摘要
文中提出了一种基于大数据的多尺度系统软测量算法,首先建立了系统输入、输出多尺度相对能量矩阵,并在此基础上定义了多尺度系统。而后针对上述多尺度系统,提出构建双模型,并利用基于卡尔曼滤波的数据融合算法,对双模型的预测值与运行参数构成的残差序列进行数据融合及多尺度分析,以实现系统的软测量。文中算法对某机组辐射受热面灰污程度的软测量结果显示,该方法简单易行,结果较为准确,可为运行优化提供技术依据。
The paper proposed a soft measurement method and its application based on big data. The construction of soft measurement parameter realized measurement for complex systems. A muhi-seale system is defined based on in- put and output relative energy matrix. Then two models were established and Kalman filter was used to analysis da- ta,which consist of the residual of operation data and predicted value of the two models. The soft measurement for ash deposition of radiant heating surface shows that,the algorithm proposed by the paper is simple and the result is accurate,which can provide technical basis for operation optimization.
出处
《自动化与仪表》
2015年第7期17-21,共5页
Automation & Instrumentation
关键词
大数据
多尺度系统
软测量
灰污染
big data
multi-scale system
soft measurement
ash deposition
