Journal of South China University of Technology (Natural Science Edition) ›› 2011, Vol. 39 ›› Issue (5): 55-60,67.doi: 10.3969/j.issn.1000-565X.2011.05.010

• Electronics, Communication & Automation Technology • Previous Articles     Next Articles

Enhanced JIT-Based Soft-Sensing Modeling and Its Application to Wastewater Treatment

Liu Yi-qi  Huang Dao-ping  Li Yan   

  1. School of Computer Science and Engineering,South China University of Technology,Guangzhou 510006,Guangdong,China
  • Received:2010-07-29 Revised:2010-11-21 Online:2011-05-25 Published:2011-04-01
  • Contact: 刘乙奇(1983-)，男，博士生，主要从事智能检测研究 E-mail:liuyiqi769@sina.com
  • About author:刘乙奇(1983-)，男，博士生，主要从事智能检测研究
  • Supported by:

    国家自然科学基金资助项目(60704012)；华南理工大学中央高校基本科研业务费资助项目(2009ZM0161)

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Abstract:

In order to overcome the difficulty in on-line measurement of five-day biochemical oxygen demand ( BOD5) during the wastewater treatment,by taking into consideration the nonlinearity and multivariant coupling characteristics of wastewater treatment process,a robust nearest correlation algorithm based on Jolliffe parameters and correlation data selection algorithm is proposed,which is then combined with the recursive partial least square
algorithm and the linear bias compensation algorithm to improve the conventional JIT ( Just-in-Time) algorithm. Finally,the enhanced JIT algorithm is used to build an on-line soft-sensing model of BOD5. The results of simulation show that the enhanced JIT algorithm outperforms the conventional JIT and RPLS algorithms in terms of on-line prediction accuracy,adaptability and robustness of soft sensing.

Key words: soft sensing, JIT algorithm, biochemical oxygen demand, wastewater treatment, recursive partial least square