基于LSSVM-MODE的水煤浆生产优化控制  

Optimization Control of Preparation of Coal Water Mixture Based on LSSVM-MODE

作　　者：刘定平[1] 叶向荣[1] 邓华裕 

机构地区：[1]华南理工大学电力学院,广东广州510640 [2]茂名热电厂,广东茂名525011

出　　处：《华南理工大学学报（自然科学版）》2009年第2期158-162,共5页Journal of South China University of Technology(Natural Science Edition)

摘　　要：水煤浆(CWM)制造过程中,生产成本的降低和水煤浆性能的提高之间存在着矛盾.文中利用最小二乘支持向量机(LSSVM)对球磨机电流和水煤浆浓度进行多目标建模,并采用基于Pareto最优概念的多目标微分进化(MODE)算法对运行工况进行寻优,然后根据模糊集理论在Pareto解集中求得满意解,获得了水煤浆浓度的优化调整方式和提高水煤浆生产效益的策略.In the production of coal water mixture （ CWM）, there exists an inconsistency between the production cost and the product performance. In order to solve this problem, the least-square support vector machine is em- ployed to establish a muhi-objective optimization model for CWM concentration and ball mill current, and the multi- objective differential evolution algorithm based on Pareto optimal concept is used to optimize the operation condi- tions, Moreover, the fuzzy set theory is introduced to obtain the satisfactory solutions in Pareto solution set. An op- timized adjustment mode of CWM concentration and some strategies to improve the CWM production benefit are fi- nally proposed in the paper.

关 键 词：水煤浆 优化运行 最小二乘支持向量机 多目标微分进化算法 

分 类 号：TK323[动力工程及工程热物理—热能工程]