摘要
对基于差分进化蚁群算法的粉煤灰颗粒粒径反演算法进行了研究,提出了基于概率密度函数的连续域蚁群算法与差分进化算法融合的混合算法,以光全散射法为基础,采用3种单峰粒径分布函数验证了反演算法,并加入5%和10%随机噪声,将混合算法与概率密度蚁群算法所得数值进行比较。结果表明:该混合反演算法重建结果与原始分布误差较小,具有较高的可靠性和正确性,能够有效用于粉煤灰颗粒粒径在线测量,加入噪声后仍表现出良好稳定性;与连续域蚁群算法相比,该算法提高了迭代收敛速度,为粉煤灰的在线测量提供了理论基础。
The particle size inversion algorithm of fly ash particle based on the differential evolution ant colony algorithm was studied. A hybrid algorithm covering both probability density function ant colony algorithm and differential evolution algorithm was proposed. By using light scattering,three kinds of single-peak practice size distribution functions were provided to prove this hybrid method. In addition,to compare the results from hybrid algorithm and probability density algorithm,5% and 10% random noise were introduced. The results show that the hybrid method has lower error than the original distribution. That means it has higher certain of reliability and validity,and it can be available to test coal dusty particle online,even adding noise. Compared with continuous domain ant colony algorithm,the hybrid one has quicker iterative convergence speed,and that contributes to the theoretical basis of online testing.
作者
赵延军
曲毅
ZHAO Yan-jun;QU Yi(College of Electrical Engineering,North China University of Science and Technology-,Tangshan 063000,Hebei Province,Chin)
出处
《化学工程》
CAS
CSCD
北大核心
2018年第2期67-71,共5页
Chemical Engineering(China)
基金
国家自然科学基金资助项目(51476154)
关键词
粉煤灰颗粒
差分进化算法
蚁群算法
粒径分布
fly ash particles
differential evolution algorithm
ant colony algorithm
particle size distribution
