基于冗余测量的电厂能耗数据诊断方法  

Power Consumption Data Redundancy Measurement-based Diagnostic Methods

作　　者：王惠杰[1] 张晓博[1] 郭江龙[2] 王妍飞 张晗[1] 曹通[1] 

机构地区：[1]华北电力大学,保定071003 [2]河北省电力研究院,石家庄050021

出　　处：《汽轮机技术》2015年第4期310-312,共3页Turbine Technology

摘　　要：电厂DCS系统可提供大量数据形成数据冗余,利用热工数据之间的内在联系能够进行数据诊断。简要介绍了数据诊断的基本原理和方法。基于冗余测量,利用最大似然估计的方法并将能量平衡、质量守恒和熵增原理作为约束条件,进行数据诊断。结合电厂THA设计工况和75%负荷与50%负荷的实际工况数据,对给水流量进行了诊断,得出了检测结果,又利用矩阵精确模型对结果进行了验证,表明结果合理、方法正确,能够用来数据诊断。实时数据经过检测,能识别出有误数据,提高机组运行监测准确性,并对产生异常数据的变送器进行重新校验。Power plant DCS systems can provide a lot of data to form the data redundancy, use the intrinsic link between thermal data can diagnose datum. This paper introduces the basic principles and methods of data diagnosis. Base on redundant measurements, using the maximum likelihood estimation method and energy balance, mass conservation and the principle of entropy as constraints for data diagnosis. Combined power plant THA design conditions and the actual condition of 75% load and 50% load data, diagnosed feed water flow data, obtained test results, and using matrix exact model verified results, it showed reasonable results, a method correctly, and the method can be used to diagnose datum. After testing real-time data, it can identify incorrect data to improve the accuracy of the monitoring unit operation. And re-check the transmitter which generated the abnormal data.

关 键 词：冗余数据 诊断方法 最大似然估计 能量平衡 

分 类 号：TK267[动力工程及工程热物理—动力机械及工程]