CN117453689A - Data processing method and system for Internet big data - Google Patents
Data processing method and system for Internet big data Download PDFInfo
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- CN117453689A CN117453689A CN202311415607.1A CN202311415607A CN117453689A CN 117453689 A CN117453689 A CN 117453689A CN 202311415607 A CN202311415607 A CN 202311415607A CN 117453689 A CN117453689 A CN 117453689A
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Abstract
The invention discloses a data processing method and a system for Internet big data, which belong to the technical field of xx and comprise a data analysis unit, wherein the input end of the data analysis unit is electrically connected with the output end of a data acquisition unit, and the output end of the data analysis unit is electrically connected with the input end of a data management module unit. In the invention, the performance and the connection of peripheral man-machine interaction modules are convenient to improve, the industrial big data storage system comprises three module access layers, namely a data interface module, a data service module and a database service module, and the cluster technology, the storage technology and the distributed parallel data processing technology are used, so that the storage and access efficiency of the industrial big data can be effectively improved, the safe and stable storage of massive data can be ensured, the front end adopts a Vue.js frame module, the rear end adopts an ECharts visual module, the front end and rear end separation development technology is realized, the development efficiency can be improved, and more effective data presentation services can be provided for users.
Description
Technical Field
The invention belongs to the technical field of data processing, and particularly relates to a data processing method and system for Internet big data.
Background
As technology develops, manufacturing gradually goes from the stage of meeting product and service functions to the stage of personalized customization during development, and the production mode is also changed from a single pipeline type to an ecological type. In such a large environment, industrial manufacturing is increasingly in close contact with the industrial internet, and industrial manufacturing is moving toward digitization, networking, automation and intelligence. As the scale of industrial manufacturing increases, manufacturing ecology becomes more and more complex, and industrial equipment also generates a large amount of data in the production process. In view of the needs of enterprise development, some of the industrial data need to be refined and analyzed.
The use of computers for industrial data acquisition has become an important component in modern industrial control, but the industrial control by means of single-chip microcomputer only is still an imperfect place.
Based on the above, the invention designs a data processing method and system for Internet big data to solve the above problems.
Disclosure of Invention
The invention aims at: the data processing method and system for the Internet big data are provided for solving the problem that the industrial data acquisition by using a computer in the modern industrial control becomes an important component of the industrial data acquisition, but the industrial control by using a single chip microcomputer only has an imperfect place.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
the data processing system of the Internet big data comprises a data analysis unit, wherein the input end of the data analysis unit is electrically connected with the output end of a data acquisition unit, the output end of the data analysis unit is electrically connected with the input end of a data management module unit, the output end of the data management module unit is electrically connected with the input end of a data storage unit, the data storage unit is in bidirectional connection with the data analysis unit, and the output end of the data analysis unit is electrically connected with the input end of a data acquisition unit;
the data acquisition unit is used for acquiring various control signals of industrial equipment, obtaining industrial big data and transmitting the obtained industrial big data to the data analysis unit and the data storage unit;
the data management module unit is used for carrying out industrial big data processing information interaction and transmitting the industrial big data analysis result;
the data acquisition unit is used for matching the industrial big data to obtain effective industrial data;
and the data analysis unit is used for sequentially receiving, cleaning, sorting and analyzing the industrial big data and then storing the data into the MySQL database.
As a further description of the above technical solution:
the data acquisition unit comprises a sensor signal acquisition module, the output end of the sensor signal acquisition module is electrically connected with the input end of the signal conditioning module, the output end of the signal conditioning module is electrically connected with the input end of the A/D conversion module, the output end of the A/D conversion module is electrically connected with the input end of the ARM processor, and the output end of the ARM processor is electrically connected with the input end of the man-machine interaction module.
As a further description of the above technical solution:
the sensor signal acquisition module is used for acquiring various industrial control signals, and the signal conditioning module is used for receiving various industrial control signals sent by the sensor signal acquisition module and conditioning the received industrial control signals, wherein the industrial control signal conditioning content comprises isolation, amplification and filtering.
As a further description of the above technical solution:
the data storage unit comprises a data interface module, wherein the output end of the data interface module is electrically connected with the input end of the data service module, and the output end of the data service module is electrically connected with the input end of the database service module.
As a further description of the above technical solution:
the data service module comprises a storage management sub-module, wherein the output end of the storage management sub-module is electrically connected with the input end of the data parallel storage sub-module, the output end of the data parallel storage sub-module is electrically connected with the input end of the data parallel query sub-module, the output end of the data parallel query sub-module is electrically connected with the input end of the data dictionary sub-module, and the output end of the data dictionary sub-module is electrically connected with the input end of the data backup atomic module.
As a further description of the above technical solution:
the data interface module is used for receiving the industrial big data obtained by the data acquisition unit.
As a further description of the above technical solution:
the storage management submodule is used for carrying out distributed management on equipment in the storage system, carrying out balanced allocation on the storage process and the performance load of the storage equipment, the data parallel storage submodule is used for realizing loading, analysis processing and storage of industrial big data, the data parallel query submodule is used for carrying out parallel query processing of data, the data dictionary submodule is used for establishing a data dictionary in the storage system, maintaining various metadata in the data system, and the data backup and restore submodule is used for carrying out backup storage and restoration on the data in the storage system.
As a further description of the above technical solution:
the data analysis unit comprises a data receiving module, the output end of the data receiving module is electrically connected with the input end of the data cleaning module, the output end of the data cleaning module is electrically connected with the input end of the data sorting module, the output end of the data sorting module is electrically connected with the output end of the data analysis module, and the output end of the data analysis module is electrically connected with the input ends of the ECharts visualization module, the Vue. Js frame module and the SpringBoot frame module respectively.
As a further description of the above technical solution:
the SpringBoot framework module is carried with Java to realize a data interface function.
A data processing method of Internet big data comprises the following steps:
the sensor signal acquisition module acquires various industrial control signals, the signal conditioning module receives the various industrial control signals sent by the sensor signal acquisition module and conditions the received industrial control signals, and the conditioning content of the industrial control signals comprises isolation, amplification and filtering;
the storage management sub-module is used for carrying out distributed management on equipment in the storage system, carrying out balanced allocation on the storage process and the performance load of the storage equipment, the data parallel storage sub-module is used for realizing loading, analysis processing and storage of the industrial large data, the data parallel query sub-module is used for carrying out parallel query processing of the data, the data dictionary sub-module is used for establishing a data dictionary in the storage system, maintaining various metadata in the data system, and the data backup atomic module is used for carrying out backup storage and restoration on the data in the storage system;
performing industrial big data processing information interaction and transmitting an industrial big data analysis result;
the industrial big data is matched to obtain valid industrial data.
In summary, due to the adoption of the technical scheme, the beneficial effects of the invention are as follows:
according to the invention, the ARM processor is provided with the Linux operating system, so that the collection of industrial control data has high precision and good anti-interference capability, the improvement of performance and the connection of peripheral human-computer interaction modules are facilitated, the industrial big data storage system comprises a data interface module, a data service module and a database service module, three module access layers, a cluster technology, a storage technology and a distributed parallel data processing technology are used, the storage and access efficiency of industrial big data can be effectively improved, the safe and stable storage of massive data is facilitated, a Vue.js frame module is adopted at the front end, an ECharts visual module is adopted at the rear end, the front end and rear end separation development technology is realized, the development efficiency is facilitated to be improved, and more effective data presentation services can be provided for users.
Drawings
FIG. 1 is a block diagram of a method and system for processing Internet big data according to the present invention;
FIG. 2 is a block diagram of a data acquisition unit in the data processing method and system for Internet big data according to the present invention;
FIG. 3 is a block diagram of a data storage unit in the data processing method and system for big Internet data according to the present invention;
fig. 4 is a block diagram of a data analysis unit in the data processing method and system for internet big data according to the present invention.
Legend description:
1. a data analysis unit; 101. a data receiving module; 102. a data cleaning module; 103. a data arrangement module; 104. a data analysis module; 105. a Vue. Js framework module; 106. an ECharts visualization module; 107. a SpringBoot frame module; 2. a data acquisition unit; 201. a sensor signal acquisition module; 202. a signal conditioning module; 203. an A/D conversion module; 204. ARM processors; 205. a man-machine interaction module; 3. a data storage unit; 301. a data interface module; 302. a data service module; 3021. a storage management sub-module; 3022. a data parallel storage sub-module; 3023. a data parallel query sub-module; 3024. a data dictionary sub-module; 3025. the data backup is carried out on an atomic module; 303. a database service module; 4. a data management module unit; 5. and a data acquisition unit.
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. 1-4, the present invention provides a technical solution: the data processing system of the Internet big data comprises a data analysis unit 1, wherein the input end of the data analysis unit 1 is electrically connected with the output end of a data acquisition unit 2, the output end of the data analysis unit 1 is electrically connected with the input end of a data management module unit 4, the output end of the data management module unit 4 is electrically connected with the input end of a data storage unit 3, the data storage unit 3 is bidirectionally connected with the data analysis unit 1, and the output end of the data analysis unit 1 is electrically connected with the input end of a data acquisition unit 5;
the data acquisition unit 2 is used for acquiring various control signals of industrial equipment, obtaining industrial big data, and transmitting the obtained industrial big data to the data analysis unit 1 and the data storage unit 3;
the data management module unit 4 is used for carrying out industrial big data processing information interaction and transmitting industrial big data analysis results;
a data acquisition unit 5 for matching the industrial big data to obtain effective industrial data;
the data analysis unit 1 sequentially receives, cleans, sorts and analyzes industrial big data and stores the data into a MySQL database.
Specifically, the data acquisition unit 2 includes a sensor signal acquisition module 201, an output end of the sensor signal acquisition module 201 is electrically connected with an input end of the signal conditioning module 202, an output end of the signal conditioning module 202 is electrically connected with an input end of the a/D conversion module 203, an output end of the a/D conversion module 203 is electrically connected with an input end of the ARM processor 204, and an output end of the ARM processor 204 is electrically connected with an input end of the man-machine interaction module 205.
Specifically, the sensor signal acquisition module 201 is configured to acquire various industrial control signals, and the signal conditioning module 202 is configured to receive various industrial control signals sent by the sensor signal acquisition module 201, and condition the received industrial control signals, where the conditioning content of the industrial control signals includes isolation, amplification and filtering.
Specifically, the data storage unit 3 includes a data interface module 301, an output end of the data interface module 301 is electrically connected to an input end of the data service module 302, and an output end of the data service module 302 is electrically connected to an input end of the database service module 303.
Specifically, the data service module 302 includes a storage management submodule 3021, an output end of the storage management submodule 3021 is electrically connected with an input end of the data parallel storage submodule 3022, an output end of the data parallel storage submodule 3022 is electrically connected with an input end of the data parallel query submodule 3023, an output end of the data parallel query submodule 3023 is electrically connected with an input end of the data dictionary submodule 3024, and an output end of the data dictionary submodule 3024 is electrically connected with an input end of the data backup reduction submodule 3025.
Specifically, the data interface module 301 is configured to receive industrial big data obtained by the data acquisition unit 2.
Specifically, the storage management sub-module 3021 is configured to perform distributed management on devices in the storage system, perform balanced allocation on a storage process and a performance load of the storage devices, the data parallel storage sub-module 3022 is configured to implement loading, analysis processing and storage of industrial big data, the data parallel query sub-module 3023 is configured to perform parallel query processing of data, the data dictionary sub-module 3024 is configured to establish a data dictionary in the storage system, maintain various metadata in the data system, and the data backup atomic module 3025 is configured to perform backup storage and restore on data in the storage system.
Specifically, the data analysis unit 1 includes a data receiving module 101, an output end of the data receiving module 101 is electrically connected with an input end of the data cleaning module 102, an output end of the data cleaning module 102 is electrically connected with an input end of the data sorting module 103, an output end of the data sorting module 103 is electrically connected with an output end of the data analysis module 104, and an output end of the data analysis module 104 is electrically connected with input ends of the ECharts visualization module 106, the Vue. Js frame module 105 and the SpringBoot frame module respectively.
Specifically, the SpringBoot framework module carries Java to realize the function of a data interface.
A data processing method of Internet big data comprises the following steps:
the sensor signal acquisition module 201 acquires various industrial control signals, the signal conditioning module 202 receives various industrial control signals sent by the sensor signal acquisition module 201 and conditions the received industrial control signals, and the industrial control signal conditioning content comprises isolation, amplification and filtering;
the storage management submodule 3021 is used for carrying out distributed management on equipment in a storage system, carrying out balanced allocation on the storage process and the performance load of the storage equipment, the data parallel storage submodule 3022 is used for realizing loading, analysis processing and storage of industrial big data, the data parallel query submodule 3023 is used for carrying out parallel query processing of data, the data dictionary submodule 3024 is used for establishing a data dictionary in the storage system, maintaining various metadata in the data system, and the data backup atomic module 3025 is used for carrying out backup storage and restoration on the data in the storage system;
carrying out industrial big data processing information interaction and transmitting industrial big data analysis results;
the industrial big data is matched to obtain valid industrial data.
Working principle, when in use:
the sensor signal acquisition module 201 acquires various industrial control signals, the signal conditioning module 202 receives various industrial control signals sent by the sensor signal acquisition module 201 and conditions the received industrial control signals, the industrial control signal conditioning content comprises isolation, amplification and filtering, and the ARM processor 204 is provided with a Linux operating system, so that the acquisition of industrial control data has high precision and good anti-interference capability, and the performance is convenient to improve and the connection of the peripheral man-machine interaction module 205 is convenient;
the storage management submodule 3021 is used for carrying out distributed management on equipment in a storage system, carrying out balanced allocation on the storage process and the performance load of the storage equipment, the data parallel storage submodule 3022 is used for realizing loading, analysis processing and storage of industrial big data, the data parallel query submodule 3023 is used for carrying out parallel query processing of data, the data dictionary submodule 3024 is used for establishing a data dictionary in the storage system, maintaining various metadata in the data system, and the data backup atomic module 3025 is used for carrying out backup storage and restoration on the data in the storage system;
the industrial big data storage system comprises three module access layers, namely a data interface module 301, a data service module 302 and a database service module 303, and the storage and access efficiency of the industrial big data can be effectively improved by using a cluster technology, a storage technology and a distributed parallel data processing technology, so that the safe and stable storage of the mass data is ensured;
after industrial big data are sequentially received, cleaned, arranged and analyzed, the data are stored in a MySQL database, a Vue.js frame module 105 is adopted at the front end, an ECharts visualization module 106 is adopted at the rear end, a front-rear end separation development technology is realized, development efficiency is improved, and more effective data presentation service can be provided for users;
carrying out industrial big data processing information interaction and transmitting industrial big data analysis results;
the industrial big data is matched to obtain valid industrial data.
The present invention is not limited to the above-mentioned embodiments, and any person skilled in the art, based on the technical solution of the present invention and the inventive concept thereof, can be replaced or changed within the scope of the present invention.
Claims (10)
1. The data processing system of the Internet big data comprises a data analysis unit (1), and is characterized in that the input end of the data analysis unit (1) is electrically connected with the output end of a data acquisition unit (2), the output end of the data analysis unit (1) is electrically connected with the input end of a data management module unit (4), the output end of the data management module unit (4) is electrically connected with the input end of a data storage unit (3), the data storage unit (3) is in bidirectional connection with the data analysis unit (1), and the output end of the data analysis unit (1) is electrically connected with the input end of a data acquisition unit (5);
the data acquisition unit (2) is used for acquiring various control signals of industrial equipment, obtaining industrial big data, and transmitting the obtained industrial big data to the data analysis unit (1) and the data storage unit (3);
the data management module unit (4) is used for carrying out industrial big data processing information interaction and transmitting the industrial big data analysis result;
a data acquisition unit (5) for matching industrial big data to obtain effective industrial data;
and the data analysis unit (1) is used for sequentially receiving, cleaning, sorting and analyzing the industrial big data and then storing the data into the MySQL database.
2. The internet big data processing system according to claim 1, wherein the data acquisition unit (2) comprises a sensor signal acquisition module (201), an output end of the sensor signal acquisition module (201) is electrically connected with an input end of a signal conditioning module (202), an output end of the signal conditioning module (202) is electrically connected with an input end of an a/D conversion module (203), an output end of the a/D conversion module (203) is electrically connected with an input end of an ARM processor (204), and an output end of the ARM processor (204) is electrically connected with an input end of a human-computer interaction module (205).
3. The internet big data processing system according to claim 2, wherein the sensor signal acquisition module (201) is configured to acquire a plurality of industrial control signals, and the signal conditioning module (202) is configured to receive the plurality of industrial control signals sent by the sensor signal acquisition module (201) and condition the received industrial control signals, and the industrial control signal conditioning content includes isolation, amplification and filtering.
4. The internet big data processing system according to claim 1, wherein the data storage unit (3) comprises a data interface module (301), an output end of the data interface module (301) is electrically connected to an input end of a data service module (302), and an output end of the data service module (302) is electrically connected to an input end of a database service module (303).
5. The internet big data processing system according to claim 4, wherein the data service module (302) includes a storage management sub-module (3021), an output end of the storage management sub-module (3021) is electrically connected to an input end of the data parallel storage sub-module (3022), an output end of the data parallel storage sub-module (3022) is electrically connected to an input end of the data parallel query sub-module (3023), an output end of the data parallel query sub-module (3023) is electrically connected to an input end of the data dictionary sub-module (3024), and an output end of the data dictionary sub-module (3024) is electrically connected to an input end of the data backup atomic module (3025).
6. The internet big data processing system according to claim 5, wherein the data interface module (301) is configured to receive the industrial big data obtained by the data acquisition unit (2).
7. The internet big data processing system according to claim 6, wherein the storage management sub-module (3021) is configured to perform distributed management on devices in the storage system, perform balanced allocation on storage processes and performance loads of the storage devices, the data parallel storage sub-module (3022) is configured to implement loading, analysis processing and storage of industrial big data, the data parallel query sub-module (3023) is configured to perform parallel query processing of data, the data dictionary sub-module (3024) is configured to establish a data dictionary in the storage system, perform maintenance on various metadata in the data system, and the data backup further atomic module (3025) is configured to perform backup storage and restoration on data in the storage system.
8. The internet big data processing system according to claim 1, wherein the data analysis unit (1) comprises a data receiving module (101), an output end of the data receiving module (101) is electrically connected with an input end of a data cleaning module (102), an output end of the data cleaning module (102) is electrically connected with an input end of a data sorting module (103), an output end of the data sorting module (103) is electrically connected with an output end of a data analysis module (104), and an output end of the data analysis module (104) is electrically connected with input ends of an echartits visualization module (106), a vue.js frame module (105) and a SpringBoot frame module respectively.
9. The internet big data processing system of claim 8, wherein the SpringBoot framework module carries Java to implement a data interface function.
10. A data processing method of internet big data according to any of claims 1 to 9, comprising:
the sensor signal acquisition module (201) acquires various industrial control signals, the signal conditioning module (202) receives various industrial control signals sent by the sensor signal acquisition module (201) and conditions the received industrial control signals, and the industrial control signal conditioning content comprises isolation, amplification and filtering;
the method comprises the steps that industrial big data obtained by a data acquisition unit (2) are received, a storage management sub-module (3021) is used for carrying out distributed management on equipment in a storage system, balancing and allocating storage processes and performance loads of the storage equipment, a data parallel storage sub-module (3022) is used for realizing loading, analysis processing and storage of the industrial big data, a data parallel query sub-module (3023) is used for carrying out parallel query processing of the data, a data dictionary sub-module (3024) is used for establishing a data dictionary in the storage system, maintaining various metadata in the data system, and a data backup and restore sub-module (3025) is used for carrying out backup storage and restoration on the data in the storage system;
performing industrial big data processing information interaction and transmitting an industrial big data analysis result;
the industrial big data is matched to obtain valid industrial data.
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| CN114416855A (en) * | 2021-12-14 | 2022-04-29 | 国网河北省电力有限公司经济技术研究院 | Visualization platform and method based on electric power big data |
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