文献类型：期刊文献

中文题名：一种针对火电厂流量计数据特点的数据处理算法

英文题名：An Approach of Data-Processing to the Flow Meter Data of Thermal Power Plant

作者：陈晶[1];吴胜昔[1];顾幸生[1]

机构：[1]华东理工大学自动化研究所,上海200237

年份：2009

卷号：35

期号：3

起止页码：475

中文期刊名：华东理工大学学报（自然科学版）

外文期刊名：Journal of East China University of Science and Technology

收录：CSTPCD;;Scopus;北大核心:【北大核心2008】；CSCD:【CSCD2011_2012】；

基金：国家高技术研究发展计划(863计划)(2007AA04Z199)

语种：中文

中文关键词：火电厂;流量计;标准差估计;数据融合

外文关键词：thermal power plant; flow meter; standard deviation of estimates; data fusion

摘要：火电厂生产流程中使用了大量流量计。由于工况的复杂性,工质流量数据特征呈现高度的非线性和时变性,给生产系统的监测与控制造成了不可忽视的影响,而现行的常规数据处理方法难以满足系统的要求。基于误差分布的数理统计规律,结合生产实际中的需求,构造了一种针对火电厂流量计数据特性的有效数据处理模型,可以实时提取数据特征,并自动根据当前数据情况对模型即时调整。实验结果表明:该数据处理算法对于电厂的流量数据处理比其他算法更加有效。
Large number of flow meters are used in the production of thermal power plant. Because of the complex status, the data of the flow have the characteristic of high nonlinears and variability, which have a high impact on the monitoring and controlling of the production system. However, the conventional model of data-processing could hardly meet the requirements of systems. Based on the mathematical statistics laws of errors probability distribution, a new model is presented in this paper to extract real-time data features. The adjustment of the model can be automatically done according to the data features. Experimental results show that the proposed data-processing method is more effective on plant flow data than the previous ones.