摘要
密闭鼓风炉熔炼过程中的铅锌冶炼反应工艺非常复杂,且工况变化较大,目前还没有比较有效的方法对其监测。主元分析(PCA)是一种有效的多元统计过程监测方法,将PCA应用于密闭鼓风炉熔炼生产的统计过程控制,分析了T^2统计、SPE统计量的变化趋势,与密闭鼓风炉实际生产状况的对应关系。试验结果表明,PCA方法可快速有效地反映生产过程的变化,生产运用效果表明该方法大大提高了对密闭鼓风炉生产工况的实时监测能力,提高了生产效率。
Imperial smelting furnace （ISF） smelt manufacture has a complex technics of Pb-Zn Smelting reaction, and its operation conditions fluctuate greatly. Thus it is important to monitor and diagnose the smelting manufacture in real time to guarantee the product quality. Principal components analysis （PCA） is an effective method for process monitoring and multiple process variables analysis. The expectations of T^2 and SPE statistics are studied in this paper and their relations to the statistical parameters of process data are presented. These relationships reveal the influence factors of the T2 and SPE tests and give a definite description of the detection behavior of PCA. Applying PCA to statistical process control of ISF, the change trends of expectations of T2 and SPE statistics and the relationship with ISF manufacture status are analyzed. The experiment results indicate that PCA method improves the real time inspecting ability for ISF smelting and the efficiency of manufacture.
出处
《计算机与应用化学》
CAS
CSCD
北大核心
2007年第2期155-158,共4页
Computers and Applied Chemistry
基金
国家973计划(2002cb312200)资助项目
关键词
密闭鼓风炉
主元分析
统计监测模型
imperial smelting furnace, principal components analysis, statistic monitoring model
作者简介
唐朝晖（1965-），博土生，副教授．
