CN116010475A - Industrial big data platform system with intelligent supervision - Google Patents
Industrial big data platform system with intelligent supervision Download PDFInfo
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- CN116010475A CN116010475A CN202211564752.1A CN202211564752A CN116010475A CN 116010475 A CN116010475 A CN 116010475A CN 202211564752 A CN202211564752 A CN 202211564752A CN 116010475 A CN116010475 A CN 116010475A
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Abstract
The invention relates to the technical field of big data application, and discloses an intelligent supervision industrial big data platform system, which comprises a data acquisition module, a data management module, a data analysis module, a data service module and a data collaboration module, wherein the data acquisition module comprises data access services for acquiring and monitoring real-time data and non-real-time data, and the data management module comprises data management services for full life cycle management, configuration definition, full type data and full process monitoring. The intelligent supervision industrial big data platform system provided by the invention has the advantages that the internal data acquisition service component provides the industrial Internet with a high-standard, flexible and available acquisition function suitable for various data sources and complex data structures, the problems of numerous enterprise states and great difficulty in upgrading and changing business rules are overcome, the intelligent supervision system is an important technical basis for unified management, sharing and service of data resources, and digital intelligent supervision transformation is realized for the live data assets of the enterprise.
Description
Technical Field
The invention relates to the technical field of big data application, in particular to an industrial big data platform system with intelligent supervision.
Background
Big data or huge amount of data refers to data which is huge in size and cannot pass through a main stream software tool, and the main operation principle is to acquire, manage, process and arrange information which is more positive in helping business operation decision in a reasonable time by means of the internet technology.
Currently, the technical idea of mixing big data into industrial production and then forming an intelligent supervision system has been proposed and disclosed in a patented manner, for example, an invention patent with publication number CN115222355a discloses an industrial internet platform based on an assembly building application, which includes: the data model layer is a data source of an industrial Internet platform, the industrial Internet platform acquires data from an external system through a compatible protocol, data acquisition, data modeling, data analysis, data integration, data application and data asset management are realized on the data model layer, and the data is uploaded to the cloud end through a cloud network; the business layer is used for carrying out component development on the data acquired from the data model layer to form various business system applications; the invention can customize the required SAAS by the enterprises through the expansion of the capacity of the PAAS after use, can shorten the development period of the application, meets the individual requirements of different enterprises, and supports the data intercommunication of the inner part and the outer part of the enterprises by integrating the data of the bottom layer and combining the data middle platform to construct business service. For example, the invention patent with the bulletin number of CN114020796a discloses an electronic specification implementation method based on an industrial internet identification analysis system, and an electronic specification implementation system based on an industrial internet identification analysis system includes a data docking module, an assembling module, an identification registration module, a query module, an identification analysis module and a generation module, wherein the data docking module collects product production data and product description information through a docking enterprise production management system, the assembling module configures the product production data and the product description information and assembles identification content of the product specification, the identification registration module registers the identification content of the specification to an industrial internet identification analysis platform in an encrypted manner, the query module queries the product specification according to the product description information through the industrial internet identification analysis platform, and the identification analysis module decrypts and analyzes the identification content of the product specification to generate a specification document. After the electronic instruction implementation method based on the industrial Internet identification analysis system is used, the method not only has the advantages of being applied to an industrial Internet identification analysis platform, but also has the advantages of being high in compatibility by configuring multiple data sources and the like, being applicable to an industrial software system of an enterprise at low cost and low risk, protecting enterprise privacy data from being disclosed by encrypting and decrypting to obtain the instruction, and being capable of reducing enterprise storage pressure and cost by storing the instruction data in the industrial Internet identification analysis platform.
From the above disclosure, the applicant has found that while the internet-enabled big data technology is associated with actual industrial production, some detail technologies are too simple, which in turn leads to a narrow range of use, for example, the collection, administration and analysis of related data of industrial production by the prior art is also based on the prior art, and the related technologies also tend to be fragmented, which is not easy for users to understand and apply.
Disclosure of Invention
The invention provides an intelligent supervision industrial big data platform system, which solves the problems set forth in the background technology.
The invention provides the following technical scheme: the utility model provides an industry big data platform system of wisdom supervision, includes data acquisition module, data governance module, data analysis module, data service module and data cooperation module, data acquisition module includes the data access service of the collection of real-time data and non-real-time data, control, data governance module includes full life cycle management, configuration definition, full type data, the data governance service of whole process control, data analysis module includes industry data modeling and analysis excavation, data service module is based on data mart or data sandbox form and directly provides the service for the business, the inside cloud limit cooperation that includes of data cooperation module.
The real-time data acquisition in the data acquisition module comprises sampling inventory data, event alarms, accident trips, fan deflection, fan faults and inverter states, the non-real-time data acquisition comprises power station operation records, power outage plans, unit power generation plans, personnel duty, equipment purchase fees, personnel wage fees, weather data, power prediction information and fault wave recording, and the monitored data access service is used for managing and monitoring the execution states of all acquisition tasks.
Carefully chosen, the full life cycle management in the treatment module comprises a creation stage, an auditing stage, a release stage, a disconnection stage and a destruction stage.
Carefully chosen, the industrial data modeling in the data analysis module comprises data set modeling and batch calculation model modeling, and the data set of the visual report development tool is derived from an industrial big data system, and any one simple query output is used as a cube.
Carefully chosen, the calculation step inside the batch calculation model modeling comprises an input step: and no relay node exists, and the external output is an abstract data set and output step: and (3) receiving an abstract result set without a subsequent node, and performing calculation output of the whole model, such as files, databases and the like, and calculation steps: receiving a data set input, providing a data set output, and setting a complex computing step and a customized computing step in the computing step, wherein the complex computing step receives the inputs of different result sets, provides a data set output, and the customized computing step is used for receiving a data set input, providing a data set output, and customizing specific implementation content.
The analysis mining in the data analysis module comprises self-service analysis service, wherein the self-service analysis service is an industrial big data analysis tool which is built on a platform and is specially used for real-time data from an equipment system, and through interactive operation, a user can build a calculation analysis task to mine association relations among different data items, extract system characteristic parameters and generate various visual image-text reports.
Carefully chosen, the data marts in the data service module are data combinations selected according to certain theme conditions, and are logically defined and do not correspond to actual physical entities.
And selecting a part of objects and data screened from the basic data area by the data sandbox in the data service module, copying and storing the objects and the data in the application data area, namely forming an isolated data aggregate after copying into the data sandbox.
Carefully chosen, cloud edge coordination in the data coordination module comprises data coordination and management coordination, wherein the data coordination has the functions of data downloading/receiving, data packing/uploading, data packet management, data resource synchronization, data transmission encryption, fault recovery and the like, and the management coordination is specifically related authority in the management coordination module, including authority control related to task coordination, calculation coordination and unified operation and maintenance management.
The data management service of the whole process monitoring inside the data management module is selected, a data label is established for setting, the data label comprises a public label and a customized label, the public label is predefined for a system platform, the labels used for all users and resources in the whole system are checked and released, the customized label is a label which is randomly marked for the users by the data in a management range, the labels are visible only in the user range, and the system provides a unified retrieval entrance, and related data resource objects can be retrieved according to one label or a plurality of label combinations.
The invention has the following beneficial effects:
1. the intelligent supervision industrial big data platform system provided by the invention has the advantages that the internal data acquisition service is built on the basis of the data support layer, is a multi-source, multi-scale and hybrid data entry, and provides high-performance concurrent data acquisition for various data sources. The data acquisition mainly supports distributed acquisition of multi-source heterogeneous data, and is divided into offline acquisition and real-time acquisition, wherein the offline acquisition is divided into offline acquisition of structured data and unstructured data, and mainly comprises acquisition of daily, weekly and monthly data; real-time acquisition also supports the acquisition of structured and unstructured data, mainly second and minute data acquisition. The layer realizes seamless visual configuration management of acquisition channels and acquisition interfaces of various data sources, can provide unified protocol access, data cleaning, data conversion, data routing, data warehouse entry processing and programming expansion support for different types of data, can provide high-speed transmission access support for specific data, is a flexible and expandable data acquisition service component, and further realizes intelligent supervision and use of the whole system.
2. The intelligent supervision industrial big data platform system provided by the invention has the advantages that the internal data acquisition service component provides the industrial Internet with a high-standard, flexible and available acquisition function suitable for various data sources and complex data structures, the problems of numerous enterprise states and great difficulty in upgrading and changing business rules are overcome, the intelligent supervision industrial big data platform system is an important technical basis for unified management, sharing and service of data resources, and necessary conditions are provided for realizing digital intelligent supervision and transformation of the enterprise live data assets.
3. According to the intelligent supervision industrial big data platform system, cloud edges used in the internal data collaboration module support data, management and application of the system, basic information and safety related business processing and business demand response. And meanwhile, the data and the model of the system and the regional centralized control big data side platform are provided, and the collaborative access is managed.
Drawings
FIG. 1 is a schematic flow chart of the principle of the invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, an intelligent supervision industrial big data platform system comprises a data acquisition module, a data management module, a data analysis module, a data service module and a data collaboration module, wherein the data acquisition module comprises real-time data and non-real-time data acquisition and monitoring data access services, the real-time data acquisition in the data acquisition module internally comprises sampling inventory data, event alarms, accident trips, fan deflection, fan faults and inverter states, the non-real-time data acquisition comprises power station operation records, power outage plans, unit power generation plans, personnel duty, equipment purchase cost, personnel wage cost, weather data, power prediction information and fault wave recording, the monitoring data access services are used for managing and monitoring the execution states of all acquisition tasks, the data acquisition services support data migration, support an internet of things universal gateway engine, support data extraction, conversion, cleaning and storage, support dragging type import of formatted data such as EXCEL, and the data after the data acquisition services provide cleaning and filtering for the industrial big data system, the data can be processed by a service basic layer, and the data processing is provided for a data processing domain, and the service analysis domain can be provided for clean data analysis domain.
Referring to fig. 1, the data management module includes a full life cycle management, a configuration definition, full type data, and a full process monitoring data management service, where the full life cycle management in the management module includes a creation stage, an audit stage, a release stage, a drop-in stage, and a destruction stage, and the big data management tool provides a full life cycle management function for data, and comprehensively serves the flow of various business data generated by the enterprise functional departments in the whole life cycle, namely: the method comprises the steps that from creation, auditing and release to the process of outdated offline and destroyed deletion, a data management service of overall process monitoring in a data management module establishes a data label for setting, the data label comprises a public label and a custom label, the public label is predefined for a system platform, the audit and release are carried out on labels used by all users and resources in the whole system, the custom label is a label which is randomly marked by the users for data in a management range, the label is visible only in the user range, the system provides a unified search entrance, related data resource objects can be searched according to one label or a plurality of label combinations, the public label is managed according to catalogs, and each catalogue contains the label of a corresponding theme. And establishing a label, and checking to enter a release state. The tags of the release state can be used for users to refer in the whole system, the users provide tag definition functions for the data assets, the data assets can be attached with a plurality of data tags, and once the data tags are confirmed to be attached to the data assets, the data tags are successfully defined.
Referring to fig. 1, the data analysis module includes industrial data modeling and analysis mining, the industrial data modeling in the data analysis module includes data set modeling and batch calculation model modeling, and the data set of the visual report development tool is derived from an industrial big data system, any one simple query output is used as a cube, and cube modification avoids the complicated processes of conventional data modeling, modification and release test. For example, for the first time a business requirement you might choose, four columns a, b, c, d as aggregated dimensions, a Cube is built, the computation steps inside the batch computation model modeling include the input steps: and no relay node exists, and the external output is an abstract data set and output step: and (3) receiving an abstract result set without a subsequent node, and performing calculation output of the whole model, such as files, databases and the like, and calculation steps: the method comprises the steps of receiving a data set input, providing a data set output, setting a complex calculation step and a customized calculation step in a calculation step, wherein the complex calculation step is used for receiving inputs of different result sets, providing a data set output, the customized calculation step is used for receiving a data set input, providing a data set output, customizing specific implementation content, analyzing and mining in a data analysis module comprises self-service analysis service, the self-service analysis service is an industrial big data analysis tool which is built on a platform and is specially used for real-time data from a device system, and through interactive operation, a user can build a calculation analysis task to mine association relations among different data items, extract system characteristic parameters, generate various visual image-text reports, realize visual and pipelined analysis and exploration of industrial data, and provide an algorithm set to conduct system characteristic extraction and training of a data model on a sample.
Referring to fig. 1, the data service module directly provides service for a service based on a data mart or a data sandbox, where the data mart in the data service module is a data combination selected according to a certain theme condition, is a logical definition, does not correspond to an actual physical entity, the data mart is a basis for providing a theme data service for the outside, and can instantiate and construct a data sandbox, or provide data sharing for the outside in a subscription manner, and a part of objects and data screened from a basic data area by the data sandbox in the data service module are copied and stored in an application data area, that is, an isolated data aggregate formed after copying is formed into the data sandbox, and the function description: creating a data sandbox: custom sandboxed groupings are supported, i.e., sandboxed list directories are configured. And newly building a data sandbox under the catalogue.
Referring to fig. 1, the data collaboration module includes cloud edge collaboration, where the cloud edge collaboration in the data collaboration module includes data collaboration and management collaboration, and the data collaboration has functions of data downloading/receiving, data packaging/uploading, data packet management, data resource synchronization, data transmission encryption, fault recovery, etc., the management collaboration is specifically related rights in the management collaboration module, including rights control related to task collaboration, calculation collaboration, unified operation and maintenance management, and the cloud edge collaboration function module of the industrial large data system can support data, management and application of the platform, basic information and safe related business processing and business demand response. And simultaneously, providing data and a model of the platform and the regional centralized control big data side platform, and managing collaborative access.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Meanwhile, in the drawings of the present invention, the filling pattern is only for distinguishing the layers, and is not limited in any way.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
1. The utility model provides an industry big data platform system of wisdom supervision, includes data acquisition module, data treatment module, data analysis module, data service module and data cooperation module, its characterized in that: the data acquisition module comprises data access services for acquisition and monitoring of real-time data and non-real-time data, the data management module comprises data management services for full life cycle management, configuration definition, full type data and full process monitoring, the data analysis module comprises industrial data modeling and analysis mining, the data service module directly provides services for services based on data marts or data sandboxes, and cloud-edge cooperation is included in the data cooperation module.
2. An intelligent supervisory industrial big data platform system according to claim 1, wherein: the real-time data acquisition in the data acquisition module comprises sampling inventory data, event alarms, accident trips, fan deflection, fan faults and inverter states, the non-real-time data acquisition comprises power station operation records, power failure plans, unit power generation plans, personnel duty, equipment purchase fees, personnel wage fees, weather data, power forecast information and fault wave recording, and the monitored data access service is used for managing and monitoring the executing states of all acquisition tasks.
3. An intelligent supervisory industrial big data platform system according to claim 1, wherein: the full life cycle management in the treatment module comprises a creation stage, an auditing stage, a release stage, a offline stage and a destruction stage.
4. An intelligent supervisory industrial big data platform system according to claim 1, wherein: the industrial data modeling in the data analysis module comprises data set modeling and batch calculation model modeling, and the data set of the visual report development tool is derived from an industrial big data system, and any one simple query output is used as a cube.
5. An intelligent supervisory industrial big data platform system according to claim 1, wherein: the calculation step inside the batch calculation model modeling comprises the input step of: and no relay node exists, and the external output is an abstract data set and output step: and (3) receiving an abstract result set without a subsequent node, and performing calculation output of the whole model, such as files, databases and the like, and calculation steps: receiving a data set input, providing a data set output, and setting a complex computing step and a customized computing step in the computing step, wherein the complex computing step receives the inputs of different result sets, provides a data set output, and the customized computing step is used for receiving a data set input, providing a data set output, and customizing specific implementation content.
6. An intelligent supervisory industrial big data platform system according to claim 1, wherein: the analysis mining in the data analysis module comprises self-service analysis service, the self-service analysis service is an industrial big data analysis tool which is built on a platform and specially aims at real-time data from the equipment system, through interactive operation, a user can build a calculation analysis task to mine association relations among different data items, extract system characteristic parameters and generate various visual image-text reports.
7. An intelligent supervisory industrial big data platform system according to claim 1, wherein: the data marts in the data service module are data combinations selected according to certain theme conditions, are logically defined and do not correspond to actual physical entities.
8. An intelligent supervisory industrial big data platform system according to claim 1, wherein: and a part of objects and data screened from the basic data area by the data sandbox in the data service module are copied and stored in the application data area, namely, the isolated data aggregate formed after copying becomes the data sandbox.
9. An intelligent supervisory industrial big data platform system according to claim 1, wherein: cloud edge collaboration in the data collaboration module comprises data collaboration and management collaboration, wherein the data collaboration has the functions of data downloading/receiving, data packaging/uploading, data packet management, data resource synchronization, data transmission encryption, fault recovery and the like, and the management collaboration specifically comprises relevant authorities in the management collaboration module, including authority control related to covering task collaboration, calculation collaboration and unified operation and maintenance management.
10. An intelligent supervisory industrial big data platform system according to claim 1, wherein: the data management service of the whole process monitoring in the data management module establishes a data label for setting, the data label comprises a public label and a customized label, the public label is predefined for a system platform, the label used for all users and resources in the whole system is checked and released, the customized label is a label which is randomly marked for the users by the data in a management range, the label is visible only in the user range, the system provides a unified retrieval entrance, and related data resource objects can be retrieved according to one label or a plurality of label combinations.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116781423A (en) * | 2023-08-18 | 2023-09-19 | 山东省信息技术产业发展研究院(中国赛宝(山东)实验室) | Sharing method and system for industrial Internet data |
| CN117278333A (en) * | 2023-11-21 | 2023-12-22 | 武汉盛博汇信息技术有限公司 | Intelligent medical data processing method, device and system based on SaaS platform |
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2022
- 2022-12-07 CN CN202211564752.1A patent/CN116010475A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116781423A (en) * | 2023-08-18 | 2023-09-19 | 山东省信息技术产业发展研究院(中国赛宝(山东)实验室) | Sharing method and system for industrial Internet data |
| CN116781423B (en) * | 2023-08-18 | 2023-11-03 | 山东省信息技术产业发展研究院(中国赛宝(山东)实验室) | Sharing method and system for industrial Internet data |
| CN117278333A (en) * | 2023-11-21 | 2023-12-22 | 武汉盛博汇信息技术有限公司 | Intelligent medical data processing method, device and system based on SaaS platform |
| CN117278333B (en) * | 2023-11-21 | 2024-01-30 | 武汉盛博汇信息技术有限公司 | Intelligent medical data processing method, device and system based on SaaS platform |
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