Offshore wind plant data transmission method based on data security

Abstract

The invention relates to the technical field of data transmission, in particular to an offshore wind plant data transmission method based on data security. The method comprises the following steps: acquiring a radio signal attenuation value monitored by a monitoring station, and determining a current transmission environment according to a comparison result of the radio signal attenuation value and an electric signal attenuation threshold value; calculating a standard loss value based on the free space propagation model and the marine environment correction term, and comparing the propagation loss value with the standard loss value; performing crisis detection according to the interruption detection and the data identification to determine whether transmission interruption exists or not; and analyzing the influence of the blocking effect and the multipath effect on the transmission of the alarm signal so as to execute a dynamic security strategy or adjust transmission parameters. According to the method, the security of data transmission is judged by monitoring attenuation of radio signals, and the influence of a wind power plant structure on radio signal transmission is considered by combining equipment life prediction, data identification, potential risk early warning and introduction of blocking analysis and multipath effect analysis, so that more accurate identification is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of data transmission, and in particular to an offshore wind farm data transmission method based on data security. Background Art

[0002] As an important component of renewable energy, offshore wind farms face numerous challenges in real-time monitoring and remote operation of their equipment operating status. Traditional monitoring systems often rely on scheduled inspections or single sensor data, which makes it difficult to fully reflect the equipment status. This is especially true in the harsh offshore environment, where signal interference, equipment aging, and data delays are more prominent.

[0003] The Chinese patent document with publication number CN115241979A discloses an offshore wind farm status monitoring system based on the power satellite Internet of Things, including: each edge intelligent terminal communicates with each other through an agent interaction protocol; the terminal acquisition device is connected to the edge intelligent terminal, used to collect field data and send the field data to the edge intelligent terminal; the edge intelligent terminal is connected to the Internet of Things management cloud platform through a satellite communication data transmission terminal, used to transmit field data to the Internet of Things management cloud platform, obtain fault information based on the field data and transmit it to the Internet of Things management cloud platform, receive control signals from the Internet of Things management cloud platform to control the terminal acquisition device; the Internet of Things management cloud platform is used to store and display fault information sent by the edge intelligent terminal, monitor the wind farm based on the fault information, and generate control signals according to the staff's operating instructions; therefore, the existing offshore wind farm data transmission technology lacks the combination of equipment life prediction and data identification to monitor the data transmission status to warn of potential risks. Summary of the Invention

[0004] To this end, the present invention provides an offshore wind farm data transmission method based on data security to overcome the problem in the prior art of signal interference caused by the lack of accurate identification of electric field structure and the failure to link the predicted equipment life with the transmission strategy, resulting in low transmission efficiency.

[0005] To achieve the above objectives, the present invention provides an offshore wind farm data transmission method based on data security, comprising:

[0006] Obtaining the radio signal attenuation value monitored by the monitoring station, and determining the current transmission environment based on the comparison result of the radio signal attenuation value and the electrical signal attenuation threshold;

[0007] Under the first transmission environment, a standard loss value is calculated based on a free space propagation model and an ocean environment correction term, and the propagation loss value is compared with the standard loss value to obtain a comparison result;

[0008] When the first comparison result is obtained, crisis detection is performed based on the interruption detection and data identification to determine whether there is a transmission interruption;

[0009] When it is determined that there is an interruption in the current transmission state, the impact of the blocking effect and multipath effect on the alarm signal transmission is analyzed, and dynamic security strategies are executed or transmission parameters are adjusted based on the analysis results.

[0010] Furthermore, determining the current transmission environment based on the comparison result of the radio signal attenuation value and the electrical signal attenuation threshold includes:

[0011] If the radio signal attenuation value is greater than the electric signal attenuation threshold, determining that the current transmission environment is the first transmission environment;

[0012] If the radio signal attenuation value is less than or equal to the electric signal attenuation threshold, it is determined that the current transmission environment is the second transmission environment.

[0013] Furthermore, the standard loss values ​​calculated based on the free space propagation model and the ocean environment correction term include:

[0014] The sum of the free space loss and the ocean environment correction term is taken as the first loss value;

[0015] The standard loss value is calculated based on the first loss value, the standard deviation of the historical loss data and the compensation parameter.

[0016] Furthermore, the free space propagation model calculates free space loss based on frequency and propagation distance;

[0017] The ocean environment correction term is the sum of the salinity correction term, the humidity correction term and the obstacle correction term.

[0018] Furthermore, the propagation loss difference is compared with the standard loss value, and the comparison results include:

[0019] If the propagation loss difference is greater than the standard loss value, the first comparison result is obtained;

[0020] If the propagation loss difference is less than or equal to the standard loss value, a second comparison result is obtained.

[0021] Further, performing crisis detection based on interrupt detection and data identification includes,

[0022] Interruption detection is performed based on the heartbeat packet loss rate and duration to determine whether there is a transmission interruption during the transmission of offshore wind farm data;

[0023] Analyze video data from offshore wind farm data to identify blade cracks and lightning damage areas in blade images in the video data based on image segmentation, and obtain location coordinates and damage area percentages;

[0024] Determine whether the current transmission status is interrupted based on the location coordinates and the percentage of the damaged area;

[0025] The ship collision risk is analyzed by fusing trajectory data with radar echoes to obtain the ship collision probability;

[0026] Determine whether the current transmission state is interrupted based on the ship collision probability.

[0027] Further, the impact of the blocking effect on the transmission of the alarm signal is analyzed, including:

[0028] The blocking effect coefficient is calculated based on the tower height, signal incident angle, and seawater attenuation coefficient to analyze the blocking effect.

[0029] Further analysis of the impact of multipath effects on alarm signal transmission includes:

[0030] The delay spread and coherence bandwidth of the received signal are extracted to perform multipath effect analysis and obtain the multipath effect analysis results.

[0031] Furthermore, executing dynamic security policies includes,

[0032] Compress the alarm information into hash values ​​based on the blocking effect coefficient and then transmit them in segments;

[0033] Based on the multipath effect analysis results, the current transmission mode is switched to the spread spectrum communication mode, and a forward error correction code is inserted into the alarm data packet.

[0034] Further, adjusting the transmission parameters includes,

[0035] Select the modulation method according to the sea water temperature;

[0036] Adjust the video stream based on the predicted remaining bearing life.

[0037] Compared with the existing technology, the beneficial effect of the present invention is that due to the harsh environment around offshore wind farms, the climate characteristics of high salt fog, high humidity, and extreme weather (storms, lightning) at sea, and the geographical location characteristics of dozens to hundreds of kilometers offshore, the reliability and durability of offshore wind farm data transmission equipment and lines are extremely high. At the same time, communication terminal equipment located in remote seas may face the risk of physical damage or unauthorized access, making its network security vulnerable to threats. Therefore, the security of data transmission is judged by monitoring the attenuation of radio signals, and combined with equipment life prediction and data identification, potential risks are warned. If the signal attenuation is too large, there may be a risk of data transmission interruption or equipment failure. Further analysis is needed, and blocking analysis and multipath effect analysis are introduced to consider the impact of wind farm structure on radio signal transmission, so as to achieve more comprehensive risk assessment and more accurate identification.

[0038] Furthermore, through heartbeat packet detection and video data analysis, the transmission status is monitored in real time, and transmission interruptions and equipment damage are discovered in a timely manner. By collecting trajectory data and obtaining the location of obstacles and ship speed detected by radar, the key variables of the moving target ship are obtained to assess the risk of ship collision and provide comprehensive risk warnings.

[0039] Furthermore, by analyzing the impact of multipath effects on alarm signal transmission and proposing effective optimization measures, the reliability and effectiveness of the alarm system in complex environments are ensured.

[0040] Furthermore, by calculating the predicted value of the remaining life of the bearing in real time and dynamically adjusting the video stream according to the predicted value, intelligent video transmission based on the equipment status is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 This is a flow chart of a method for transmitting data in an offshore wind farm based on data security according to an embodiment of the present invention;

[0042] Figure 2 A schematic diagram of a process for calculating a standard loss value according to an embodiment of the present invention;

[0043] Figure 3 A schematic diagram of a process for performing crisis detection based on interruption detection and data identification according to an embodiment of the present invention;

[0044] Figure 4 The figure is a flow chart of executing dynamic security policies according to an embodiment of the present invention. DETAILED DESCRIPTION

[0045] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are merely used to explain the present invention and are not intended to limit the present invention.

[0046] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0047] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside", and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0048] Furthermore, it should be noted that, in the description of the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0049] See also Figure 1 As shown, it is a flow chart of an offshore wind farm data transmission method based on data security according to an embodiment of the present invention. The present invention provides an offshore wind farm data transmission method based on data security, comprising:

[0050] Step S1, obtaining a radio signal attenuation value monitored by a monitoring station, and determining a current transmission environment based on a comparison result of the radio signal attenuation value and an electrical signal attenuation threshold;

[0051] Step S2: Under the first transmission environment, a standard loss value is calculated based on a free space propagation model and an ocean environment correction term, and the propagation loss value is compared with the standard loss value to obtain a comparison result;

[0052] Step S3, when the first comparison result is obtained, performing crisis detection based on interruption detection and data identification to determine whether there is a transmission interruption;

[0053] Step S4: When it is determined that there is an interruption in the current transmission state, the influence of the blocking effect and the multipath effect on the transmission of the alarm signal is analyzed, and a dynamic security strategy is executed or the transmission parameters are adjusted according to the analysis results.

[0054] The offshore wind farm data in this embodiment is image data, including monitoring videos, inspection images and remote sensing images. Among them, the monitoring videos are real-time monitoring of key areas such as wind turbine towers, engine rooms, substations, offshore booster stations, and ship berthing areas. The inspection images are high-definition photos and videos of wind turbine blades, foundation structures, submarine cables, anti-scour protection, etc. taken by drones, underwater robots or equipment onboard maintenance ships. Remote sensing images are images of wind farm areas obtained by satellite or aerial photography, which are used for environmental monitoring, ice condition analysis, ship traffic monitoring, etc.

[0055] Due to the harsh environment surrounding offshore wind farms, including the climate characteristics of high salt fog, high humidity, and extreme weather (storms, lightning), and the geographical location of dozens to hundreds of kilometers offshore, the reliability and durability of offshore wind farm data transmission equipment and lines are extremely high. At the same time, communication terminal equipment located in remote offshore areas may face the risk of physical damage or unauthorized access, making its network security vulnerable to threats. Therefore, the security of data transmission is judged by monitoring the attenuation of radio signals, and combined with equipment life prediction and data identification, potential risks are warned. If the signal attenuation is too large, there may be a risk of data transmission interruption or equipment failure. Further analysis is needed, introducing blocking analysis and multipath effect analysis to consider the impact of wind farm structure on radio signal transmission, achieving more comprehensive risk assessment and more accurate identification.

[0056] Specifically, the current transmission environment is determined based on the comparison result of the radio signal attenuation value and the electrical signal attenuation threshold, including:

[0057] If the radio signal attenuation value is greater than the electric signal attenuation threshold, determining that the current transmission environment is the first transmission environment;

[0058] If the radio signal attenuation value is less than or equal to the electric signal attenuation threshold, it is determined that the current transmission environment is the second transmission environment.

[0059] In this embodiment, the electrical signal attenuation threshold is set based on the statistical value of historically measured path loss: the electrical signal attenuation threshold = historical average path loss + 3 × historical path loss standard deviation. The current path loss is measured in real time as the radio signal attenuation value and compared with the electrical signal attenuation threshold. The comparison result is used to predict the risk of the current transmission environment when transmitting data from the offshore wind farm. The first transmission environment represents a high-risk transmission environment, and the second transmission environment represents a lower-risk transmission environment. In the first transmission environment, a more accurate model is used, namely, a theoretical loss is calculated based on a free-space propagation model and a modified marine environment model. The actual transmission loss level is analyzed based on the comparison between the theoretical loss and the actual propagation loss. Because the actual measured current path loss includes environmental influences, the difference between the current path loss and the electrical signal attenuation threshold is calculated as the propagation loss difference. A preliminary determination is made based only on the statistical value of the historically measured data. Subsequent precise calculations are performed only when necessary, i.e., in the first transmission environment. This simplifies the determination method, ensures safety warnings, and reduces implementation complexity.

[0060] See Figure 2 As shown, it is a schematic diagram of the process of calculating the standard loss value according to an embodiment of the present invention;

[0061] Specifically, the standard loss values ​​calculated based on the free space propagation model and the ocean environment correction terms include:

[0062] Step S201: taking the sum of the free space loss and the ocean environment correction term as the first loss value;

[0063] Step S202: Calculate the standard loss value based on the first loss value, the standard deviation of historical loss data, and the compensation parameter.

[0064] In this embodiment, the standard loss value = PL theory +3σ+K, where PL theory is the first loss value calculated, σ is the standard deviation of the historical loss data obtained, PL meas,i is the real-time measurement value, PL theory,i is the theoretical measurement value, K is the set compensation parameter, and the compensation parameter is the encryption level compensation, which is used to describe the transmission overhead introduced by different encryption algorithms. For example, no encryption is suitable for internal test networks, and the corresponding compensation parameter is 0; the AES-128 encryption algorithm is suitable for monitoring video streams, and the corresponding compensation parameter is 1dB; the national secret SM4 is suitable for operating status data, and the corresponding compensation parameter is 2dB; CRYSTALS-Kyber (anti-quantum) is suitable for alarm commands and remote control, and the corresponding compensation parameter is 5dB; the historical database updates the standard deviation of the loss data for the past 30 days every hour. The system dynamically assigns encryption levels according to the data transmission type, so that the higher the risk, the higher the protection level.

[0065] Specifically, the free space propagation model calculates free space loss based on frequency and propagation distance;

[0066] The ocean environment correction term is the sum of the salinity correction term, the humidity correction term and the obstacle correction term.

[0067] The free space propagation model in this embodiment is 20log 10 (f)+20log 10 (d)+32.44;

[0068] Where f is the frequency in GHz, d is the propagation distance, and the salinity correction term is the product of the loss coefficient and the salt spray concentration. The loss coefficient is 0.02dB·ppt -1 The unit of salt spray concentration is ppt, humidity correction term = 0.02dB / % × (RH-80%), RH is relative humidity, when relative humidity > 80%, humidity correction term is calculated, obstacle correction term calculation formula is: O = 0.5dB / piece × N + 0.1dB / m 2 ×A, N represents the number of major obstacles in the wind farm, and A represents the total cross-sectional area of ​​the major obstacles, in square meters; the major obstacles include fixed wind turbines, submarine cables, and operation and maintenance ships.

[0069] The salinity correction term represents the loss caused by salinity. The ocean air contains salt aerosols, and the ions in the salt (mainly Na + and Cl-) will absorb and scatter radio wave energy, resulting in additional loss. The higher the salinity, the greater the loss. The humidity correction term is the additional loss caused by humidity. Due to the high humidity in the marine environment, water molecules have a significant absorption effect on radio waves in specific frequency bands, especially microwave bands. For example, the water vapor absorption peak is at 22.24GHz, 183.31GHz, etc., which will cause additional loss. The higher the humidity, the greater the loss. The obstacle correction term is the additional loss caused by the blocking effect of obstacles on the propagation path on the propagation of radio signals, such as spray, droplets, hulls, islands, reefs, etc. It can also include additional loss caused by sea surface reflection and diffraction loss, that is, water droplets in the form of spray and droplets generated by breaking waves will scatter and absorb signals. The hull itself or other large structures may block signals between ships or between ships and shore. In offshore or island and reef areas, terrain and objects will block signals. Therefore, considering the changes in seawater salinity and high humidity The influence of air absorption of radio waves and shielding effect of ships or islands on radio wave propagation loss is used to improve the calculation accuracy of radio wave propagation path loss. For example, the frequency of the offshore wind farm monitored is 3.5GHz, the propagation distance is 28km, σ is 4.2dB, the compensation parameter is 2dB, the salinity concentration is 30ppt, the relative humidity is 85%, the main obstacle is the wind tower, the number of main obstacles is 5, and the total cross-sectional area of ​​the main obstacles is A = 10 square meters. , then the free space loss is about 133.74dB, the salinity correction term = 0.02×30 = 0.6dB, the humidity correction term = 0.02×(85-80) = 0.1dB, the obstacle correction term is: O = 0.5×5+0.1×10=3.5dB, then the ocean environment correction term is 4.2dB, the first loss value is 137.94dB, and the standard loss value = 137.94dB+3×4.2+2dB=152.54dB.

[0070] Specifically, the propagation loss difference is compared with the standard loss value, and the comparison results include:

[0071] If the propagation loss difference is greater than the standard loss value, the first comparison result is obtained;

[0072] If the propagation loss difference is less than or equal to the standard loss value, a second comparison result is obtained.

[0073] The propagation loss difference in this embodiment represents the additional loss in the actual transmission environment. The standard loss value is a theoretical value calculated based on the free space propagation model, the marine environment correction term, the standard deviation of historical data, and the compensation parameter, representing the expected maximum loss under the conditions of the offshore wind farm. When it is determined that the propagation loss difference is greater than the standard loss value, it means that the actual transmission loss exceeds the expected standard loss value. This may be due to severe signal attenuation caused by factors such as high salinity, high humidity, and multiple obstacles caused by sudden harsh environments. In this case, it means that the current transmission environment of the offshore wind farm is in a high-risk transmission environment, which is likely to cause data transmission interruption or error. It is necessary to further trigger crisis detection and analysis, that is, to perform transmission interruption detection and data identification to ensure timely identification of potential problems and ensure the transmission of important data. Transmission and storage, such as the transmission security and integrity of monitoring video and alarm information, maintain the normal operation of offshore wind farm data transmission; when it is determined that the propagation loss difference is less than or equal to the standard loss value, it means that the actual transmission loss is within an acceptable range, the transmission environment is relatively stable, and the risk is low. At this time, the current transmission parameters can be maintained for data transmission without frequent adjustments, saving computing and adjustment resources while improving transmission efficiency. In a low-risk environment, the stability and reliability of data transmission can be guaranteed. By avoiding unnecessary adjustments and resource consumption, the system operation is more efficient and the overall operation and maintenance cost is reduced. The first comparison result and the second comparison result together constitute a dynamic risk assessment and response mechanism to ensure the reliability and security of offshore wind farm data transmission and adapt to harsh environments and high safety requirements.

[0074] See Figure 3 As shown, it is a schematic diagram of a process of performing crisis detection based on interruption detection and data identification according to an embodiment of the present invention;

[0075] Specifically, crisis detection based on disruption detection and data identification includes:

[0076] Step S3001: performing an interruption detection based on the heartbeat packet loss rate and duration to determine whether there is a transmission interruption during the transmission of offshore wind farm data;

[0077] Step S3002: analyzing the video data in the offshore wind farm data to identify blade cracks and lightning damage areas in the blade images in the video data based on image segmentation, and obtaining position coordinates and damage area percentages;

[0078] Step S3003, determining whether there is an interruption in the current transmission state based on the position coordinates and the damage area percentage;

[0079] Step S3004: Analyze the ship collision risk based on the trajectory data and radar echo fusion to obtain the ship collision probability;

[0080] Step S3005: Determine whether there is any interruption in the current transmission state according to the ship collision probability.

[0081] In this embodiment, the reception of heartbeat packets is recorded, the number of lost packets in each time window is counted, and the ratio of the number of lost packets to the total number of packets is calculated to obtain the heartbeat packet loss rate. When the heartbeat packet loss rate exceeds a threshold, the loss duration is tracked through continuous detection. When the loss duration exceeds the threshold, the transmission is interrupted. When the loss duration does not exceed the threshold, whether there is an interruption in the current transmission state is determined based on the position coordinates and the damage area percentage. The position coordinates include the position coordinates of the blade crack and the position coordinates of the lightning damage area. The damage area percentage includes the blade damage area percentage and the lightning damage area percentage. Videos related to the wind farm structure in monitoring videos and inspection images are obtained, the video stream is decomposed using OpenCV, each frame of the blade image is processed, cracks are extracted through edge detection Canny and image segmentation U-Net, the ratio of the number of blade damage pixels to the total number of blade pixels is calculated, and the blade damage area percentage is obtained. The target detection model YOLO is used for lightning damage detection to locate the damage and record the coordinates. The lightning damage area percentage is the ratio of the number of lightning damage pixels to the total number of pixels in the effective area of ​​the blade.

[0082] Calculate the actual comprehensive risk index R = S × Ws + L × Wi based on the location coordinates and the percentage of damaged area;

[0083] S is the percentage of damaged area, Ws is the area weight, Ws=0.6, L is the risk level corresponding to the position coordinate, Wi is the position weight, Wi=0.4, L=1 for the blade root area, L=0.7 for the main beam area, and L=0.3 for the airfoil area. The comprehensive risk index threshold is set to 0.55. When the actual comprehensive risk index is greater than or equal to the comprehensive risk index threshold, the transmission is judged to be interrupted. When the actual comprehensive risk index is less than the comprehensive risk index threshold, the current transmission state is determined to be interrupted based on the ship collision probability. The position (xi, yi), relative speed, and RCS intensity of the obstacle and target ship are obtained based on the radar echo, and the heading θ of the target ship is obtained based on the trajectory data. i (i=1,2,...,n), speed V i , obtain meteorological sea conditions: wind speed (m / s), wave height (m), visibility (m),

[0084] Calculate the relative velocity vector

[0085] Calculate relative position vector

[0086] Calculate the closest encounter distance

[0087] Calculate the nearest encounter time

[0088] Probability of ship collision P = (1-DCPA / Dsafe) / (1-TCPA / Tsafe);

[0089] DCPA represents the minimum distance between the ship and the obstacle, TCPA represents the time required for the ship to reach the minimum point, Dsafe represents the safety distance threshold in meters, and Tsafe represents the safety time threshold in seconds. Dsafe is 500 meters and Tsafe is 60 seconds. By considering the minimum distance and time factors, the risk probability of ship collision is effectively assessed, ranging from 0 to 1. The larger the value, the higher the risk.

[0090] The threshold corresponding to the heartbeat packet loss rate is 60%, and the threshold corresponding to the loss duration is set between 3 and 5 times the heartbeat packet sending interval; the crack area percentage threshold is 0.5%, and the lightning damage area percentage threshold is 1%; the collision probability threshold is set between 0.4 and 0.8. The set value is related to the collision risk of the sea area location. The higher the risk of the sea area, the smaller the corresponding collision probability threshold.

[0091] Through heartbeat packet detection and video data analysis, the transmission status is monitored in real time, and transmission interruptions and equipment damage are discovered in a timely manner. By collecting trajectory data and obtaining the obstacle positions and ship speeds detected by radar, the key variables of the moving target ship are obtained to assess the risk of ship collision. When the risk of ship collision is high, the interruption risk is correspondingly high. It is determined that there is an interruption in the current transmission status, an alarm is issued in time, and the quality of the alarm signal transmission is analyzed to determine whether to implement dynamic security strategies or adjust transmission parameters to ensure data security.

[0092] Specifically, the impact of the blocking effect on the transmission of alarm signals includes:

[0093] The blocking effect coefficient is calculated based on the tower height, signal incident angle, and seawater attenuation coefficient to analyze the blocking effect.

[0094] The calculation formula of the barrier effect coefficient in this embodiment is:

[0095]

[0096] Where H is the tower height in meters;

[0097] γ is the signal wavelength in meters;

[0098] θ is the signal incident angle, in degrees;

[0099] α is the attenuation coefficient of seawater, in dB / m.

[0100] Specifically, the analysis of the impact of multipath effects on alarm signal transmission includes:

[0101] The delay spread and coherence bandwidth of the received signal are extracted to perform multipath effect analysis and obtain the multipath effect analysis results.

[0102] In this embodiment, if an obstacle is encountered during the transmission of the original alarm signal, multiple paths will be generated, and the receiving end receives signals from different paths, then the delay spread and coherence bandwidth of the received signal are extracted, wherein the delay spread of the received signal is extracted, including sending a pulse signal, recording the response of the receiving end, and analyzing the arrival time difference of each path in the response signal to calculate the delay spread, and the coherence bandwidth of the received signal is extracted, including Fourier transforming the received signal to obtain a frequency domain representation, calculating the power spectral density of the signal, and determining the coherence by analyzing the correlation of adjacent frequency components. Bandwidth; Set the delay spread threshold to 0.1Ts and the coherence bandwidth threshold to 0.5B. When the delay spread exceeds 10% of the symbol period, multipath delay will cause adjacent symbols to overlap, resulting in severe inter-symbol interference. When the channel coherence bandwidth is less than half of the signal bandwidth, the high-frequency components of the signal will be severely attenuated, resulting in demodulation failure. Therefore, when it is determined that the delay spread is greater than the delay spread threshold and the coherence bandwidth is less than the coherence bandwidth threshold, it is necessary to switch to an anti-interference transmission mode, that is, a spread spectrum communication mode. Among them, Ts is the symbol period, which represents the duration of a single data symbol, and the symbol period is the inverse of the code rate.

[0103] By analyzing the impact of multipath effects on alarm signal transmission and proposing effective optimization measures, the reliability and effectiveness of the alarm system in complex environments are ensured.

[0104] See Figure 4 As shown, it is a schematic diagram of the process of executing dynamic security policies according to an embodiment of the present invention;

[0105] Specifically, executing dynamic security policies includes:

[0106] Step S4001: compressing the alarm information into hash values ​​based on the blocking effect coefficient and then transmitting the hash values ​​in segments;

[0107] Step S4002: Switch the current transmission mode to the spread spectrum communication mode based on the multipath effect analysis result, and insert a forward error correction code into the alarm data packet.

[0108] Segmented transmission is to divide the hash-compressed data into multiple small segments, each block is 128 bits, and is identified by a serial number to facilitate reassembly at the receiving end. Specifically, adjusting the transmission parameters includes:

[0109] Select the modulation method according to the sea water temperature;

[0110] Adjust the video stream based on the predicted remaining bearing life.

[0111] Selecting modulation mode according to seawater temperature includes:

[0112] If the seawater temperature is greater than or equal to 25 degrees Celsius, select the QPSK transmission mode;

[0113] If the seawater temperature is less than 25 degrees Celsius, select the 16-QAM transmission mode;

[0114] Calculating the predicted value of the remaining bearing life includes:

[0115] Fitting the vibration growth slope k based on the vibration history data, k = (Vc - Vi) / t, where Vc is the current vibration rate of the bearing, Vi is the initial vibration rate of the bearing, with the unit of m / s 2 , t is the operating time of the bearing in hours;

[0116] Calculating the theoretical remaining life Ulb under rated conditions, Ulb = (Vf - Vc) / k, where Vf is the vibration rate at wear;

[0117] Calculating the wear rate ratio as the temperature correction factor R, R = 1 + k2×(T - T0) + k3×(T - T0) 2 , where k2 = 0.02, k3 = 0.0005, T is the absolute temperature, T0 is the rated temperature, T0 = 20°C, when T < T0, R < 1, indicating that the wear slows down;

[0118] Calculating the actual remaining life ULr based on the theoretical remaining life and the temperature correction factor, ULr = ULb / R;

[0119] Adjusting the video bitstream based on the predicted value of the remaining bearing life includes:

[0120] Based on the calculated actual remaining life ULr, determine the adjustment ratio of the video bitstream. The adjustment ratio can be divided into the following intervals:

[0121] ULr ≥ 100%: The adjustment ratio is +20%, that is, increasing the video bitstream to 1.2 times the original;

[0122] 50% < ULr < 100%: The adjustment ratio is 0%, keeping the current video bitstream unchanged;

[0123] 20% ≤ ULr ≤ 50%: The adjustment ratio is -10%, that is, reducing the video bitstream to 0.9 times the original;

[0124] ULr < 20%: The adjustment ratio is -30%, that is, reducing the video bitstream to 0.7 times the original.

[0125] By calculating the predicted value of the remaining bearing life in real time and dynamically adjusting the video bitstream according to the predicted value, intelligent video transmission based on the device status is achieved.

[0126] Thus far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present invention.

[0127] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that the present invention is susceptible to various modifications and variations. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A data transmission method for offshore wind farms based on data security, characterized in that: include, Obtaining the radio signal attenuation value monitored by the monitoring station, and determining the current transmission environment based on the comparison result of the radio signal attenuation value and the electrical signal attenuation threshold; Under the first transmission environment, a standard loss value is calculated based on a free space propagation model and an ocean environment correction term, and the propagation loss value is compared with the standard loss value to obtain a comparison result; When the first comparison result is obtained, crisis detection is performed based on the interruption detection and data identification to determine whether there is a transmission interruption; When it is determined that there is an interruption in the current transmission state, the impact of the blocking effect and multipath effect on the alarm signal transmission is analyzed, and dynamic security strategies are executed or transmission parameters are adjusted based on the analysis results.

2. The offshore wind farm data transmission method based on data security according to claim 1 is characterized in that: The current transmission environment is determined based on the comparison between the radio signal attenuation value and the electrical signal attenuation threshold, including: If the radio signal attenuation value is greater than the electric signal attenuation threshold, determining that the current transmission environment is the first transmission environment; If the radio signal attenuation value is less than or equal to the electric signal attenuation threshold, it is determined that the current transmission environment is the second transmission environment.

3. The offshore wind farm data transmission method based on data security according to claim 1 is characterized in that: The standard loss values ​​calculated based on the free space propagation model and the ocean environment correction terms include: The sum of the free space loss and the ocean environment correction term is taken as the first loss value; The standard loss value is calculated based on the first loss value, the standard deviation of the historical loss data and the compensation parameter.

4. The offshore wind farm data transmission method based on data security according to claim 3 is characterized in that: The free space propagation model calculates free space loss based on frequency and propagation distance; The ocean environment correction term is the sum of the salinity correction term, the humidity correction term and the obstacle correction term.

5. The offshore wind farm data transmission method based on data security according to claim 1 is characterized in that: Compare the propagation loss difference with the standard loss value, and the comparison results include: If the propagation loss difference is greater than the standard loss value, the first comparison result is obtained; If the propagation loss difference is less than or equal to the standard loss value, a second comparison result is obtained.

6. The offshore wind farm data transmission method based on data security according to claim 1 is characterized in that: Performing crisis detection based on disruption detection and data identification includes, Interruption detection is performed based on the heartbeat packet loss rate and duration to determine whether there is a transmission interruption during the transmission of offshore wind farm data; Analyze video data from offshore wind farm data to identify blade cracks and lightning damage areas in blade images in the video data based on image segmentation, and obtain location coordinates and damage area percentages; Determine whether the current transmission status is interrupted based on the location coordinates and the percentage of the damaged area; The ship collision risk is analyzed by fusing trajectory data with radar echoes to obtain the ship collision probability; Determine whether the current transmission state is interrupted based on the ship collision probability.

7. The offshore wind farm data transmission method based on data security according to claim 1 is characterized in that: Analysis of the impact of blocking effects on alarm signal transmission includes: The blocking effect coefficient is calculated based on the tower height, signal incident angle, and seawater attenuation coefficient to analyze the blocking effect.

8. The offshore wind farm data transmission method based on data security according to claim 1 is characterized in that: Analysis of the impact of multipath effects on alarm signal transmission includes: The delay spread and coherence bandwidth of the received signal are extracted to perform multipath effect analysis and obtain the multipath effect analysis results.

9. The offshore wind farm data transmission method based on data security according to claim 8, characterized in that: Executing dynamic security policies includes, Compress the alarm information into hash values ​​based on the blocking effect coefficient and then transmit them in segments; Based on the multipath effect analysis results, the current transmission mode is switched to the spread spectrum communication mode, and a forward error correction code is inserted into the alarm data packet.

10. The offshore wind farm data transmission method based on data security according to claim 1, characterized in that: Adjusting transmission parameters includes, Select the modulation method according to the sea water temperature; Adjust the video stream based on the predicted remaining bearing life.

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