Industrial internet data service processing system based on multi-dimensional data

Abstract

The invention discloses an industrial internet data service processing system based on multi-dimensional data, which belongs to the technical field of industrial internet data service processing and comprises an application analysis module, a data acquisition module, a transmission control module and a storage management module. The application analysis module performs demand analysis on each upper-layer application to obtain each demand data type corresponding to each upper-layer application and a demand emergency value corresponding to each demand data type; the data acquisition module is used for acquiring multi-dimensional data in real time to obtain corresponding network monitoring data and storage monitoring data; the transmission control module is used for transmission control; identifying each data type corresponding to the multi-dimensional data, and performing association analysis on each data type to form an association chain of each data type; evaluating each data type association chain to obtain a transmission sequence corresponding to each data type association chain; determining transmission data according to the network monitoring data and the transmission sequence; transmitting the transmission data; and the storage management module is used for data storage management.

Description

Technical Field

[0001] The present invention belongs to the technical field of industrial Internet data service processing, and specifically is an industrial Internet data service processing system based on multi-dimensional data. Background Art

[0002] With the rapid development of industrial Internet technology, enterprises have an increasing demand for the collection, processing and analysis of industrial data. As a key bridge connecting industrial sites and upper-level applications, the industrial Internet data service processing system undertakes multiple tasks such as data collection, storage, processing, analysis and transmission. However, the existing industrial Internet data service processing system still has many problems and challenges when processing multi-dimensional data.

[0003] For example, the existing system has deficiencies in data collection. Due to the complex and changeable environment of the Industrial Internet, there are many types of data sources, including sensor data, equipment status data, operation data, etc., and these data often have the characteristics of heterogeneity, real-time and massive. Traditional data collection methods often find it difficult to meet these requirements, resulting in low data collection efficiency and low data quality. Moreover, the existing system also has deficiencies in data services. Since the Industrial Internet data service processing system needs to provide real-time, accurate and reliable data support for upper-level applications, the performance and stability of data services are crucial. However, the existing data service processing system often cannot meet these requirements, resulting in the upper-level applications being unable to obtain the required data in a timely manner, which in turn affects the production efficiency and decision-making accuracy of the enterprise.

[0004] In response to the above problems, the present invention proposes an industrial Internet data service processing system based on multi-dimensional data. Summary of the invention

[0005] In order to solve the problems existing in the above-mentioned solutions, the present invention provides an industrial Internet data service processing system based on multi-dimensional data.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] An industrial Internet data service processing system based on multi-dimensional data, including an application analysis module, a data acquisition module, a transmission control module and a storage management module;

[0008] The application analysis module performs demand analysis on each upper-layer application to obtain each demand data type corresponding to each upper-layer application and a demand urgency value corresponding to each demand data type.

[0009] Furthermore, the method of performing demand analysis on each upper-layer application includes:

[0010] Acquire historical application data of each upper layer application, and determine the types of required data corresponding to each upper layer application according to each of the historical application data;

[0011] Establishing a usage detail database, wherein the usage detail database is used to store each application usage corresponding to each upper-layer application and usage feature collection items corresponding to each application usage;

[0012] According to the usage details library, the current application usage of each upper-layer application and the usage feature collection items corresponding to each application usage are identified in real time, and data is collected according to each usage feature collection item to obtain usage emergency analysis data of each application usage;

[0013] An emergency analysis model is established, and the use emergency analysis data of corresponding application uses are analyzed by the emergency analysis model to obtain the demand emergency value of each demand data type.

[0014] Furthermore, the method for establishing the usage details library includes:

[0015] Obtain each application purpose of each upper-layer application; set corresponding purpose feature collection items according to each application purpose; integrate each application purpose and each purpose feature collection item to establish a purpose detail library.

[0016] The data acquisition module is used to collect multi-dimensional data in real time, and monitor the network load status and local data storage status in real time, and obtain corresponding network monitoring data and store monitoring data.

[0017] The transmission control module is used to perform transmission control based on the collected multi-dimensional data, network monitoring data and storage monitoring data;

[0018] Identify each data type corresponding to the multidimensional data, perform association analysis on each data type, and form association chains of each data type; evaluate each data type association chain, and obtain a transmission order corresponding to each data type association chain;

[0019] Determine the transmission data according to the network monitoring data and the transmission order; and transmit the transmission data.

[0020] Furthermore, the method of performing association analysis on each data type includes:

[0021] The historical application data of each upper layer application is obtained, and each combination data is determined according to each historical application data; each data type association chain is set according to each combination data, and a corresponding application usage label is marked for each data type association chain.

[0022] Furthermore, the method for evaluating the association chain of each data type includes:

[0023] Acquire the demand data types of each upper layer application and the demand urgency value corresponding to each demand data type in real time; mark the corresponding demand urgency representative value for each data type in the data type association chain;

[0024] Sort the demand urgency representative values ​​in the data type association chain from high to low to obtain a first sequence, and mark the demand urgency representative values ​​as XDv according to the first sequence, where v is the sequence of the corresponding demand urgency representative value in the first sequence, and v=1, 2, ..., z, where z is a positive integer;

[0025] According to the formula Calculate the transmission value of the association chain of each data type;

[0026] Where: PB is the transmission value; XDv is the corresponding demand emergency representative value; v = 1, 2, ..., z, z is a positive integer; e is a natural constant;

[0027] The corresponding transmission order is determined according to the transmission value corresponding to the association chain of each data type.

[0028] Furthermore, the method of marking a corresponding demand urgency representative value for each data type in the data type association chain includes:

[0029] Identify the demand data type corresponding to each data type in the data type association chain, and identify each demand urgency value corresponding to the data type;

[0030] Determine the weight index corresponding to each of the demand urgency values, and obtain the weight value of each of the weight indexes; mark the weight index as i, i=1, 2, ..., n, n is a positive integer; mark the weight value as δi;

[0031] According to the formula Calculate the weight coefficient of each demand urgency value;

[0032] Where: β is the weight coefficient;

[0033] Each demand urgency value is marked as XQj, j = 1, 2, ..., m, m is a positive integer; the corresponding weight coefficient is marked as βj;

[0034] According to the formula Calculate the demand urgency representative value of each data type;

[0035] Where: XD is the representative value of demand urgency;

[0036] When the data type has no corresponding demand data type, a preset emergency value corresponding to the data type is obtained; and the preset emergency value is marked as a demand emergency representative value of the data type.

[0037] Further, when determining the transmission data, identifying each data type association chain that the transmission data does not correspond to; identifying the transmission value corresponding to each data type association chain;

[0038] Mark the data type association chain whose transmission value is greater than the threshold value X1 as a target to be adjusted; determine the adjustment data to be transmitted according to the target to be adjusted;

[0039] Transmission adjustment is performed according to the adjusted data to be transmitted, new transmission data is obtained, and the transmission data is transmitted.

[0040] The storage management module is used to perform data storage management, receive transmission data in real time, and perform data management according to a preset data management method and storage monitoring data.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] Through the cooperation among application analysis module, data acquisition module, transmission control module and storage management module, the comprehensive, efficient and accurate processing of multi-dimensional data in the industrial Internet is realized, and standard and reliable data services are provided for upper-layer applications; the problems existing in the existing technology are solved, and the data acquisition efficiency, data processing capability and data service quality are improved; BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0044] Figure 1 This is a principle block diagram of the present invention. DETAILED DESCRIPTION

[0045] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] like Figure 1 As shown, the industrial Internet data service processing system based on multi-dimensional data includes an application analysis module, a data acquisition module, a transmission control module, and a storage management module;

[0047] The application analysis module is used to analyze the upper-layer applications served by the industrial Internet data service processing system, determine the demand data types of each upper-layer application and the demand urgency value corresponding to each demand data type.

[0048] The upper layer application is a relative concept, which is relative to the underlying system or platform. The underlying system may include infrastructure such as operating system, database, network communication protocol, etc., while the upper layer application is the specific application or service built on top of these infrastructures. These upper layer applications can be user-oriented desktop applications, mobile applications, web applications, or business logic-oriented backend services, middleware, etc.

[0049] The type of required data is determined based on the actual data required by the corresponding upper-layer application.

[0050] The demand urgency value is the urgency of the upper-layer application's demand for the corresponding demand data type under the current circumstances; the demand urgency value ranges from [0, 100], and the higher the demand urgency value, the more urgent the demand for the data type.

[0051] In one embodiment, an emergency status assessment may be performed based on existing methods to obtain a corresponding demand emergency value.

[0052] In one embodiment, the method for evaluating the demand urgency value is:

[0053] Obtain each application purpose of each upper-layer application, that is, the working purpose of the upper-layer application; set corresponding use feature collection items according to each application purpose, for collecting corresponding data in the demand emergency of the application purpose; the above steps can be set manually; integrate each application purpose and each use feature collection item to establish a use detail library;

[0054] According to the usage details library, the current application usage of each upper-layer application and the usage feature collection items corresponding to each application usage are identified in real time, and data is collected according to the usage feature collection items to obtain the usage emergency analysis data of each application usage;

[0055] Establish an emergency analysis model. In one embodiment, a large amount of historical use emergency analysis data can be analyzed, and the demand emergency values ​​corresponding to each demand data type under each use emergency analysis data of different application uses can be preset, and then matching calculations can be performed in combination with interpolation. In other embodiments, emergency analysis models can also be established based on other existing technologies, such as establishing emergency analysis models based on neural networks such as CNN networks or DNN networks, and establishing corresponding training sets manually. The training sets include input data and output data, and the input data are application uses and use emergency analysis data; the output data are demand emergency values ​​of corresponding demand data types; and analysis is performed after successful training.

[0056] The use emergency analysis data of the corresponding application purposes are analyzed through the emergency analysis model to obtain the demand emergency value of each demand data type.

[0057] The data acquisition module is used to collect multi-dimensional data in real time in the industrial Internet environment through various sensors, smart terminals and other devices; at the same time, it continuously monitors the network load status and local data storage status, including key indicators such as network bandwidth usage, data storage capacity, data reading and writing speed, and obtains corresponding network monitoring data and storage monitoring data.

[0058] The transmission control module is used to perform transmission control based on the collected multi-dimensional data, network monitoring data and storage monitoring data, and obtain the types of demand data of each upper-layer application and the corresponding demand urgency value in real time;

[0059] Identify the data types corresponding to the multidimensional data, perform association analysis on the data types, and form association chains of the data types; evaluate the association chains of the data types, and obtain the transmission order corresponding to the association chains of the data types;

[0060] The amount of data that can be transmitted is determined based on network monitoring data, and the transmission data is determined in combination with the multi-dimensional data amount corresponding to the association chain of each data type corresponding to the transmission order; and the transmission data is transmitted.

[0061] In one embodiment, the method for performing association analysis on each data type includes:

[0062] Obtain the historical application data of each upper-level application, and determine the various combinations of data that the upper-level application needs to apply when performing data analysis based on each historical application data. That is, in order to achieve a certain analysis goal, a combination of required data types is required. If a single required data type can be used as all the analysis materials for a certain goal, it can be used as combined data alone. Set up association chains for each data type based on each combined data to indicate the association between each data type, and mark each data type association chain with a corresponding application usage label, that is, to which application usage the target to be analyzed belongs.

[0063] In one embodiment, the method for evaluating the association chain of each data type includes:

[0064] Obtain the demand data types of each upper-layer application and the demand urgency values ​​corresponding to each demand data type in real time; mark the corresponding demand urgency representative value for each data type in the data type association chain;

[0065] Sort the demand urgency representative values ​​in the data type association chain from high to low to obtain a first sequence, and mark the demand urgency representative values ​​as XDv according to the first sequence, where v is the sequence of the corresponding demand urgency representative value in the first sequence, and v=1, 2, ..., z, where z is a positive integer;

[0066] According to the formula Calculate the transmission value of the association chain of each data type;

[0067] Where: PB is the transmission value; XDv is the corresponding demand emergency representative value; v = 1, 2, ..., z, z is a positive integer; e is a natural constant;

[0068] The corresponding transmission order is determined according to the transmission value corresponding to the association chain of each data type.

[0069] The method of marking the corresponding demand urgency representative value for each data type in the data type association chain includes:

[0070] Identify the demand data types corresponding to each data type in the data type association chain, and identify each demand urgency value corresponding to the data type, because the urgency demand values ​​of the same demand data type in different upper layer applications may not be the same, because a data type can have multiple demand urgency values;

[0071] According to user needs, a corresponding weight value is set for each upper layer application or application purpose, and the upper layer application or application purpose based on it is marked as a weight index, and the weight value is the weight value of the corresponding weight index; the weight index is marked as i, i = 1, 2, ..., n, n is a positive integer; the weight value is marked as δi;

[0072] According to the formula Calculate the weight coefficient of each demand urgency value;

[0073] Each demand urgency value is marked as XQj, j = 1, 2, ..., m, m is a positive integer; the corresponding weight coefficient is marked as βj;

[0074] According to the formula Calculate the demand urgency representative value of each data type;

[0075] Where: XD is the representative value of demand urgency;

[0076] When a data type does not have a corresponding demand data type, that is, there is no corresponding demand urgency value, its demand urgency value is set to a default value, such as 0, 10, etc. The specific default value is set according to user needs and the importance of the corresponding data type, and the corresponding default value is marked as a preset urgency value; the preset urgency value is marked as a demand urgency representative value.

[0077] In one embodiment, in actual applications, there is a situation where the transmitted data cannot meet the application requirements, that is, the data that should be transmitted in time according to the emergency situation cannot be transmitted in time; in view of this situation, this embodiment is proposed to identify the association chains of various data types not included in the transmitted data, and identify the transmission values ​​corresponding to the association chains of the corresponding data types;

[0078] Mark the data type association chain whose transmission value is greater than the threshold value X1 as the target to be adjusted; determine the adjustment data to be transmitted according to the multidimensional data corresponding to each target to be adjusted;

[0079] Transmission adjustment is performed according to the adjusted data to be transmitted, so that the transmission adjustment data is merged into the transmission data for transmission, such as performing flow adjustment, data compression and other existing methods to enable the combined transmission data to be transmitted.

[0080] The storage management module is used to perform data storage management. Before transmitting data to the storage management module, it identifies the storage space required for the transmitted data, and then performs corresponding storage management in advance, such as data compression, deletion of useless elements, etc., to avoid storage failure, and adjusts the data format, consistency, etc. at the same time; obtains the corresponding storage status according to the storage monitoring data; and is specifically based on the existing storage management method; that is, the received transmission data is managed according to the preset data management method.

[0081] The above formulas are all calculated by removing dimensions and taking numerical values. The formula is a formula that is closest to the actual situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained by simulating a large amount of data.

[0082] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An industrial Internet data service processing system based on multidimensional data, characterized in that: It includes application analysis module, data acquisition module, transmission control module and storage management module; The application analysis module performs demand analysis on each upper layer application to obtain each demand data type corresponding to each upper layer application and a demand urgency value corresponding to each demand data type; The data acquisition module is used to collect multi-dimensional data in real time, and monitor the network load status and local data storage status in real time, and obtain corresponding network monitoring data and store monitoring data; The transmission control module is used to perform transmission control based on the collected multi-dimensional data, network monitoring data and storage monitoring data; Identify each data type corresponding to the multidimensional data, perform association analysis on each data type, and form association chains of each data type; evaluate each data type association chain, and obtain a transmission order corresponding to each data type association chain; Determine transmission data according to network monitoring data and transmission order; transmit the transmission data; The storage management module is used to perform data storage management, receive transmission data in real time, and perform data management according to a preset data management method and store monitoring data.

2. The industrial Internet data service processing system based on multidimensional data according to claim 1 is characterized in that: Methods for demand analysis of upper-layer applications include: Acquire historical application data of each upper layer application, and determine the types of required data corresponding to each upper layer application according to each of the historical application data; Establishing a usage detail database, wherein the usage detail database is used to store each application usage corresponding to each upper-layer application and usage feature collection items corresponding to each application usage; According to the usage details library, the current application usage of each upper-layer application and the usage feature collection items corresponding to each application usage are identified in real time, and data is collected according to each usage feature collection item to obtain usage emergency analysis data of each application usage; An emergency analysis model is established, and the use emergency analysis data of corresponding application uses are analyzed by the emergency analysis model to obtain the demand emergency value of each demand data type.

3. The industrial Internet data service processing system based on multidimensional data according to claim 2 is characterized in that: The methods for establishing a usage details library include: Obtain each application purpose of each upper-layer application; set corresponding purpose feature collection items according to each application purpose; integrate each application purpose and each purpose feature collection item to establish a purpose detail library.

4. The industrial Internet data service processing system based on multidimensional data according to claim 1 is characterized in that: Methods for correlation analysis of various data types include: The historical application data of each upper layer application is obtained, and each combination data is determined according to each historical application data; each data type association chain is set according to each combination data, and a corresponding application usage label is marked for each data type association chain.

5. The industrial Internet data service processing system based on multidimensional data according to claim 4 is characterized in that: Methods for evaluating the association chain of each data type include: Acquire the demand data types of each upper layer application and the demand urgency value corresponding to each demand data type in real time; mark the corresponding demand urgency representative value for each data type in the data type association chain; Sort the urgency representative values ​​of each demand in the data type association chain in descending order to obtain a first sequence; Mark each demand urgency representative value as XDv according to the first sequence, where v is the order of the corresponding demand urgency representative value in the first sequence, v=1, 2, ..., z, and z is a positive integer; According to the formula Calculate the transmission value of the association chain of each data type; Where: PB is the transmission value; XDv is the corresponding demand emergency representative value; v = 1, 2, ..., z, z is a positive integer; e is a natural constant; The corresponding transmission order is determined according to the transmission value corresponding to the association chain of each data type.

6. The industrial Internet data service processing system based on multidimensional data according to claim 5 is characterized in that: The method of marking the corresponding demand urgency representative value for each data type in the data type association chain includes: Identify the demand data type corresponding to each data type in the data type association chain, and identify each demand urgency value corresponding to the data type; Determine the weight index corresponding to each of the demand urgency values, and obtain the weight value of each of the weight indexes; mark the weight index as i, i=1, 2, ..., n, n is a positive integer; mark the weight value as δi; According to the formula Calculate the weight coefficient of each demand urgency value; Where: β is the weight coefficient; Each demand urgency value is marked as XQj, j = 1, 2, ..., m, m is a positive integer; the corresponding weight coefficient is marked as βj; According to the formula Calculate the demand urgency representative value of each data type; Where: XD is the representative value of demand urgency; When the data type has no corresponding demand data type, a preset emergency value corresponding to the data type is obtained; and the preset emergency value is marked as a demand emergency representative value of the data type.

7. The industrial Internet data service processing system based on multidimensional data according to claim 5 is characterized in that: When determining the transmission data, identifying each data type association chain that the transmission data does not correspond to; identifying the transmission value corresponding to each data type association chain; Mark the data type association chain whose transmission value is greater than the threshold value X1 as a target to be adjusted; determine the adjustment data to be transmitted according to the target to be adjusted; Transmission adjustment is performed according to the adjusted data to be transmitted, new transmission data is obtained, and the transmission data is transmitted.

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