Transmission method and device for realizing service optimization aiming at power private network data

Abstract

The invention provides a transmission method and device for realizing service optimization for power private network data, and belongs to the technical field of power communication. The method is applied to a monitoring platform with 5G, Beidou short messages and LORA communication. The method comprises the steps of starting a monitoring platform 5G network and monitoring a communication state, and if communication can be carried out, obtaining service data and determining a service type and adaptive 5G channel transmission. And if the transmission network signal quality is higher than a set threshold value, transmitting the transmission network signal quality to a remote monitoring center in a 5G manner. When the monitoring rate in transmission is higher than a first threshold value, the current 5G channel is used for transmission; if the first threshold is lower than the first threshold but higher than the second threshold, optimizing the communication parameter; and if the information is lower than the second threshold value, switching to the LORA channel, transmitting the information to the edge processing equipment for processing, and then transmitting the information to a remote monitoring center through the Beidou short message channel. According to the invention, multi-channel transmission is fused, and inspection data can be timely and rapidly sent to a remote monitoring center without obstacles.

Description

Technical Field

[0001] This invention belongs to the field of power communication technology, specifically relating to a transmission method and apparatus for optimizing data transmission services in power private networks. Background Technology

[0002] With the advancement of smart grid construction, digital transformation has become an important trend in the development of power businesses. Communication technology plays a crucial role in this process, needing to meet the stringent requirements of the power system for high reliability, low latency, and massive connectivity in order to ensure the stable operation and efficient management of the power system.

[0003] Among numerous communication technologies, 5G technology, with its high bandwidth, low latency, massive connectivity, and network slicing capabilities, has become a core communication means supporting the digital transformation of power businesses. Currently, in power grid scenarios, dedicated 5G networks are often used to transmit power-related data back to remote control centers for further analysis or decision-making.

[0004] However, existing 5G technology faces numerous challenges in power grid applications. First, there is insufficient compatibility between the diverse needs of various services and the communication capabilities of 5G devices. The power grid encompasses diverse services such as load monitoring, fault early warning, and equipment inspection, each with significantly different requirements for transmission latency and bandwidth. Traditional device transmission lacks a service type-communication channel adaptation mechanism, relying solely on a unified channel. This leads to packet loss for high-latency services (such as fault early warning) and the consumption of redundant resources by low-bandwidth services (such as routine monitoring), failing to meet the diverse needs of different services. Second, poor signal stability and fluctuating transmission rates in complex terrain result in inefficient or interrupted data transmission. Mountainous and hilly terrain easily causes signal attenuation and obstruction for 5G devices. Third, in complex terrain, the coverage and transmission of existing power grid wireless private networks are severely affected, preventing real-time data transmission of critical data and exacerbating data transmission problems due to insufficient adaptability to dynamic network environments. Summary of the Invention

[0005] In view of this, the present invention provides a transmission method and apparatus for optimizing data transmission in power private networks, aiming to solve the above-mentioned shortcomings of existing 5G technology in power grid service transmission.

[0006] To achieve the above objectives, the technical solution provided by the present invention is as follows:

[0007] In a first aspect, the present invention provides a transmission method for optimizing data transmission in a dedicated power grid, applicable to a monitoring platform equipped with 5G communication, BeiDou short message communication, and LoRa communication. The monitoring platform is equipped with edge processing devices and is communicatively connected to a remote monitoring center. The transmission method includes:

[0008] The monitoring platform starts its 5G network and monitors the current network communication status. If the current network communication status is in a communicable state, it acquires the service data and determines the service type. Based on the determined service type, it selects the appropriate 5G network communication channel as the transmission network to transmit the service data of the corresponding service type.

[0009] Determine the signal quality of the current transmission network. If the signal quality of the current transmission network is higher than a set threshold, transmit the corresponding service data to the remote monitoring center via 5G communication. At the same time, monitor the transmission rate of the current transmission network during the service data transmission process.

[0010] If the transmission rate is detected to be higher than or equal to the first transmission rate threshold, the 5G network communication channel will continue to be used as the current transmission network to transmit service data.

[0011] If the transmission rate is detected to be lower than the first transmission rate threshold but higher than or equal to the second transmission rate threshold, the current transmission network communication parameters will be optimized and adjusted.

[0012] If the transmission rate is detected to be lower than the second transmission rate threshold, the system switches to the LORA technology radio frequency channel to transmit service data to the edge processing device, enabling the edge processing device to process the service data and transmit the processed results to the remote monitoring center via the BeiDou short message channel.

[0013] Furthermore, after monitoring the current transmission network's transmission rate, it also includes:

[0014] Generate the trend of transmission rate changes based on the transmission rate;

[0015] If the predicted transmission rate is lower than the first transmission rate threshold but higher than or equal to the second transmission rate threshold, the current transmission network communication parameters are optimized and adjusted, and the optimized transmission network is used as the latest current transmission network. At the same time, the current transmission network is monitored again.

[0016] Furthermore, determine the signal quality of the current transmission network, including:

[0017] Monitor the channel of the current transmission network and determine the various indicators that affect the network signal quality as signal quality parameters;

[0018] The determined signal quality parameters are input into the constructed signal quality scoring model to obtain an information quality score used to evaluate the strength of the current network signal.

[0019] Furthermore, the signal quality scoring model is a model determined by fusing signal quality parameters and service types according to the importance of each signal quality parameter to the determined service type; after inputting the determined signal quality parameters into the signal quality scoring model to obtain the information quality score, it also includes:

[0020] If the information quality score is higher than or equal to the set score threshold, it is determined that the signal quality of the current transmission network is higher than the set threshold, and then the corresponding service data is transmitted to the remote monitoring center via 5G communication.

[0021] Furthermore, it also includes updating the signal quality scoring model, and the update process includes:

[0022] Based on the current business type, determine the weight percentage of the signal quality parameters that affect the business type, and use the weight percentage of the signal quality parameters as the current weight parameters;

[0023] Adjust the signal quality scoring model based on the determined current weight parameters to generate a new signal quality scoring model;

[0024] Replace the existing signal quality scoring model with a new one.

[0025] Furthermore, if the service data includes image data, the service data is transmitted to the edge processing device via the LoRa technology radio frequency channel, enabling the edge processing device to perform service processing on the service data, including:

[0026] Image data is transmitted to edge processing devices via the LORA technology radio frequency channel;

[0027] Image data is transmitted to an edge processing device for processing. The edge processing device preprocesses the business data and then inputs the preprocessed business data into a pre-built image recognition model to obtain image recognition results. The image recognition results are then classified to obtain classification results. Finally, the processed business data is input into a fault identification model corresponding to the classification result to obtain the business processing result. The fault identification model is a pre-trained machine learning model used to identify faults in power components. Different classification results correspond to different fault identification models.

[0028] Receive the service processing results sent by the edge processing device.

[0029] Furthermore, the current transmission network communication parameters will be optimized and adjusted, including:

[0030] Obtain communication parameters that affect the transmission rate;

[0031] The communication parameters are input into the trained fault prediction model to obtain the communication fault prediction results of the current network channel.

[0032] Based on the communication fault prediction results, an optimization scheme is matched, and the communication parameters of the current transmission network are optimized and adjusted according to the optimization scheme.

[0033] Secondly, this invention provides a transmission device for optimizing data services in a dedicated power grid. It is applied to a monitoring platform equipped with 5G communication, BeiDou short message communication, and LoRa communication. The monitoring platform is equipped with edge processing devices and is communicatively connected to a remote monitoring center.

[0034] The transmission device includes:

[0035] The network startup and service module is used to start the 5G network of the monitoring platform and monitor the current network communication status. If the current network communication status is in a communicable state, it acquires service data and determines the service type. Based on the determined service type, it selects the appropriate 5G network communication channel as the transmission network to transmit the service data of the corresponding service type.

[0036] The signal judgment and transmission module is used to determine the signal quality of the current transmission network. If the signal quality of the current transmission network is higher than a set threshold, the corresponding service data is transmitted to the remote monitoring center via 5G communication. At the same time, during the service data transmission, the transmission rate of the current transmission network is monitored. When the transmission rate is detected to be higher than or equal to the first transmission rate threshold, the maintenance module is triggered. When the transmission rate is detected to be lower than the first transmission rate threshold but higher than or equal to the second transmission rate threshold, the rate optimization module is triggered. When the transmission rate is detected to be lower than the second transmission rate threshold, the channel switching and processing module is triggered.

[0037] The maintenance module is used to maintain the use of the 5G network communication channel as the current transmission network for transmitting service data.

[0038] The rate optimization module is used to optimize and adjust the communication parameters of the current transmission network.

[0039] The channel switching and processing module is used to switch to the LORA technology radio frequency channel, and transmit service data to the edge processing device through the LORA technology radio frequency channel, so that the edge processing device can perform service data processing, and transmit the processing results to the remote monitoring center through the Beidou short message channel.

[0040] Thirdly, the present invention provides a computer device, the device including a processor and a memory:

[0041] The memory is used to store computer programs and send the instructions of the computer programs to the processor;

[0042] The processor executes, according to the instructions of the computer program, a transmission method for optimizing data transmission in a dedicated power grid, as described in the first aspect.

[0043] Fourthly, the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements a transmission method for optimizing data transfer services for a dedicated power grid, as described in the first aspect.

[0044] In summary, this invention provides a transmission method and apparatus for optimizing data transmission in power private networks, applicable to monitoring platforms with 5G, BeiDou short message, and LoRa communication capabilities. By activating the 5G network of the monitoring platform and monitoring its communication status, this invention acquires service data and determines the service type when 5G communication is available. Based on the service type, it selects an appropriate 5G network communication channel, thereby establishing a matching mechanism between service type and 5G channel. This solves the problems of insufficient compatibility between the diverse needs of multiple services and 5G communication, high latency packet loss due to traditional unified channel transmission, and low bandwidth resource redundancy in existing technologies. Simultaneously, it improves the compatibility between services and 5G communication, reduces transmission anomalies and resource waste. Furthermore, by determining the signal quality of the current transmission network, 5G is used only when the signal quality exceeds a set threshold to transmit data to the remote monitoring center, and during transmission... Real-time monitoring of transmission rates and differentiated measures for different rate ranges—that is, continuing to use the 5G channel when the rate is higher than or equal to the first transmission rate threshold, and optimizing 5G communication parameters when the rate is between the first and second transmission rate thresholds—effectively solves the problems of poor 5G signal stability and inefficient data transmission caused by transmission rate fluctuations in complex terrain, thus improving the stability and efficiency of 5G transmission in complex terrain. Furthermore, by switching to the LoRa technology radio frequency channel when the transmission rate is lower than the second transmission rate threshold, the service data is transmitted to the edge processing device for processing, and then the processing results are transmitted to the remote monitoring center via the BeiDou short message channel. This constructs link redundancy in a dynamic network environment, solving the problems of critical data not being able to be transmitted back in real time in complex terrain and insufficient adaptability to dynamic network environments. It ensures the real-time transmission of critical data in complex terrain and improves adaptability to dynamic network environments. Attached Figure Description

[0045] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1A flowchart illustrating a transmission method for optimizing data transmission in a dedicated power grid, provided as an embodiment of the present invention;

[0047] Figure 2 This is a schematic diagram of the monitoring platform provided in an embodiment of the present invention;

[0048] Figure 3 This is a schematic diagram of another monitoring platform provided in an embodiment of the present invention;

[0049] Figure 4 This is a schematic diagram of the structure of the drone charging connection device provided in an embodiment of the present invention;

[0050] Figure 5 A block diagram of a transmission device for optimizing data services in a dedicated power grid, provided as an embodiment of the present invention;

[0051] Figure 6 This is a block diagram of a computer device provided in an embodiment of the present invention.

[0052] In the attached image:

[0053] 1-Horizontal motion platform, 11-Horizontal motor, 12-Horizontal lead screw, 13-Horizontal balance lead screw, 14-Horizontal threaded plate;

[0054] 2-Vertical motion platform, 21-Vertical lead screw, 22-Vertical balance lead screw, 23-Vertical thread plate;

[0055] 3-Rotating platform, 31-Rotating motor, 32-Rotating table;

[0056] 4-Communication plug-in mechanism, 41-Longitudinal motor, 42-Longitudinal lead screw, 43-Threaded tube, 44-Communication plug, 45-Charging plug;

[0057] 5-Accommodation cavity, 6-Charging cavity. Detailed Implementation

[0058] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0059] Please see Figure 1This embodiment provides a transmission method for optimizing data services in a dedicated power grid. It is applied to a monitoring platform with 5G communication, Beidou short message communication and LoRa communication. The monitoring platform is equipped with edge processing equipment and is connected to a remote monitoring center.

[0060] The transmission method includes:

[0061] S11: Start the 5G network of the monitoring platform and monitor the current network communication status. If the current network communication status is in a communicable state, obtain the service data and determine the service type. Based on the determined service type, select the appropriate 5G network communication channel as the transmission network to transmit the service data of the corresponding service type.

[0062] In this step, power grid services encompass various scenarios, including control-related scenarios such as relay protection and remote control, monitoring-related scenarios such as equipment status sensing and video inspection, and data acquisition-related scenarios such as metering data feedback. Each scenario has significantly different requirements for communication latency, reliability, and bandwidth. Therefore, when the network is in a communicable state, the service data is quickly acquired and its type is determined. Since 5G network channels can be divided into multiple network channels, and different service scenarios have different network channel requirements, a suitable 5G network communication channel is selected as the transmission network based on the service type. This enables different service data to be transmitted in a 5G network channel that meets its specific needs, satisfying the diverse communication requirements of power grid services.

[0063] S12: Determine the signal quality of the current transmission network. If the signal quality of the current transmission network is higher than the set threshold, transmit the corresponding service data to the remote monitoring center via 5G communication. At the same time, monitor the transmission rate of the current transmission network during the service data transmission process.

[0064] In this step, the signal quality of the selected current transmission network (i.e., the adapted 5G network communication channel) is determined. Only when the signal quality exceeds a set threshold will 5G communication be used to transmit the corresponding service data to the remote monitoring center. Simultaneously, considering that network congestion, weak signals, and other issues may affect transmission efficiency during service data transmission, the transmission rate of the current transmission network needs to be continuously monitored during data transmission to determine its current range.

[0065] S13: If the transmission rate is detected to be higher than or equal to the first transmission rate threshold, the 5G network communication channel will continue to be used as the current transmission network to transmit service data.

[0066] In this step, when the monitored transmission rate is higher than or equal to the first transmission rate threshold, it indicates that the transmission efficiency of the current 5G network communication channel can meet the needs of business data transmission, and there is no problem of slow transmission or congestion. Therefore, there is no need to adjust the transmission network, and the 5G network channel can continue to be used as the current network channel to transmit business data, ensuring the stability and continuity of business transmission.

[0067] S14: If the transmission rate is detected to be lower than the first transmission rate threshold but higher than or equal to the second transmission rate threshold, the current transmission network communication parameters are optimized and adjusted.

[0068] In this step, when the monitored current transmission network rate is lower than the first transmission rate threshold but higher than or equal to the second transmission rate threshold, it indicates that the 5G network communication channel transmission rate is slow, possibly indicating some network congestion or signal attenuation. However, it still possesses basic data transmission capabilities and has not reached a state where transmission is completely impossible. At this point, it is necessary to optimize and adjust the communication parameters of the current transmission network (5G network channel) to improve network congestion, increase the transmission rate, and restore the network to a state that can meet the needs of service transmission.

[0069] S15: If the transmission rate is detected to be lower than the second transmission rate threshold, switch to the LORA technology radio frequency channel and transmit service data to the edge processing device through the LORA technology radio frequency channel so that the edge processing device can process the service data and transmit the processing results to the remote monitoring center through the Beidou short message channel.

[0070] In this step, when the monitored current transmission network rate is lower than the second transmission rate threshold, it indicates that the 5G network channel is unable to transmit service data normally, potentially resulting in communication signal interruption or extremely weak signal. At this time, it is necessary to switch to the LoRa (Local-to-Area Resonance) radio frequency channel. This channel transmits service data to the edge processing device, which performs service data processing (such as fault identification; to reduce communication consumption and data transmission burden, only the fault identification results can be retained). Afterward, the processed results are transmitted to the remote monitoring center via the BeiDou short message channel. The BeiDou short message channel is suitable for areas without mobile communication network coverage and has encryption capabilities, ensuring data transmission security and guaranteeing effective transmission and processing of service data even when the 5G network fails.

[0071] In this embodiment, the BeiDou short message channel allows users to send and receive short messages via satellite, making it particularly suitable for areas without mobile communication network coverage. For use cases where the transmission rate is below the second transmission rate threshold, specifically: at the perception layer, various sensors and monitoring devices can utilize LoRa technology for data collection. The LoRa gateway, as a key component of the transmission layer, is responsible for receiving data sent by perception layer devices and transmitting this data to the central node or data processing center via the LoRa network. At the fusion layer, the LoRa network is combined with the BeiDou short message system. When the LoRa network cannot cover the area or a wider area of ​​communication is required, data can be transmitted through the BeiDou short message system. This fusion ensures reliable data transmission even in remote areas or places with inadequate communication infrastructure. BeiDou short message communication has encryption capabilities, which improves data transmission security and protects data from unauthorized access. With the increase in IoT devices, the LoRa network can be flexibly expanded, and the BeiDou short message system can also increase satellite resources as needed to support more users and higher data transmission rates. Through the above architecture, the combination of LoRa and BeiDou short message service can realize an efficient, reliable and widely covered data transmission system, which is particularly suitable for application scenarios that require data collection and monitoring in a wide area.

[0072] The transmission method for optimizing power grid data provided in this embodiment uses LoRa technology radio frequency channel to acquire service data when 5G network communication is poor. The service data is then processed by edge processing equipment, and the processing results are sent to a remote monitoring center via BeiDou short message channel based on satellite for further analysis or processing. In addition, the remote monitoring center can also select the above multiple channels to send control commands for remote operation.

[0073] In one embodiment, after monitoring the transmission rate of the current transmission network, the method further includes:

[0074] S21: Generate the trend of transmission rate changes based on the transmission rate;

[0075] S22: Predict the transmission rate at the next moment based on the trend of change. If the predicted transmission rate is lower than the first transmission rate threshold but higher than or equal to the second transmission rate threshold, optimize and adjust the current transmission network communication parameters, and use the optimized transmission network as the latest current transmission network. At the same time, monitor the current transmission network again.

[0076] In this embodiment, after monitoring the transmission rate of the current transmission network, a trend of its change is first generated based on the acquired transmission rate data, and then the transmission rate at the next moment is predicted based on the trend. Subsequently, a first transmission rate threshold and a second transmission rate threshold are introduced for judgment. When the predicted rate is in the intermediate range of "lower than the first transmission rate threshold but higher than the second transmission rate threshold", the transmission channel is not switched directly. Instead, the communication parameters of the current transmission network (such as modulation and demodulation method and channel bandwidth allocation) are optimized and adjusted, and the optimized network is used as the new current transmission network for re-monitoring. By predicting the rate change in advance and actively optimizing the parameters, the stability of service data transmission is avoided due to rate fluctuations.

[0077] In some embodiments, determining the signal quality of the current transmission network includes:

[0078] S31: Monitor the channel where the current transmission network is located, and determine the various indicators that affect the network signal quality as signal quality parameters;

[0079] S32: Input the determined signal quality parameters into the constructed signal quality scoring model to obtain the information quality score used to evaluate the strength of the current network signal.

[0080] In this embodiment, channel characteristic data of the current transmission network can be captured by channel monitoring technology, and key indicators that directly reflect network quality (such as signal-to-noise ratio, bit error rate, signal attenuation, etc.) can be extracted as signal quality parameters, transforming the abstract "network quality" into calculable quantitative data. In the second step, these quantitative parameters are input into a pre-built signal quality scoring model. The model has built-in comprehensive evaluation logic (such as weighted calculation based on parameter importance or machine learning inference rules trained based on historical quality data) to perform fusion analysis on multi-dimensional parameters and finally output information quality scores.

[0081] For example, signal quality parameters include: Signal-to-Noise Ratio (SNR): the ratio of signal power to noise power; Peak Signal-to-Noise Ratio (PSNR): the ratio of maximum signal power to noise power; Mean Squared Error (MSE): the difference between the original signal and the processed signal; Dynamic Range: the ratio of the maximum to minimum amplitude of the signal; Spectral Flatness: the uniformity of the signal spectrum; Harmonic Distortion: the harmonic components caused by nonlinear distortion; Bandwidth Utilization: the ratio of occupied bandwidth to available bandwidth; Kurtosis: the sharpness of the signal amplitude distribution; Skewness: the asymmetry of the signal amplitude distribution; Autocorrelation: the periodicity of the signal; Bit Error Rate (BER): the proportion of errors in digital communication; Eye Diagram Aperture: a visual indicator of digital signal quality; Signal Attenuation: power loss during transmission.

[0082] In some embodiments, the signal quality scoring model is a model determined by fusing signal quality parameters and service types according to the importance of each signal quality parameter to the determined service type; after inputting the determined signal quality parameters into the signal quality scoring model to obtain the information quality score, it further includes:

[0083] If the information quality score is higher than or equal to the set score threshold, it is determined that the signal quality of the current transmission network is higher than the set threshold, and then the corresponding service data is transmitted to the remote monitoring center via 5G communication.

[0084] In this embodiment, during the signal quality scoring model construction phase, the basic parameters affecting signal quality are taken as the core, and the transmission requirements of specific service types are combined with the weight allocation (such as industrial control services being sensitive to bit error rate and video services being sensitive to bandwidth utilization rate) to integrate service requirements into the model, so that the model output score can match the service's network quality requirements. Then, a score threshold corresponding to the minimum quality requirements of the service is set. When the information quality score output by the model is higher than the threshold, it is determined that the current network quality meets the service transmission conditions, thereby triggering the 5G transmission mechanism (utilizing the high speed and low latency characteristics of 5G) to transmit the data matching the current service type to the remote monitoring center.

[0085] In some embodiments, the method further includes updating the signal quality scoring model, the update process including:

[0086] S41: Based on the current service type, determine the weight percentage of the signal quality parameter's influence on the service type, and use the weight percentage of the signal quality parameter as the current weight parameter;

[0087] S42: Adjust the signal quality scoring model based on the determined current weight parameters to generate a new signal quality scoring model.

[0088] S43: Replace the existing signal quality scoring model with a new signal quality scoring model.

[0089] In this embodiment, the evaluation criteria for network signal quality need to be adjusted according to changes in service type. Since different services have varying sensitivities to signal parameters, the impact of each signal quality parameter on the transmission performance of the current service type is first analyzed to determine the weight of each parameter (parameters with greater impact have higher weights). Then, based on these weights, the parameter weight matrix of the original signal quality scoring model is adjusted, the importance of each parameter in the model is redefined, and a new model is generated. This ensures that the model's output score always aligns with the quality requirements of the current service, avoiding distortion of the model's evaluation due to service changes.

[0090] In some embodiments, if the service data includes image data, the service data is transmitted to the edge processing device via a LoRa (LoRa) radio frequency channel so that the edge processing device can perform service processing on the service data, including:

[0091] S51: Transmits image data to edge processing devices via the LORA technology radio frequency channel;

[0092] S52: The image data is transmitted to the edge processing device for processing, so that the edge processing device preprocesses the business data and inputs the preprocessed business data into a pre-built image recognition model to obtain the image recognition result. The image recognition result is classified to obtain the classification result. Finally, the processed business data is input into the fault recognition model corresponding to the classification result to obtain the business processing result. Here, the fault recognition model is a pre-trained machine learning model used to identify faults in power components. Different classification results correspond to different fault recognition models.

[0093] S53: Receive the service processing result sent by the edge processing device.

[0094] In this embodiment, for services containing image data, the first step is to eliminate image interference and unify the data format through preprocessing (denoising, size normalization, etc.) to reduce the impact of noise on subsequent recognition; the second step is to use an image recognition model to extract target features (such as the shape and texture of power components) in the image to obtain preliminary recognition results; the third step is to classify the recognition results according to target features (such as component size and type) in order to match fault recognition models for different types of targets. Because the fault features of different targets vary greatly (for example, faults of small metal components are mostly minor deformations, while faults of large components are mostly overall structural abnormalities), the fault recognition model is optimized and trained for the fault features of specific targets, resulting in higher recognition accuracy; finally, the fault recognition model analyzes the data and outputs business processing results such as fault type, achieving accurate and efficient fault recognition at the edge.

[0095] In some embodiments, optimizing and adjusting the current transmission network communication parameters includes:

[0096] S61: Obtain communication parameters that affect the transmission rate;

[0097] S62: Input the communication parameters into the pre-trained fault prediction model to obtain the communication fault prediction result of the current network channel;

[0098] S63: Match an optimization scheme based on the communication fault prediction results, and optimize and adjust the current transmission network communication parameters according to the optimization scheme.

[0099] In this embodiment, firstly, communication parameters that directly affect the transmission rate (such as coding rate, transmission power, and interference level) are collected. These parameters are the core representations of the network transmission status. Secondly, the parameters are input into a pre-trained fault prediction model. The model learns the correlation between "parameter features and fault types" based on historical data and analyzes the communication faults that the current parameter combination may cause (such as excessively high interference levels potentially leading to a sudden drop in rate). Finally, using a pre-set "fault-optimization scheme" mapping library (which pre-associates common faults with corresponding parameter adjustment strategies, such as adjusting the anti-interference coding method for interference faults), optimization schemes are matched according to the predicted fault types, and the network communication parameters are adjusted according to the schemes.

[0100] Furthermore, regarding the monitoring platform used in the above embodiments, in a further embodiment of the present invention, a monitoring platform design is proposed, such as... Figure 2 As shown, it includes:

[0101] It is applied to a monitoring platform with 5G communication, Beidou short message communication and LoRa communication. The monitoring platform is equipped with edge processing equipment and the monitoring platform is connected to a remote monitoring center.

[0102] The edge processing device is installed at the monitored power equipment. Among them, the edge processing device is a localized intelligent device deployed near the monitored power equipment (such as poles and towers, substations, etc.), and has functions of data acquisition, analysis, storage, and communication control.

[0103] In addition to the edge processing device main body, a 5G communication module, a Beidou short message communication module, and a LORA communication module are also arranged in the edge processing device. The edge processing device and the LORA communication module are arranged in the monitoring platform. Among them, the 5G communication module is a communication component integrated in the edge processing device, supports data transmission through the 5G network, has the characteristics of large bandwidth (can transmit a large amount of data) and low latency (strong real-time performance), and is suitable for monitoring data or inspection data that need to be efficiently transmitted in the power system. The Beidou short message communication module is a communication component based on the Beidou satellite navigation system, integrated in the edge processing device, and can send data in the form of short messages through satellites in scenarios without ground networks (such as 5G signal coverage blind areas), and is suitable for emergency communication and data transmission in remote areas. The LORA communication module is connected to external electronic devices.

[0104] The 5G communication module is electrically connected to the remote monitoring center through a switching device, and the Beidou short message communication module is communicatively connected to the remote monitoring center through a Beidou short message passive antenna. Among them, the switching device is a network device that cooperates with the 5G communication module, is responsible for data forwarding, routing management, and link maintenance, and is used to achieve a stable connection between the 5G communication module and the remote monitoring center. The Beidou short message passive antenna is an antenna supporting the Beidou short message communication module, does not require additional power supply, and is used to receive and transmit Beidou satellite signals. The Beidou short message passive antenna is embedded and installed on the outside of the edge processing device in a detachable and retractable manner.

[0105] The edge processing device is configured to obtain the monitoring data of the power equipment and / or the inspection data of the transmission line, and monitor the signal strength of the 5G communication module; if the signal strength of the 5G communication module is higher than the set signal strength threshold, the monitoring data and / or the inspection data are sent to the remote monitoring center through the 5G communication module, and if the signal strength of the 5G communication module is not higher than the set signal strength threshold, the key data of the monitoring data and / or the inspection data are extracted, and the key data are sent to the remote monitoring center through the Beidou short message communication module.

[0106] It should be noted that the monitoring data is the operation state data of the power equipment directly collected by the edge processing device (such as the inclination angle of the pole and tower, equipment temperature, voltage and current, etc.). The inspection data is the transmission line state data obtained through methods such as drones and manual inspections (such as line damage images, foreign object intrusion videos, etc.). The key data is the core information (such as fault warning, emergency status identification, etc.) extracted from the monitoring data or inspection data when the 5G signal is poor, with the highest priority and needs to be preferentially transmitted through the Beidou short message.

[0107] In power distribution networks, drones are frequently used to inspect power poles and lines. Current technology typically involves mounting an edge computing box on the bottom of the drone. However, this largely relies on a 5G network connection to a remote monitoring center. Without a 5G signal, the edge computing box cannot send inspection results to the remote monitoring center. Therefore, in some implementations, such as... Figure 3 As shown, the monitoring platform also includes: a drone charging connection device, which includes:

[0108] Charging placement cavity, moving mechanism, communication plug-in mechanism, and position receiver;

[0109] The charging placement cavity is used to park the inspection drone and is electrically connected to the edge processing device to charge the inspection drone;

[0110] The location receiver is mounted on the communication plug-in mechanism and electrically connected to the edge processing device. It is used to receive location information sent by the location transmitter on the inspection drone.

[0111] The communication plug-in mechanism is installed on the mobile mechanism and is used to plug into the charging and communication port of the inspection drone under the drive of the mobile mechanism, so as to realize the wired connection between the inspection drone and the edge processing equipment.

[0112] The mobile mechanism is electrically connected to the edge processing device, which is configured to control the mobile mechanism to move the communication plug-in mechanism to the charging communication port and complete the plug-in based on the location information obtained by the location receiver.

[0113] In this embodiment, the charging placement cavity is used for parking the inspection drone and is electrically connected to the edge processing device. During drone parking, the edge processing device can directly replenish the drone's power. A location receiver is mounted on the communication plug-in mechanism and is also electrically connected to the edge processing device. Its function is to receive location information sent by the location transmitter on the inspection drone for subsequent precise docking. The communication plug-in mechanism is installed on the mobile mechanism and can move flexibly under the movement of the mobile mechanism, ultimately plugging into the charging communication port of the inspection drone, thereby achieving a wired connection between the inspection drone and the edge processing device. All the above-mentioned electrical connections are wired connections. Wired connections ensure the stability and security of data transmission and avoid interference problems that may occur with wireless transmission in complex power environments. The mobile mechanism is also electrically connected to the edge processing device.

[0114] The edge processing device is configured to precisely control the movement trajectory of the mobile mechanism based on the location information of the inspection drone obtained from the location receiver, driving the communication plug-in mechanism to move accurately to the charging communication port and complete the plug-in. After the plug-in is completed and the wired connection is successfully established, the edge processing device sends a command to the edge computing box on the inspection drone side to retrieve inspection data, and the inspection drone then sends the stored inspection data to the edge processing device.

[0115] In some specific implementations, when the drone charging connection device determines that the inspection drone is parked in the charging placement cavity, the inspection drone activates its position transmitter. The position receiver receives the position information from the position transmitter and sends the acquired position information to the edge processing device. Based on the acquired position information, the edge processing device controls the moving mechanism to move the communication plug-in mechanism to below the charging communication port of the inspection drone, and controls the communication plug-in mechanism to insert into the charging communication port and connect with the edge processing device via wire. After confirming that the wired connection is successful, it sends a data acquisition command to the edge computing box on the inspection drone side, indicating that it wants to acquire inspection data. Based on the acquisition command, the inspection drone sends the stored inspection data to the edge processing device so that the edge processing device can perform fault identification processing on the inspection data and analyze the fault identification processing results. If the fault identification result is determined to be faulty, the fault identification result is marked as the highest priority and sent to the remote monitoring center through the Beidou short message communication module. If the 5G signal strength of the current network reaches the signal strength threshold during the parking of the inspection drone, the inspection data of the inspection drone will be sent to the remote monitoring center through the 5G dedicated channel so that the remote monitoring center can further analyze the inspection data.

[0116] In other specific implementations, when the inspection drone detects that the 5G signal strength of the current network has reached the signal strength threshold during the inspection process, the inspection drone processes the captured data images through the edge computing box and sends the fault identification results after fault monitoring to the remote monitoring center through a dedicated channel.

[0117] In some embodiments, the charging communication port includes a charging sub-port and a communication sub-port that are independent of each other;

[0118] The communication connector is equipped with a retractable plug, which includes a charging sub-connector adapted to the charging sub-port and a communication sub-connector adapted to the communication sub-port.

[0119] The edge processing device is configured to: if it detects that the battery level of the inspection drone is lower than a set threshold, control the charging sub-connector to supply power to the inspection drone, and at the same time receive the inspection data sent by the inspection drone through the communication sub-connector.

[0120] In this embodiment, to further optimize the coordination efficiency of charging and data transmission in the drone charging connection device, the charging communication port of the inspection drone is equipped with independent charging sub-ports and communication sub-ports. This separate design allows for the independent operation and synchronous implementation of charging and data transmission functions. Correspondingly, the retractable plug of the communication connector also has charging sub-connectors and communication sub-connectors, which can be plugged into the charging sub-port and communication sub-port of the charging communication port, respectively. During actual operation, the edge processing device is configured to monitor the battery status of the inspection drone in real time. If the battery level is detected to be below a set threshold, a collaborative control process is initiated: on the one hand, the charging sub-connector of the retractable plug is connected to the charging sub-port of the charging communication port to supply power to the inspection drone; on the other hand, while charging, the inspection data sent by the inspection drone is simultaneously received through the connection of the communication sub-connector of the retractable plug to the communication sub-port of the charging communication port, eliminating the need to wait for charging to complete before data transmission. This greatly improves the transmission efficiency of inspection data and further enhances the reliable transmission of inspection data in scenarios with no or poor 5G signal. In addition, the edge computing device is networked with the drone, enabling it to acquire image information captured by the drone in real time and store the image information locally. In practical applications, if it is determined that the drone and the edge computing device are connected via a 5G communication link, the device acquires image data captured by the drone in real time or image data stored locally. If it is determined that the drone and the edge monitoring device are connected via a BeiDou link, the device acquires warning information indicating faults sent by the edge computing device deployed on the bottom of the drone in real time, and sends the received warning information to the remote monitoring system in the form of BeiDou short messages.

[0121] In some embodiments, the edge processing device is configured to: if it detects that an inspection drone has entered the radio frequency transmission range of the LoRa communication module, attempt to establish a LoRa communication connection with the inspection drone; if the connection is successful, receive the inspection data sent by the inspection drone through the LoRa communication module; if the connection fails, control the drone charging connection device to receive the inspection data sent by the inspection drone through a wired connection.

[0122] In this embodiment, a LoRa communication module is provided to further enrich the transmission path of inspection data and improve the flexibility and reliability of data transmission. During actual operation, the edge processing device is configured to monitor the location status of the inspection drone in real time. When the inspection drone enters the preset radio frequency transmission range of the LoRa communication module, it first attempts to establish a LoRa communication connection with the drone. This leverages the low power consumption and long-distance transmission advantages of LoRa communication technology to achieve wireless transmission of inspection data without requiring the drone to dock for charging, thus improving data transmission efficiency. If the LoRa communication connection fails due to signal interference, equipment failure, or other reasons (i.e., when the inspection drone determines that the LoRa communication module is not responding), the edge processing device switches the data transmission mode and controls the previously configured drone charging connection device to initiate a wired connection process. This involves connecting the device to the drone's charging communication port via a communication plug-in mechanism to receive the inspection data sent by the drone via a wired connection.

[0123] In some embodiments, the edge processing device is further configured to:

[0124] During the transmission of inspection data through the LoRa communication module, the current frequency usage, current signal-to-noise ratio, current signal strength, and current network load of the neighboring wireless communication network are obtained. The various information of the neighboring wireless communication network are then input into the model used to determine the transmission channel to obtain the spreading factor, bandwidth, coding rate, operating frequency, data transmission frequency, and current frequency band channel.

[0125] The data transmission configuration of the LoRa communication module is adjusted according to the obtained spreading factor, bandwidth, coding rate, operating frequency, and data transmission frequency, and the current frequency band channel is used as the transmission channel, thereby realizing the dynamic adjustment of the LoRa communication module.

[0126] It should be noted that the nearby wireless communication network refers to various wireless communication networks that are geographically close to the distribution network communication network where the LoRa communication module is located and may cause signal interaction or interference. The model used to determine the transmission channel can be a rule-driven computational model or a machine learning model. By receiving data from the nearby wireless communication network collected by the edge processing device, and combining the data parsing and logical operations with the requirements of LoRa communication in the power distribution network inspection scenario, the transmission channel with minimal communication interference and optimal transmission efficiency, along with the corresponding parameter settings, can be obtained.

[0127] In this embodiment, to further optimize communication efficiency, avoid interference, and ensure communication quality under harsh conditions, the edge processing device is also configured to dynamically adjust the transmission parameters of the LoRa communication module. First, the edge processing device actively acquires key information about the neighboring wireless communication network, specifically including current frequency usage, current signal-to-noise ratio, current signal strength, and current network load. Next, the edge processing device inputs the collected information from the neighboring network into a pre-set model for determining the transmission channel. Through model analysis and calculation, it obtains the spreading factor, bandwidth, coding rate, operating frequency, data transmission frequency, and current frequency band channel suitable for the current environment, ensuring that all parameters match the actual communication scenario. Subsequently, the edge processing device adjusts the data transmission configuration of the LoRa communication module according to the model output, and uses the determined current frequency band channel as the transmission channel for the inspection data. During the dynamic adjustment process, communication efficiency is improved by optimizing the spreading factor, bandwidth, and coding rate. Simultaneously, the frequency band with the least interference and highest signal-to-noise ratio is selected by referencing the frequency usage of neighboring networks. The operating frequency and data transmission frequency can be flexibly adjusted to avoid sudden interference. If interference is detected between the current frequency usage of a neighboring network and the local network, the process returns to the step of obtaining neighboring network information and recalculating and adjusting parameters. This embodiment fully considers the impact of neighboring networks, effectively avoiding co-channel interference. Even under adverse communication conditions, it can maintain minimum communication quality through dynamic adjustment, ensuring the stability and reliability of inspection data transmission.

[0128] In some embodiments, the mobility mechanism includes:

[0129] Horizontal motion platform, vertical motion platform, and rotary platform;

[0130] The horizontal motion platform is installed at the monitored power equipment;

[0131] The vertical motion platform is installed on the horizontal motion platform;

[0132] The rotating platform is mounted on the vertical motion platform;

[0133] The communication connector is mounted on a rotating platform;

[0134] The horizontal motion platform, vertical motion platform, and rotary platform are all electrically connected to the edge processing equipment.

[0135] The edge processing device is configured to control the coordinated movement of the horizontal motion platform, the vertical motion platform, and the rotating platform, thereby driving the communication plug-in mechanism to connect to the charging and communication port of the inspection drone.

[0136] In this embodiment, the moving mechanism consists of a horizontal motion platform, a vertical motion platform, and a rotating platform. The horizontal motion platform, serving as the basic support, is directly installed at the monitored power equipment, providing a stable mounting base for the entire moving mechanism. The vertical motion platform is installed on top of the horizontal motion platform, enabling vertical position adjustment. The rotating platform is installed on top of the vertical motion platform, driving the communication plug-in mechanism to rotate at an angle. The communication plug-in mechanism is ultimately fixed to the rotating platform, and all three move together in three dimensions. The edge processing device controls the coordinated movement of the three platforms based on the position information of the inspection drone's charging communication port obtained by the position receiver. The horizontal motion platform adjusts the left-right and front-back positions of the communication plug-in mechanism on the horizontal plane, the vertical motion platform adjusts its vertical height, and the rotating platform corrects its docking angle, ultimately allowing the communication plug-in mechanism to align and dock with the inspection drone's charging communication port in three-dimensional space.

[0137] For example, Figure 4The structural design of a drone charging connection device is shown. The device includes a horizontal motion platform 1, a vertical motion platform 2, a rotating platform 3, and a communication connection mechanism 4. The horizontal motion platform 1 is housed within a receiving cavity 5. The vertical motion platform 2 is mounted on the horizontal motion platform 1 and can move horizontally under the influence of the horizontal motion platform 1. The rotating platform 3 is mounted on the vertical motion platform 2 and can move vertically under the influence of the vertical motion platform 2. The communication connection mechanism 4 is mounted on the rotating platform 3. The horizontal motion platform 1, vertical motion platform 2, and rotating platform 3 are all electrically connected to an edge processing device to drive the communication connection mechanism 4 to achieve horizontal, vertical, and rotational movements. Above the communication connection mechanism 4 is the charging cavity 6. The horizontal motion platform 1 includes a horizontal motor 11, a horizontal lead screw 12, a horizontal balance lead screw 13, two horizontal bearings, and a horizontal threaded plate 14 with two threaded holes. The output end of the horizontal motor 11 is equipped with a horizontal lead screw 12. The vertical motion platform 2 includes a vertical motor, a vertical lead screw 21, a vertical balance lead screw 22, two vertical bearings, and a vertical threaded plate 23 with two threaded holes. The rotating platform 3 includes a rotating motor 31 and a rotating table 32. The communication plug-in mechanism 4 includes a longitudinal motor 41, a longitudinal lead screw 42, a threaded tube 43, and a plug (including a communication plug 44 and a charging plug 45). The horizontal lead screw 12 and the horizontal balance lead screw 13 are fitted into the corresponding threaded holes of the horizontal threaded plate 14, and the output ends of both the horizontal lead screw 12 and the horizontal balance lead screw 13 are connected to water. A horizontal bearing is mounted on the receiving cavity 5; a vertical motor is mounted on a horizontal threaded plate 14, and a vertical lead screw 21 is mounted on the output end of the vertical motor. The vertical lead screw 21 and the vertical balance lead screw 22 are fitted into the corresponding threaded holes of the vertical threaded plate 23, and the output ends of the vertical lead screw 21 and the vertical balance lead screw 22 are both connected to the vertical bearing. The vertical bearing is mounted on the horizontal threaded plate 14 or the receiving cavity 5; a rotary motor 31 is mounted at the middle position of the vertical threaded plate 23, and one end face of the rotary table 32 is mounted on the output end of the rotary motor 31. A longitudinal motor 41 is also mounted on the other end face of the rotary table 32. A longitudinal lead screw 42 is mounted on the output end of the longitudinal motor 41, and a threaded tube 43 is fitted onto the longitudinal lead screw 42. A charging plug 44 and a communication plug 45 are mounted on the end of the threaded tube 43.

[0138] In some embodiments, the edge processing device is further configured to:

[0139] Perform fault identification and processing on the received inspection data;

[0140] If a fault is identified, the fault identification result is marked as the highest priority;

[0141] If the signal strength of the 5G communication module is higher than the set signal strength threshold, the fault identification result will be sent through the 5G communication module.

[0142] If the signal strength of the 5G communication module is lower than or equal to the set signal strength threshold, the fault identification result will be used as key data and sent to the remote monitoring center via the Beidou short message communication module. At the same time, the fault identification result and the original inspection data will be stored locally. After the signal strength of the 5G communication module is restored, the original inspection data will be sent to the remote monitoring center.

[0143] In the technical solution provided in this embodiment, the transmission method for optimizing power grid data is applied to a monitoring platform. This monitoring platform enables multi-channel transmission and integrates these multi-channel transmissions to ensure timely and unimpeded transmission of inspection data to the remote monitoring center. Based on the integrated power emergency technology of 5G, LoRa, and BeiDou navigation, the high bandwidth and low latency of 5G allow for rapid acquisition of on-site information, enabling real-time monitoring and positioning of tower information. Simultaneously, the precise positioning function of the BeiDou navigation system improves the accuracy and reliability of monitoring. Furthermore, based on real-time monitoring and analysis results, an adaptive communication strategy is formulated to automatically adjust communication parameters to adapt to dynamically changing communication conditions. A comprehensive signal quality scoring model is constructed, integrating multiple signal quality indicators to form a unified scoring system that intuitively reflects the overall performance of communication signals. A real-time feedback mechanism is also built to immediately notify system administrators or automatically trigger emergency plans when network anomalies are detected. Data analysis techniques such as statistics and machine learning are used to deeply explore the patterns and rules behind communication data, providing data support for communication network optimization. A fault prediction model is developed to predict potential communication faults by analyzing historical and real-time monitoring data, and provides fault diagnosis solutions, resulting in a better user experience.

[0144] Based on the same inventive concept, this application also provides a transmission apparatus for optimizing power grid data services, which implements the above-described transmission method for optimizing power grid data services. The solution provided by this apparatus is similar to the solution described in the above-described method. Therefore, the specific limitations in the embodiments of the transmission apparatus for optimizing power grid data services provided below can be found in the limitations of the transmission method for optimizing power grid data services described above, and will not be repeated here.

[0145] Please see Figure 5This embodiment provides a transmission device 500 for optimizing data services on a dedicated power grid. It is applied to a monitoring platform equipped with 5G communication, BeiDou short message communication, and LoRa communication. The monitoring platform is equipped with edge processing devices and is communicatively connected to a remote monitoring center.

[0146] The transmission device includes:

[0147] The network startup and service module 501 is used to start the 5G network of the monitoring platform and monitor the current network communication status. If the current network communication status is in a communicable state, it acquires service data and determines the service type. Based on the determined service type, it selects an appropriate 5G network communication channel as the transmission network to transmit the service data of the corresponding service type.

[0148] The signal judgment and transmission module 502 is used to determine the signal quality of the current transmission network. If the signal quality of the current transmission network is higher than a set threshold, the corresponding service data is transmitted to the remote monitoring center via 5G communication. At the same time, during the service data transmission, the transmission rate of the current transmission network is monitored. When the transmission rate is detected to be higher than or equal to the first transmission rate threshold, the maintenance module is triggered. When the transmission rate is detected to be lower than the first transmission rate threshold but higher than or equal to the second transmission rate threshold, the rate optimization module is triggered. When the transmission rate is detected to be lower than the second transmission rate threshold, the channel switching and processing module is triggered.

[0149] The maintenance module 503 is used to maintain the use of the 5G network communication channel as the current transmission network for transmitting service data.

[0150] The rate optimization module 504 is used to optimize and adjust the communication parameters of the current transmission network;

[0151] The channel switching and processing module 505 is used to switch to the LORA technology radio frequency channel, transmit service data to the edge processing device through the LORA technology radio frequency channel, so that the edge processing device can perform service processing on the service data, and transmit the processing results to the remote monitoring center through the Beidou short message channel.

[0152] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0153] Reference Figure 6 The present invention also provides a computer device, including: a memory and a processor, and a computer program stored in the memory. When the computer program is executed on the processor, it implements the transmission method for optimizing power grid data services as described in any of the above methods.

[0154] The computer device may be a desktop computer, laptop, handheld computer, or cloud server, etc. This computer device may include, but is not limited to, a processor and memory. Those skilled in the art will understand that... Figure 6 The examples of computer devices are merely examples and do not constitute a limitation on computer devices. They may include more or fewer components than shown in the illustration, or combinations of certain components, or different components. For example, they may also include input / output devices, network access devices, etc.

[0155] The processor referred to can be a Central Processing Unit (CPU), but it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0156] In some embodiments, the memory may be an internal storage unit of the computer device, such as a hard drive or RAM. In other embodiments, the memory may be an external storage device of the computer device, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, the memory may include both internal and external storage units of the computer device. The memory is used to store the operating system, applications, boot loader, data, and other programs, such as the program code of the computer program. The memory can also be used to temporarily store data that has been output or will be output.

[0157] This invention also provides a computer-readable storage medium storing a computer program thereon. When the computer program is run by a processor, it implements a transmission method for optimizing power grid data services, as described in any of the above methods.

[0158] In this embodiment, if the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to a photographing device / terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0159] This invention provides a computer program product, including a computer program that, when executed by a processor, implements a transmission method for optimizing data transfer services on a dedicated power grid, as described in any of the above methods.

[0160] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0161] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0162] In the embodiments disclosed in this application, it should be understood that the disclosed devices / terminal equipment and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling or direct coupling or communication connection may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0163] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A transmission method for optimizing data services in a dedicated power grid, characterized in that, An application is made to a monitoring platform equipped with 5G communication, BeiDou short message communication, and LoRa communication. The monitoring platform is equipped with edge processing devices and is communicatively connected to a remote monitoring center. The transmission method includes: The monitoring platform's 5G network is activated and the current network communication status is monitored. If the current network communication status is in a communicable state, the service data is obtained and the service type is determined. Based on the determined service type, an appropriate 5G network communication channel is selected as the transmission network to transmit the service data of the corresponding service type. Determine the signal quality of the current transmission network. If the signal quality of the current transmission network is higher than a set threshold, transmit the corresponding service data to the remote monitoring center via 5G communication. At the same time, monitor the transmission rate of the current transmission network during the service data transmission process. If the transmission rate is detected to be higher than or equal to the first transmission rate threshold, the 5G network communication channel will continue to be used as the current transmission network to transmit service data. If the transmission rate is detected to be lower than the first transmission rate threshold but higher than or equal to the second transmission rate threshold, the current transmission network communication parameters are optimized and adjusted. If the transmission rate is detected to be lower than the second transmission rate threshold, the system switches to the LORA technology radio frequency channel and transmits the service data to the edge processing device through the LORA technology radio frequency channel, so that the edge processing device can process the service data and transmit the processing result to the remote monitoring center through the Beidou short message channel.

2. The transmission method for optimizing services of power private network data according to claim 1, characterized in that, After monitoring the transmission rate of the current transmission network, the method further includes: Generate a trend of transmission rate change based on the aforementioned transmission rate; Based on the changing trend, the transmission rate at the next moment is predicted. If the predicted transmission rate is lower than the first transmission rate threshold but higher than or equal to the second transmission rate threshold, the communication parameters of the current transmission network are optimized and adjusted, and the optimized transmission network is taken as the latest current transmission network. At the same time, the current transmission network is monitored again.

3. The transmission method for optimizing services of power private network data according to claim 1, characterized in that, Determining the signal quality of the current transmission network includes: Monitor the channel of the current transmission network and determine the various indicators that affect the network signal quality as signal quality parameters; The determined signal quality parameters are input into the constructed signal quality scoring model to obtain an information quality score used to evaluate the strength of the current network signal.

4. The transmission method for optimizing services of power private network data according to claim 3, characterized in that, The signal quality scoring model is a model determined by fusing the signal quality parameters and the service type according to the importance of each signal quality parameter to the determined service type. After inputting the determined signal quality parameters into the constructed signal quality scoring model to obtain the information quality score used to evaluate the strength of the current network signal, the process further includes: If the information quality score is higher than or equal to the set score threshold, it is determined that the signal quality of the current transmission network is higher than the set threshold, and then the corresponding service data is transmitted to the remote monitoring center via 5G communication.

5. The transmission method for optimizing services of power private network data according to claim 4, characterized in that, It also includes updating the signal quality scoring model, and the update process includes: Based on the current service type, determine the weight percentage of the signal quality parameter's influence on the service type, and use the weight percentage of the signal quality parameter as the current weight parameter; The signal quality scoring model is adjusted based on the determined current weight parameters to generate a new signal quality scoring model; Replace the existing signal quality scoring model with a new one.

6. The transmission method for optimizing services of power private network data according to claim 1, characterized in that, If the service data includes image data, then transmitting the service data to the edge processing device via the LoRa technology radio frequency channel, so that the edge processing device can perform service processing on the service data, includes: The image data is transmitted to the edge processing device via the LORA technology radio frequency channel; The image data is transmitted to the edge processing device for processing, whereby the edge processing device preprocesses the business data and inputs the preprocessed business data into a pre-built image recognition model to obtain image recognition results. The image recognition results are then classified to obtain classification results. Finally, the processed business data is input into a fault identification model corresponding to the classification results to obtain business processing results. The fault identification model is a pre-trained machine learning model used to identify faults in power components; different classification results correspond to different fault identification models. Receive the service processing results sent by the edge processing device.

7. The transmission method for optimizing services of power private network data according to claim 1, characterized in that, The optimization and adjustment of the current transmission network communication parameters includes: Obtain communication parameters that affect the transmission rate; The communication parameters are input into the trained fault prediction model to obtain the communication fault prediction result of the current network channel; An optimization scheme is matched based on the communication fault prediction results, and the current transmission network communication parameters are optimized and adjusted according to the optimization scheme.

8. A transmission device for optimizing data services in a dedicated power grid, characterized in that, This is applied to a monitoring platform equipped with 5G communication, BeiDou short message communication, and LoRa communication. The monitoring platform is equipped with edge processing devices and is communicatively connected to a remote monitoring center. The transmission device includes: The network startup and service module is used to start the 5G network of the monitoring platform and monitor the current network communication status. If the current network communication status is in a communicable state, it acquires service data and determines the service type. Based on the determined service type, it selects an appropriate 5G network communication channel as the transmission network to transmit the service data of the corresponding service type. The signal judgment and transmission module is used to determine the signal quality of the current transmission network. If the signal quality of the current transmission network is higher than a set threshold, the corresponding service data is transmitted to the remote monitoring center via 5G communication. At the same time, during the service data transmission, the transmission rate of the current transmission network is monitored. When the transmission rate is detected to be higher than or equal to a first transmission rate threshold, the maintenance module is triggered. When the transmission rate is detected to be lower than the first transmission rate threshold but higher than or equal to a second transmission rate threshold, the rate optimization module is triggered. When the transmission rate is detected to be lower than the second transmission rate threshold, the channel switching and processing module is triggered. The maintenance module is used to maintain the use of the 5G network communication channel as the current transmission network for transmitting service data. The rate optimization module is used to optimize and adjust the communication parameters of the current transmission network. The channel switching and processing module is used to switch to the LORA technology radio frequency channel, transmit the service data to the edge processing device through the LORA technology radio frequency channel, so that the edge processing device can perform service processing on the service data, and transmit the processing result to the remote monitoring center through the Beidou short message channel.

9. A computer device, characterized in that, The device includes a processor and a memory: The memory is used to store computer programs and send the instructions of the computer programs to the processor; The processor executes, according to the instructions of the computer program, a transmission method for optimizing data services in a dedicated power grid as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which, when executed by a processor, implements a transmission method for optimizing data transfer services for power grid private networks as described in any one of claims 1-7.

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