CN110222100B - Processing method, system and storage medium based on big data display process timing diagram - Google Patents
Processing method, system and storage medium based on big data display process timing diagram Download PDFInfo
- Publication number
- CN110222100B CN110222100B CN201910346102.1A CN201910346102A CN110222100B CN 110222100 B CN110222100 B CN 110222100B CN 201910346102 A CN201910346102 A CN 201910346102A CN 110222100 B CN110222100 B CN 110222100B
- Authority
- CN
- China
- Prior art keywords
- data
- database
- equipment data
- equipment
- timing diagram
- 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.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2471—Distributed queries
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/248—Presentation of query results
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
- G06F16/285—Clustering or classification
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Databases & Information Systems (AREA)
- Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- General Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Computational Linguistics (AREA)
- Software Systems (AREA)
- Probability & Statistics with Applications (AREA)
- Mathematical Physics (AREA)
- Fuzzy Systems (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention discloses a processing method, a system and a storage medium based on a big data display process timing diagram, wherein the method comprises the following steps: collecting a plurality of first equipment data in real time, and storing the first equipment data in a first database in a classified manner according to preset rules; reading a plurality of pieces of first equipment data from a first database according to preset time; obtaining second equipment data with process configuration information according to the read first equipment data, and storing the second equipment data in a second database; receiving a data request uploaded by a first terminal; reading third device data from the second database according to the data request; and transmitting the third device data to the first terminal, so that the first terminal displays the third device data in a time sequence chart mode. The invention can visually present the equipment data acquired in real time in the form of the timing diagram at the first terminal, so that a manager can master the running state of the equipment in time. The invention can be widely applied to the technical field of big data processing.
Description
Technical Field
The invention relates to the technical field of big data processing, in particular to a processing method, a processing system and a storage medium based on a big data display process timing diagram.
Background
The application of the manufacturing industry in China to the operation data of the production line and the production equipment mostly stays in a small workshop mode and an information isolated island mode for controlling the whole production line in a single machine mode, and when the two modes face the operation data of the miscellaneous equipment in a production workshop and a manufacturing factory, due to the lack of system and timely technical analysis and processing, the quantitative analysis of early warning on the operation condition, the process optimization space, the operation faults and risks of the production line or the factory and the hidden capacity cannot be carried out, so that the manufacturing industry in China is difficult to further upgrade from an automatic factory to an intelligent factory under the development strategy of transformation and upgrade.
At present, various monitoring management systems and software are already arranged on an industrial automatic production site, but the systems and the software can only statically embody the production status from one aspect or a plurality of aspects, and the dynamic process of each action of each device in the device production process cannot be visually presented, so that managers cannot timely master the running condition of the device.
Disclosure of Invention
To solve the above technical problems, the present invention aims to: the processing method, the system and the storage medium based on the big data display process sequence diagram can intuitively present the real-time situation of each action of each device in the production process of the device, so that a manager can timely master the most running state of the device.
The first technical scheme adopted by the invention is as follows:
a processing method based on a big data display process timing diagram comprises the following steps:
collecting a plurality of first equipment data in real time, and storing the first equipment data in a first database in a classified manner according to preset rules;
reading a plurality of pieces of first equipment data from a first database according to preset time;
obtaining second equipment data with process configuration information according to the read first equipment data, and storing the second equipment data in a second database;
receiving a data request uploaded by a first terminal;
reading third device data from the second database according to the data request;
and transmitting the third device data to the first terminal, so that the first terminal displays the third device data in a time sequence chart mode.
Further, the classifying and storing the first device data in the first database according to the preset rule specifically includes:
and storing the first equipment data in three category tables of a first database according to preset rules in a classified manner, wherein the three category tables are respectively action, state and parameter.
Further, the reading of the plurality of pieces of first device data from the first database according to the preset time specifically includes:
and reading at least one thousand pieces of first equipment data from a first database according to preset time, wherein the first equipment data are equipment data from three category tables read in the same process.
Further, the obtaining of the second device data with process configuration information according to the read first device data includes the following steps:
acquiring process configuration information and process level information;
and matching the read first equipment data with the process configuration information and the process level information to obtain second equipment data with process matching information.
Further, when the second device data is stored in the second database, the method further comprises the following steps:
and respectively storing the second equipment data in a third storage database and a fourth storage database.
Further, the method also comprises the following steps:
and when the received data request uploaded by the first terminal is a historical data request, reading fourth equipment data from a third storage database according to the data request.
Further, the method also comprises the following steps:
and when the received data request uploaded by the first terminal is a data comparison request, acquiring at least two different station information in the data request, and respectively reading fifth equipment data from the fourth storage database according to the station information.
The second technical scheme adopted by the invention is as follows:
a processing system based on big data display process sequence diagram includes:
the acquisition module is used for acquiring a plurality of pieces of first equipment data in real time and storing the first equipment data in a first database in a classified manner according to preset rules;
the first reading module is used for reading a plurality of pieces of first equipment data from the first database according to preset time;
the storage module is used for obtaining second equipment data with process configuration information according to the read first equipment data and storing the second equipment data in a second database;
the receiving module is used for receiving a data request uploaded by a first terminal;
the second reading module is used for reading third equipment data from the second database according to the data request;
and the sending module is used for sending the third equipment data to the first terminal so that the first terminal displays the third equipment data in a time sequence form.
The third technical scheme adopted by the invention is as follows:
a processing system based on big data display process sequence diagram includes:
at least one memory for storing a program;
and the at least one processor is used for loading the program to realize the processing method based on the big data display process timing diagram.
The fourth technical proposal adopted by the invention is that
A storage medium having stored therein processor-executable instructions for implementing a method of processing based on big data display process timing diagrams when executed by a processor.
The beneficial effects of the invention are: according to the method and the device, the first equipment data acquired in real time are read from the database through the data request uploaded by the first terminal, and the first equipment data are sent to the first terminal, so that the first terminal visually presents the real-time equipment data in a time sequence diagram form, and a manager can timely master the operation condition of the equipment according to the displayed time sequence diagram.
Drawings
FIG. 1 is a flow chart of a processing method based on a big data display process timing diagram according to the present invention;
FIG. 2 is a block diagram of a processing system based on a big data display process timing diagram according to the present invention.
Detailed Description
The invention is described in further detail below with reference to the figures and the specific embodiments. For the step numbers in the following embodiments, they are set for convenience of illustration only, the order between the steps is not limited at all, and the execution order of each step in the embodiments can be adapted according to the understanding of those skilled in the art.
Referring to fig. 1, a processing method based on a big data display process timing diagram includes the following steps:
s101, collecting a plurality of pieces of first equipment data in real time, and storing the first equipment data in a first database in a classified manner according to preset rules; the first device data is device data acquired from a programmable logic device in a production field through a data acquisition unit, wherein the data acquisition unit is an Epson data acquisition unit. The preset rules are classified storage modes which are edited in advance by designers in the first database, for example, the equipment data are classified according to actions, states and parameters. The first database may be MySQL, which is a relational database management system.
S102, reading a plurality of pieces of first equipment data from a first database according to preset time; the preset time is the interval time for reading the data of the first device. The number of the bars can be one bar or one hundred bars. After the current required equipment data is read, the original data of the data terminal of the required equipment data is deleted, and the accumulation of the original data of the data terminal is avoided.
S103, obtaining second equipment data with process configuration information according to the read first equipment data, and storing the second equipment data in a second database; the read first device data is packaged into a data format of a publish-subscribe message system, and the packaged first device data is sent to the publish-subscribe message system through a data synchronization service gateway. When the publish-subscribe message system is Kafka and Kafka is a high-throughput distributed publish-subscribe message system, the first device data is packaged into a Protobufde format, and after the first device data is packaged, the first device data is written into Kafka and sent to a plurality of topics, and then the first device data is processed into second device data with process configuration information in a plurality of processes. The second database is Redis which is a key-value storage system, the reading and writing performance per second is extremely high, and the requirements of a user for repeatedly inquiring the station parameter graph and the station Gantt graph in real time can be met.
S104, receiving a data request uploaded by a first terminal; the first terminal is a browser client, and the communication mode between the first terminal and the server is a Websocket full-duplex communication protocol.
S105, reading third equipment data from the second database according to the data request; specifically, after the data request is sent to the server, the server reads the third device data from the second database. The third device data is the device data in the second device data, which conforms to the data request.
And S106, sending the third device data to the first terminal, and enabling the first terminal to display the third device data in a time sequence form. Specifically, after the third device data is sent to the first terminal, the page program of the first terminal renders the third device data, and then displays the third device data in a graphical form.
According to the method and the device, the first equipment data acquired in real time are read from the database through the data request uploaded by the first terminal, and the first equipment data are sent to the first terminal, so that the first terminal visually presents the real-time equipment data in a time sequence diagram form, and a manager can timely master the operation state of the equipment according to the displayed time sequence diagram.
As a further preferred embodiment, the classifying and storing the first device data in the first database according to preset rules specifically includes:
and storing the first equipment data in three category tables of a first database according to preset rules in a classified manner, wherein the three category tables are respectively actions, states and parameters. The device data contained in the three classification tables are respectively action data, state data and parameters, and the first device data is stored in a classification mode so as to be convenient for reading the following data.
As a further preferred embodiment, the reading a plurality of pieces of first device data from the first database according to the preset time specifically includes:
and reading at least one thousand pieces of first equipment data from a first database according to preset time, wherein the first equipment data are equipment data from three category tables read in the same process. The number of pieces of first device data read at a time may be 1 or more. Wherein, by reading at least one thousand pieces of first device data at a time, the I/O operation of the database can be reduced. The first device data is read from the three category tables, and the reading process is completed in the same process.
Further as a preferred embodiment, the obtaining of the second device data with process configuration information according to the read first device data includes the following steps:
acquiring process configuration information and process level information; the process configuration information includes a Collector _ ID, a PLC _ ID, and an EVENT _ ID.
And matching the read first equipment data with the process configuration information and the process level information to obtain second equipment data with process matching information. And processing the first equipment data according to the process configuration information and the process level information to enable the first equipment data to carry the process configuration information as a unique identifier for data query.
Further as a preferred embodiment, when storing the second device data in the second database, the method further includes the following steps:
and respectively storing the second equipment data in a third storage database and a fourth storage database.
Specifically, the third storage database is infilxdb, the infixdb is a time sequence database, and the third storage database is used for storing device data within one month. The fourth storage database is MySQL and is used for storing equipment data which is not strong in timeliness. And storing the second equipment data into different databases for meeting different service requirements.
Further as a preferred embodiment, the method further comprises the following steps:
and when the received data request uploaded by the first terminal is a historical data request, reading fourth equipment data from a third storage database according to the data request. The historical data request is used for inquiring equipment data and equipment data reports in one month. The third storage database is used for storing equipment data within one month and generating a data report according to the equipment data.
Further as a preferred embodiment, the method further comprises the following steps:
and when the data request uploaded by the first terminal is received as a data comparison request, at least two different station information in the data request are obtained, and the fifth equipment data are respectively read from the fourth storage database according to the station information. The different stations have different equipment data. The fourth storage database is used for storing the device data with weak real-time performance and providing offline report query contents. The fourth storage database stores equipment data including existing equipment data and equipment data for one month or even several years. The fourth storage database can provide query contents of the equipment data of different stations and different time, and the Gantt chart for comparing the two equipment data can be displayed in a graphic form at the first terminal by acquiring the equipment data of the two different stations.
Referring to fig. 2, an embodiment of the present invention further provides a processing system based on a big data display process timing diagram corresponding to the method in fig. 1, including:
the acquisition module is used for acquiring a plurality of pieces of first equipment data in real time and storing the first equipment data in a first database in a classified manner according to preset rules;
the first reading module is used for reading a plurality of pieces of first equipment data from the first database according to preset time;
the storage module is used for obtaining second equipment data with process configuration information according to the read first equipment data and storing the second equipment data in a second database;
the receiving module is used for receiving a data request uploaded by a first terminal;
the second reading module is used for reading third equipment data from the second database according to the data request;
and the sending module is used for sending the third equipment data to the first terminal so that the first terminal displays the third equipment data in a timing chart form.
The contents in the above method embodiments are all applicable to the present system embodiment, the functions specifically implemented by the present system embodiment are the same as those in the above method embodiments, and the beneficial effects achieved by the present system embodiment are also the same as those achieved by the above method.
The embodiment of the invention also provides a processing system based on the big data display process timing diagram corresponding to the method shown in fig. 1, which comprises the following steps:
at least one memory for storing a program;
and the at least one processor is used for loading the program to realize the processing method based on the big data display process timing diagram.
The contents in the above method embodiments are all applicable to the present system embodiment, the functions specifically implemented by the present system embodiment are the same as those in the above method embodiments, and the beneficial effects achieved by the present system embodiment are also the same as those achieved by the above method.
In addition, the embodiment of the invention also provides a storage medium, wherein processor-executable instructions are stored in the storage medium, and when the processor-executable instructions are executed by a processor, the processor-executable instructions are used for realizing the processing method based on the big data display process timing diagram.
In summary, the first device data collected in real time is read from the database through the data request uploaded by the first terminal, and the first device data is sent to the first terminal, so that the first terminal visually presents the real-time device data in a time sequence form, and thus a manager can timely master the operation state of the device according to the displayed time sequence; furthermore, the second device data are stored in three different databases to meet the service requirements of different users.
While the preferred embodiments of the present invention have been illustrated and described, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A processing method based on a big data display process timing diagram is characterized in that: the method comprises the following steps:
collecting a plurality of first equipment data in real time, and storing the first equipment data in a first database in a classified manner according to preset rules;
reading a plurality of pieces of first equipment data from a first database according to preset time, wherein the first database is a relational database;
obtaining second equipment data with process configuration information according to the read first equipment data, and storing the second equipment data in a second database, wherein the second database is a key-value storage system;
receiving a data request uploaded by a first terminal;
reading third device data from a second database according to a data request, wherein the third device data is the second device data conforming to the data request;
and transmitting the third device data to the first terminal, so that the first terminal displays the third device data in a time sequence chart mode.
2. The processing method based on the big data display process timing diagram according to claim 1, wherein: the method comprises the following steps of classifying and storing first equipment data in a first database according to preset rules, wherein the method specifically comprises the following steps:
and storing the first equipment data in three category tables of a first database according to preset rules in a classified manner, wherein the three category tables are respectively actions, states and parameters.
3. The processing method based on the big data display process timing diagram according to claim 2, wherein: the reading of the plurality of pieces of first device data from the first database according to the preset time specifically includes:
and reading at least one thousand pieces of first equipment data from a first database according to preset time, wherein the first equipment data are equipment data from three category tables read in the same process.
4. The processing method based on the big data display process timing diagram according to claim 1, wherein: the step of obtaining second equipment data with process configuration information according to the read first equipment data comprises the following steps:
acquiring process configuration information and process level information;
and matching the read first equipment data with the process configuration information and the process level information to obtain second equipment data with process matching information.
5. The processing method based on the big data display process timing diagram according to claim 1, wherein: when the second device data is stored in the second database, the method further comprises the following steps:
and respectively storing the second equipment data in a third storage database and a fourth storage database.
6. The processing method based on the big data display process timing diagram according to claim 5, wherein: further comprising the steps of:
and when the received data request uploaded by the first terminal is a historical data request, reading fourth equipment data from a third storage database according to the data request.
7. The processing method based on the big data display process timing diagram according to claim 5, wherein: further comprising the steps of:
and when the data request uploaded by the first terminal is received as a data comparison request, at least two different station information in the data request are obtained, and the fifth equipment data are respectively read from the fourth storage database according to the station information.
8. A processing system based on big data display technology timing diagram is characterized in that: the method comprises the following steps:
the system comprises an acquisition module, a storage module and a control module, wherein the acquisition module is used for acquiring a plurality of pieces of first equipment data in real time, and storing the first equipment data in a first database in a classified manner according to preset rules, and the first database is a relational database;
the first reading module is used for reading a plurality of pieces of first equipment data from the first database according to preset time;
the storage module is used for obtaining second equipment data with process configuration information according to the read first equipment data and storing the second equipment data in a second database, wherein the second database is a key-value storage system;
the receiving module is used for receiving a data request uploaded by a first terminal;
the second reading module is used for reading third equipment data from a second database according to a data request, wherein the third equipment data is the second equipment data which accords with the data request;
and the sending module is used for sending the third equipment data to the first terminal so that the first terminal displays the third equipment data in a timing chart form.
9. A processing system based on big data display technology timing diagram is characterized in that: the method comprises the following steps:
at least one memory for storing a program;
at least one processor, configured to load the program to implement a processing method based on big data display process timing diagram according to any one of claims 1 to 7.
10. A storage medium having stored therein instructions executable by a processor, the storage medium comprising: the processor-executable instructions are used for realizing a processing method based on a big data display process timing diagram according to any one of claims 1 to 7 when being executed by a processor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910346102.1A CN110222100B (en) | 2019-04-26 | 2019-04-26 | Processing method, system and storage medium based on big data display process timing diagram |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910346102.1A CN110222100B (en) | 2019-04-26 | 2019-04-26 | Processing method, system and storage medium based on big data display process timing diagram |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110222100A CN110222100A (en) | 2019-09-10 |
| CN110222100B true CN110222100B (en) | 2023-04-07 |
Family
ID=67820110
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910346102.1A Active CN110222100B (en) | 2019-04-26 | 2019-04-26 | Processing method, system and storage medium based on big data display process timing diagram |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110222100B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110928898A (en) * | 2019-10-24 | 2020-03-27 | 长城计算机软件与系统有限公司 | Data acquisition method, data acquisition device, storage medium and electronic equipment |
| CN112835334B (en) * | 2020-12-31 | 2022-05-27 | 广州明珞装备股份有限公司 | Industrial data platform testing method and device, computer equipment and storage medium |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102176278A (en) * | 2011-01-12 | 2011-09-07 | 首都师范大学 | Risk factor data acquisition system for high applicability agricultural product production |
| CN109165136A (en) * | 2018-07-25 | 2019-01-08 | 平安科技（深圳）有限公司 | Monitoring method, terminal device and the medium of terminal operating data |
| CN109299164A (en) * | 2018-09-03 | 2019-02-01 | 中国平安人寿保险股份有限公司 | A kind of data query method, computer readable storage medium and terminal device |
Family Cites Families (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8522217B2 (en) * | 2010-04-20 | 2013-08-27 | Microsoft Corporation | Visualization of runtime analysis across dynamic boundaries |
| CN102262401A (en) * | 2010-05-31 | 2011-11-30 | 北京德尔福万源发动机管理系统有限公司 | Industrial production line monitoring system |
| CN102542396A (en) * | 2010-12-27 | 2012-07-04 | 软控股份有限公司 | Tire vulcanizing production control system and operation adjusting method |
| CN103532780B (en) * | 2013-10-11 | 2017-09-22 | 北京有度致远信息科技股份有限公司 | O＆M for IT field monitors integral system and integrated monitoring method |
| CN103970903B (en) * | 2014-05-27 | 2017-05-24 | 重庆大学 | Large industrial system feedback data real-time processing method and system based on Web |
| CN104979912A (en) * | 2015-07-22 | 2015-10-14 | 中国华能集团清洁能源技术研究院有限公司 | Monitoring method of photovoltaic power generation system and system thereof |
| CN106850318B (en) * | 2017-03-27 | 2019-11-12 | 国网山东省电力公司信息通信公司 | The visualization of IMS signaling process shows system, method and server |
| CN107196910B (en) * | 2017-04-18 | 2019-09-10 | 国网山东省电力公司电力科学研究院 | Threat early warning monitoring system, method and deployment framework based on big data analysis |
| CN109034662B (en) * | 2018-08-31 | 2022-03-25 | 东北大学 | Production index visual monitoring system and method based on process flow |
| CN109559027B (en) * | 2018-11-20 | 2022-12-06 | 冶金自动化研究设计院 | Plan scheduling system applied to high-speed tool steel smelting process of iron and steel enterprise |
-
2019
- 2019-04-26 CN CN201910346102.1A patent/CN110222100B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102176278A (en) * | 2011-01-12 | 2011-09-07 | 首都师范大学 | Risk factor data acquisition system for high applicability agricultural product production |
| CN109165136A (en) * | 2018-07-25 | 2019-01-08 | 平安科技（深圳）有限公司 | Monitoring method, terminal device and the medium of terminal operating data |
| CN109299164A (en) * | 2018-09-03 | 2019-02-01 | 中国平安人寿保险股份有限公司 | A kind of data query method, computer readable storage medium and terminal device |
Non-Patent Citations (1)
| Title |
|---|
| 基于Shapelet的时间序列分类方法研究;嵇存;《中国博士学位论文全文数据库 (基础科学辑)》;20180315(第3期);A002-30 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110222100A (en) | 2019-09-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106951694B (en) | Adaptive modeling method for online monitoring system of secondary equipment of power system | |
| CN109947810A (en) | Industrial equipment data real-time collecting system | |
| CN107749811B (en) | Power distribution terminal access adaptive debugging analysis method based on power distribution master station | |
| CN107065813A (en) | A kind of workshop appliance data monitoring system and method | |
| CN110222100B (en) | Processing method, system and storage medium based on big data display process timing diagram | |
| CN110784398A (en) | Data acquisition gateway and data analysis method for industrial Internet of things processing equipment | |
| CN108009258A (en) | It is a kind of can Configuration Online data collection and analysis platform | |
| CN102222270B (en) | Manufacture and perform management system and production curves device | |
| CN114430353B (en) | Modbus protocol-based data acquisition method, system, device and medium | |
| CN105589410A (en) | Workshop monitoring and management system based on Android platform | |
| CN103970530A (en) | Data acquisition and implementation method based on Intouch configuration technology of OPC interface | |
| CN113054743A (en) | Internet of things terminal data access system and method suitable for power distribution cloud master station | |
| CN107508728B (en) | Secondary equipment online monitoring method based on IEC61850 service tracking | |
| CN112633769A (en) | Advanced plan scheduling system | |
| CN109561155B (en) | Remote centralized monitoring and operation and maintenance method for substation equipment | |
| CN202854576U (en) | Automobile production line data management system | |
| CN107291865A (en) | A kind of workshop appliance monitoring system describes method | |
| CN103414595B (en) | Power dispatch data network link monitoring system topological drawing generating method | |
| CN113485265B (en) | Real-time interconnection method based on chart and industrial intelligent manufacturing equipment data | |
| CN110531724B (en) | Remote measurement automatic sampling definition method based on smart power grid dispatching control system | |
| CN113110361A (en) | Intelligent factory integrated control system based on production networking | |
| CN111858670A (en) | Intelligent risk report generation method and report system for consumption financial industry | |
| CN109426947B (en) | Enterprise information interaction system based on tree-shaped virtual node network | |
| CN113291980B (en) | Multisource fault alarm system suitable for automatic crane | |
| CN115499273B (en) | Edge computing soft gateway for numerical control equipment and implementation method thereof |
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 | ||
| CB02 | Change of applicant information | ||
| CB02 | Change of applicant information |
Address after: 510530 Unit A and Second Floor of Building C3, No.11 Kaiyuan Avenue, Guangzhou High-tech Industrial Development Zone, Guangdong Province Applicant after: Guangzhou mingluo Equipment Co.,Ltd. Address before: 510530 Unit A and Second Floor of Building C3, No.11 Kaiyuan Avenue, Guangzhou High-tech Industrial Development Zone, Guangdong Province Applicant before: GUANGZHOU MINO AUTOMOTIVE EQUIPMENT Co.,Ltd. |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant |