摘要
通过发酵过程建模实现发酵过程优化控制和关键参量实时在线监测,但是牛粪高温厌氧发酵过程机理复杂,建立发酵过程的精确模型具有一定难度,而传统的单一建模预测方法又不能很好的反映过程机理。为了解决上述问题,采用混合建模方法,以传统的厌氧发酵动力学模型为基础,结合支持向量机建立牛粪厌氧发酵过程测量的混合模型,弥补了单一模型的不精确性。将混合模型运用到牛粪高温厌氧发酵过程监测中,结果表明该混合模型能够有效地预测估计关键变量,指导大型沼气工程的智能控制。
The purpose of this paper is to optimize the control and achieve the key parameters of real - time online detection. It is achieved through the fermentation process modeling. Due to the complexity of Anaerobic - Thermophilic Fermentation process of Cattle Manure,it is difficult to model the process of fermentation precisely. Furthermore traditional single modeling prediction ＇meth- od cannot be a good reflection of the process mechanism. In order to solve the above - mentioned problems, the paper uses＇ Support Vector Machine and mechanistic model to model. It compensates for the kinetic mechanism of model inaccuracies. The hybrid model is applied to monitoring process of cow dung thermophilic anaerobic fermentation, the results show that the hybrid model can effec- tively forecast estimates of the key variables. It can guide the intelligent control of large - scale biogas projects.
出处
《黑龙江科学》
2013年第1期45-47,50,共4页
Heilongjiang Science
关键词
混合模型
机理模型
支持向量机
厌氧发酵
Hybrid model
mechanism model
support vector machine
anaerobic fermentation
