Nonlinear Dynamic Soft Senser modeling of Wastewater Treatment Effluent Quality
Due to the lack of widely stable and reliable water quality parameters on-line instrumentation, it is difficult to implement closed-loop control of water quality and optimize the operation for wastewater treatment plant. In this paper, a nonlinear dynamic soft-sensing multi-model based on PLS is proposed to solve the problem of multi-variable, non-linear and time-varying uncertainty in wastewater treatment process, through selection of such auxiliary variables easily received as water flow and quality, the dissolved oxygen and oxygen aeration. The methodology integrates dynamic ARX with Fuzzy C-means identifies operating conditions of time-varying and uncertainty in the wastewater treatment process. NNPLS is used to establish a number of non-linear model in different operating conditions and the whole non-linear system. The proposed method is applied in soft-sensing of effluent quality component concentration in wastewater treatment plant Simulation results indicate that the method which establishes a multi-variable model of water quality indicators is more precise than traditional linear PLS model.
NNPLS fuzzy-c-mems clustering (FCM) ARX soft-sensor WWTP
ZHAO Li-Jie XIAO Hui DIAO Xiao-Kun Chai tianyou
College Of Information Engineering,Shenyang Institute of Chemical Technology Shenyang, China key lab College Of Information Engineering,Shenyang Institute of Chemical Technology Shenyang, China key laboratory of integrated automation of process industry, Ministry of Education,Northeastern Univ
国际会议
The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)
沈阳
英文
413-417
2010-03-27（万方平台首次上网日期，不代表论文的发表时间）