A large-scale distributed data acquisition system and method based on industrial process

Abstract

A large-scale distributed data collection system and method based on industrial processes, the system includes several groups of field devices, several field control stations, data collection and scheduling modules, several data collection clients, several databases, and data collection and scheduling modules According to the operation status information of the field control station, the operation status information of the data collection client, the data collection cycle, and the data items to be collected, data collection tasks are assigned to several data collection clients; the data collection client is used to set the data collection cycle, the The collected data items, the operating status threshold of the data collection client, and store the collected data in the database; several databases store the data collected by several data collection clients. The invention can set data items and data collection cycle according to user's requirements, and has high fault tolerance, high reliability, ease of use and expansibility.

Description

technical field [0001] The invention belongs to the technical field of data collection, in particular to a large-scale distributed data collection system and method based on industrial processes. Background technique [0002] Industrial processes can be divided into continuous production process, discrete production process and batch production process according to the raw materials used and the form of finished products. The signals in the continuous production process are mainly analog quantities, and the signals in the discrete production process are mainly digital quantities. The batch production process is a combination of continuous production process and discrete production process. Therefore, different industrial processes present different types of industrial data. As the production scale of the industrial process is different, the data items generated in the industrial process are quite different. [0003] According to the different signals in the production proc...

AI Technical Summary

Problems solved by technology

Different on-site control stations in these systems often complete the data collection of specific production links, there is isolation between each link, and the data sharing is poor, so it is impossible to analyze the production situation of the production process as a whole

Data collection clients corresponding to key areas usually adopt a 1:1 redundant configuration, which will lead to waste of data collection client resources

When the corresponding data collection client in other areas fails, the corresponding on-site data will be lost, which will bring losses to the enterprise

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