Multi-hop relay networking transmission method and system based on multi-dimensional data

Abstract

The invention relates to the technical field of data transmission, and discloses a multi-hop relay networking transmission method and system based on multi-dimensional data. The method comprises the steps of acquiring obstacle data and wind direction data, generating a multi-hop relay networking strategy library, updating the obstacle data and the wind direction data, outputting a plurality of corresponding multi-hop relay networking strategies, screening the multi-hop relay networking strategies, performing multi-hop relay networking and performing centralized monitoring and early warning. The system corresponds to the method. According to the application, multi-hop relay networking is carried out by acquiring the historical wind field obstacle data and the wind direction data, the strategy library is generated, the data is updated in combination with the mobile monitoring equipment, and the strategy is screened through similarity analysis and energy analysis, so that multi-dimensional data-based multi-hop relay networking transmission is finally realized; therefore, the stability, timeliness and continuity of wind field data transmission are optimized.

Description

Technical Field

[0001] The present application relates to the technical field of data transmission, and in particular to a multi-hop relay networking transmission method and system based on multi-dimensional data. Background Art

[0002] In the field of wind power generation, data transmission in wind farms is extremely important. With the continuous development of technology, the scale of wind farms continues to expand, the number of wind turbines is also increasing, and the requirements for data transmission are also getting higher and higher. However, the inventors found that the existing technology has the following problems in their research on wind farm data transmission methods:

[0003] 1. Rely on traditional wired or single wireless transmission methods. In wired transmission, the wiring cost is high and maintenance is difficult, especially in wind farm environments with complex terrain, which are greatly restricted by topography. Single wireless transmission methods often have the problem of incomplete signal coverage. The hills, gullies and other terrains in the wind farm and the structure of the wind turbine itself may block and interfere with the signal, resulting in unstable data transmission.

[0004] 2. The data types in wind farms are becoming increasingly diverse, including wind turbine operating status data, meteorological data and other multi-dimensional data. The existing transmission methods are inefficient in processing these multi-dimensional data. For operating status data with high real-time requirements, traditional transmission methods may be delayed, affecting the timely monitoring and fault diagnosis of wind turbines.

[0005] 3. Wind farms are usually located in remote areas with limited power supply conditions for equipment. Existing transmission methods also lack effective control strategies in terms of energy consumption, which may lead to insufficient equipment endurance and affect the continuity of data transmission.

[0006] In the existing technology, multi-dimensional data processing and multi-hop relay networking transmission, due to their characteristics corresponding to wind farm data and wind farm environment, research on multi-hop relay networking transmission based on multi-dimensional data is a feasible technical direction to optimize the stability, timeliness and sustainability of wind farm data transmission.

[0007] Therefore, a new technical solution for multi-hop relay networking transmission based on multi-dimensional data is urgently needed to optimize the stability, timeliness and continuity of wind farm data transmission. Summary of the invention

[0008] The purpose of this application is to provide a multi-hop relay networking transmission method and system based on multi-dimensional data to solve the technical problems raised in the above background technology.

[0009] To achieve the above objectives, this application discloses the following technical solutions:

[0010] In a first aspect, the present application discloses a multi-hop relay networking transmission method based on multi-dimensional data, the method comprising:

[0011] S1: Obtain historical obstacle data and wind direction data of the wind field, perform multi-hop relay networking, and generate a multi-hop relay networking strategy library; wherein the obstacle data is used to perform multi-hop relay networking based on the obstacle conditions of the wind field, and the obstacle conditions at least include terrain conditions; the wind direction data is used to perform multi-hop relay networking based on the wind direction conditions of the wind field, and the wind direction conditions are the wind directions corresponding to the transmission nodes for performing multi-hop relay networking; the multi-hop relay networking is used to generate corresponding multi-hop relay networking strategies for guiding multi-hop relay networking based on the obstacle data and the wind direction data; the multi-hop relay networking strategy library stores a plurality of the multi-hop relay networking strategies and the corresponding obstacle data and wind direction data;

[0012] S2: using a mobile monitoring device to obtain updated obstacle data and wind direction data;

[0013] S3: Outputting corresponding multiple multi-hop relay networking strategies using similarity analysis technology;

[0014] S4: Filtering the multiple multi-hop relay networking strategies obtained in step S3 using energy analysis technology; wherein the screening conditions include at least a remaining energy value and a charging efficiency value, wherein the remaining energy value is used to characterize the duration for which the current transmission node can continue to operate, and the charging efficiency value is used to characterize the impact of the current transmission node on data transmission when charging, and the higher the charging efficiency value, the smaller the impact of the current transmission node on data transmission when charging;

[0015] S5: Perform multi-hop relay networking using the multi-hop relay networking strategy obtained by screening in step S4;

[0016] S6: Conduct centralized monitoring and early warning of the data transmission network that implements multi-hop relay networking.

[0017] As a preference, the multi-hop relay networking is performed in step S1 to generate a multi-hop relay networking strategy library, specifically:

[0018] Based on the obstacle data and wind direction data of the historical wind farm, a multi-hop relay combination is performed on each transmission node in the wind farm, and the result of the multi-hop relay combination is extracted to generate a corresponding multi-hop relay networking strategy;

[0019] The multi-hop relay networking strategy library is generated by utilizing the expert database technology and combining the obtained multi-hop relay networking strategy.

[0020] Preferably, the obstacle data is used to perform multi-hop relay networking based on the obstacle conditions of the wind farm, specifically: performing field measurements and modeling to determine the best path for signal propagation.

[0021] Preferably, the wind direction data is used for multi-hop relay networking based on the wind direction of the wind field, specifically: dynamically adjusting the data transmission path based on changes in wind direction.

[0022] Preferably, the mobile monitoring device is equipped with at least a sensor for identifying obstacles and a sensor for wind direction.

[0023] Preferably, step S3 is specifically:

[0024] A similarity match is performed with the obstacle data and the wind direction data of the historical wind farm in the multi-hop relay networking strategy library, and the multi-hop relay networking strategy corresponding to the obstacle data and the wind direction data of the historical wind farm that meet a preset similarity threshold is output.

[0025] Preferably, step S4 is specifically:

[0026] S41: obtaining the residual energy value according to the residual energy of each transmission node, the data transmission demand and the network topology, and dynamically adjusting the transmission power and the working mode based on the residual energy value;

[0027] S42: using energy collection technology, setting a corresponding energy collection device at each transmission node, and collecting energy to obtain a charging efficiency value, and updating step S41;

[0028] S43: Based on the result of the dynamic adjustment of the transmission power and the working mode in step S41, screening is performed, and the result of the screening is the multi-hop relay networking strategy corresponding to the maximum value after combining the remaining energy value and the charging efficiency value.

[0029] Preferably, step S5 is specifically:

[0030] Based on the multi-hop relay networking strategy obtained by screening in step S4, communication connections are established between corresponding transmission nodes to perform data transmission.

[0031] Preferably, step S6 is specifically:

[0032] Monitor the operating status and equipment health of the data transmission network constructed in step S5 in real time, use machine learning technology to predict faults, and perform remote centralized management and control based on the results of fault prediction. The remote centralized management and control at least includes remote early warning and calling the corresponding mobile application to assist in data transmission control.

[0033] In a second aspect, the present application discloses a multi-hop relay networking transmission system based on multi-dimensional data, which is applicable to the multi-hop relay networking transmission system based on multi-dimensional data as described above, and is characterized in that the system includes:

[0034] A data acquisition module, wherein the data acquisition module is configured to: acquire historical obstacle data and wind direction data of a wind farm, perform multi-hop relay networking, and generate a multi-hop relay networking strategy library; wherein the obstacle data is used to perform multi-hop relay networking based on the obstacle conditions of the wind farm, and the obstacle conditions at least include terrain conditions; the wind direction data is used to perform multi-hop relay networking based on the wind direction conditions of the wind farm, and the wind direction conditions are the wind directions corresponding to the transmission nodes for performing multi-hop relay networking; the multi-hop relay networking is used to generate corresponding multi-hop relay networking strategies for guiding multi-hop relay networking based on the obstacle data and the wind direction data; and the multi-hop relay networking strategy library stores a plurality of the multi-hop relay networking strategies and the corresponding obstacle data and wind direction data;

[0035] A data updating module, wherein the data updating module is configured to: obtain updated obstacle data and wind direction data using a mobile monitoring device;

[0036] A strategy generation module, wherein the strategy generation module is configured to: output a corresponding plurality of the multi-hop relay networking strategies using a similarity analysis technology;

[0037] A strategy screening module, wherein the strategy screening module is configured to: use energy analysis technology to screen the multiple multi-hop relay networking strategies obtained in step S3; wherein the screening conditions include at least a remaining energy value and a charging efficiency value, wherein the remaining energy value is used to characterize the duration for which the current transmission node can continue to operate, and the charging efficiency value is used to characterize the impact of the current transmission node on data transmission when charging, and the higher the charging efficiency value, the smaller the impact of the current transmission node on data transmission when charging;

[0038] A networking execution module, wherein the networking execution module is configured to: perform multi-hop relay networking using the multi-hop relay networking strategy obtained by screening in step S4;

[0039] A monitoring and early warning module, wherein the monitoring and early warning module is configured to: centrally monitor and early warning the data transmission network that performs multi-hop relay networking;

[0040] Among them, the data acquisition module, the data update module, the policy generation module, the policy screening module and the networking execution module are all communicatively connected with the monitoring and early warning module, the data acquisition module is communicatively connected with the data update module, the data update module is communicatively connected with the policy generation module, the policy generation module is communicatively connected with the policy screening module, and the policy screening module is communicatively connected with the networking execution module.

[0041] Beneficial effects: The multi-hop relay networking transmission method and system based on multi-dimensional data of the present application, by virtue of the above, this embodiment utilizes the acquisition of historical wind farm obstacle data and wind direction data for multi-hop relay networking, generates a strategy library, and combines the mobile monitoring device to update the data, and selects the strategy through similarity analysis and energy analysis, and finally realizes the multi-hop relay networking transmission based on multi-dimensional data to optimize the stability, timeliness and continuity of wind farm data transmission. Specifically, it includes generating a strategy library according to the obstacle and wind direction conditions, using mobile monitoring equipment to obtain new data, outputting multiple strategies and selecting the optimal strategy for networking, and finally centrally monitoring and warning the data transmission network, thereby effectively solving the problems of high wired transmission cost, unstable wireless transmission, low multi-dimensional data processing efficiency and insufficient energy supply in the existing wind farm data transmission. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without paying any creative work.

[0043] Figure 1 A flowchart of a multi-hop relay networking transmission method based on multi-dimensional data provided in an embodiment of the present application;

[0044] Figure 2 A structural block diagram of a multi-hop relay networking transmission system based on multi-dimensional data provided in an embodiment of the present application. DETAILED DESCRIPTION

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

[0046] In this article, the term "comprising" is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of more restrictions, the elements defined by the sentence "comprising..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0047] The first aspect of this embodiment discloses Figure 1 A multi-hop relay networking transmission method based on multi-dimensional data is shown, the method comprising:

[0048] S1: Obtain historical obstacle data and wind direction data of the wind farm, perform multi-hop relay networking, and generate a multi-hop relay networking strategy library; wherein the obstacle data is used to perform multi-hop relay networking based on the obstacle conditions of the wind farm, and the obstacle conditions at least include the terrain conditions; the wind direction data is used to perform multi-hop relay networking based on the wind direction conditions of the wind farm, and the wind direction conditions are the wind directions corresponding to the transmission nodes for performing multi-hop relay networking; the multi-hop relay networking is used to generate corresponding multi-hop relay networking strategies for guiding multi-hop relay networking based on the obstacle data and wind direction data; the multi-hop relay networking strategy library stores a variety of multi-hop relay networking strategies and corresponding obstacle data and wind direction data;

[0049] S2: Use mobile monitoring equipment to obtain updated obstacle data and wind direction data;

[0050] S3: Use similarity analysis technology to output corresponding multiple multi-hop relay networking strategies;

[0051] S4: using energy analysis technology to screen multiple multi-hop relay networking strategies obtained in step S3; wherein the screening conditions include at least a remaining energy value and a charging efficiency value, the remaining energy value is used to characterize the duration for which the current transmission node can continue to operate, and the charging efficiency value is used to characterize the impact of the current transmission node on data transmission when charging, and the higher the charging efficiency value, the smaller the impact of the current transmission node on data transmission when charging;

[0052] S5: Perform multi-hop relay networking using the multi-hop relay networking strategy obtained by screening in step S4;

[0053] S6: Conduct centralized monitoring and early warning of the data transmission network that implements multi-hop relay networking.

[0054] In a specific application, this embodiment arranges a large number of different types of sensors in a wind farm, such as wind speed sensors, wind direction sensors, temperature sensors, vibration sensors, sound sensors, etc., to collect multi-dimensional data such as the operating status of wind turbines and meteorological conditions, and uses existing data fusion algorithms to deeply fuse these multi-source data to obtain more comprehensive and accurate wind farm information. For example, by fusing vibration and sound data, it is possible to more accurately determine whether the mechanical parts of the wind turbine have abnormal wear or failure.

[0055] Based on the above, this embodiment uses the acquisition of historical wind farm obstacle data and wind direction data to perform multi-hop relay networking, generate a strategy library, and combine the mobile monitoring device to update the data. Through similarity analysis and energy analysis, the strategy is screened, and finally the multi-hop relay networking transmission based on multi-dimensional data is realized to optimize the stability, timeliness and sustainability of wind farm data transmission. Specifically, it includes generating a strategy library according to obstacles and wind direction conditions, using mobile monitoring equipment to obtain new data, outputting multiple strategies and screening out the optimal strategy for networking, and finally centrally monitoring and warning the data transmission network, thereby effectively solving the problems of high wired transmission cost, unstable wireless transmission, low multi-dimensional data processing efficiency and insufficient energy supply in existing wind farm data transmission.

[0056] Specifically, the multi-hop relay networking is performed in step S1 to generate a multi-hop relay networking strategy library, specifically:

[0057] Based on the historical obstacle data and wind direction data of the wind farm, the transmission nodes in the wind farm are combined by multi-hop relay, and the results of the multi-hop relay combination are extracted to generate the corresponding multi-hop relay networking strategy;

[0058] By using the expert database technology and combining the obtained multi-hop relay networking strategy, a multi-hop relay networking strategy library is generated.

[0059] It should be noted that the method for initially combining transmission nodes in the wind farm in a multi-hop relay in this embodiment may be, but is not limited to, manual combination and verification using expert experience, and generation of a multi-hop relay networking strategy library using existing knowledge base technology.

[0060] Based on the above, this embodiment uses historical obstacle data and wind direction data to perform multi-hop relay combination of wind farm transmission nodes and extract results, and combines expert library technology to generate a multi-hop relay networking strategy library, which provides a variety of feasible networking strategies for subsequent data transmission, so that they can be selected and applied according to different wind farm conditions.

[0061] Specifically, obstacle data is used to perform multi-hop relay networking based on the obstacle conditions in the wind farm, specifically: conducting field measurements and modeling to determine the best path for signal propagation.

[0062] In a specific application, it is understandable that wind farms are usually distributed over a wide area with complex and diverse topography, and there may be obstacles such as hills, gullies, and buildings. These obstacles will interfere with and block the propagation of wireless signals, affecting the quality and stability of data transmission. Therefore, when designing a routing strategy, it is necessary to fully consider the topographical characteristics of the wind farm, and determine the optimal path for signal propagation through field measurements and modeling of existing technologies. For example, for wind turbines located behind hills, data transmission can be carried out through signal reflection or diffraction to avoid signal attenuation caused by directly crossing the hills. At the same time, for areas where signal interference may exist, signal relay nodes can be added or the transmission power can be adjusted to ensure that data can be transmitted stably.

[0063] Based on the above, this embodiment uses field measurement and modeling to determine the optimal signal propagation path according to the wind field obstacle conditions, realizes multi-hop relay networking based on obstacle data, effectively avoids signals being blocked by obstacles, and improves the stability and reliability of data transmission.

[0064] Specifically, the wind direction data is used to perform multi-hop relay networking based on the wind direction conditions of the wind farm, specifically: dynamically adjusting the data transmission path based on changes in wind direction.

[0065] In a specific application, it is understandable that the wind direction in the wind field is constantly changing, which will affect the propagation of wireless signals. For example, when the wind direction is consistent with the signal propagation direction, the signal propagation speed may be accelerated; when the wind direction is opposite to the signal propagation direction, the signal propagation speed may be slowed down or even blocked. Therefore, when designing a routing strategy, it is necessary to consider the change in wind direction and dynamically adjust the data transmission path. By installing a wind direction sensor, the wind direction change can be monitored in real time and fed back to the routing decision system. For example, when the wind direction changes, the system can automatically adjust the data transmission path and select a path where the signal propagation is less affected by the wind direction for transmission.

[0066] Based on the above, this embodiment utilizes the dynamic adjustment of the data transmission path according to the change of wind direction to realize multi-hop relay networking based on wind direction data. The change of wind direction will affect the signal propagation, and the dynamic adjustment of the path can ensure the high efficiency of data transmission.

[0067] Specifically, the mobile monitoring device is equipped with at least a sensor for identifying obstacles and a sensor for wind direction.

[0068] In a specific application, in order to better adapt to changes in the wind farm environment and improve the adaptability of routing, this embodiment can use drones or mobile monitoring equipment to conduct regular inspections of wind farms. Drones can carry wireless signal monitoring equipment to monitor the signal coverage of wind farms in the air and obtain real-time change information on the wind farm environment. Mobile monitoring equipment can inspect equipment in wind farms on the ground to collect information such as the operating status and signal strength of the equipment. This information can be fed back to the routing decision system to help the system adjust routing strategies in a timely manner and achieve real-time optimization of routing. For example, when a drone detects that signal interference in a certain area is increased, the system can automatically adjust the data transmission path to avoid the area; when a mobile monitoring device finds that the signal strength of a certain device is weak, the system can add signal relay nodes or adjust the transmission power to improve the data transmission quality of the device.

[0069] Based on the above, this embodiment uses mobile monitoring equipment equipped with sensors for identifying obstacles and wind direction to obtain updated obstacle data and wind direction data, providing real-time and accurate data support for multi-hop relay networking.

[0070] Specifically, step S3 is as follows:

[0071] A similarity match is performed with the historical wind farm obstacle data and wind direction data in the multi-hop relay networking strategy library, and a multi-hop relay networking strategy corresponding to the historical wind farm obstacle data and wind direction data that meets a preset similarity threshold is output.

[0072] It should be noted that this embodiment uses existing similarity technology to perform similarity matching, for example, by calculating the Pearson coefficient of obstacle data and wind direction data to achieve similarity analysis, and the similarity threshold is an empirical value known to those skilled in the art.

[0073] Based on the above, this embodiment uses similarity matching in the multi-hop relay networking strategy library to output strategies that meet the similarity threshold, thereby realizing rapid search for appropriate multi-hop relay networking strategies based on new data and improving the efficiency and accuracy of strategy selection.

[0074] Specifically, step S4 is as follows:

[0075] S41: obtaining a residual energy value according to the residual energy of each transmission node, data transmission requirements, and network topology, and dynamically adjusting the transmission power and the working mode based on the residual energy value;

[0076] S42: using energy collection technology, setting a corresponding energy collection device at each transmission node, and collecting energy to obtain a charging efficiency value, and updating step S41;

[0077] S43: Based on the result of the dynamic adjustment of the transmission power and the working mode in step S41, screening is performed, and the result of the screening is a multi-hop relay networking strategy corresponding to the maximum value after the remaining energy value and the charging efficiency value are integrated.

[0078] In a specific application, it is understandable that most of the equipment in the wind farm is distributed in the wild, and the power supply conditions are limited. Therefore, it is necessary to adopt an energy-efficient transmission strategy to reduce the energy consumption of the equipment and extend the service life of the equipment. Among them, the existing dynamic adjustment of transmission power and working mode is an effective method, which can dynamically adjust the transmission power and working mode of the node according to factors such as the remaining energy of the node, data transmission requirements, and network topology. For example, when the remaining energy of the node is low, the transmission power can be reduced to reduce energy consumption; when the data transmission demand is small, it can enter a low-power mode and shut down unnecessary functional modules to reduce energy consumption. At the same time, the transmission power and working mode of the node can also be dynamically adjusted according to the changes in the network topology to improve the efficiency and stability of data transmission. In addition, in order to reduce dependence on external power supplies and improve the endurance of equipment in the wind farm, energy collection technology, such as solar energy and wind energy collection devices, can be introduced. These devices can convert solar energy and wind energy in nature into electrical energy to provide additional energy supply for equipment in the wind farm. At the same time, combined with energy management algorithms, the collected energy is reasonably allocated and utilized to improve energy utilization efficiency. For example, the electric energy collected by the energy harvesting device can be reasonably allocated according to the energy demand and priority of the equipment, and energy supply can be provided to key equipment on a priority basis. When the energy harvesting device collects a large amount of electric energy, the excess electric energy can be stored for emergency use.

[0079] It should be noted that the calculation of the maximum value of the comprehensive remaining energy value and charging efficiency value in this embodiment is achieved by utilizing existing data processing technology, for example, such as weight allocation technology, which performs corresponding weight allocation on the remaining energy value and the charging efficiency value to realize the calculation of the comprehensive remaining energy value and the charging efficiency value.

[0080] Based on the above, this embodiment dynamically adjusts the transmission power and working mode according to the remaining energy value, combines energy collection technology to obtain the charging efficiency value and screen the strategy, and realizes the selection of the optimal multi-hop relay networking strategy based on energy analysis, ensuring data transmission while reducing energy consumption and improving equipment endurance.

[0081] Specifically, step S5 is as follows:

[0082] Based on the multi-hop relay networking strategy obtained by screening in step S4, communication connections are established between corresponding transmission nodes to perform data transmission.

[0083] Based on the above, this embodiment uses the strategy obtained based on screening to perform communication connection and data transmission between transmission nodes, realizes data transmission in multi-hop relay networking, and performs networking according to the optimal strategy to ensure the stability and efficiency of data transmission.

[0084] Specifically, step S6 is as follows:

[0085] Monitor the operating status and equipment health of the data transmission network constructed in step S5 in real time, use machine learning technology to predict faults, and perform remote centralized management and control based on the results of fault prediction. The remote centralized management and control at least includes remote early warning and calling the corresponding mobile application to assist in data transmission control.

[0086] In a specific application, this embodiment establishes an intelligent monitoring and early warning system based on the analysis and processing of multi-dimensional data, which can monitor the operating status of wind turbines, equipment health status and environmental parameters of wind farms in real time, and use existing machine learning and artificial intelligence technologies to learn and analyze the fault modes of wind turbines, thereby realizing fault prediction. Among them, remote centralized management and control, for example, staff can monitor the power generation, operating efficiency and other indicators of wind turbines in real time through the remote management platform, and adjust the operating parameters of wind turbines according to these indicators to improve the power generation efficiency of wind turbines. Calling the corresponding mobile application for auxiliary data transmission control can be through mobile devices such as mobile phones or tablets to access the wind farm management system anytime and anywhere, which is convenient for on-site inspections and emergency handling.

[0087] Based on the above, this embodiment utilizes real-time monitoring of the data transmission network status, fault prediction, and remote centralized management and control to achieve centralized monitoring and early warning of the multi-hop relay networking data transmission network, timely discover and solve problems, and improve the reliability and security of wind farm data transmission.

[0088] The second aspect of this embodiment discloses Figure 2 A multi-hop relay networking transmission system based on multi-dimensional data is shown, which is applicable to the multi-hop relay networking transmission system based on multi-dimensional data as described above, and is characterized in that the system includes:

[0089] A data acquisition module, the data acquisition module is configured to: acquire historical obstacle data and wind direction data of a wind farm, perform multi-hop relay networking, and generate a multi-hop relay networking strategy library; wherein the obstacle data is used to perform multi-hop relay networking based on the obstacle conditions of the wind farm, the obstacle conditions at least include terrain conditions, the wind direction data is used to perform multi-hop relay networking based on the wind direction conditions of the wind farm, the wind direction conditions are the wind directions corresponding to the transmission nodes for performing multi-hop relay networking, the multi-hop relay networking is used to generate corresponding multi-hop relay networking strategies for guiding multi-hop relay networking based on the obstacle data and wind direction data, and the multi-hop relay networking strategy library stores a variety of multi-hop relay networking strategies and corresponding obstacle data and wind direction data;

[0090] The data updating module is configured to: obtain updated obstacle data and wind direction data using a mobile monitoring device;

[0091] The strategy generation module is configured to: output corresponding multiple multi-hop relay networking strategies using similarity analysis technology;

[0092] A strategy screening module, the strategy screening module is configured to: use energy analysis technology to screen multiple multi-hop relay networking strategies obtained in step S3; wherein the screening conditions include at least a remaining energy value and a charging efficiency value, the remaining energy value is used to characterize the duration for which the current transmission node can continue to operate, and the charging efficiency value is used to characterize the impact of the current transmission node on data transmission when charging, and the higher the charging efficiency value, the smaller the impact of the current transmission node on data transmission when charging;

[0093] A networking execution module, wherein the networking execution module is configured to: perform multi-hop relay networking using the multi-hop relay networking strategy obtained by screening in step S4;

[0094] Monitoring and early warning module, the monitoring and early warning module is configured to: centrally monitor and early warning the data transmission network that performs multi-hop relay networking;

[0095] Among them, the data acquisition module, data update module, policy generation module, policy screening module and networking execution module are all communicated with the monitoring and early warning module, the data acquisition module is communicated with the data update module, the data update module is communicated with the policy generation module, the policy generation module is communicated with the policy screening module, and the policy screening module is communicated with the networking execution module.

[0096] It should be noted that the multi-hop relay networking transmission system based on multi-dimensional data of this embodiment corresponds to the aforementioned multi-hop relay networking transmission method based on multi-dimensional data. Therefore, the contents not specifically described in the multi-hop relay networking transmission system based on multi-dimensional data of this embodiment may include but are not limited to function definitions, working principles and technical effects, etc., and may refer to the aforementioned multi-hop relay networking transmission method based on multi-dimensional data, and this text will not elaborate on them here.

[0097] In summary, the multi-hop relay networking transmission method and system based on multi-dimensional data of this embodiment, through the above, this embodiment uses the acquisition of historical wind farm obstacle data and wind direction data for multi-hop relay networking, generates a strategy library, and combines the mobile monitoring device to update data, and selects strategies through similarity analysis and energy analysis, and finally realizes multi-hop relay networking transmission based on multi-dimensional data to optimize the stability, timeliness and sustainability of wind farm data transmission. Specifically, it includes generating a strategy library according to obstacles and wind direction conditions, using mobile monitoring equipment to obtain new data, outputting multiple strategies and selecting the optimal strategy for networking, and finally centrally monitoring and warning the data transmission network, thereby effectively solving the problems of high wired transmission cost, unstable wireless transmission, low multi-dimensional data processing efficiency and insufficient energy supply in existing wind farm data transmission.

[0098] In the embodiments provided in the present application, it should be understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code or any appropriate combination thereof. For hardware implementation, the processor can be implemented in one or more of the following units: application specific integrated circuit (ASIC), digital signal processor (DSP), digital signal processing device (DSPD), programmable logic device (PLD), field programmable gate array (FPGA), processor, controller, microcontroller, microprocessor, other electronic units designed to implement the functions described herein or their combination. For software implementation, part or all of the flow of the embodiment can be completed by instructing the relevant hardware through a computer program. When implemented, the above program can be stored in a computer-readable storage medium or transmitted as one or more instructions or codes on a computer-readable storage medium. Computer-readable storage media include computer storage media and communication media, wherein the communication medium includes any medium that is convenient for transmitting a computer program from one place to another. The storage medium can be any available medium that a computer can access. The computer-readable storage medium can include but is not limited to RAM, ROM, EEPROM, CD-ROM or other optical disk storage, disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of an instruction or data structure and can be accessed by a computer.

[0099] Finally, it should be noted that the above is only a preferred embodiment of the present application and is not intended to limit the present application. Although the present application has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A multi-hop relay networking transmission method based on multi-dimensional data, characterized in that: The method includes: S1: Obtain historical obstacle data and wind direction data of the wind field, perform multi-hop relay networking, and generate a multi-hop relay networking strategy library; wherein the obstacle data is used to perform multi-hop relay networking based on the obstacle conditions of the wind field, and the obstacle conditions at least include terrain conditions; the wind direction data is used to perform multi-hop relay networking based on the wind direction conditions of the wind field, and the wind direction conditions are the wind directions corresponding to the transmission nodes for performing multi-hop relay networking; the multi-hop relay networking is used to generate corresponding multi-hop relay networking strategies for guiding multi-hop relay networking based on the obstacle data and the wind direction data; the multi-hop relay networking strategy library stores a plurality of the multi-hop relay networking strategies and the corresponding obstacle data and wind direction data; S2: using a mobile monitoring device to obtain updated obstacle data and wind direction data; S3: Outputting corresponding multiple multi-hop relay networking strategies using similarity analysis technology; S4: Filtering the multiple multi-hop relay networking strategies obtained in step S3 using energy analysis technology; wherein the screening conditions include at least a remaining energy value and a charging efficiency value, wherein the remaining energy value is used to characterize the duration for which the current transmission node can continue to operate, and the charging efficiency value is used to characterize the impact of the current transmission node on data transmission when charging, and the higher the charging efficiency value, the smaller the impact of the current transmission node on data transmission when charging; S5: Perform multi-hop relay networking using the multi-hop relay networking strategy obtained by screening in step S4; S6: Conduct centralized monitoring and early warning of the data transmission network that implements multi-hop relay networking.

2. The multi-hop relay networking transmission method based on multi-dimensional data according to claim 1, characterized in that: Step S1 performs multi-hop relay networking and generates a multi-hop relay networking strategy library, specifically: Based on the obstacle data and wind direction data of the historical wind farm, a multi-hop relay combination is performed on each transmission node in the wind farm, and the result of the multi-hop relay combination is extracted to generate a corresponding multi-hop relay networking strategy; The multi-hop relay networking strategy library is generated by utilizing the expert database technology and combining the obtained multi-hop relay networking strategy.

3. The multi-hop relay networking transmission method based on multi-dimensional data according to claim 1, characterized in that: The obstacle data is used to perform multi-hop relay networking based on the obstacle conditions of the wind farm, specifically: conduct field measurements and modeling to determine the best path for signal propagation.

4. The multi-hop relay networking transmission method based on multi-dimensional data according to claim 1, characterized in that: The wind direction data is used to perform multi-hop relay networking based on the wind direction conditions of the wind farm, specifically: dynamically adjusting the data transmission path based on changes in wind direction.

5. The multi-hop relay networking transmission method based on multi-dimensional data according to claim 1, characterized in that: The mobile monitoring device is equipped with at least a sensor for identifying obstacles and a sensor for wind direction.

6. The multi-hop relay networking transmission method based on multi-dimensional data according to claim 1, characterized in that: Step S3 is specifically: A similarity match is performed with the obstacle data and the wind direction data of the historical wind farm in the multi-hop relay networking strategy library, and the multi-hop relay networking strategy corresponding to the obstacle data and the wind direction data of the historical wind farm that meet a preset similarity threshold is output.

7. The multi-hop relay networking transmission method based on multi-dimensional data according to claim 1, characterized in that: Step S4 is specifically: S41: obtaining the residual energy value according to the residual energy of each transmission node, the data transmission demand and the network topology, and dynamically adjusting the transmission power and the working mode based on the residual energy value; S42: using energy collection technology, setting a corresponding energy collection device at each transmission node, and collecting energy to obtain a charging efficiency value, and updating step S41; S43: Based on the result of the dynamic adjustment of the transmission power and the working mode in step S41, screening is performed, and the result of the screening is the multi-hop relay networking strategy corresponding to the maximum value after combining the remaining energy value and the charging efficiency value.

8. The multi-hop relay networking transmission method based on multi-dimensional data according to claim 1, characterized in that: Step S5 is specifically: Based on the multi-hop relay networking strategy obtained by screening in step S4, communication connections are established between corresponding transmission nodes to perform data transmission.

9. The multi-hop relay networking transmission method based on multi-dimensional data according to claim 1, characterized in that: Step S6 is specifically: Monitor the operating status and equipment health of the data transmission network constructed in step S5 in real time, use machine learning technology to predict faults, and perform remote centralized management and control based on the results of fault prediction. The remote centralized management and control at least includes remote early warning and calling the corresponding mobile application to assist in data transmission control.

10. A multi-hop relay networking transmission system based on multi-dimensional data, the system being applicable to the multi-hop relay networking transmission system based on multi-dimensional data as claimed in any one of claims 1 to 9, characterized in that: The system includes: A data acquisition module, wherein the data acquisition module is configured to: acquire historical obstacle data and wind direction data of a wind farm, perform multi-hop relay networking, and generate a multi-hop relay networking strategy library; wherein the obstacle data is used to perform multi-hop relay networking based on the obstacle conditions of the wind farm, and the obstacle conditions at least include terrain conditions; the wind direction data is used to perform multi-hop relay networking based on the wind direction conditions of the wind farm, and the wind direction conditions are the wind directions corresponding to the transmission nodes for performing multi-hop relay networking; the multi-hop relay networking is used to generate corresponding multi-hop relay networking strategies for guiding multi-hop relay networking based on the obstacle data and the wind direction data; and the multi-hop relay networking strategy library stores a plurality of the multi-hop relay networking strategies and the corresponding obstacle data and wind direction data; A data updating module, wherein the data updating module is configured to: obtain updated obstacle data and wind direction data using a mobile monitoring device; A strategy generation module, wherein the strategy generation module is configured to: output a corresponding plurality of the multi-hop relay networking strategies using a similarity analysis technology; A strategy screening module, wherein the strategy screening module is configured to: use energy analysis technology to screen the multiple multi-hop relay networking strategies obtained in step S3; wherein the screening conditions include at least a remaining energy value and a charging efficiency value, wherein the remaining energy value is used to characterize the duration for which the current transmission node can continue to operate, and the charging efficiency value is used to characterize the impact of the current transmission node on data transmission when charging, and the higher the charging efficiency value, the smaller the impact of the current transmission node on data transmission when charging; A networking execution module, wherein the networking execution module is configured to: perform multi-hop relay networking using the multi-hop relay networking strategy obtained by screening in step S4; A monitoring and early warning module, wherein the monitoring and early warning module is configured to: centrally monitor and early warning the data transmission network that performs multi-hop relay networking; Among them, the data acquisition module, the data update module, the policy generation module, the policy screening module and the networking execution module are all communicatively connected with the monitoring and early warning module, the data acquisition module is communicatively connected with the data update module, the data update module is communicatively connected with the policy generation module, the policy generation module is communicatively connected with the policy screening module, and the policy screening module is communicatively connected with the networking execution module.

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