基于大数据分析的锅炉过量空气系数评估模型

Boiler excess air coefficient model based on the large data analysis

锅炉过量空气系数的大小直接影响着锅炉效率。采用大数据分析方法中的多元线性回归方法,在对历史运行数据进行预处理后,利用SPSS软件对样本数据进行回归分析,对影响过量空气系数的影响因子进行了研究,得到了几个选定的影响因子的相关系数,使用残差分析方法对模型的准确性进行了验证,最后基于设计值对实际运行的过量空气系数进行了分析。

Excess air coefficient value of boiler directly affects boiler efficiency. The multivariate linear regression method in the large data analysis method was used,after the preprocessing of the historical running data,the SPSS software was used to regress the sample data,and the evaluation model of the influence factors for the excess air coefficient was established. The correlation coefficient of the selected influence factors was obtained,and the accuracy of the model was carried out by the residual analysis method. Finally,the excess air coefficient of the actual operation was analyzed based on the design value.