发酵过程生物量软测量技术的研究进展

Research progress in soft-sensor techniques for on-line biomass estimation in fermentative process

生物量是发酵过程中的关键过程参数之一,它直接影响着发酵过程的优化和控制。综述了近年来发酵过程生物量软测量技术的研究现状,讨论了基于过程机理分析、回归分析、状态估计和神经网络等的软测量建模方法,对基于神经网络和改进的神经网络建模方法进行了分析。指出基于多尺度建立软测量混合模型,是实现发酵过程生物量在线测量的有效方法,并给出了建立混合模型需要解决的关键问题。

Biomass is one of the most important variables in the fermentative process, and it directly influences the automatic control performance of fermentation system as well as in system monitoring and on-line optimization. The researches of soft-sensor techniques for on-line biomass estimation in the fermentative process are reviewed in past years, and modeling methods based on the fermentative process mechanism analysis, regression analysis, state estimation, artificial neural network (ANN), are discussed, and furthermore the modeling methods based on ANN and improved ANN are analyzed. It is pointed out that the soft-sensor hybrid model is an effective approach to the on-line biomass estimation in the fermentative process, which tries to use the best available process mechanism model to describe the fermentative process dynamics, coupled with the so-called 'black box' models such as ANN or support vector machine (SVM). The key problems involved in the hybrid modeling are presented.