CN115016422A - Configurable seamless steel tube production line data acquisition method - Google Patents
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM]
- G05B19/4183—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM] characterised by data acquisition, e.g. workpiece identification
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B21—MECHANICAL METAL-WORKING WITHOUT ESSENTIALLY REMOVING MATERIAL; PUNCHING METAL
- B21B—ROLLING OF METAL
- B21B37/00—Control devices or methods specially adapted for metal-rolling mills or the work produced thereby
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/32—Operator till task planning
- G05B2219/32252—Scheduling production, machining, job shop
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Abstract
The invention belongs to the field of data acquisition of steel pipe production lines, and provides a configurable data acquisition method for a seamless steel pipe production line, which comprises the following steps: dividing a seamless steel tube production line into a plurality of edge nodes according to procedures, and configuring a data acquisition engine and a data acquisition gateway under the edge nodes; associating production equipment under the data acquisition engine of each edge node, and associating data acquisition points to each production equipment, wherein the data acquisition points are control and operation parameters in seamless steel pipe production; and dividing gateways for the data acquisition gateways and configuring corresponding communication protocols respectively according to the corresponding data acquisition points under each edge node to realize data acquisition. And for each data acquisition point, the edge node reduces the amount of transmitted data by constructing a difference value. The invention realizes data format conversion and unified data acquisition, reduces the data transmission amount and achieves rapid data intercommunication and sharing.
Description
Technical Field
The invention belongs to the field of data acquisition of steel pipe production lines, and particularly relates to a configurable data acquisition method for a seamless steel pipe production line.
Background
In the production process of seamless steel pipes, thousands of mass production data can be generated every day, but the data are isolated from each other and exist in different control systems and files, the current steel industry has a trend of digital transformation, data are generated by digitalizing objects such as people, objects, environments, processes and the like, the data are taken as production elements, the gathered data are subjected to deep analysis, and the control and management decisions of each production link are guided by using data analysis results. The first solution of digital transformation is to collect and store a large amount of data generated in each key link in the production process. However, the steel industry is a typical process industry, and has the characteristics of production connectivity, time-varying property, inter-process heredity, non-linearity of various influence factors and the like, so that the data are different in structure, acquisition period and application scene, and a data acquisition system which can adapt to the industrial production process is required to uniformly collect and arrange the data of each link.
The invention discloses a steel pipe data acquisition material tracking device (application number 201510795526.8). The invention patent mainly aims to track the whole process of steel pipe production line materials through a secondary management system, and simultaneously leads the steel pipe information which is automatically sprayed and printed on partial specification (0.8-1.2 meters) of pipes by spraying and printing the information of the outer diameter, the wall thickness, the steel grade, the production time and the like of the steel pipe on the whole length of the steel pipe. The invention relates to a data access system, an access method, computer equipment and a storage medium (application number 202110971748.6), which realizes the access of used data through a collection front module, a first receiving and both sides module and an operation and maintenance monitoring module, and monitors the data access process, wherein the data collection method mainly aims at a power grid system. The invention patent of 'a data acquisition method and device' (202010076393. X) mainly describes a filtering method in a data acquisition process, when results acquired for N times are the same, an acquisition result is selected, otherwise, the acquisition result is discarded, the number of acquisition error rounds is recorded, and then data acquisition of the next round is carried out.
In the seamless steel tube production, basic automation and process automation systems of all procedures are complex, system integrators are numerous, automatic control systems of different manufacturers and various database management systems and the like are deployed in different procedures, therefore, the data generated in the seamless steel tube manufacturing process is characterized by multi-source isomerism, high flux, strong coupling and the like, the data is difficult to acquire uniformly, different data are stored in different systems, data islands are prominent, the data value is difficult to further mine, and as production control system integrators are numerous, the data collection can bring dependence on suppliers such as original meters, control systems and the like, high cost can be generated, the data collection can not be implemented, meanwhile, the production data of the seamless steel tube has high requirements on real-time performance and safety, and therefore, the development of a reliable, safe and configurable seamless steel tube data acquisition technology is particularly critical.
Aiming at the characteristics and data characteristics of a seamless steel pipe production line, the invention develops a configurable data acquisition method, which can acquire various data of each process, realize centralized management and caching of the data and provide a data basis for various application scenes.
Disclosure of Invention
The invention aims to provide a configurable data acquisition method for a seamless steel pipe production line, which aims at solving the outstanding problems of data acquisition in the digital and intelligent transformation process of a seamless steel pipe factory, can realize the acquisition and matching of various data of each procedure in the production process of seamless steel pipes, realize the unified management of the data and provide data support for intelligent upper-layer application.
A configurable seamless steel tube production line data acquisition method comprises the following steps:
dividing a seamless steel tube production line into a plurality of edge nodes according to procedures, and configuring a data acquisition engine and a data acquisition gateway under each edge node;
associating production equipment under the data acquisition engine of each edge node, and associating data acquisition points to each production equipment, wherein the data acquisition points are control and operation parameters in seamless steel pipe production;
dividing the data acquisition gateways into gateways and configuring corresponding communication protocols respectively according to corresponding data acquisition points under each edge node, establishing a data acquisition communication link with a remote I/O interface of the data acquisition point to realize data acquisition,
different communication protocols are adopted for different industrial scene data acquisition gateways, and for a basic automation control system, an OPCUA communication protocol is adopted to realize multi-protocol conversion with different PLCs; for the data of the detecting instrument, a communication protocol in a TCP/IP database interface form is adopted; for a production process control system, a communication protocol in a TCP/IP database interface form is adopted; for the production execution system, through a communication protocol based on an ODBC interface form,
for each data acquisition point, the edge node receives a plurality of detection data of the data acquisition point according to a specified detection period, calculates an average value of the plurality of detection data in the current detection period, and calculates a difference value between each detection data which is greater than or equal to the average value in the plurality of detection data and a stored first comparison value, wherein the first comparison value is the last detection value which is greater than or equal to the average value in the previous detection period;
calculating a difference value between each detection data smaller than the average value in the plurality of detection data and a stored second comparison value, wherein the second comparison value is the last detection value smaller than the average value in the previous detection period;
combining all the calculated difference values, the seamless steel pipe codes and the data acquisition points into a detection data block and sending the detection data block to the edge node;
the edge node restores the plurality of detection data of the current detection period according to the received detection data block, the stored first comparison value and the second comparison value;
and storing the last detection data which is larger than or equal to the average value in the plurality of detection data of the current detection period as the first comparison value, and storing the last detection data which is smaller than the average value as the second comparison value.
Optionally, the basic automation control system comprises a heating area PLC, a puncher area PLC, a rolling mill area PLC, a sizing mill area PLC, a cooling bed area PLC, a tube row sawing area PLC, a straightener area PLC, a flaw detector area PLC, and a length measuring and weighing area PLC, each PLC is respectively connected with corresponding equipment to control the corresponding equipment to move, and the opua communication protocol supports protocols and software communication interfaces of siemens S7, TEMIC corporation EGD, ModBusTCP, OPCDA, Profibus, ABCIP.
Optionally, the production process control system comprises a steel pipe intelligent combustion system, and after the steel pipe intelligent combustion system acquires initial data of the furnace temperature, the steel type, the specification and the tapping target temperature of the pipe blank, the furnace temperature of each section of the heating furnace and the set value of the furnace time of the steel pipe are calculated according to the combustion control model.
Optionally, the data center is further comprised by a data acquisition switch and a server cluster, the data acquisition switch and the server cluster form a data center, the data acquisition switch is connected with the edge computing server, the edge computing server buffers and stores data of each data acquisition point in the edge computing server when the network fails, and the buffered data is uploaded to the data center when the network recovers.
Optionally, the edge nodes include a heating area edge node, a piercer area edge node, a rolling mill area edge node, a sizer area edge node, a cooling bed area edge node, a tube row saw area edge node, and a finishing area edge node, and the finishing area edge node includes a straightener area process, a defectoscope area process, and a length measurement and weighing area process.
Optionally, before the seamless steel tube production line is divided into a plurality of edge nodes according to the process, a seamless steel tube production line cluster is established according to different production specification ranges of the seamless steel tubes, and the production line cluster comprises a plurality of seamless steel tube production lines.
Optionally, the edge node of the heating area corresponds to a furnace entering roller way, a pipe blank saw, a heating furnace feeding and discharging control device and a combustion control device, the edge node of the puncher area corresponds to a puncher, the edge node of the rolling area corresponds to a rolling mill, the edge node of the sizing mill area corresponds to a reducing mill, the edge node of the tube gang saw area corresponds to a tube gang saw, the edge node of the cooling bed area corresponds to a high-pressure water descaling device and a cooling bed, and the edge node of the finishing area corresponds to a finishing roller way control device, a straightening machine, a magnetic flux leakage flaw detection device and a length measurement weighing device.
The configurable data acquisition method for the seamless steel pipe production line can set required seamless steel pipe production equipment and data acquisition points of the equipment according to needs, configure corresponding communication protocols for data acquisition gateways according to the difference of the data acquisition points, realize data format conversion and unified data acquisition, achieve the efficiency of millisecond level, provide a data source for subsequent intelligent big data application and facilitate data intercommunication and sharing of a later application layer. And the data of the data acquisition point can be transmitted only by constructing the difference value during transmission, so that the data transmission amount is reduced.
Drawings
The above features and technical advantages of the present invention will become more apparent and readily appreciated from the following description of the embodiments thereof taken in conjunction with the accompanying drawings.
FIG. 1 is a flow chart illustrating a configurable seamless steel pipe data collection method according to an embodiment of the invention.
Fig. 2 is a schematic diagram illustrating device data access and adaptation management in different industrial scenarios according to an embodiment of the present invention.
FIG. 3 is a schematic connection diagram of an edge node for data acquisition in a seamless steel pipe production line according to an embodiment of the present invention.
Detailed Description
The embodiments of the present invention will be described below with reference to the accompanying drawings. Those of ordinary skill in the art will recognize that the described embodiments can be modified in various different ways, or combinations thereof, without departing from the spirit and scope of the present invention. Accordingly, the drawings and description are illustrative in nature and not intended to limit the scope of the claims. Furthermore, in the present description, the drawings are not to scale and like reference numerals refer to like parts.
As shown in fig. 1, the configurable data collecting method for the seamless steel tube production line of the embodiment includes the following steps:
and step S1, dividing the seamless steel tube production line into a plurality of edge nodes according to the process, and configuring a data acquisition engine and a data acquisition gateway under each edge node. The dividing edge nodes can be divided into heating area edge nodes, perforator area edge nodes, rolling mill area edge nodes, sizing mill area edge nodes, cooling bed area edge nodes, tube row saw area edge nodes and finishing area edge nodes, wherein the finishing area edge nodes comprise a straightener area process, a flaw detector area process and a length measuring and weighing area process.
The data acquisition engine is used for allocating physical resources for data acquisition, the physical resources include a plurality of edge computing servers, configuration parameters of the physical resources at least include information of the name of the edge computing server, a user name, a password, a storage flag bit and an acquisition period, and the information is conventional setting parameters and is not described in detail herein.
The data acquisition engine is connected with each production device through the data acquisition gateway. The configuration of the data acquisition gateway, including the gateway name (such as IOT1, IOT2, etc.), type, port number, activity status, security mode, etc., is conventional setting parameters, and will not be described in detail herein.
Step S2, associating production equipment under a data acquisition engine of each edge node, for example, the edge node of the heating area corresponds to a furnace roller way, a pipe blank saw, a heating furnace feeding and discharging control device and a combustion control device, the edge node of the puncher area corresponds to a puncher, the edge node of the rolling mill area corresponds to a rolling mill, the edge node of the sizing mill area corresponds to a reducer, the edge node of the pipe row saw area corresponds to a pipe row saw, the edge node of the cooling bed area corresponds to a high-pressure water descaling device and a cooling bed, and the edge node of the finishing area corresponds to a finishing roller way control device, a straightener, a magnetic leakage flaw detection device and a length measurement weighing device.
And step S3, associating data acquisition points under each production device, wherein the data acquisition points are a large number of control and operation parameters in all seamless steel tube production, and include, for example, information of a mandrel car, such as mandrel car position, mandrel car current and mandrel car torque, upper (lower) roller data, such as an upper (lower) roller motor current actual value and an upper (lower) roller speed actual value, guide plate data, oblique feeding roller way data and other related data. The data acquisition points may be the same data acquisition points contained in different devices, for example, the edge node of the heating area may have an oblique feeding roller data acquisition point, and the edge node of the sizing mill area may also have an oblique feeding roller data acquisition point, as long as the data acquisition points are allocated according to the data acquisition points required by the devices. Specifically, the data acquisition points, such as the perforator zone edge nodes, are shown in Table 1.
The configuration of the data acquisition point comprises information such as data acquisition point name, remarks, equipment number, data type, data acquisition address, offset and the like. The data types of the data acquisition points comprise Boolean types, integer types, floating point number types, character types and the like. TABLE 1 partial data acquisition Point of perforation procedure
And step S4, dividing the data acquisition gateways according to the corresponding data acquisition points under each edge node, configuring corresponding communication protocols respectively, and establishing a data acquisition communication link with the remote I/O interfaces of the data acquisition points to realize data acquisition. For example, the control system of the furnace entering roller way is siemens/S7-1500, and gateways are divided for the furnace entering roller way (namely, gateway IP addresses are divided from the IP address sections of the data acquisition gateways to the data acquisition points), and connection is established between the data acquisition points and the data acquisition gateways. The data acquisition configuration table is shown in table 2 and includes different devices, control systems, data acquisition contents, communication protocols and the like corresponding to different production areas for seamless steel pipe production.
The data acquisition gateway can realize different types of data acquisition, and provides equipment data access and adaptation management under different industrial scenes aiming at equipment sensing data, as shown in fig. 2, the data access and adaptation management comprises basic automation control system (L1 level) management, large-scale instrument adaptation management, process control system (L2 level) data acquisition adaptation management and production execution system (L3 level) acquisition adaptation management.
The L1 level is a basic automation system and comprises a pipe billet area PLC, a heating area PLC, a puncher area PLC, a rolling mill area PLC, a sizing and reducing mill area PLC, a cooling bed area PLC, a pipe row sawing area PLC, a straightener area PLC, a flaw detector area PLC, a length measuring and weighing area PLC and the like, wherein the PLCs of all production equipment are respectively connected with position switches, instruments, frequency converters and the like of corresponding equipment to control the actions of the corresponding equipment, carry out tracking logic control and realize the direct control of the equipment, such as steel pipe rolling, perforating and conveying control, sequence control and logic control. The data acquisition of the basic automation system is oriented to equipment and mechanisms, and for real-time data acquisition, the data is stored in a real-time database. The communication gateway can be adopted to communicate with a primary basic automation system or iba PDA, the data acquisition gateway provides an OPCUA technology to realize multi-protocol conversion, and supports domestic and foreign mainstream PLC protocols, such as: siemens S7, EGD of TEMIC company, ModBusTCP, OPCDA, Profibus, ABCIP and other various industrial communication protocols and software communication interfaces, and reliable high-performance real-time data acquisition is realized.
The basic automation system also includes the collection of steel pipe data through large-scale instruments, such as wall thickness meters, diameter meters, etc., the data are stored in a real-time database, and can also communicate through accessing a database or an interface mode, such as a TCP/IP database interface.
The L2 level is a process automation system, which is located between a basic automation system and a Manufacturing Execution System (MES), and sets and calculates model parameters after PDI data (production plan, product information, etc.) are acquired from the MES, and transmits the model parameters to the L1 level. The system can acquire the set value of the production process parameter of each steel pipe, the data is the set value of the key operation parameter of the steel pipe production equipment for meeting the requirements of the size, the quality (with a relevant quality report), the performance and the like of a steel pipe product, and the key operation parameter during the production of each steel pipe usually has a set value, such as the target heating temperature of each heating section of a heating furnace, the set roll gap of a puncher, the set roll gap and the speed of a pipe mill and the like. For process control system data collection, the data may be stored in a relational database by accessing a database or data interface, such as a TCP/IP database interface. The L2 level includes, for example, an intelligent combustion control system for steel pipes, which aims to improve the heating quality of pipe blanks, obtain initial data such as the furnace temperature for loading pipe blanks, the steel type, the specification, the target temperature for tapping, and the like, and then calculate the set values such as the furnace temperature of each section of the heating furnace, the furnace time of steel pipes in the furnace, and the like, according to a combustion control model.
The L3 level is a production execution system used for compiling and executing seamless steel tube production plans, which contains the order, incoming material and finished product information of each steel tube in each steel tube production plan list and stores the information in a relational database, wherein the data is contract order information of each steel tube, such as the order number, quality requirement and the like, the incoming material tube blank number, steel type, length, diameter and the like, and the finished product length, inner diameter, outer diameter, surface quality and the like. The data may be stored in a relational database by storing the corresponding data in an ODBC-based interface, in particular, an MQTT, database interface.
After the data acquisition point is deployed, a data acquisition engine is started according to configuration information such as a communication protocol of the data acquisition point, a large amount of real-time data generated in a production field are stored in a real-time database of the edge computing server, and real-time data access service is provided for an application layer through an API (application programming interface).
Table 2 communication protocol configuration table
For each data acquisition point, the edge node receives a plurality of detection data of the data acquisition point according to a specified detection period, calculates an average value of the plurality of detection data in the current detection period, and calculates a difference value between each detection data which is greater than or equal to the average value in the plurality of detection data and a stored first comparison value, wherein the first comparison value is the last detection value which is greater than or equal to the average value in the previous detection period;
calculating a difference value between each detection data smaller than the average value in the plurality of detection data and a stored second comparison value, wherein the second comparison value is the last detection value smaller than the average value in the previous detection period;
and combining the calculated difference values, the seamless steel pipe codes and the data acquisition points into a detection data block and sending the detection data block to an edge node, such as a No. 0001 seamless steel pipe, wherein the data acquisition points are outer diameters, the difference values are a1, a2, a3, a4 and a5 … …, and combining the data into the detection data block and sending the detection data block.
The edge node restores the plurality of detection data of the current detection period according to the received detection data block, the stored first comparison value and the second comparison value;
and storing the last detection data which is larger than or equal to the average value in the plurality of detection data of the current detection period as the first comparison value, and storing the last detection data which is smaller than the average value as the second comparison value.
By constructing the difference value, only the difference value can be transmitted at the time of transmission, which can reduce the data amount of data transmission.
Further, step S0 is included before step S1, a seamless steel tube production line cluster is established according to the different production specification ranges of seamless steel tubes, the production line cluster includes a plurality of seamless steel tube production lines, each production line is used for producing seamless steel tubes with corresponding specification ranges, such as a certain seamless steel tube production line, which can produce seamless steel tubes with diameters of 114mm-273.1mm and wall thicknesses of 4mm-31.8 mm.
Further, as shown in fig. 3, the system further includes a data acquisition switch and a server cluster, the data acquisition switch and the server cluster form a data center, the data acquisition switch is sequentially connected with the edge computing server and the data acquisition gateway, and the data acquisition gateway is connected with a primary database of the basic automation system, a secondary database of the process automation system, a tertiary database of the production execution system, and a meter inspection database of the large-scale instrument. The edge computing server can store the production real-time data of each production area in the edge computing server (can keep the real-time data for 7 days), and simultaneously plays a role in data buffering, so that the data collected in real time on site can be buffered when the network is unavailable, and the buffered data can be uploaded to a server cluster of the data center when the network is recovered to be normal.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (7)
1. A configurable data acquisition method for a seamless steel tube production line is characterized by comprising the following steps:
dividing a seamless steel tube production line into a plurality of edge nodes according to procedures, and configuring a data acquisition engine and a data acquisition gateway under each edge node;
associating production equipment under the data acquisition engine of each edge node, and associating data acquisition points to each production equipment, wherein the data acquisition points are control and operation parameters in seamless steel pipe production;
dividing the data acquisition gateways into gateways and configuring corresponding communication protocols respectively according to corresponding data acquisition points under each edge node, establishing a data acquisition communication link with a remote I/O interface of the data acquisition point to realize data acquisition,
different communication protocols are adopted for different industrial scene data acquisition gateways, and for a basic automation control system, an OPCUA communication protocol is adopted to realize multi-protocol conversion with different PLCs; for the data of the detecting instrument, a communication protocol in a TCP/IP database interface form is adopted; for a production process control system, a communication protocol in a TCP/IP database interface form is adopted; for the production execution system, through a communication protocol based on an ODBC interface form,
for each data acquisition point, the edge node receives a plurality of detection data of the data acquisition point according to a specified detection period, calculates an average value of the plurality of detection data in the current detection period, and calculates a difference value between each detection data which is greater than or equal to the average value in the plurality of detection data and a stored first comparison value, wherein the first comparison value is the last detection value which is greater than or equal to the average value in the previous detection period;
calculating a difference value between each detection data smaller than the average value in the plurality of detection data and a stored second comparison value, wherein the second comparison value is the last detection value smaller than the average value in the previous detection period;
combining all the calculated difference values, the seamless steel pipe codes and the data acquisition points into a detection data block and sending the detection data block to the edge node;
the edge node restores the plurality of detection data of the current detection period according to the received detection data block, the stored first comparison value and the second comparison value;
and storing the last detection data which is larger than or equal to the average value in the plurality of detection data of the current detection period as the first comparison value, and storing the last detection data which is smaller than the average value as the second comparison value.
2. The configurable seamless steel tube production line data collection method of claim 1,
the basic automatic control system comprises a heating area PLC, a puncher area PLC, a rolling mill area PLC, a sizing mill area PLC, a cooling bed area PLC, a tube row sawing area PLC, a straightener area PLC, a flaw detector area PLC and a length measuring and weighing area PLC, wherein each PLC is respectively connected with corresponding equipment and used for controlling the corresponding equipment to act, and an OPCUA communication protocol supports protocols and software communication interfaces of Siemens S7, TEMIC company EGD, ModBusTCP, OPCDA, Profibus and ABCIP.
3. The configurable data collection method for the seamless steel tube production line according to claim 1, wherein the production process control system comprises a steel tube intelligent combustion system, and after the steel tube intelligent combustion system obtains initial data of the furnace temperature for loading tube blanks, the steel type, the specification and the target temperature for tapping, the furnace temperature of each section of the heating furnace and the furnace time of steel tubes are calculated according to a combustion control model.
4. The configurable data acquisition method for the seamless steel tube production line according to claim 1, further comprising a data acquisition switch and a server cluster, wherein the data acquisition switch and the server cluster form a data center, the data acquisition switch is connected with the edge computing server, the edge computing server buffers and stores data of each data acquisition point in the edge computing server when a network fails, and uploads the buffered data to the data center when the network is restored.
5. The configurable data collection method for a seamless steel tube production line according to claim 2, wherein the edge nodes comprise heating zone edge nodes, piercer zone edge nodes, rolling mill zone edge nodes, sizer zone edge nodes, cooling bed zone edge nodes, tube row saw zone edge nodes, and finishing zone edge nodes, and the finishing zone edge nodes comprise a straightener zone process, a defectoscope zone process, and a length measurement and weighing zone process.
6. The configurable data collection method for a seamless steel tube production line according to claim 1, wherein a seamless steel tube production line cluster is established according to different seamless steel tube production specification ranges before the seamless steel tube production line is divided into a plurality of edge nodes according to the process, wherein the production line cluster comprises a plurality of seamless steel tube production lines.
7. The configurable data acquisition method for the production line of the seamless steel tubes as claimed in claim 5, wherein the edge nodes of the heating area correspond to a furnace roller table, a tube blank saw, a heating furnace feeding and discharging control device and a combustion control device, the edge nodes of the piercer area correspond to a piercer, the edge nodes of the mill area correspond to a rolling mill, the edge nodes of the sizer area correspond to a reducer, the edge nodes of the tube gang saw area correspond to a tube gang saw, the edge nodes of the cooling bed area correspond to a high-pressure water descaling device and a cooling bed, and the edge nodes of the finishing area correspond to a finishing roller table control device, a straightener, a magnetic leakage flaw detection device and a length measurement weighing device.
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