October 2007 , pp.1560-1568.

DOI: 10.1016/j.epsr.2006.11.003

[6] Zhilin Li, Jianhua Yin. MATLAB software application in the establishment of regression model[J]．Mathematical Statistics and Management (Supplement)2005，24(1): 392—397.

[7] Lijuan Wang. Sewage treatment energy consumption analysis based on principal component analysis and neural network [J]． Computer Technology and Development, 2011，21（3）: 243—245.

[8] Mingyue Li, Xi Cao, Yanhua Jiang. A OD in slag splashing lance automatic control expert system[J]．Instrumentation Customer，2008，6（1）: 14—15.

[9] Liu, Wansheng Tang. Modern control theory[M]．Beijing: Machinery Industry Press，(2007).

[10] Wang, Jun．Performance improvement of VAV air conditioning system through soft measurement technology[J]．Shanghai Jiaotong Daxue Xuebao/Journal of Shanghai Jiaotong University, March 2007, pp.428-431.

[11] Jian Wang, Yaoquan Yang, Gaowei Ma. Study on the selection of secondary variables of soft measurement method[J]． Electric power science and Engineering，2011，27（7）: 37—40.

[12] Zhaoming Yan, Yangmin Zhou, Zhiyuan Yang. Situation and development trend of the comprehensive utilization of blast furnace slag[J]．Iron and Steel Research，2010，38(2): 53—56.

[13] Yu Xie. Regression Analysis[M]．BeiJing: Social Sciences Academic Press，(2010).

[14] Liu, Chunfeng．Research of binocular positioning mathematical model based on the least square method[J]．Applied Mechanics and Materials, 2011, pp.473-477.

DOI: 10.4028/www.scientific.net/amm.50-51.473

[15] Lideng Pan, Dayu Li, Junying Ma. Principles and Applications of Soft Measurement Technology[M]．Beijing: China Electric Power Press, (2009).

[16] Jin Cao，Guizeng Wang. Fault monitoring method based on principal component analysis[J] Journal of Zhejiang University，1996，30（2）（Supplement）: 174-180.

[17] Jiageng Chen, Jose A. Bandoni, Jose A. Romagnoli. Robust PCA and Normal Region in Multivariate Statistical Process Mointoring[J]．AIChE Journal, 1996: 3563~3566.

DOI: 10.1002/aic.690421228

[18] Zheng, Xiao-Xia, Qian, Feng．Soft sensor modeling based on PCA and support vector machines[J]． Xitong Fangzhen Xuebao / Journal of System Simulation, March 2006 , pp.739-741.