基于SPSS分析煤灰白度特征和灰成分关系的研究  

Study on the relationship between coal ash composition and ash whiteness characteristics based on SPSS regression analysis

作　　者：许琴 XU Qin(South China Branch,China Energy Coal Trading Go.,LTD.,Guangzhou,Guangdong 510610,China)

机构地区：[1]国能销售集团有限公司华南销售分公司,广东广州510610

出　　处：《煤炭加工与综合利用》2024年第8期127-130,136,共5页Coal Processing & Comprehensive Utilization

摘　　要：为了探索国能集团煤灰白度特征和灰成分的关系,借助SPSS统计分析软件进行了相关性分析,以灰白度为因变量,煤灰各成分为自变量建立多元线性回归模型。结果表明,煤灰白度与灰成分中的K_(2)O、Fe_(2)O_(3)、MnO_(2)、Al_(2)O_(3)具有很强的相关性,而与P_(2)O _(5)没有相关关系;建立了含Al_(2)O_(3)、Fe_(2)O_(3)、K_(2)O三个自变量的模型,可以解释白度的94.6%变化原因,模型具有一定的统计学意义,为煤灰白度特征和灰成分关系的探究提供参考。In order to explore the characteristic relationship between coal ash composition and ash whiteness of Guoneng Group,a correlation analysis was carried out with the help of SPSS statistical analysis software.A multiple linear regression model was established with ash whiteness as the dependent variable and coal ash composition as the independent variable.The results showed that K_(2)O,Fe_(2)O_(3),MnO_(2) and Al_(2)O_(3) in coal ash had a strong correlation with ash whiteness,while P_(2)O_(5) had no correlation with ash whiteness,and the established model contained three independent variables,namely Al_(2)O_(3),Fe_(2)O_(3) and K_(2)O,which could explain the 94.6%change in whiteness.The model is statistically significant.This study provides a reference for the exploration of the relationship between the whiteness characteristics and ash composition of coal ash.

关 键 词：煤灰成分 灰白度 SPSS 多元线性回归 相关性 

分 类 号：TQ536.4[化学工程—煤化学工程]