摘要
探讨厂级监控系统中实时数据的校正算法及其应用技术.介绍了测量数据误差的相关概念;基于多元统计分析基本原理,建立了数据校正的基本模型;基于信号处理原理,重点研究了数字滤波方法在数据协调中的应用;结合火电机组厂级监控系统的应用特点,提出了数据分级的概念,建立了基于设备特性的数据误差识别及其修补的关联模型.应用上述关联模型,在冗余检验和数字滤波等技术的支持下,建立并实现了数据显著误差检验与数据协调相互统一的数据校正方法.应用结果表明,该方法具有算法简单,概念清晰,保证了实时分析结果的有效性.
Data rectification algorithm and its application in the supervisory information system in power plant were studied in this paper. Fundamental concepts of measurement error and data rectification were introduced. Based on the principle of multivariate statistical analysis, the theoretical model of data rectification was developed. Data reconciliation algorithm based on Kalman digital filtering was analyzed in detail. Combined with the characteristic of supervisory information system in power plant, by grading the measured parameters, a new measurement error detection and amendment model was established. Based on this model and the techniques of redundancy check and digital filtering, a new data rectification algorithm has been proposed, which unifies the data reconciliation and the gross error detection and identification. Results show that the model has clear physical meaning and can meet the needs of performance analysis.
出处
《东南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2005年第1期11-15,共5页
Journal of Southeast University：Natural Science Edition
基金
国家自然科学基金资助项目(50376011)
江苏省自然科学基金资助项目(BK2001005)
关键词
厂级监控系统
测量误差
数据校正
Algorithms
Data handling
Kalman filtering
Measurement errors
Power plants
Statistical methods
