Chin.J.Chem.Eng. ›› 2018, Vol. 26 ›› Issue (5): 1071-1077.doi: 10.1016/j.cjche.2017.08.007

• Process Systems Engineering and Process Safety • Previous Articles     Next Articles

A sludge volume index (SVI) model based on the multivariate local quadratic polynomial regression method

Honggui Han1,2, Xiaolong Wu1,2, Luming Ge1,2, Junfei Qiao1,2   

  1. 1 College of Automation, Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China;
    2 Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing 100124, China
  • Received:2017-05-24 Revised:2017-08-09 Online:2018-05-28 Published:2018-06-29
  • Contact: Honggui Han,E-mail

Abstract: In this study, a multivariate local quadratic polynomial regression (MLQPR) method is proposed to design a model for the sludge volume index (SVI). In MLQPR, a quadratic polynomial regression function is established to describe the relationship between SVI and the relative variables, and the important terms of the quadratic polynomial regression function are determined by the significant test of the corresponding coefficients. Moreover, a local estimation method is introduced to adjust the weights of the quadratic polynomial regression function to improve the model accuracy. Finally, the proposed method is applied to predict the SVI values in a real wastewater treatment process (WWTP). The experimental results demonstrate that the proposed MLQPR method has faster testing speed and more accurate results than some existing methods.

Key words: Sludge volume index, Multivariate quadratic polynomial regression, Local estimation method, Wastewater treatment process