A digital information transmission shared operation and maintenance platform based on AI technology

Abstract

The present invention discloses a digital information transmission shared operation and maintenance platform based on AI technology, which relates to the field of digital information transmission technology. The components of the platform include: a data acquisition module, an AI intelligent analysis module, a spectrum dynamic allocation module, a data classification and transmission optimization module, and a storage adaptation module. The present invention optimizes the spectrum resource utilization efficiency and transmission stability. Through AI real-time spectrum perception and dynamic frequency allocation technology, the platform can accurately grasp the spectrum usage status in real time. When facing a complex and changeable wireless environment, the platform can quickly identify idle spectrum and dynamically allocate optimal frequencies for different services to avoid spectrum congestion and interference. This not only ensures the smoothness of bandwidth and delay sensitive services, but also reduces the risk of transmission interruption.

Description

Technical Field

[0001] The present invention relates to the field of digital information transmission technology, and in particular to a digital information transmission shared operation and maintenance platform based on AI technology. Background Art

[0002] With the rapid development of information technology, digital information transmission has become an indispensable part. From personal communication to enterprise-level data transmission, the demand for digital information transmission is growing, which puts higher requirements on transmission efficiency, reliability and security. Especially in the field of wireless communications, the limited spectrum resources have become a key factor restricting the speed and capacity of information transmission.

[0003] However, in the existing digital information transmission sharing operation and maintenance platform, in terms of spectrum allocation, traditional solutions mostly adopt a fixed frequency allocation mode. Whether it is the base station coverage network in the city or the wireless access in remote areas, fixed frequency bands are pre-set for different services to use. This leads to the inability to flexibly adjust spectrum resources in the face of complex and changeable wireless environments in actual operation, such as sudden signal interference and sharp changes in bandwidth requirements of different services during peak traffic periods. The spectrum utilization rate is low, interference occurs frequently, and the transmission stability and efficiency are seriously affected. In terms of data storage and transmission priority processing, existing solutions often lack sophisticated intelligent distinction. When a large amount of data pours in, the timeliness and importance of the data are not distinguished, resulting in delays in the transmission of key business data and missing the best processing opportunity. At the same time, the storage resource allocation is unreasonable, and the precious high-speed storage medium is occupied by low-value data, resulting in a waste of storage costs and obstruction of the overall information flow.

[0004] In summary, the existing digital information transmission sharing operation and maintenance methods are insufficient in spectrum resource management and data transmission optimization. Therefore, there is an urgent need for a digital information transmission sharing operation and maintenance platform based on AI technology to meet the transmission needs of massive digital information. Summary of the invention

[0005] The purpose of the present invention is to make up for the shortcomings of the existing technology and provide a digital information transmission shared operation and maintenance platform based on AI technology. It can perform spectrum perception and dynamic frequency allocation in real time through AI technology. In wireless transmission scenarios, it can monitor spectrum usage in real time and accurately identify idle spectrum resources. When there is a new data transmission demand, it can quickly and dynamically allocate the optimal frequency for it, avoiding spectrum congestion and interference caused by fixed frequency allocation, and adapting to complex and changeable wireless communication environments.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a digital information transmission sharing operation and maintenance platform based on AI technology, the components of which include: a data acquisition module, an AI intelligent analysis module, a spectrum dynamic allocation module, a data classification and transmission optimization module, and a storage adaptation module;

[0007] The data acquisition module collects raw data at the starting end of the digital information transmission link, wherein the raw data includes raw information of the wireless spectrum, data flow size, and data source identification, and transmits the collected raw data to the AI ​​intelligent analysis module in real time;

[0008] The AI ​​intelligent analysis module receives the raw data from the data acquisition module and analyzes the data, including:

[0009] On the one hand, the spectrum data in the original wireless spectrum information is identified by the spectrum recognition algorithm. Identify idle spectrum resources and accurately quantify idle spectrum conditions, including: Indicates the comprehensive value of the availability of idle spectrum resources. To monitor the number of subdivisions in the frequency band, It is the frequency band The power spectral density of It is the frequency band The bandwidth factor, It is the frequency band Interference degree coefficient, the coefficient range is 0-1, 0 means no interference, 1 means complete interference;

[0010] On the other hand, based on the data flow and source information, the timeliness and importance of the data are comprehensively judged, and the data is classified according to the importance. The classification adopts the data classification algorithm: ,in, Indicates the importance level of the data. is the timeliness weight of the data, is the weight of the data source, is the frequency of data operations, is the data transmission cycle;

[0011] Output the spectrum analysis results to the spectrum dynamic allocation module, and output the data classification judgment results to the data classification and transmission optimization module and the storage adaptation module;

[0012] The spectrum dynamic allocation module uses the intelligent optimization algorithm to quickly formulate the optimal spectrum allocation strategy based on the spectrum analysis results output by the AI ​​intelligent analysis module and the real-time load and signal strength of the current network;

[0013] After receiving the data classification judgment result of the AI ​​intelligent analysis module and the spectrum usage information of the spectrum dynamic allocation module, the data classification and transmission optimization module adopts differentiated transmission strategies for data of different levels;

[0014] The storage adaptation module performs intelligent storage arrangement for the data that has completed transmission according to the transmission status fed back by the data classification and transmission optimization module and in combination with the data classification situation.

[0015] Furthermore, in the process of analyzing the data, the AI ​​intelligent analysis module divides the data into urgent, important and temporary data according to the importance level of the data, where:

[0016] When G≥0.7, the data is judged as urgent and important data. In the transmission link, the optimal bandwidth resources are allocated first.

[0017] When 0.4≤G<0.7, the data is classified as important data, and its transmission efficiency is ensured while giving priority to emergency data transmission;

[0018] When G < 0.4, the data are classified as provisional data.

[0019] Furthermore, the spectrum allocation strategy of the spectrum dynamic allocation module performs spectrum allocation based on an intelligent optimization algorithm, that is, when a new data transmission task is initiated, the spectrum is allocated based on the real-time load of the current network. , signal strength , using intelligent optimization algorithms , immediately dynamically allocate the most suitable idle spectrum to it, and synchronize the spectrum usage to the data classification and transmission optimization module to ensure that wireless transmission avoids congested frequency bands. represents the optimal frequency of new transmission task allocation, is the current number of selectable frequencies, is the frequency The corresponding link load, It is the comprehensive value of the availability of idle spectrum resources.

[0020] Furthermore, when processing data flow information, the AI ​​intelligent analysis module introduces a flow trend prediction algorithm to accurately determine the timeliness of data. Based on historical flow data, the module uses a time series analysis method to Analyze the flow data at each moment and calculate the flow change trend coefficient ,in is the flow rate change, To predict the time span, , is the trend threshold, indicating that the traffic is in a rapid growth stage. At this time, combined with the business type, for business data with high timeliness requirements, its timeliness weight is increased in the data classification algorithm. ,Right now , The timeliness weight adjustment amount is increased according to the traffic trend so that this type of data can be transmitted first, ensuring the timeliness of key information. At the same time, it continues to self-optimize and continuously updates parameters as new data flows in to maintain the ability to capture traffic trends.

[0021] Furthermore, the platform also includes an operation and maintenance monitoring module, which collects operating status information of each module of the entire platform, including judging spectrum allocation, judging data transmission, and judging storage media. The operation and maintenance monitoring module records in detail the decision basis for each data, the transmission path selection process, and the specific values ​​of the spectrum allocation. By establishing data backtracking, when a problem occurs, the module where the problem occurs can be accurately located.

[0022] Furthermore, the differentiated transmission strategies of the data classification and transmission optimization module include:

[0023] For urgent and important data, we prioritize the allocation of optimal bandwidth resources and the planning of the shortest transmission path, and ensure that it is transmitted at the fastest speed based on spectrum allocation.

[0024] For temporary data, the transmission is flexibly arranged according to the network idle period, so as to achieve differentiated processing according to the characteristics of the data and ensure the overall data transmission and storage efficiency of the platform;

[0025] The transmission status of all data is fed back to the storage adapter module in real time to achieve efficient and orderly data transmission.

[0026] Furthermore, the intelligent storage arrangement of the storage adapter module includes:

[0027] For urgent and important data, multiple redundant backups are performed and stored in high-speed storage media;

[0028] Temporary data is stored in ordinary storage media;

[0029] After all data is stored, storage confirmation information is sent to the operation and maintenance platform.

[0030] Furthermore, when the storage adapter module performs intelligent storage arrangement, the storage management of urgent and important data is stored in the high-speed storage medium, and the storage management follows the data layout strategy, which utilizes the storage block size of the storage medium. , data file size , using data block storage ,in Indicates rounding up, dividing the data file into Blocks are stored, and adjacent blocks are separated by ,in is the check code length, The first Bytes, checksums are used to detect the integrity of data storage. Once an error is found, the data recovery program is immediately started to restore data from redundant backups; for temporary data, data cleanup is performed regularly ,in is the survival time of the data, is the current time, is the cleaning interval, when When the system is running, it cleans up expired data and releases storage space.

[0031] Compared with the existing technology, this digital information transmission shared operation and maintenance platform based on AI technology has the following beneficial effects:

[0032] 1. The present invention optimizes the utilization efficiency of spectrum resources and transmission stability. Through AI real-time spectrum perception and dynamic frequency allocation technology, the platform can accurately grasp the spectrum usage status in real time. When facing a complex and changeable wireless environment, the platform can quickly identify idle spectrum and dynamically allocate the optimal frequency for different services to avoid spectrum congestion and interference. This not only ensures the smoothness of bandwidth and delay-sensitive services, but also reduces the risk of transmission interruption.

[0033] 2. The present invention realizes the intelligent management of data storage and transmission, significantly improving the overall efficiency. With the help of the intelligent data hierarchical storage and transmission module, data is hierarchically processed according to its timeliness and importance. For urgent and important control instructions, it can give priority to ensuring that they are transmitted to the terminal at the fastest speed and optimal path, avoiding the risk of production stagnation due to transmission delays; for long-term and important operating history data, it is stored in reliable media to facilitate subsequent retrospective analysis. At the same time, temporary data storage and transmission are reasonably arranged to optimize storage costs and avoid waste of resources, so that data can be efficiently processed throughout its life cycle.

[0034] Other advantages, objectives and features of the present invention will be set forth in part in the following description and, in part, will be apparent to those skilled in the art based on an examination of the following or may be taught from the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] 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 prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0036] Figure 1 This is an operation flow chart of a digital information transmission shared operation and maintenance platform based on AI technology;

[0037] Figure 2 This is a block diagram of the components of a digital information transmission shared operation and maintenance platform based on AI technology. DETAILED DESCRIPTION

[0038] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation mode, structure, characteristics and effects of the present invention are described in detail below in combination with the accompanying drawings and preferred embodiments.

[0039] Embodiment 1

[0040] This embodiment is based on a digital information transmission sharing operation and maintenance platform based on AI technology, and elaborates on the composition of each module of the platform and the collaborative workflow in actual operation, such as Figure 2 The figure shows the module composition of the platform. The data acquisition module obtains raw data, the AI ​​intelligent analysis module performs in-depth analysis, and the spectrum dynamic allocation module, data classification and transmission optimization module, and storage adaptation module perform corresponding operations based on the analysis results to achieve efficient and stable transmission, storage and management of digital information.

[0041] The implementation process of the operation and maintenance platform provided in this embodiment is as follows: Figure 1 As shown, the data acquisition module is deployed at the starting end and key nodes of the digital information transmission link, equipped with electromagnetic sensors, flow monitors, and equipment identification readers. The electromagnetic sensors monitor the wireless spectrum environment in real time, collect original information such as electromagnetic signal strength and frequency distribution in different frequency bands, and provide a data basis for subsequent spectrum analysis; the flow monitor accurately counts the data flow through the node, captures the instantaneous changes and long-term trends of the flow, and the equipment identification reader obtains the relevant identification of the data source, such as the device number, the system to which it belongs, and other information. The collection work is continuous and uninterrupted, and various types of data are quickly collected at fixed time intervals. The collected data covers multiple dimensions such as wireless spectrum original information, data flow size, data source identification, etc., forming a collection of original data, and through high-speed data transmission channels, these original data are transmitted to the AI ​​intelligent analysis module in real time and accurately, providing timely and comprehensive data support for subsequent analysis and processing.

[0042] After receiving the raw data from the data acquisition module, the AI ​​intelligent analysis module starts the multi-dimensional analysis work and uses the spectrum recognition algorithm to analyze the spectrum data in the original wireless spectrum information. Accurately identify idle spectrum resources. In this algorithm, Represents the number of subdivisions of the monitoring frequency band. The monitoring frequency band can be finely divided into different numbers of sub-bands. For each subdivided frequency band , Indicates frequency band The power spectrum density reflects the signal power distribution per unit frequency in this frequency band; It is the frequency band The bandwidth factor reflects the relative size of the effective bandwidth that can be used for data transmission in this frequency band; It is the frequency band The interference degree coefficient ranges from 0 to 1, where 0 means no interference in the frequency band and 1 means complete interference. By calculating and summing the relevant parameters of each subdivided frequency band, the comprehensive value of the availability of idle spectrum resources is obtained. This value directly reflects the availability of the overall idle spectrum resources and provides a key reference for subsequent dynamic spectrum allocation. Then, based on the data flow and source information, a data classification algorithm is used. Comprehensively judge the timeliness and importance of data and classify them into urgent, important and temporary data. Represents the timeliness weight of the data, is the weight of the data source, Indicates the frequency of data operations. For data that is frequently read, written, or processed, the value is larger. It is the data transmission period, which is used to normalize the calculation results and ensure the importance level of the data. Within a reasonable range, this algorithm is used to assign a corresponding importance level value to each piece of data. When G≥0.7, the data is judged as urgent and important data. In the transmission link, the optimal bandwidth resources are allocated first. When 0.4≤G<0.7, the data is classified as important data. Under the premise of giving priority to emergency data transmission, its transmission efficiency is ensured. When G<0.4, the data is classified as temporary data. At the same time, in order to more accurately judge the timeliness of data, the AI ​​intelligent analysis module introduces a traffic trend prediction algorithm. Based on historical traffic data, the time series analysis method is used to predict the past Conduct in-depth analysis of traffic data at each moment and calculate the traffic change trend coefficient ,in, is the flow change at adjacent moments, is the number of historical moments used for analysis, is the forecast time span, when the calculated flow change trend coefficient Greater than a pre-set trend threshold When the traffic is in a rapid growth stage, the timeliness weight of the business data with high timeliness requirements is increased in the data classification algorithm according to the business type. ,Right now , In order to increase the timeliness weight adjustment amount according to the traffic trend, in this way, data with high timeliness requirements can obtain higher priority in data classification, so that it can be given priority in the subsequent transmission process. At the same time, the AI ​​intelligent analysis module continues to optimize itself. As new data continues to flow in, it automatically updates the various parameters in the algorithm to maintain the ability to accurately capture traffic trends. After completing the analysis, the AI ​​intelligent analysis module outputs the spectrum analysis results to the spectrum dynamic allocation module, and outputs the data importance level values ​​to the data classification and transmission optimization module and the storage adaptation module respectively, providing data support for the work of subsequent modules.

[0043] The spectrum dynamic allocation module receives the comprehensive value of the availability of idle spectrum resources output by the AI ​​intelligent analysis module Finally, combined with the real-time load of the current network , signal strength And other information, using intelligent optimization algorithm Formulate the optimal spectrum allocation strategy. In this algorithm, is the current number of selectable frequencies, is the frequency The corresponding link load reflects the busyness of the frequency in the current network environment. When a new data transmission task is initiated, the spectrum dynamic allocation module quickly calls this algorithm to conduct a comprehensive evaluation of each optional frequency and selects the one that can make the data transmission more efficient by comparing the calculation results of different frequencies. The frequency with the largest value is used as the optimal frequency for allocating new transmission tasks. After completing the frequency allocation, the spectrum dynamic allocation module synchronizes the spectrum usage to the data classification and transmission optimization module to ensure that the appropriate spectrum resources can be fully utilized during the data transmission process, effectively avoiding congested frequency bands, and ensuring the stability and efficiency of wireless transmission.

[0044] After receiving the data importance level value G from the AI ​​intelligent analysis module and the spectrum usage information from the spectrum dynamic allocation module, the data classification and transmission optimization module adopts a differentiated transmission strategy according to the importance level of the data. The differentiated transmission strategy is as follows: for data that is determined to be urgent and important, that is, data with an importance level value G greater than or equal to 0.7, the optimal bandwidth resources are allocated first, and the shortest transmission path is planned. When allocating bandwidth, the largest possible bandwidth share is allocated to such data from the network bandwidth resource pool to ensure that the data can be transmitted at the fastest speed. At the same time, combined with the spectrum usage information provided by the spectrum dynamic allocation module, the data with the best signal quality and the shortest transmission path are selected. The spectrum channel with the least interference is used for transmission, so as to ensure the timeliness and stability of data transmission to the greatest extent and avoid serious consequences caused by transmission delays; for important data, its importance level value G is between 0.4 and 0.7. Under the premise of giving priority to emergency data transmission, bandwidth resources are reasonably allocated for important data and the transmission path is optimized. By dynamically adjusting the transmission queue order, it is ensured that important data can be transmitted as soon as possible after the emergency data. At the same time, according to the real-time network load and spectrum usage status, the transmission parameters such as transmission rate and data packet size are flexibly adjusted to ensure the transmission efficiency of important data; for temporary data, its importance level value is between 0.4 and 0.7. Less than 0.4, the data classification and transmission optimization module flexibly arranges transmission according to the network idle period, and starts the temporary data transmission task when the network is found to be idle by real-time monitoring of the network load. This can not only make full use of the idle resources of the network, but also will not affect the transmission quality of urgent and important data due to the transmission of temporary data, so as to achieve efficient and orderly data transmission. During the data transmission process, the data classification and transmission optimization module will feed back the transmission status of all data, including transmission progress, success or failure, etc., to the storage adapter module in real time, so that the storage adapter module can make corresponding storage preparations.

[0045] The storage adapter module intelligently arranges the storage of the transmitted data according to the transmission status fed back by the data classification and transmission optimization module and the data classification. For urgent and important data, the storage adapter module performs multiple redundant backups and stores them in high-speed storage media to ensure data security and fast reading. During the storage process, the storage block size of the storage medium is used. and data file size , using data block storage , divide the data file into To ensure the integrity of data storage, checksums are used between adjacent blocks. To perform a check, is the check code length, The first After the data is stored, the data is regularly checked by the checksum. Once an error is found, the data recovery program is immediately started to restore the data from the redundant backup to ensure the accuracy and integrity of the data. For temporary data, the storage adapter module stores it in ordinary storage media. In order to avoid temporary data occupying too much storage space, the storage adapter module regularly performs data cleaning operations. Calculate the data cleaning condition, where is the survival time of the data, is the current time, is the cleaning interval, when the calculated When the data has exceeded its survival time, the storage adapter module will clean up the expired data, release storage space, and ensure efficient use of the storage medium. After all data is stored, the storage adapter module sends a storage confirmation message to the operation and maintenance platform to inform the operation and maintenance personnel that the data storage operation has been completed.

[0046] During the operation of the platform, the operation and maintenance monitoring module continuously collects the operating status information of each module of the entire platform, including whether the spectrum is successfully allocated, whether the data transmission is abnormal, and whether the storage medium has been completely stored. The operation and maintenance monitoring module records in detail the decision-making basis for each data, the transmission path selection process, and the specific values ​​of the spectrum allocation. By establishing data backtracking, when a problem occurs, the module where the problem occurs can be accurately located to improve the automation level of the platform.

[0047] To sum up, through the close collaboration and mutual coordination of various modules, the digital information transmission shared operation and maintenance platform based on AI technology has realized the full-process intelligent management of digital information from collection, analysis, spectrum allocation, transmission optimization to storage, which has significantly improved the efficiency and stability of digital information transmission and the utilization rate of storage resources.

[0048] Embodiment 2

[0049] This embodiment introduces in detail the application process of a digital information transmission shared operation and maintenance platform based on AI technology in a smart grid scenario. The smart grid relies on the real-time and stable transmission of large amounts of data to achieve efficient management of electricity production, transmission, distribution and use.

[0050] In smart grids, the data acquisition module continuously monitors the operating parameters of power equipment, such as the oil temperature, winding temperature, oil level of transformers, the opening and closing status of circuit breakers, the number of operations, etc. The monitoring devices on the transmission lines collect data such as current, voltage, power, phase angle, and meteorological environment information of the lines. The data acquisition module summarizes the raw data generated in real time, marks the data source, and monitors the data flow. Subsequently, the raw data is transmitted to the AI ​​intelligent analysis module to provide a rich and accurate data source for subsequent intelligent processing.

[0051] After receiving the original data, the AI ​​intelligent analysis module conducts multi-dimensional analysis. In terms of spectrum analysis, it evaluates the use of wireless spectrum for data transmission between different areas and different devices in the smart grid. For example, during the peak period of electricity consumption, the data transmission volume of the central area power grid increases dramatically. Through analysis, the frequency band with less interference and more idle resources is found, and the spectrum analysis results are passed to the spectrum dynamic allocation module to provide a basis for the selection of data transmission frequency bands. For data classification, the AI ​​intelligent analysis module judges the importance of the data based on its source and timeliness. When a fault occurs in the power grid, such as a line short circuit or equipment tripping, the location information of the fault point, the fault type, the impact range and other data are crucial for fault repair and stable operation of the power grid. They are extremely time-sensitive and important, and will be judged as urgent and important data. Daily power grid operation status monitoring data, such as the routine operation parameters of each substation, have relatively low timeliness requirements and are of medium importance, and will be classified as important data. After analysis, the AI ​​intelligent analysis module divides the data into urgent and important, important and temporary data, and sends the classification results to the data classification and transmission optimization module and the storage adaptation module respectively.

[0052] After receiving the spectrum analysis results from the AI ​​intelligent analysis module, the spectrum dynamic allocation module combines the real-time load and signal strength of the current network and other information. When there is a new data transmission task, such as the real-time monitoring data of power grid equipment that needs to be uploaded, the spectrum dynamic allocation module will comprehensively consider various factors and dynamically allocate the most suitable idle spectrum for it. For example, when the network load is high during peak power consumption, it will avoid congested frequency bands and select frequency bands with stable signals and low interference for data transmission. The spectrum usage will be synchronized to the data classification and transmission optimization module to ensure the stability and efficiency of data transmission.

[0053] The data classification and transmission optimization module adopts differentiated transmission strategies based on the data classification results of the AI ​​intelligent analysis module and the spectrum usage information of the spectrum dynamic allocation module. For urgent and important data, such as power grid fault information, the optimal bandwidth resources are allocated first, and the shortest and most reliable transmission path is planned. When allocating bandwidth, the largest possible bandwidth share is allocated to this type of data from the network bandwidth resource pool to ensure that the data can be transmitted to the power grid dispatching center or related repair departments at the fastest speed. At the same time, combined with the spectrum usage information, the spectrum channel with the best signal quality and the least interference is selected for transmission to ensure the timeliness of data transmission so that measures can be taken in time to restore the normal operation of the power grid. For important data, such as daily power grid operation status monitoring data, bandwidth resources are reasonably allocated and the transmission path is optimized on the premise of giving priority to emergency data transmission. By dynamically adjusting the transmission queue order, it is ensured that important data can be transmitted as soon as possible after the emergency data. At the same time, according to the real-time network load and spectrum usage status, the transmission parameters such as transmission rate and data packet size are flexibly adjusted to ensure the transmission efficiency of important data and provide data support for the daily operation analysis and optimization of the power grid. For temporary data, such as debugging information of some equipment and non-critical environmental monitoring data, the transmission is flexibly arranged according to the idle period of the network. When the network is found to be idle, the temporary data transmission task is started to make full use of the idle resources of the network without affecting the transmission quality of urgent and important data, so as to achieve efficient and orderly data transmission. During the data transmission process, the data classification and transmission optimization module will feed back the transmission status of all data, including transmission progress, success, and other information, to the storage adapter module in real time.

[0054] The storage adapter module intelligently arranges the storage of the transmitted data according to the transmission status and data classification feedback from the data classification and transmission optimization module. For urgent and important data, multiple redundant backups are performed and stored in high-speed storage media to ensure data security and fast reading. For example, power grid fault data and long-term power grid operation monitoring data need to be stored for a long time and can be quickly queried and analyzed when needed for fault cause tracing and power grid operation optimization. For temporary data, it is stored in ordinary storage media and data cleaning operations are performed regularly. When temporary data exceeds the set survival time, the storage adapter module will clean up expired data, release storage space, and ensure efficient use of storage media. After all data storage is completed, the storage adapter module sends a storage confirmation message to the operation and maintenance platform to inform the operation and maintenance personnel that the data storage operation has been completed.

[0055] In summary, through the collaborative work of the above modules in the smart grid scenario, the digital information transmission shared operation and maintenance platform based on AI technology realizes the efficient transmission, storage and management of large amounts of data in the smart grid, ensuring the stable and reliable operation of the smart grid.

[0056] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any brief modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. A digital information transmission shared operation and maintenance platform based on AI technology, characterized in that: The components of the platform include: data collection module, AI intelligent analysis module, spectrum dynamic allocation module, data classification and transmission optimization module, and storage adaptation module; The data acquisition module collects raw data at the starting end of the digital information transmission link, wherein the raw data includes raw information of the wireless spectrum, data flow size, and data source identification, and transmits the collected raw data to the AI ​​intelligent analysis module in real time; The AI ​​intelligent analysis module receives the raw data from the data acquisition module and analyzes the raw data, including: On the one hand, the spectrum data in the original wireless spectrum information is identified by the spectrum recognition algorithm. Identify idle spectrum resources and accurately quantify idle spectrum conditions, including: Indicates the comprehensive value of the availability of idle spectrum resources. To monitor the number of subdivisions in the frequency band, It is the frequency band The power spectral density of It is the frequency band The bandwidth factor, It is the frequency band Interference degree coefficient, the coefficient range is 0-1, 0 means no interference, 1 means complete interference; On the other hand, based on the data flow and data source identification, the timeliness and importance of the original data are comprehensively judged, and the original data is classified according to the importance. The classification adopts the data classification algorithm: ,in, Indicates the importance level of the data. is the timeliness weight of the data, is the weight of the data source, is the frequency of data operations, is the data transmission cycle; Output the spectrum analysis results to the spectrum dynamic allocation module, and output the raw data classification judgment results to the data classification and transmission optimization module and the storage adaptation module; The spectrum dynamic allocation module formulates the optimal spectrum allocation strategy based on the spectrum analysis results output by the AI ​​intelligent analysis module and the real-time load and signal strength of the current network; After receiving the data classification judgment result of the AI ​​intelligent analysis module and the spectrum usage information of the spectrum dynamic allocation module, the data classification and transmission optimization module adopts differentiated transmission strategies for data of different levels; The storage adaptation module performs intelligent storage arrangement for the data that has completed transmission according to the transmission status fed back by the data classification and transmission optimization module and in combination with the data classification situation.

2. According to claim 1, a digital information transmission sharing operation and maintenance platform based on AI technology is characterized in that: In the process of analyzing the data, the AI ​​intelligent analysis module divides the data into urgent, important and temporary data according to the importance level of the data, where: When G≥0.7, the data is judged as urgent data. In the transmission link, the optimal bandwidth resources are allocated first. When 0.4≤G<0.7, the data is classified as important data, and its transmission efficiency is ensured while giving priority to emergency data transmission; When G < 0.4, the data are classified as provisional data.

3. According to claim 1, a digital information transmission sharing operation and maintenance platform based on AI technology is characterized in that: When processing data flow information, the AI ​​intelligent analysis module introduces a flow trend prediction algorithm to accurately determine the timeliness of data. Based on historical flow data, the time series analysis method is used to calculate the flow change trend coefficient by analyzing the flow data at the past A moments. ,in is the flow rate change, To predict the time span, , is the trend threshold, indicating that the traffic is in a rapid growth stage. At this time, combined with the business type, for business data with high timeliness requirements, its timeliness weight is increased in the data classification algorithm. ,Right now , The timeliness weight adjustment amount is increased according to the traffic trend so that this type of data can be transmitted first, ensuring the timeliness of key information. At the same time, it continues to self-optimize and continuously updates parameters as new data flows in to maintain the ability to capture traffic trends.

4. According to claim 1, a digital information transmission shared operation and maintenance platform based on AI technology is characterized in that: The platform also includes an operation and maintenance monitoring module, which collects the operating status information of each module of the entire platform, including judging spectrum allocation, judging data transmission, and judging storage media. The operation and maintenance monitoring module records in detail the decision basis for each data, the transmission path selection process, and the specific values ​​of the spectrum allocation. By establishing data backtracking, when a problem occurs, the module where the problem occurs can be accurately located.

5. According to claim 1, a digital information transmission sharing operation and maintenance platform based on AI technology is characterized in that: The differentiated transmission strategies of the data classification and transmission optimization module include: For urgent and important data, we prioritize the allocation of optimal bandwidth resources and the planning of the shortest transmission path, and ensure that it is transmitted at the fastest speed based on spectrum allocation. For temporary data, the transmission is flexibly arranged according to the network idle period, so as to achieve differentiated processing according to the characteristics of the data and ensure the overall data transmission and storage efficiency of the platform; The transmission status of all data is fed back to the storage adapter module in real time to achieve efficient and orderly data transmission.

6. According to claim 1, a digital information transmission sharing operation and maintenance platform based on AI technology is characterized in that: The intelligent storage arrangement of the storage adapter module includes: For urgent and important data, multiple redundant backups are performed and stored in high-speed storage media; Temporary data is stored in ordinary storage media; After all data is stored, storage confirmation information is sent to the operation and maintenance platform terminal.

7. According to claim 6, a digital information transmission sharing operation and maintenance platform based on AI technology is characterized in that: When the storage adapter module performs intelligent storage arrangement, the urgent and important data are stored in the high-speed storage medium, and its storage management follows the data layout strategy, which uses the storage block size of the storage medium. , data file size , using data block storage ,in Indicates rounding up, dividing the data file into Blocks are stored, and checksums are used between adjacent blocks. Check, where q is the check code length, The pth byte in the data block is used to detect the integrity of data storage through the checksum. Once an error is found, the data recovery program is immediately started to restore the data from the redundant backup; For temporary data, perform data cleanup regularly ,in is the survival time of the data, is the current time, is the cleaning interval, when When the system is running, it cleans up expired data and releases storage space.

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