A Method for Screening the Accuracy of Online Measurement Data

Abstract

A discrimination method for on-line measured data accuracy comprises on-line measured data collection, data testing and reconfiguration, data warning and data warning message Web release. With the method, an abnormal tested point can be found automatically, and a warning prompt message is generated. Meanwhile, a thorough alarming mechanism exists, so that statistical analysis and management for tested point information are achieved. A data pre-processing method is based on a classical method for dynamic testing data processing, and experience in a heating power productive process is introduced to discriminate the accuracy of the data, so that the discrimination process is scientific, and the discrimination result is reliable. Statistical information of data accuracy discrimination can motivate self tested point maintenance of an electric power plant, and the electric power plant is also assisted in relative examination of thermotechnical measurement. Configuration and debugging of the method are completed at a time, the maintenance workload is small, and a big problem of large method data maintenance is resolved.

Description

technical field [0001] The invention relates to a data processing method, in particular to a method for identifying the accuracy of on-line thermal measurement data in thermal power plants. Background technique [0002] With the advent of the era of big data, all walks of life are faced with the processing of massive data and information, and the accuracy of data is particularly important. [0003] For thermal power plants, the working environment of thermal measuring instruments is harsh, and there are frequent interferences such as noise, high temperature, pressure waves, electromagnetic waves, and mechanical vibrations. The reliability and stability of measurement data decline accordingly, and sudden failures are prone to occur at measurement points. This situation poses a great threat to the automatic control of thermal power plants, and the control parameters will be disordered; at the same time, the data collected by other information systems such as SIS, MIS and EAM w...

AI Technical Summary

Problems solved by technology

[0003] For thermal power plants, the working environment of thermal measuring instruments is harsh, with frequent interferences such as noise, high temperature, pressure waves, electromagnetic waves, and mechanical vibrations. The reliability and stability of measurement data will decline accordingly, and sudden failures will easily occur at measurement points.

This situation poses a great threat to the automatic control of thermal power plants, and the control parameters will be disordered; at the same time, the data collected by other information systems such as SIS, MIS and EAM will also be affected, and the statistics and analysis of upper-level data will be affected. Pollution

[0004] In recent years, more and more attention has been paid to the research and application of measurement data correction technology in the performance monitoring system of thermal power units, mainly including the elimination and reconstruction of significant errors, the filtering method of random errors, etc., but only limited to the research of algorithm models, few independent data processing system

Images