Journal of South China University of Technology (Natural Science Edition) ›› 2009, Vol. 37 ›› Issue (8): 56-60.

• Mechanical Engineering • Previous Articles     Next Articles

Approach to Modeling Nonlinear Multi-Sensor Coupling Information Based on INLR-PPLS

Hong Xiao-bin  Liu Gui-xiong  Ye Ting-dong  Huang Guo-jian  Chen Tie-qun   

  1. School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510640, Guangdong, China
  • Received:2008-08-03 Revised:2008-09-12 Online:2009-08-25 Published:2009-08-25
  • Contact: 洪晓斌（1979-），男，博士后，主要从事新型智能传感技术、网络化测控的研究． E-mail:mexbhong@scut．edu．cn
  • About author:洪晓斌（1979-），男，博士后，主要从事新型智能传感技术、网络化测控的研究．
  • Supported by:

    广东省自然科学基金资助项目（7000815）;中国博士后基金资助项目（20070420779）;广东省教育部产学研结合项目（2007A090302039）;华南理工大学博士后创新基金资助项目（20080215）

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Abstract:

:In order to remedy the shortcomings of linear PLSR （ Partial Least Squares Regression） in multi-sensor information regression modeling, a novel modeling approach based on INLR （Implicit Nonlinear Latent Variable Regression）-PPLS （Polynomial Partial Least Squares） is put forward. In this method, multi-sensor information is preprocessed by means of linear PLSR to reduce the dimension, and a nonlinear sample-matrix transform formula of the outer model is established and linearized based on INLR. Then, the nonlinear mapping of the inner model is performed via PPLS and the reverse regression model is obtained. The proposed method is finally applied to the measurement and control system of liquid alcohol concentration. It is found that the prediction accuracy of the pro- posed approach is 21% higher than that of linear PLSR.

Key words: muhi-sensor information, partial least squares regression, INLR, PPLS