基于系统测量冗余的电厂异常运行数据检测与校正

电厂异常运行数据对汽轮发电机组性能监测、能损诊断的准确性有很大的影响：该文基于测量冗余，考虑不同变量的测量精度，根据最大似然原理，给出异常测量数据的检测和校正方法，校正后的数据满足物质平衡、能量平衡或熵增原理等基本定律：发电厂给水流量、入炉煤量、低位发热量的检测和校正结果表明，该方法是合理的，能够进行显著测量误差检测，并将其校正到合理的数据：实时数据经过校正后，能更为真实地反映机组的实际运行状况，提高了性能监测和能损诊断的准确性，并提醒管理人员对数据异常的变送器进行校验和维护。

DETECTION AND RECONCILIATION ON THE ABNORMAL OPERATION DATA BASED ON REDUNDANCY MEASUREMENT IN A POWER PLANT

Much attention should be paid to the impacts of abnormal operation data on the perfection of performance on-line monitoring and energy-loss diagnosis in a power plant. Considering different precision of the instruments onsite, this paper puts forward measures to detect and reconcile the abnormal operation data, based on measurement redundancy and maximum likelihood estimation, the reconciled data are perfectly fitted the basic theorems such as matter and energy conservation, principle of entropy increase in the system. Reconciliation of feed water flow, heat value and flow rate of coal to the boiler shows that this method can detect gross measurement errors in power plant, and reconcile them to reasonable data, the reconciled data reveal more actual conditions of the generating units, improve of the performance on-line monitoring and energy-loss diagnosing, and moreover it can remind the supervisor to calibrate the fault transmitters.