Industrial equipment-oriented distributed data acquisition method

Abstract

The invention discloses an industrial equipment-oriented distributed data acquisition method. According to the technical scheme, the method specifically comprises the following steps of S1, adopting unified equipment to access a terminal, namely an Internet of Things acquisition control terminal MIG200L, and connecting the Internet of Things acquisition control terminal MIG200L to equipment to besubjected to data acquisition; S2, carrying out data acquisition on the equipment to be subjected to data acquisition through the Internet of Things acquisition control terminal MIG200L, carrying outa series of data computations and statistics on the data, and judging whether uploading is carried out or not according to data computation and statistics results; and S3, if a judging result is uploading, uploading and storing the data after computation and statistics into a Cassandra database through WiFi or 2 / 3 / 4G or a wired or Lora or NBIoT network. The industrial equipment-oriented distributed data acquisition method is more reasonable, the unnecessary memory occupation ratio is reduced, and point position acquisition, operation and processing can be carried out on multiple devices.

Description

technical field [0001] The invention relates to the field of data collection methods, more specifically, it relates to a distributed data collection method for industrial equipment. Background technique [0002] Under the situation of increasingly fierce competition in the field of industrial manufacturing, the requirements for delivery, performance, and quality of industrial products are getting higher and higher. In the practice process of improving core capabilities and transforming and upgrading, enterprises use technologies such as in-depth integration of industrialization and industrialization to build advanced "smart factories" to realize informatization of enterprise management, digitization of product design, intelligence of process control, and production. The numerical control of equipment and the way of visualization of production process. [0003] Realizing a "smart factory" is an arduous task and an ambitious goal. The basis for realizing this vision is the co...

AI Technical Summary

Problems solved by technology

However, the equipment of industrial enterprises is composed of multiple brands, and the models, interfaces, communication protocols, and purchase time are inconsistent. It is difficult to adapt all equipment through one access terminal, so enterprises need to purchase it when accessing. A variety of access terminals, and there are differences in the connection methods between terminals and databases, resulting in the inability to use a unified architecture; secondly, the existing data acquisition and transmission solutions for industrial equipment in the existing market. Most of the data acquisition and transmission solutions for industrial equipment are Transparent transmission mode, transparent transmission, that is, transparent transmission, means that regardless of the business content transmitted during communication, it is only responsible for transmitting the transmitted content from the source address to the destination address, without making any changes to the business data content

This transmission method is too simple, has low security performance, and is easy to be monitored. In addition, because it does not do any processing on the data, the data is mixed, valid data cannot be separated from invalid data, and abnormal data cannot be distinguished from normal data. The amount of effective information is low and the occupied traffic is high; in addition, the storage methods in the existing industrial equipment data collection and storage solutions are mostly relational data structures. Relational data refers to data represented by relational mathematical models. The table structure is not flexible enough, and the support for high concurrent read and write requirements is weak, and the support for high-efficiency read and write of massive data is weak