Industrial real-time data processing system and method

Abstract

The invention discloses an industrial real-time data processing method, which comprises the following steps: acquiring data to be processed, and packaging the acquired data to be processed according to an appointed data format; unpacking the packed data according to a routing strategy, and processing and distributing the unpacked data; receiving the processed data, analyzing the processed data according to a data analysis model, and outputting an analysis result; and receiving data, carrying out alarm analysis on the processed data according to an alarm strategy, carrying out alarm analysis onan analysis result according to the alarm strategy, and sending the alarm analysis result to a user terminal, wherein the received data comprises unpacked and processed data and analysis result data.On one hand, the molten iron detection efficiency is improved, and the detection accuracy is guaranteed, and on the other hand, it is guaranteed that a user can rapidly obtain the detection effect, and the user can make a timely and reasonable decision according to the detection effect.

Description

technical field [0001] The invention relates to the technical field of iron and steel production, in particular to an industrial real-time data processing system and method. Background technique [0002] In steel production, molten iron needs to be analyzed to ensure the qualified rate of finished steel. Molten iron analysis usually analyzes the composition of molten iron and the proportion of each component. Existing analysis mostly adopts manual detection, and analysis is assisted by tables. This analysis method has the following disadvantages: low analysis efficiency, inability to obtain data in real time, and lack of a unified processing platform to realize functions such as collection and storage of important real-time data, monitoring and alarming, and retrospective analysis. [0003] The second is that the data is scattered, and it is difficult to distribute statistics, and the obtainers cannot effectively and quickly obtain the desired data. Third, there is a lack...

AI Technical Summary

Problems solved by technology

This analysis method has the following disadvantages: low analysis efficiency, unable to obtain data in real time, and lacks a unified processing platform to realize functions such as collection and storage of important real-time data, monitoring and alarming, and retrospective analysis

[0003] The second is that the data is scattered, and it is difficult to distribute statistics, and the acquirer cannot effectively and quickly obtain the desired data

The third is the lack of system support for real-time monitoring, real-time alarms and post-event retrospective analysis of data such as equipment operating status and energy consumption, which makes it difficult for front-line operators and managers to find abnormal situations and deal with them in a timely manner

Images