CN117056136A - Hot backup method for two-level control model server in production process - Google Patents
Hot backup method for two-level control model server in production process Download PDFInfo
- Publication number
- CN117056136A CN117056136A CN202311105150.4A CN202311105150A CN117056136A CN 117056136 A CN117056136 A CN 117056136A CN 202311105150 A CN202311105150 A CN 202311105150A CN 117056136 A CN117056136 A CN 117056136A
- Authority
- CN
- China
- Prior art keywords
- server
- standby
- main
- main server
- control model
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000004519 manufacturing process Methods 0.000 title claims abstract description 71
- 238000000034 method Methods 0.000 title claims abstract description 25
- 238000004891 communication Methods 0.000 claims abstract description 13
- 230000001360 synchronised effect Effects 0.000 claims abstract description 7
- 238000012545 processing Methods 0.000 abstract description 6
- 238000005266 casting Methods 0.000 description 13
- 230000006870 function Effects 0.000 description 13
- 238000004364 calculation method Methods 0.000 description 10
- 238000001816 cooling Methods 0.000 description 9
- 238000009749 continuous casting Methods 0.000 description 8
- 238000012544 monitoring process Methods 0.000 description 7
- 230000009467 reduction Effects 0.000 description 5
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 5
- 239000000498 cooling water Substances 0.000 description 4
- 229910000831 Steel Inorganic materials 0.000 description 3
- 238000003825 pressing Methods 0.000 description 3
- 238000012797 qualification Methods 0.000 description 3
- 238000004088 simulation Methods 0.000 description 3
- 239000010959 steel Substances 0.000 description 3
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 2
- 238000004422 calculation algorithm Methods 0.000 description 2
- 238000012423 maintenance Methods 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000011143 downstream manufacturing Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 229910052742 iron Inorganic materials 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
Classifications
-
- 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
- G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
- G05B19/05—Programmable logic controllers, e.g. simulating logic interconnections of signals according to ladder diagrams or function charts
- G05B19/058—Safety, monitoring
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
- G06F11/16—Error detection or correction of the data by redundancy in hardware
- G06F11/20—Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements
- G06F11/202—Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements where processing functionality is redundant
- G06F11/2023—Failover techniques
- G06F11/2028—Failover techniques eliminating a faulty processor or activating a spare
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
- G06F11/16—Error detection or correction of the data by redundancy in hardware
- G06F11/20—Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements
- G06F11/2097—Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements maintaining the standby controller/processing unit updated
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2201/00—Indexing scheme relating to error detection, to error correction, and to monitoring
- G06F2201/80—Database-specific techniques
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2201/00—Indexing scheme relating to error detection, to error correction, and to monitoring
- G06F2201/805—Real-time
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2201/00—Indexing scheme relating to error detection, to error correction, and to monitoring
- G06F2201/82—Solving problems relating to consistency
-
- 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]
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Quality & Reliability (AREA)
- General Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Hardware Redundancy (AREA)
Abstract
The invention relates to a hot backup method of a two-level control model server in a production process, which belongs to the field of data processing and comprises the following steps: s1: determining a main server and one or more standby servers; s2: the main and standby servers all read production data from each PLC of the primary system in real time, and calculate and obtain optimized production control data or alarm information in real time based on the secondary control model; the main server participates in real-time online control; s3: the main server and the standby server ensure the consistency of the production object parameters, the secondary control model parameters, the addresses of the main server and the standby order and the main and standby states through a database synchronization function; s4: the main server, the standby server and all PLCs of the primary system keep heartbeat communication; s5: when the main server is down, based on the information in the databases of the servers, a proper standby server is selected for switching, and meanwhile, the information in the databases is updated and synchronized.
Description
Technical Field
The invention belongs to the field of data processing, and relates to a hot backup method of a secondary control model server in a production process.
Background
The production process secondary control model is to read all relevant production data from a PLC (programmable logic processor) of a primary control object system in real time, calculate and obtain optimized control parameters based on a secondary control model optimization algorithm, write the optimized control parameters into the PLC and participate in the online control of the production process. The data reading, the secondary control model, the data writing and other works related to the process are all completed in the server. And the production process secondary control model usually needs to be tracked from the beginning of production, and if a fault exits in the middle, the process can be continued to participate in control after waiting for a long time. Therefore, the stability of the production process secondary control model server is of great importance. If the secondary control model server of the production process is down, the secondary control model of the whole production process cannot work, and serious consequences are caused to production control.
Hot-standby refers to a data processing system in which one server is active and the other servers are standby. The user can only access the active state server, and all updating operations of the user must be synchronized to other servers in the backup state, so that after the active state server is down, any one of the servers in the backup state can be switched to the active state to provide service, and in general, one master can be used for one slave, and one master can be used for more slaves to further improve the service availability.
The current hot-standby scheme is as follows: 1) The hot backup is implemented in the primary server, which means that dynamic data is stored in a disk. However, this treatment scheme has the disadvantages that: there is a risk of failure to write to disk because the data needs to persist in disk. Once the data is lost, the problems of user data damage or inconsistent system state and the like can be caused. Therefore, this hot backup scheme needs a complex transaction mechanism to ensure the atomicity of the primary and secondary submitted data, which in turn can burden the performance of the server. 2) The dynamic data are stored in the local memory of the main server, and the standby server learns to acquire all the dynamic data in the memory of the main server and also stores the dynamic data in the local memory; if the main server receives and executes the write request of which the memory data is changed successfully, the write request is broadcast to the standby server, and the standby server executes the received write request, so that the hot backup of the server is realized.
However, in the field of steel production process control, especially in a secondary control model of a continuous casting production process, in each calculation period (usually less than 5 seconds), data points are read, dynamic data involved in model optimization calculation is up to hundreds of thousands, and calculation amount is large (the dynamic data and calculation amount involved in simulation such as a temperature field are multiplied), and written data points are up to hundreds. Thus, by storing dynamic data in disk; or after the dynamic data is stored in the memory of the main server, the standby server realizes the hot backup by a write request broadcasting mode. The processing logic of the hot backup of the secondary control model server in the production process is complex, the adaptability and the reliability are poor, and the use and maintenance cost of the hot backup are high; in particular, the two-level model relates to dynamic data and calculation amount of simulation calculation of a temperature field and the like, and the method is almost impossible to realize. Finally, most of the two-level control model servers in the production process are not provided with a hot backup function, and the whole system is not serviceable once the server fails, so that the safety is too low.
Disclosure of Invention
In view of the above, the present invention is directed to a hot standby method for a secondary control model server in a production process.
In order to achieve the above purpose, the present invention provides the following technical solutions:
a method for hot backup of a production process secondary control model server comprises the following steps:
s1: determining a main server and one or more standby servers from servers with the same hardware and software running environments;
s2: the main server and the standby server read production data from each PLC of the primary system of the factory in real time, and calculate and obtain optimized production control data or alarm information based on the secondary control model in real time; the main server writes the production control data or the alarm information into each PLC of the primary system of the factory to participate in real-time online control;
s3: the main server and the standby server ensure the consistency of the production object parameters, the secondary control model parameters, the addresses of the main server and the standby order and the main and standby states through a database synchronization function;
s4: the main server, the standby server and all PLCs of the primary system of the factory keep heartbeat communication;
s5: when the main server is down, based on the information in the databases of the servers, a proper standby server is selected for switching, and meanwhile, the information in the databases is updated and synchronized.
Further, in step S1, when there are a plurality of backup servers, the backup order of the backup servers is designated and stored in the database in real time.
Further, in step S2, the main server and the standby server read all real-time production data required by the production process control object on line in real time through the timing task, and each PLC sends a heartbeat communication watchdog variable to each server.
Further, in step S4, heartbeat communication is maintained among the main server, the standby server and each PLC of the primary system of the factory, which specifically includes: the main server sends out heartbeat signals to each PLC of the primary system of the factory; the standby server receives heartbeat signals from each PLC of the primary system of the factory; at the same time, the standby server transmits a heartbeat signal to the main server, and the main server receives the heartbeat signal from the standby server.
Further, in step S5, the main server is judged to be down by: when the heartbeat signal of the main server received by a certain standby server is overtime and the communication between the standby server and each PLC heartbeat of the factory primary system is normal; the standby server disqualification of the original main server, the standby server selects the server with the smallest standby order as the main server, and the main and standby server addresses and main and standby states in the local database of each standby server are updated.
Further, the timeout is: the server executes an execution cycle of the hot backup function, wherein the execution cycle time is required to be less than 10 seconds; the heartbeat signal is deemed to have a timeout of less than 10 cycles.
The primary system of the factory refers to an automatic control system of the factory, and is a control system level directly aiming at specific equipment in the factory, wherein the primary system of the factory comprises a plurality of automatic control and management devices such as PLC. The secondary control model is an upper control model of the primary system of the factory and is used for managing, integrating and processing the data uploaded by the primary system of each factory, and finally sending the optimized data to the primary and participating in real-time control.
The invention has the beneficial effects that: the method and the system have the advantages of simple processing logic, high adaptability and reliability of the hot backup of the production process secondary control model, low use and maintenance cost of the hot backup, and particular suitability for the situation that the production process secondary control model involves extremely large dynamic data and calculation amount such as temperature fields.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention. The objects and other advantages of the invention may be realized and obtained by means of the instrumentalities and combinations particularly pointed out in the specification.
Drawings
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in the following preferred detail with reference to the accompanying drawings, in which:
FIG. 1 is a flow chart of a method for hot standby of a secondary control model server in a production process according to the present invention;
FIG. 2 is a schematic diagram of a relationship between a primary server and a secondary server of a secondary control model and a PLC in a primary system of a factory according to the hot backup method of the present invention;
FIG. 3 shows the main operation modules in each server in the present invention.
Detailed Description
Other advantages and effects of the present invention will become apparent to those skilled in the art from the following disclosure, which describes the embodiments of the present invention with reference to specific examples. The invention may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present invention. It should be noted that the illustrations provided in the following embodiments merely illustrate the basic idea of the present invention by way of illustration, and the following embodiments and features in the embodiments may be combined with each other without conflict.
Wherein the drawings are for illustrative purposes only and are shown in schematic, non-physical, and not intended to limit the invention; for the purpose of better illustrating embodiments of the invention, certain elements of the drawings may be omitted, enlarged or reduced and do not represent the size of the actual product; it will be appreciated by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted.
The same or similar reference numbers in the drawings of embodiments of the invention correspond to the same or similar components; in the description of the present invention, it should be understood that, if there are terms such as "upper", "lower", "left", "right", "front", "rear", etc., that indicate an azimuth or a positional relationship based on the azimuth or the positional relationship shown in the drawings, it is only for convenience of describing the present invention and simplifying the description, but not for indicating or suggesting that the referred device or element must have a specific azimuth, be constructed and operated in a specific azimuth, so that the terms describing the positional relationship in the drawings are merely for exemplary illustration and should not be construed as limiting the present invention, and that the specific meaning of the above terms may be understood by those of ordinary skill in the art according to the specific circumstances.
Referring to fig. 1 to 3, the present invention provides a hot backup method for a two-level control model server in a production process, which is based on at least two servers with the same hardware and software operation environments, wherein one server is provided with only one main server, and one or more standby servers, if a plurality of standby servers exist, the standby order of the standby servers needs to be designated and stored in a database in real time.
The main server or each standby server in the servers specifically comprises the following functions or modules: the system comprises a reading module, a production process secondary (L2) control model, a main and standby server monitoring module and a writing module. The reading module has the functions of: all real-time production data required by a production process control object and heartbeat communication watchdog variables sent to all servers by all PLCs are read on line in real time through a timing task. The L2 control model of the production process has the following functions: based on the read real-time production data, obtaining an optimized result or an alarm result through real-time calculation of a production process L2 control model; according to the main and standby states, only the optimized result or alarm result of the main server is written into the PLC of the primary system L1 of the factory or production operators are provided to participate in the control of the online production process. The function of the main and standby server monitoring module is as follows: heartbeat communication management for the primary server and the backup server; primary-backup switchover and qualification for primary and backup servers.
In the case that the server is determined as a standby server, the server periodically reads relevant real-time production data from the PLC of the L1; based on the read real-time production data, the production process L2 control model software calculates and obtains optimized production control data or alarm information.
In the case that the server is determined to be the main server, the server reads relevant real-time production data from the PLC of the L1 at regular time; based on the read real-time production data, the production process L2 control model software calculates and obtains optimized production control data or alarm information; and finally writing the optimized production control data or alarm information into the PLC of the L1 or providing production operators to participate in real-time on-line control.
Both the primary and backup servers maintain heartbeat communications with each PLC of L1. And the heartbeat communication is kept between the main server and each standby server.
And in the main server and the standby servers, the production object parameters, the control parameters, the addresses of the main server and the standby order and the main and standby states which are used for the calculation of the production process control model software are stored in a database, and the consistency of the data in the main server and the data in each standby server is ensured through the synchronous function of the database.
Taking a certain iron and steel manufacturing enterprise as an example, a continuous casting machine is adopted to produce casting blanks with the cross section of 250mm multiplied by 1870mm, the production steel grade is X, the working pulling speed is 1.0m/min, and the casting temperature is 1539 ℃.
In order to ensure that the quality of the produced casting blank meets the quality requirement of a downstream process, a dynamic secondary cooling and dynamic soft reduction model based on a three-dimensional temperature field is required to be adopted in the whole production process to control the secondary cooling water quantity and the fan-shaped section roll gap of L1.
The dynamic secondary cooling and dynamic soft reduction model is developed based on a B/S software architecture, and a server side is responsible for reading production process data from a PLC of a continuous casting machine L1 in real time, and comprises the following steps: casting pulling speed, casting temperature, real-time secondary cooling water quantity, real-time fan-shaped section roll gap value and other information; based on the read real-time production process data, obtaining the optimally calculated secondary cooling water quantity of each secondary cooling loop and the inlet and outlet roll gap values of each sector section through a dynamic secondary cooling and dynamic soft reduction model of a server side; and writing the water quantity and the roll gap value which are optimally calculated into the PLC of the L1 through a writing module of the main server end, and participating in real-time control of the L1.
In order to improve the reliability of the control system, the dynamic secondary cooling and dynamic soft-pressing model server adopts a primary and secondary hot backup mode. The method for hot backup of the server is as follows:
three servers with the same hardware and software operating environment. Furthermore, the hardware systems such as the CPU model, the memory model, the size, the operating system and the like of the three servers are all the same; in order to ensure the running of the dynamic secondary cooling and dynamic soft-pressing model software, the three servers are provided with java, mysql, redis and other software and the dynamic secondary cooling and dynamic soft-pressing model software, and the software and version numbers of the three servers are identical.
Any one of the servers is selected as a main server, and the other two servers are standby servers. Further, the IP address of the main server, the IP address of the standby server and the main and standby states are stored in a database of the main server; storing the casting machine parameter configuration information of the continuous casting machine into a database of a main server; storing control parameters of the dynamic secondary cooling and dynamic soft reduction model software into a database of a main server; after the main server and the standby server are started, a database synchronization function is configured, the information of the database in the main server is completely synchronized into the database of the standby server based on the database synchronization function, and the database synchronization function of the main server and the standby server is periodically executed to ensure the complete consistency of the data in the main server and each standby server.
After the main server and the standby server are started:
1) Reading real-time production data such as casting mode, casting pulling speed, casting temperature and the like of the continuous casting machine from an instrument PLC, casting flow PLC, public PLC and soft-reduction PLC of the L1; at the same time, the heartbeat watchdog variables sent by the PLCs are also required to be read.
2) Based on the read real-time production data of the continuous casting machine, for example, the continuous casting machine is in a casting or tailing pulling blank mode, based on a finite element difference method, an online three-dimensional temperature field of casting blanks of the continuous casting machine is obtained through simulation, and the optimized secondary cooling water quantity of each secondary cooling loop and the inlet and outlet roll gap values of each sector section are obtained through calculation through a target surface temperature control method and a dynamic soft reduction control algorithm of the casting blanks.
3) The master-slave server monitoring module reads the master-slave state information:
if the water quantity and the roll gap value data are the main server, the finally optimized water quantity and the roll gap value data are written into the PLC corresponding to the L1 to participate in real-time on-line control.
If the water quantity and the roll gap value data are standby servers, the final optimized water quantity and the roll gap value data are not written into the PLC corresponding to the L1, and the real-time online control is not participated.
4) The master-slave server monitoring module reads the master-slave state information:
and if the server is the main server, the heartbeat watchdog variable of the main server is written into each PLC through the writing module.
And if the server is a standby server, reading the heartbeat watchdog variable written into each PLC by the main server through a reading module.
5) The master-slave server monitoring module reads the master-slave state information:
if the server is the main server, the next step is executed.
If the server is the standby server, judging whether the read heartbeat watchdog variables written into all the PLCs by the main server are overtime at the same time, and judging whether the read heartbeat watchdog variables of all the PLCs are overtime at the same time. If none of them time out, the next step is performed. If the first time is out and the second time is not out, the occurrence of downtime of the main server can be judged, the standby server disqualifys the original main server, the standby server selects the server with the minimum standby sequence number as the main server, and the main and standby server addresses and the main and standby states in the local database of the standby server are updated.
6) The master-slave server monitoring module reads the master-slave state information:
if the server is a standby server, the heartbeat watchdog variable is sent to the main server.
In the case of a primary server, the heartbeat watchdog variable is read from each standby server. If the time-out occurs, the standby qualification of the standby server is canceled; if not, reserve qualification of the reserve server is preserved.
7) The master-slave server monitoring module reads the master-slave state information:
if the data is the main server, the database synchronization function is started, the data which changes in the period of the main server database is synchronized to the database of each standby server, and the consistency of the data in the main server and the database of each standby server is ensured.
If the server is a standby server, the next step is performed.
8) The steps 1) to 7) are one execution period of the server executing the hot backup function, and the execution period time is 2 seconds. If the heartbeat watchdog variable is unchanged for 3 execution periods, the timeout is considered.
Finally, it is noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made thereto without departing from the spirit and scope of the present invention, which is intended to be covered by the claims of the present invention.
Claims (6)
1. A method for hot backup of a production process secondary control model server is characterized in that: the method comprises the following steps:
s1: determining a main server and one or more standby servers from servers with the same hardware and software running environments;
s2: the main server and the standby server read production data from each PLC of the primary system of the factory in real time, and calculate and obtain optimized production control data or alarm information based on the secondary control model in real time; the main server writes the production control data or the alarm information into each PLC of the primary system of the factory to participate in real-time online control;
s3: the main server and the standby server ensure the consistency of the production object parameters, the secondary control model parameters, the addresses of the main server and the standby order and the main and standby states through a database synchronization function;
s4: the main server, the standby server and all PLCs of the primary system of the factory keep heartbeat communication;
s5: when the main server is down, based on the information in the databases of the servers, a proper standby server is selected for switching, and meanwhile, the information in the databases is updated and synchronized.
2. The method for hot standby of a two-level control model server for a production process according to claim 1, wherein: in step S1, when there are a plurality of backup servers, the backup order of the backup servers is designated and stored in the database in real time.
3. The method for hot standby of a two-level control model server for a production process according to claim 1, wherein: in step S2, the main server and the standby server read all real-time production data required by the production process control object on line in real time through a timing task, and each PLC sends a heartbeat communication watchdog variable to each server.
4. The method for hot standby of a two-level control model server for a production process according to claim 1, wherein: and step S4, the main server, the standby server and each PLC of the primary system of the factory keep heartbeat communication, and the method specifically comprises the following steps: the main server sends out heartbeat signals to each PLC of the primary system of the factory; the standby server receives heartbeat signals from each PLC of the primary system of the factory; at the same time, the standby server transmits a heartbeat signal to the main server, and the main server receives the heartbeat signal from the standby server.
5. The method for hot standby of a two-level control model server for a production process according to claim 1, wherein: in step S5, the main server is judged to be down by the following method: when the heartbeat signal of the main server received by a certain standby server is overtime and the communication between the standby server and each PLC heartbeat of the factory primary system is normal; the standby server disqualification of the original main server, the standby server selects the server with the smallest standby order as the main server, and the main and standby server addresses and main and standby states in the local database of each standby server are updated.
6. The method for hot standby of a two-level control model server for a production process according to claim 1, wherein: the timeout is: the server executes an execution cycle of the hot backup function, wherein the execution cycle time is required to be less than 10 seconds; the heartbeat signal is deemed to have a timeout of less than 10 cycles.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311105150.4A CN117056136A (en) | 2023-08-30 | 2023-08-30 | Hot backup method for two-level control model server in production process |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311105150.4A CN117056136A (en) | 2023-08-30 | 2023-08-30 | Hot backup method for two-level control model server in production process |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117056136A true CN117056136A (en) | 2023-11-14 |
Family
ID=88664342
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311105150.4A Pending CN117056136A (en) | 2023-08-30 | 2023-08-30 | Hot backup method for two-level control model server in production process |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117056136A (en) |
-
2023
- 2023-08-30 CN CN202311105150.4A patent/CN117056136A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109951331B (en) | Method, device and computing cluster for sending information | |
| US10454754B1 (en) | Hybrid cluster recovery techniques | |
| CN103593266B (en) | A kind of double hot standby method based on arbitration disk mechanism | |
| US7814360B2 (en) | Synchronizing cluster time to a master node with a faster clock | |
| CN103199972B (en) | The two-node cluster hot backup changing method realized based on SOA, RS485 bus and hot backup system | |
| US8169856B2 (en) | Time synchronization in cluster systems | |
| JP2000137694A (en) | System and method for supplying continuous data base access by using common use redundant copy | |
| US20080281938A1 (en) | Selecting a master node in a multi-node computer system | |
| CN105915391B (en) | The distributed key assignments storage method of self-recovering function is submitted and had based on single phase | |
| CN113987064A (en) | Data processing method, system and equipment | |
| CN103703464A (en) | Method and apparatus for distributed configuration management | |
| US20140019793A1 (en) | Strictly increasing virtual clock for high-precision timing of programs in multiprocessing systems | |
| CN107919977A (en) | A kind of on-line rapid estimation of the distributed consensus system based on Paxos agreements, the method and apparatus of online capacity reducing | |
| CN113646749A (en) | IOT partition management and load balancing | |
| CN108984320A (en) | A kind of anti-fissure method and device of message queue cluster | |
| CN111064672A (en) | Cloud platform communication system, election method and resource scheduling management method | |
| EP3561694A1 (en) | Management method, system, and device for master and standby databases | |
| CN111447097A (en) | Cloud platform resource scheduling management method and system | |
| CN111447096A (en) | Election method and election system based on cloud platform communication system | |
| CN115562911B (en) | Virtual machine data backup method, device, system, electronic equipment and storage medium | |
| CN104767794A (en) | Node election method in distributed system and nodes in distributed system | |
| CN112653734A (en) | Server cluster real-time master-slave control and data synchronization system and method | |
| CN117056136A (en) | Hot backup method for two-level control model server in production process | |
| Balegas et al. | Towards fast invariant preservation in geo-replicated systems | |
| CN112564938B (en) | Equipment controller reconfigurable system based on EtherCAT protocol and implementation method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |