CN117631598B - Data acquisition system based on 5G network - Google Patents
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Abstract
The invention discloses a data acquisition system based on a 5G network, which relates to the technical field of data acquisition and processing, and comprises: based on data source acquisition demand characteristic information, configuring data acquisition parameter information, performing channel deployment on a data source end based on the data acquisition parameter information by utilizing a 5G network technology, establishing data acquisition multi-channels to respectively perform industrial data acquisition on the data source end, and further performing branch preprocessing on the acquired multi-channel industrial data stream set through the data acquisition multi-channels to obtain a multi-channel standard industrial data stream set; and distributing network resource slices for data acquisition and multichannel distribution, and integrally transmitting a multichannel standard industrial data stream set to an industrial data cloud for labeling storage processing. The method achieves the technical effects of realizing personalized data acquisition multichannel deployment through data source acquisition demand analysis, improving real-time acquisition and transmission efficiency of a large amount of data by utilizing 5G network characteristics, and further ensuring data acquisition accuracy and safety.
Description
Technical Field
The invention relates to the technical field of data acquisition and processing, in particular to a data acquisition system based on a 5G network.
Background
With the rapid development of technologies such as the internet of things, big data, artificial intelligence and the like, data acquisition has become an important requirement for various industries. Real-time monitoring and control of the industrial production process can be realized through data real-time acquisition, so that abnormal conditions can be found in time and corresponding measures can be taken, and further the industrial production efficiency is improved. However, the existing data acquisition method generally depends on a wired network or a low-speed wireless network, so that real-time transmission of a large amount of data is difficult to meet, and the transmission efficiency is low. With the development of 5G networks, support technology is provided for solving the problem.
Disclosure of Invention
The utility model provides a data acquisition system based on 5G network has solved prior art data acquisition and has be difficult to satisfy the real-time transmission of a large amount of data, and the lower technical problem of transmission efficiency, reaches and realizes individualized data acquisition multichannel branch preliminary treatment through data source acquisition demand analysis, utilizes 5G network slice transmission to improve a large amount of data and gathers transmission efficiency in real time simultaneously, and then ensures the technical effect of data acquisition accuracy and security.
In view of the above problems, the present invention provides a data acquisition system based on a 5G network.
In a first aspect, the present application provides a data acquisition method based on a 5G network, where the method is applied to a data acquisition system based on a 5G network, and the method includes: a data acquisition device with a 5G interface is configured at a data source end, and then data acquisition demand analysis is carried out on the data acquisition device to acquire data source acquisition demand characteristic information; based on the data source acquisition demand characteristic information, configuring data acquisition parameter information; carrying out acquisition channel deployment on the data source end based on the data acquisition parameter information by using a 5G network technology, and establishing a data acquisition multi-channel; respectively carrying out industrial data acquisition on the data source end based on the data acquisition multi-channel to acquire a multi-channel industrial data stream set; branching pretreatment is carried out on the multi-channel industrial data stream set through the data acquisition multi-channel to obtain a multi-channel standard industrial data stream set; and distributing network resource slices for the data acquisition multichannel, and integrally transmitting the multichannel standard industrial data stream set to an industrial data cloud for labeling storage processing through the network resource slices.
In another aspect, the present application further provides a data acquisition system based on a 5G network, where the system includes: the data acquisition demand analysis module is used for configuring data acquisition equipment with a 5G interface at a data source end, and then carrying out data acquisition demand analysis on the data acquisition equipment to acquire data source acquisition demand characteristic information; the data acquisition parameter configuration module is used for configuring data acquisition parameter information based on the data source acquisition demand characteristic information; the acquisition channel deployment module is used for deploying the acquisition channels of the data source end based on the data acquisition parameter information by using a 5G network technology, and establishing a data acquisition multi-channel; the industrial data acquisition module is used for respectively carrying out industrial data acquisition on the data source end based on the data acquisition multiple channels to acquire a multiple-channel industrial data stream set; the branch preprocessing module is used for carrying out branch preprocessing on the multi-channel industrial data stream set through the data acquisition multi-channel to obtain a multi-channel standard industrial data stream set; and the labeling storage processing module is used for distributing network resource slices for the data acquisition multichannel, and integrating and transmitting the multichannel standard industrial data stream set to an industrial data cloud for labeling storage processing through the network resource slices.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
the method comprises the steps of configuring data acquisition equipment with a 5G interface at a data source end, analyzing data acquisition requirements of the data acquisition equipment, acquiring data acquisition parameter information of data source acquisition requirement characteristic information configuration data, deploying acquisition channels of the data source end based on the data acquisition parameter information by utilizing a 5G network technology, establishing data acquisition multiple channels to acquire industrial data of the data source end respectively, and acquiring a multiple-channel industrial data stream set; and carrying out branch pretreatment on the multi-channel industrial data stream set through the data acquisition multi-channel to obtain a multi-channel standard industrial data stream set, distributing network resource slices for the data acquisition multi-channel, and further integrally transmitting the multi-channel standard industrial data stream set to an industrial data cloud for carrying out the technical scheme of labeling storage treatment through the network resource slices. And further, personalized data acquisition multichannel branch preprocessing is realized through data source acquisition demand analysis, and meanwhile, the 5G network slice transmission is utilized to improve the real-time acquisition transmission efficiency of a large amount of data, so that the technical effects of data acquisition accuracy and safety are ensured.
The foregoing description is only an overview of the technical solutions of the present application, and may be implemented according to the content of the specification in order to make the technical means of the present application more clearly understood, and in order to make the above-mentioned and other objects, features and advantages of the present application more clearly understood, the following detailed description of the present application will be given.
Drawings
Fig. 1 is a flow chart of a data collection method based on a 5G network according to the present application;
fig. 2 is a schematic flow chart of configuring data acquisition parameter information in a data acquisition method based on a 5G network;
fig. 3 is a schematic structural diagram of a data acquisition system based on a 5G network according to the present application;
reference numerals illustrate: the system comprises a data acquisition demand analysis module 11, a data acquisition parameter configuration module 12, an acquisition channel deployment module 13, an industrial data acquisition module 14, a branch preprocessing module 15 and a labeling storage processing module 16.
Detailed Description
The utility model provides a data acquisition system based on 5G network has solved prior art data acquisition and has been difficult to satisfy the real-time transmission of a large amount of data, and the lower technical problem of transmission efficiency, reaches and realizes individualized data acquisition multichannel branch preliminary treatment through data source acquisition demand analysis, utilizes 5G network slice transmission to improve a large amount of data real-time acquisition transmission efficiency simultaneously, and then ensures the technical effect of data acquisition accuracy and security.
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
Example 1
As shown in fig. 1, the present application provides a data acquisition method based on a 5G network, where the method is applied to a data acquisition system based on a 5G network, and the method includes:
step S1: a data acquisition device with a 5G interface is configured at a data source end, and then data acquisition demand analysis is carried out on the data acquisition device to acquire data source acquisition demand characteristic information;
specifically, in order to realize efficient collection of industrial data in large quantities by using the 5G technology, a data collection device with a 5G interface, for example, a data collection device such as a 5G industrial gateway or a 5G CPE, is configured at an industrial data source end. And then carrying out data acquisition demand analysis on the data acquisition equipment, and acquiring corresponding data source acquisition demand characteristic information through carrying out acquisition sensor analysis on a data source end connected with the data acquisition equipment, wherein the data source acquisition demand characteristic information comprises data source acquisition types, data source acquisition amounts and the like, so that the demand basis is provided for improving the subsequent data acquisition multichannel parameter configuration, and the acquisition parameter configuration accuracy is improved.
Step S2: based on the data source acquisition demand characteristic information, configuring data acquisition parameter information;
as shown in fig. 2, further, the configuration data collects parameter information, and the steps of the application further include:
acquiring a data acquisition rule, wherein the data acquisition rule comprises a data attribute acquisition rule and a data sensitivity acquisition rule;
constructing an attribute feature classifier through the data attribute collection rule, wherein the attribute feature classifier comprises a data collection type, a data collection amount and a data collection format;
classifying and identifying the data source acquisition demand characteristic information according to the attribute characteristic classifier to obtain data acquisition attribute information;
performing sensitivity grading on the data source acquisition demand characteristic information based on the data sensitivity acquisition rule, and determining data acquisition sensitivity grade information;
and carrying out acquisition parameter configuration based on the data acquisition attribute information and the data acquisition sensitivity level information, and determining the data acquisition parameter information.
Specifically, data acquisition parameters are configured based on the data source acquisition demand characteristic information, and firstly, an acquisition data acquisition rule is formulated, wherein the data acquisition rule is a data acquisition parameter configuration basis and comprises a data attribute acquisition rule and a data sensitivity acquisition rule. The data attribute collection rule is a basis rule for data collection according to data attributes, an attribute feature classifier is constructed through the data attribute collection rule, the attribute feature classifier is a model for classification according to data attribute feature classification indexes, and the data attribute feature classification indexes comprise data collection types, namely industrial data types, such as temperature data, pressure data, electric power data and the like; the data acquisition amount is the industrial data generation acquisition amount; and data acquisition formats, i.e., industrial data generation formats, such as text formats, image formats, JSON formats, and the like. And classifying and identifying the data source acquisition demand characteristic information of the data source end according to the attribute characteristic classifier to obtain the data acquisition attribute information after classification marking.
And carrying out sensitivity grading on the data source acquisition demand characteristic information based on the data sensitivity acquisition rule, wherein the data sensitivity acquisition rule is a basis rule for carrying out data acquisition according to data sensitivity, sensitive data is data which possibly causes serious harm to society or individuals after leakage, the data sensitivity grading standard is determined by the actual industrial data acquisition standard, and further the data source acquisition demand characteristic information is subjected to sensitivity grading according to the data sensitivity grading standard, the corresponding data acquisition sensitivity grading information is obtained through matching, and the higher the data privacy degree is, the higher the corresponding sensitivity grade is. And carrying out acquisition parameter configuration based on the data acquisition attribute information and the data acquisition sensitivity level information, wherein each data source end is provided with a data acquisition channel, and determining data acquisition parameter information corresponding to each data acquisition channel, wherein the data acquisition parameter information is specific acquisition parameter information of the data acquisition channel and comprises sampling rate, sampling storage format, encrypted sampling parameters and the like. The personalized data acquisition multichannel parameter configuration is realized through data source acquisition demand analysis, the applicability of data acquisition parameters is improved, and further, the efficient real-time acquisition of a large amount of data is ensured.
Step S3: carrying out acquisition channel deployment on the data source end based on the data acquisition parameter information by using a 5G network technology, and establishing a data acquisition multi-channel;
step S4: respectively carrying out industrial data acquisition on the data source end based on the data acquisition multi-channel to acquire a multi-channel industrial data stream set;
specifically, by using the MIMO technology in the 5G network technology, a plurality of acquisition channels are deployed at the data source based on the data acquisition parameter information, and each data source corresponds to one acquisition channel, so as to establish a data acquisition multi-channel for implementing parallel data acquisition of the data source. And respectively carrying out industrial data acquisition on the data source end based on the data acquisition multiple channels, and simultaneously acquiring corresponding multiple-channel industrial data stream sets, so that real-time parallel acquisition of data is realized, and the data acquisition efficiency is improved.
Step S5: branching pretreatment is carried out on the multi-channel industrial data stream set through the data acquisition multi-channel to obtain a multi-channel standard industrial data stream set;
further, the step of obtaining the multi-channel standard industrial data stream set further includes:
performing data preprocessing association extraction based on the data attribute acquisition rule and the data sensitivity acquisition rule to generate a data attribute preprocessing program and a sensitive data preprocessing program;
respectively carrying out matching mapping on the data acquisition parameter information, the data attribute preprocessing program and the sensitive data preprocessing program to obtain a multichannel associated preprocessing program set;
loading and configuring the data acquisition multichannel based on the multichannel associated preprocessing program set, and determining multichannel data preprocessing node information;
and synchronously preprocessing the multi-channel industrial data stream set based on the multi-channel data preprocessing node information to obtain the multi-channel standard industrial data stream set.
Specifically, in order to realize the standardization of the acquired data, the multi-channel industrial data stream set is subjected to branch preprocessing through the data acquisition multi-channel. Firstly, carrying out data preprocessing association extraction based on the data attribute acquisition rule and the data sensitivity acquisition rule, namely respectively carrying out association step extraction of data preprocessing according to the data attribute type and the data sensitivity level, and generating a corresponding data attribute preprocessing program, wherein the data attribute preprocessing program is a preprocessing step of each data attribute type and comprises data cleaning, normalization and the like, the preprocessing steps corresponding to different data attribute types are different, and the association preprocessing step is determined according to the industrial data attribute preprocessing requirement; and the sensitive data preprocessing program is a preprocessing step of industrial data with different sensitive grades, and comprises data cleaning, protocol, encryption desensitization and the like, wherein the preprocessing steps corresponding to the data with different sensitive grades are different, and the related preprocessing step is determined according to the preprocessing requirement of the industrial sensitive data.
And respectively carrying out matching mapping on the data acquisition parameter information, the data attribute preprocessing program and the sensitive data preprocessing program, namely respectively carrying out association matching on acquisition parameters of all data acquisition channels and data preprocessing steps to obtain corresponding multi-channel association preprocessing program sets, wherein the multi-channel association preprocessing program sets are the data attribute preprocessing steps and the sensitive data preprocessing steps matched with all the data acquisition channels. And loading and configuring the data acquisition multichannel based on the multichannel associated preprocessing program set, and determining multichannel data preprocessing node information, wherein the multichannel data preprocessing node information is a preprocessing step execution node of the data acquisition channel. And synchronously preprocessing the multi-channel industrial data stream set based on the multi-channel data preprocessing node information to obtain a multi-channel standard industrial data stream set after parallel preprocessing. The personalized branch preprocessing of the data acquisition multi-channel is realized, the preprocessing efficiency of industrial data is improved, and the standardization and the applicability of the acquired data are further ensured.
Step S6: and distributing network resource slices for the data acquisition multichannel, and integrally transmitting the multichannel standard industrial data stream set to an industrial data cloud for labeling storage processing through the network resource slices.
Further, the allocating network resource slices for the data acquisition multi-channel further includes:
performing task transmission characteristic identification on the data acquisition multi-channel to acquire acquisition channel transmission characteristic information, wherein the acquisition channel transmission characteristic information comprises task transmission quantity, task encryption transmission and task transmission timeliness;
constructing a network resource load balancing model, and performing resource allocation on the 5G network transmission resources and the acquisition channel transmission characteristic information based on the network resource load balancing model to acquire network resource balance allocation information;
and carrying out network transmission parameter configuration based on the network resource balanced allocation information, and cutting to obtain the network resource slice.
Furthermore, the integrated data is transmitted to the industrial data cloud for labeling storage processing, and the steps of the application further include:
performing label traversal extraction on the data description information of the multi-channel standard industrial data stream set to obtain industrial data description label information;
generating a data tag coding rule according to the industrial data description tag information, wherein the data tag coding rule comprises coding marks and coding sequences;
encoding the industrial data description tag information based on the data tag encoding rule to construct a stored data tag dictionary;
and carrying out tagged compression storage on the multi-channel standard industrial data stream set based on the stored data tag dictionary.
Specifically, an independent network slice is allocated to each data acquisition channel by using a slicing technology of a 5G network, so that the data transmission of each acquisition channel is ensured not to interfere with each other, and the real-time transmission of the data is realized. The method comprises the steps of firstly, respectively carrying out task transmission characteristic identification on a data acquisition multi-channel through data acquisition parameter information and industrial data application requirements of the data acquisition channel to obtain corresponding acquisition channel transmission characteristic information, wherein the acquisition channel transmission characteristic information is transmission task characteristics of the data acquisition channel and comprises task transmission quantity, task encryption transmission and task transmission timeliness. And then transmitting resource allocation information and corresponding transmission record information of historical acquisition data through a historical network, wherein the transmission record information comprises transmission task characteristic data and transmission effect data, and training and constructing a network resource load balancing model which is a neural network model and is used for carrying out on-demand balanced allocation on network transmission resources so as to ensure that the acquired data transmission meets the application requirements of industrial data.
And carrying out resource allocation on the 5G network transmission resources and the acquisition channel transmission characteristic information based on the network resource load balancing model, wherein the 5G network transmission resources are applicable resource information of the industrial data transmission 5G network, and comprise spectrum resources, power resources, time resources and the like, and outputting and acquiring network resource balanced allocation information, and the network resource balanced allocation information is the network transmission resource information allocated according to the acquisition channel characteristic. And carrying out network transmission parameter configuration based on the network resource balance allocation information, namely carrying out corresponding transmission parameter setting according to the network transmission resource allocation information, wherein the transmission parameters comprise transmission rate, transmission delay, spectrum efficiency and the like, and dividing the 5G network transmission resource into a plurality of virtual network slices through the transmission parameter configuration, namely obtaining the network resource slices so as to ensure the real-time and reliable transmission of the data acquisition channel. The requirement of different acquisition channels on network transmission quality is met by distributing independent 5G network slices, network transmission resource distribution is optimized, real-time acquisition and transmission efficiency of a large amount of data is improved, and data acquisition accuracy and safety are further ensured.
The multi-channel standard industrial data stream set is integrally transmitted to an industrial data cloud for labeling storage processing through the network resource slice, wherein the industrial data cloud is a data processing end for processing and analyzing acquired data by utilizing a cloud computing technology, and the multi-channel standard industrial data stream set has the advantages of being rich in computing resources and high in processing efficiency. The specific storage processing process firstly carries out label traversal extraction on the data description information of the multi-channel standard industrial data stream set, namely, carries out labeling on the attribute information of each acquisition channel data stream, including description such as data acquisition attribute, sensitivity attribute and the like, so as to obtain industrial data description label information, wherein the industrial data description label information is an attribute description label of industrial acquisition data, for example, the data label is numerical format, low sensitivity and electric power type data.
Because the industrial data collection amount is large, the attribute description part occupies a large memory besides the data value. Generating a data tag coding rule corresponding to the description tag type according to the industrial data description tag information, wherein the data tag coding rule is used for rapidly coding each data description tag and comprises coding marks, namely, coding marks such as letters, numbers and the like of each description tag; and the coding sequence, namely the sequence before and after each description label codes the identification, can set the coding rule according to the industrial practical application. And sequentially encoding the industrial data description tag information based on the data tag encoding rule, and performing tag encoding on all industrial data descriptions to obtain a stored data tag dictionary, wherein the stored data tag dictionary is a tag query basis of industrial data storage, so that attribute information of the data description can be queried succinctly and rapidly. And further, based on the stored data tag dictionary, the multi-channel standard industrial data stream set is subjected to tagged compression storage, and the industrial data attribute description part is subjected to tagged compression, so that the occupied space of data storage is reduced. The method realizes the compression storage of the data in the tagging mode, reduces the redundancy of stored data and the cost of storage space, and further improves the industrial data processing efficiency.
Further, the steps of the present application further include:
performing transmission network resource evaluation on the network resource slice, and determining preset multichannel data transmission parameters;
respectively acquiring data transmission time of the acquisition multi-channel through data transmission monitoring of the data acquisition multi-channel;
taking the difference value between the acquired multi-channel data transmission time and the preset multi-channel data transmission parameter as a data timeout delay coefficient;
and activating a channel expansion instruction, and performing expansion allocation on the network resource slice based on the channel expansion instruction and the data timeout delay coefficient.
Specifically, when the multi-channel standard industrial data stream set is transmitted in an integrated manner, in order to ensure the data transmission quality, the data transmission condition needs to be controlled in real time. Firstly, carrying out transmission network resource evaluation on the network resource slices, and evaluating corresponding preset transmission time parameters of each data acquisition channel on the allocated network resource slices so as to determine preset multi-channel data transmission parameters, wherein the preset multi-channel data transmission parameters are preset transmission time of data quantity of each data acquisition channel. Meanwhile, data transmission monitoring is carried out on the data acquisition multiple channels, acquisition multiple channel data transmission time corresponding to each data acquisition channel is respectively obtained, and the difference value between the acquisition multiple channel data transmission time and the preset multiple channel data transmission parameters is used as a data timeout delay coefficient, wherein the larger the data timeout delay coefficient is, the slower the data transmission rate is indicated.
Because the data acquisition channel has data transmission delay, a channel expansion instruction is activated, and the network resource slice is subjected to expansion allocation based on the channel expansion instruction and the data timeout delay coefficient so as to avoid the data transmission delay. The network slice can be transmitted and expanded in three modes of enhancement, expansion and special use, such as means of increasing network resources, upgrading network equipment and the like, more nodes and equipment are added on a transmission path of the network slice, the transmission capacity and performance of the network slice are improved, the coverage area of the network slice is enlarged, the influence of data timeout delay is removed, the transmission efficiency and quality are improved, and further the data transmission is ensured to meet application requirements.
Further, the steps of the present application further include:
performing interaction authority analysis on the data acquisition multi-channel based on the data acquisition parameter information to form a data channel interaction authority cooperation network;
performing extensible flow direction identification according to the data channel interaction authority collaboration network, and determining extensible data channel information;
based on the data timeout delay coefficient, carrying out transmission cooperative allocation on the expandable data channel information to obtain a network transmission resource cooperative allocation task;
and carrying out cooperative expansion transmission on the network resource slices based on the network transmission resource cooperative allocation task.
Specifically, when the transmission delay occurs in the data, the network resource slice is expanded, and the cooperative transmission can be performed through other transmission channels. The method specifically comprises the steps of firstly carrying out interaction permission analysis on the data acquisition multi-channel based on the data acquisition parameter information, namely marking the data interactable permission of each channel according to the data acquisition channel attribute, and enabling the data of a lower-level type to flow to a data channel of a higher-level type in an interaction manner and enabling the data of a non-sensitive type to flow to a data channel of a sensitive type in an interaction manner. The data channel interaction authority cooperation network is formed by marking the interaction authority of the actual application information of the industrial acquisition data, and is used for visually and intuitively displaying the data interaction relation among the data acquisition channels.
And carrying out extensible flow direction identification on the channel with the transmission delay according to the data channel interaction authority cooperation network, namely determining the interactive flow direction channel of the delay channel to obtain corresponding extensible data channel information for carrying out data interaction cooperation transmission on the delay channel. And carrying out transmission cooperation distribution on the expandable data channel information based on the data timeout delay coefficient, namely carrying out cooperation task quantity distribution on each cooperative transmission channel according to the data transmission timeout delay degree, wherein the larger the allowance transmission resources of the cooperative transmission channels are, the larger the distributed cooperation task quantity is correspondingly, so as to obtain the network transmission resource cooperation distribution tasks corresponding to each cooperative transmission channel. And carrying out cooperative expansion transmission on the network resource slices based on the network transmission resource cooperative allocation task, avoiding the condition of overtime delay of data transmission, improving the channel transmission efficiency and the transmission utilization rate, and further ensuring that the data transmission meets the application requirements.
In summary, the data acquisition system based on the 5G network provided by the present application has the following technical effects:
the method comprises the steps of configuring data acquisition equipment with a 5G interface at a data source end, analyzing data acquisition requirements of the data acquisition equipment, acquiring data acquisition parameter information of data source acquisition requirement characteristic information configuration data, deploying acquisition channels of the data source end based on the data acquisition parameter information by utilizing a 5G network technology, establishing data acquisition multiple channels to acquire industrial data of the data source end respectively, and acquiring a multiple-channel industrial data stream set; and carrying out branch pretreatment on the multi-channel industrial data stream set through the data acquisition multi-channel to obtain a multi-channel standard industrial data stream set, distributing network resource slices for the data acquisition multi-channel, and further integrally transmitting the multi-channel standard industrial data stream set to an industrial data cloud for carrying out the technical scheme of labeling storage treatment through the network resource slices. And further, personalized data acquisition multichannel branch preprocessing is realized through data source acquisition demand analysis, and meanwhile, the 5G network slice transmission is utilized to improve the real-time acquisition transmission efficiency of a large amount of data, so that the technical effects of data acquisition accuracy and safety are ensured.
Example two
Based on the same inventive concept as the data acquisition method based on the 5G network in the foregoing embodiment, the present invention further provides a data acquisition system based on the 5G network, as shown in fig. 3, where the system includes:
the data acquisition demand analysis module 11 is configured to configure a data acquisition device with a 5G interface at a data source end, and then perform data acquisition demand analysis on the data acquisition device to acquire data source acquisition demand characteristic information;
a data acquisition parameter configuration module 12, configured to configure data acquisition parameter information based on the data source acquisition requirement characteristic information;
the acquisition channel deployment module 13 is used for deploying the acquisition channels of the data source end based on the data acquisition parameter information by utilizing a 5G network technology, and establishing a data acquisition multi-channel;
an industrial data acquisition module 14, configured to acquire a multi-channel industrial data stream set by respectively performing industrial data acquisition on the data source ends based on the data acquisition multiple channels;
the branch preprocessing module 15 is configured to perform branch preprocessing on the multi-channel industrial data stream set through the data acquisition multi-channel to obtain a multi-channel standard industrial data stream set;
and the labeling storage processing module 16 is used for distributing network resource slices for the data acquisition multichannel, and integrally transmitting the multichannel standard industrial data stream set to an industrial data cloud for labeling storage processing through the network resource slices.
Further, the system further comprises:
the data acquisition rule acquisition unit is used for acquiring data acquisition rules, wherein the data acquisition rules comprise data attribute acquisition rules and data sensitivity acquisition rules;
the characteristic classifier construction unit is used for constructing an attribute characteristic classifier according to the data attribute acquisition rule, wherein the attribute characteristic classifier comprises a data acquisition type, a data acquisition amount and a data acquisition format;
the characteristic classification identification unit is used for classifying and identifying the data source acquisition demand characteristic information according to the attribute characteristic classifier to obtain data acquisition attribute information;
the sensitivity rating unit is used for carrying out sensitivity rating on the data source acquisition demand characteristic information based on the data sensitivity acquisition rule and determining data acquisition sensitivity rating information;
and the acquisition parameter configuration unit is used for carrying out acquisition parameter configuration based on the data acquisition attribute information and the data acquisition sensitivity level information and determining the data acquisition parameter information.
Further, the system further comprises:
the preprocessing association extraction unit is used for carrying out data preprocessing association extraction based on the data attribute acquisition rule and the data sensitivity acquisition rule to generate a data attribute preprocessing program and a sensitive data preprocessing program;
the program matching mapping unit is used for respectively matching and mapping the data acquisition parameter information with the data attribute preprocessing program and the sensitive data preprocessing program to obtain a multichannel associated preprocessing program set;
the channel loading configuration unit is used for loading and configuring the data acquisition multichannel based on the multichannel associated preprocessing program set and determining multichannel data preprocessing node information;
and the synchronous preprocessing unit is used for synchronously preprocessing the multi-channel industrial data stream set based on the multi-channel data preprocessing node information to obtain the multi-channel standard industrial data stream set.
Further, the system further comprises:
the channel transmission characteristic acquisition unit is used for carrying out task transmission characteristic identification on the data acquisition multi-channel to acquire acquisition channel transmission characteristic information, wherein the acquisition channel transmission characteristic information comprises task transmission quantity, task encryption transmission and task transmission timeliness;
the transmission resource allocation unit is used for constructing a network resource load balancing model, and carrying out resource allocation on the 5G network transmission resources and the acquisition channel transmission characteristic information based on the network resource load balancing model to acquire network resource balance allocation information;
and the transmission parameter configuration unit is used for carrying out network transmission parameter configuration based on the network resource balanced allocation information and obtaining the network resource slice by segmentation.
Further, the system further comprises:
the network resource evaluation unit is used for carrying out transmission network resource evaluation on the network resource slices and determining preset multichannel data transmission parameters;
the data transmission monitoring unit is used for respectively acquiring the data transmission time of the acquisition multichannel by carrying out data transmission monitoring on the data acquisition multichannel;
the overtime delay coefficient obtaining unit is used for taking the difference value between the acquired multi-channel data transmission time and the preset multi-channel data transmission parameter as a data overtime delay coefficient;
and the slice expansion allocation unit is used for activating a channel expansion instruction and performing expansion allocation on the network resource slice based on the channel expansion instruction and the data timeout delay coefficient.
Further, the system further comprises:
the interaction right analysis unit is used for carrying out interaction right analysis on the data acquisition multi-channel based on the data acquisition parameter information to form a data channel interaction right cooperation network;
the expandable flow direction identification unit is used for carrying out expandable flow direction identification according to the data channel interaction authority cooperation network and determining expandable data channel information;
the transmission cooperation distribution unit is used for carrying out transmission cooperation distribution on the expandable data channel information based on the data timeout delay coefficient to obtain a network transmission resource cooperation distribution task;
and the cooperative expansion transmission unit is used for carrying out cooperative expansion transmission on the network resource slice based on the network transmission resource cooperative allocation task.
Further, the system further comprises:
the label traversing and extracting unit is used for carrying out label traversing and extracting on the data description information of the multi-channel standard industrial data stream set to obtain industrial data description label information;
the tag coding rule generating unit is used for generating a data tag coding rule according to the industrial data description tag information, wherein the data tag coding rule comprises coding marks and coding sequences;
the data tag dictionary construction unit is used for encoding the industrial data description tag information based on the data tag encoding rule to construct a stored data tag dictionary;
and the labeling compression storage unit is used for labeling compression storage of the multi-channel standard industrial data stream set based on the stored data label dictionary.
The foregoing various modifications and specific examples of a 5G network-based data acquisition method in the first embodiment of fig. 1 are equally applicable to a 5G network-based data acquisition system of this embodiment, and those skilled in the art will be aware of the foregoing detailed description of a 5G network-based data acquisition method in this embodiment, so that the detailed description of the implementation of the 5G network-based data acquisition system will not be repeated herein for brevity.
The foregoing is merely a specific embodiment of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think about changes or substitutions within the technical scope of the present application, and the changes and substitutions are intended to be covered in the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (7)
1. A 5G network-based data acquisition system, the system comprising:
the data acquisition demand analysis module is used for configuring data acquisition equipment with a 5G interface at a data source end, and then carrying out data acquisition demand analysis on the data acquisition equipment to acquire data source acquisition demand characteristic information;
the data acquisition parameter configuration module is used for configuring data acquisition parameter information based on the data source acquisition demand characteristic information;
the acquisition channel deployment module is used for deploying the acquisition channels of the data source end based on the data acquisition parameter information by using a 5G network technology, and establishing a data acquisition multi-channel;
the industrial data acquisition module is used for respectively carrying out industrial data acquisition on the data source end based on the data acquisition multiple channels to acquire a multiple-channel industrial data stream set;
the branch preprocessing module is used for carrying out branch preprocessing on the multi-channel industrial data stream set through the data acquisition multi-channel to obtain a multi-channel standard industrial data stream set;
the labeling storage processing module is used for distributing network resource slices for the data acquisition multi-channel, and integrating and transmitting the multi-channel standard industrial data stream set to an industrial data cloud for labeling storage processing through the network resource slices;
wherein, the data acquisition parameter configuration module further includes:
the data acquisition rule acquisition unit is used for acquiring data acquisition rules, wherein the data acquisition rules comprise data attribute acquisition rules and data sensitivity acquisition rules;
the characteristic classifier construction unit is used for constructing an attribute characteristic classifier according to the data attribute acquisition rule, wherein the attribute characteristic classifier comprises a data acquisition type, a data acquisition amount and a data acquisition format;
the characteristic classification identification unit is used for classifying and identifying the data source acquisition demand characteristic information according to the attribute characteristic classifier to obtain data acquisition attribute information;
the sensitivity rating unit is used for carrying out sensitivity rating on the data source acquisition demand characteristic information based on the data sensitivity acquisition rule and determining data acquisition sensitivity rating information;
and the acquisition parameter configuration unit is used for carrying out acquisition parameter configuration based on the data acquisition attribute information and the data acquisition sensitivity level information and determining the data acquisition parameter information.
2. The system of claim 1, wherein the finger preprocessing module further comprises:
the preprocessing association extraction unit is used for carrying out data preprocessing association extraction based on the data attribute acquisition rule and the data sensitivity acquisition rule to generate a data attribute preprocessing program and a sensitive data preprocessing program;
the program matching mapping unit is used for respectively matching and mapping the data acquisition parameter information with the data attribute preprocessing program and the sensitive data preprocessing program to obtain a multichannel associated preprocessing program set;
the channel loading configuration unit is used for loading and configuring the data acquisition multichannel based on the multichannel associated preprocessing program set and determining multichannel data preprocessing node information;
and the synchronous preprocessing unit is used for synchronously preprocessing the multi-channel industrial data stream set based on the multi-channel data preprocessing node information to obtain the multi-channel standard industrial data stream set.
3. The system of claim 1, wherein the tagged storage processing module further comprises:
the channel transmission characteristic acquisition unit is used for carrying out task transmission characteristic identification on the data acquisition multi-channel to acquire acquisition channel transmission characteristic information, wherein the acquisition channel transmission characteristic information comprises task transmission quantity, task encryption transmission and task transmission timeliness;
the transmission resource allocation unit is used for constructing a network resource load balancing model, and carrying out resource allocation on the 5G network transmission resources and the acquisition channel transmission characteristic information based on the network resource load balancing model to acquire network resource balance allocation information;
and the transmission parameter configuration unit is used for carrying out network transmission parameter configuration based on the network resource balanced allocation information and obtaining the network resource slice by segmentation.
4. The system of claim 1, wherein the system comprises:
the network resource evaluation unit is used for carrying out transmission network resource evaluation on the network resource slices and determining preset multichannel data transmission parameters;
the data transmission monitoring unit is used for respectively acquiring the data transmission time of the acquisition multichannel by carrying out data transmission monitoring on the data acquisition multichannel;
the overtime delay coefficient obtaining unit is used for taking the difference value between the acquired multi-channel data transmission time and the preset multi-channel data transmission parameter as a data overtime delay coefficient;
and the slice expansion allocation unit is used for activating a channel expansion instruction and performing expansion allocation on the network resource slice based on the channel expansion instruction and the data timeout delay coefficient.
5. The system of claim 4, wherein the system comprises:
the interaction right analysis unit is used for carrying out interaction right analysis on the data acquisition multi-channel based on the data acquisition parameter information to form a data channel interaction right cooperation network;
the expandable flow direction identification unit is used for carrying out expandable flow direction identification according to the data channel interaction authority cooperation network and determining expandable data channel information;
the transmission cooperation distribution unit is used for carrying out transmission cooperation distribution on the expandable data channel information based on the data timeout delay coefficient to obtain a network transmission resource cooperation distribution task;
and the cooperative expansion transmission unit is used for carrying out cooperative expansion transmission on the network resource slice based on the network transmission resource cooperative allocation task.
6. The system of claim 1, wherein the tagged storage processing module further comprises:
the label traversing and extracting unit is used for carrying out label traversing and extracting on the data description information of the multi-channel standard industrial data stream set to obtain industrial data description label information;
the tag coding rule generating unit is used for generating a data tag coding rule according to the industrial data description tag information, wherein the data tag coding rule comprises coding marks and coding sequences;
the data tag dictionary construction unit is used for encoding the industrial data description tag information based on the data tag encoding rule to construct a stored data tag dictionary;
and the labeling compression storage unit is used for labeling compression storage of the multi-channel standard industrial data stream set based on the stored data label dictionary.
7. A data acquisition method based on a 5G network, the method being applied to a data acquisition system based on a 5G network according to any one of claims 1 to 6, the method comprising:
a data acquisition device with a 5G interface is configured at a data source end, and then data acquisition demand analysis is carried out on the data acquisition device to acquire data source acquisition demand characteristic information;
based on the data source acquisition demand characteristic information, configuring data acquisition parameter information;
carrying out acquisition channel deployment on the data source end based on the data acquisition parameter information by using a 5G network technology, and establishing a data acquisition multi-channel;
respectively carrying out industrial data acquisition on the data source end based on the data acquisition multi-channel to acquire a multi-channel industrial data stream set;
branching pretreatment is carried out on the multi-channel industrial data stream set through the data acquisition multi-channel to obtain a multi-channel standard industrial data stream set;
distributing network resource slices for the data acquisition multichannel, and integrally transmitting the multichannel standard industrial data stream set to an industrial data cloud for labeling storage processing through the network resource slices;
the configuration data acquisition parameter information further includes:
acquiring a data acquisition rule, wherein the data acquisition rule comprises a data attribute acquisition rule and a data sensitivity acquisition rule;
constructing an attribute feature classifier through the data attribute collection rule, wherein the attribute feature classifier comprises a data collection type, a data collection amount and a data collection format;
classifying and identifying the data source acquisition demand characteristic information according to the attribute characteristic classifier to obtain data acquisition attribute information;
performing sensitivity grading on the data source acquisition demand characteristic information based on the data sensitivity acquisition rule, and determining data acquisition sensitivity grade information;
and carrying out acquisition parameter configuration based on the data acquisition attribute information and the data acquisition sensitivity level information, and determining the data acquisition parameter information.
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