Soft Sensor of Biological Parameters in the Marine Protease Fermentation Process

摘要：

　　In order to solve the difficulties of online measurement in the marine protease fermentation process of crucial biological variables(such as biomass concentration,substrate concentration and enzyme activity,etc),a soft sensing method based on KPCA-RBF neural network is proposed by combining the kernel principal component analysis(KPCA)with the radial basis function(RBF)neural network.Establishing the soft sensing model of KPCA-RBF neural network,KPCA is applied to compress data,and choose the nonlinear component as the input of RBF neural network and biomass concentration,substrate concentration,relative enzyme activity as the output.Simulation results indicate that this model has a higher accuracy,better tracking performance when compared with RBF and PCA-RBF neural network model.Therefore,the proposed method can satisfy the requirements of on-line measurement of biological parameters and is proved to be an efficient modeling method.

关键词： marine protease biological parameters kernel principal component analysis radial basis function neural network soft sensing

作者: DING Shen-ping WANG Ying-hai SUN Li-na

作者单位: Suzhou Industrial Park Institute of Vocational Technology,Jiangsu,Suzhou 215123,P.R.China

会议类型: 国际会议

会议名称: The 33th Chinese Control Conference第33届中国控制会议

会议地点: 南京

会议语种:英文

页码: 3620-3624

在线出版日期: 2014-07-28（万方平台首次上网日期，不代表论文的发表时间）