Offshore wind power intelligent wind field inspection method and system

Abstract

The invention relates to the technical field of offshore wind power operation and maintenance, in particular to an offshore wind power intelligent wind field inspection method and system, and the method comprises an offshore data collection step, an operation and maintenance intelligent scheduling step, a ship yaw correction step and an offshore intelligent inspection step. According to the method, the dynamic influence of the wind action on the course of the inspection ship can be sensed in real time, the course offset is accurately calculated, and accurate deviation input data is provided for subsequent course compensation control. According to the technology, the risk of routing inspection path deviation caused by sudden environment change is effectively reduced, it is ensured that the routing inspection ship executes tasks according to the preset travel, and routing inspection efficiency loss and potential safety hazards caused by course correction delay are avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of offshore wind power operation and maintenance, and particularly to an offshore wind power intelligent wind farm inspection method and system. Background Art

[0002] With the continuous growth of global energy demand and the increasing awareness of environmental protection, the development and utilization of renewable energy have become the focus of attention of countries around the world. Among them, offshore wind power, as a clean and renewable energy form, has developed rapidly in recent years due to its advantages such as rich resources, high power generation efficiency, and small land occupation. However, the operation and maintenance and monitoring of offshore wind farms face many challenges, such as long distances, poor accessibility, low safety supervision performance, high transportation costs, high operation and maintenance costs, etc. These problems not only affect the operation efficiency of the wind farm, but also increase the complexity and risk of operation and maintenance.

[0003] In the prior art, although the application of technologies such as the Internet of Things, big data, and artificial intelligence has realized the intelligence and automation of offshore wind power operation and maintenance to a certain extent, there are still many deficiencies. For example, existing operation and maintenance systems often lack effective coping strategies when dealing with complex sea conditions and sudden weather events, resulting in difficulties in smoothly executing operation and maintenance plans. In addition, existing inspection methods also have certain limitations in ship yaw correction and fault detection, and cannot meet the requirements of efficient and accurate operation and maintenance.

[0004] Therefore, to solve the above problems, the present invention proposes an offshore wind power intelligent wind farm inspection method and system. Summary of the Invention

[0005] Aiming at the deficiencies of the prior art, the purpose of the present invention is to provide an offshore wind power intelligent wind farm inspection method and system.

[0006] To achieve the above purpose, the present invention provides the following technical solutions: An offshore wind power intelligent wind farm inspection method includes the following steps: An offshore data collection step of collecting wind speed and wind direction data of the wind farm in real time through lidar and ultrasonic devices; and obtaining sea condition information and typhoon warning information by accessing a real-time database; An operation and maintenance intelligent scheduling step of judging the scheduling situation according to the sea condition information, typhoon warning information, and the positioning of the inspection ship and outputting an inspection ship scheduling instruction, where the inspection ship scheduling instruction includes an inspection instruction and a return instruction; when the inspection instruction is output, perform operation and maintenance scheduling on the inspection ship to obtain the navigation itinerary of the inspection ship; Vessel yaw correction steps: Determine the yaw situation of the vessel based on the wind speed, wind direction, and the output of the inspection vessel scheduling instruction, calculate the yaw value of the inspection vessel, calculate the yaw compensation value through the yaw compensation strategy according to the yaw value, and correct the course of the inspection vessel according to the yaw compensation value; Intelligent offshore inspection steps: When receiving an inspection instruction, reach the destination according to the navigation itinerary of the inspection vessel and conduct fault detection on offshore equipment.

[0007] As a further improvement of the present invention, the intelligent operation and maintenance scheduling steps further include: obtaining the typhoon path and the typhoon arrival time as typhoon warning information; obtaining the sea waves, tide levels, visibility, and rainfall of the current wind farm as sea condition information; judging the offshore operation and maintenance plan scheduling situation of the inspection vessel according to the inspection vessel positioning, sea condition information, typhoon warning information combined with the port window period information, and outputting an inspection vessel scheduling instruction. When the inspection vessel scheduling instruction outputs an inspection instruction, enter the vessel operation and maintenance scheduling steps.

[0008] As a further improvement of the present invention, the vessel operation and maintenance scheduling steps include: transmitting the positions, vessel course information, and destination information to be inspected of all inspection vessels to the central control system. Based on the destination information to be inspected, determine the inspection vessel closest to the destination to be inspected by combining the position of the inspection vessel with the vessel course information, and use this destination to be inspected as the navigation itinerary of the inspection vessel.

[0009] As a further improvement of the present invention, the vessel yaw correction steps include: determining the course of the inspection vessel according to the inspection vessel scheduling instruction, and determining the influence of the wind field on the course deviation of the inspection vessel according to the real-time collected wind direction and wind speed data and the course of the inspection vessel, and calculating the yaw value.

[0010] As a further improvement of the present invention, the yaw compensation strategy includes: when the yaw value is greater than the yaw threshold, input the collected wind direction, wind speed, yaw value, and the difference between the current inspection vessel positioning and the inspection vessel travel destination into the compensation value calculation model to calculate the deviation compensation value. After feeding back the deviation compensation value to the inspection vessel, adjust the travel course of the inspection vessel according to the deviation compensation value.

[0011] As a further improvement of the present invention, the compensation value calculation model is configured to: comprehensively calculate the yaw value representing the course deviation degree of the inspection vessel without adjustment control under the influence of the current wind force by combining the inspection vessel orientation and the vessel target course with the wind speed and wind direction, calculate a wind force influence factor representing the dynamic resistance of the wind field on the inspection vessel through the wind speed and wind direction, and calculate the deviation compensation value through the yaw value and the wind force influence factor.

[0012] As a further improvement of the present invention, it further includes an inspection safety detection step. After the inspection vessel receives an inspection instruction, the partial discharge condition and unit failure of the submarine cable are monitored through a configured intelligent submarine cable status perception system.

[0013] As a further improvement of the present invention, it further includes a three-dimensional model construction and simulation step. After real-time sea condition information and typhoon warning information are collected and the navigation schedule of the inspection vessel is arranged, the results are verified by constructing a three-dimensional model.

[0014] An offshore wind power intelligent wind farm inspection system includes: An offshore data collection module that collects wind speed and wind direction data of the wind farm in real time through lidar and ultrasonic devices; and obtains sea condition information and typhoon warning information by accessing a real-time database; An operation and maintenance intelligent scheduling module that determines the scheduling situation based on the sea condition information, typhoon warning information, and the positioning of the inspection vessel and outputs an inspection vessel scheduling instruction. The inspection vessel scheduling instruction includes an inspection instruction and a return instruction; when the inspection instruction is output, the operation and maintenance scheduling of the inspection vessel is performed to obtain the navigation schedule of the inspection vessel; A vessel yaw correction module that determines the yaw situation of the vessel based on the wind speed, wind direction, and the output situation of the inspection vessel scheduling instruction, calculates the yaw value of the inspection vessel, calculates the yaw compensation value through a yaw compensation strategy based on the yaw value, and corrects the course of the inspection vessel according to the yaw compensation value; An offshore intelligent inspection module that, when receiving an inspection instruction, reaches the destination according to the navigation schedule of the inspection vessel and performs offshore equipment fault detection.

[0015] Through the above solution, the present invention can real-time perceive the dynamic influence of the wind force on the course of the inspection vessel, accurately calculate the course offset, and provide accurate deviation input data for subsequent course compensation control. This technology effectively reduces the risk of the inspection path deviation caused by environmental mutations, ensures that the inspection vessel performs tasks according to the predetermined schedule, and avoids the loss of inspection efficiency and potential safety hazards caused by delayed course correction. Brief Description of the Drawings

[0016] Figure 1 is a method flow chart of an offshore wind power intelligent wind farm inspection method of the present invention; Figure 2 is a system diagram of the three-dimensional modeling and simulation step of the present invention; Figure 3 is a system diagram of the present invention. Detailed Embodiments

[0017] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. The same components are denoted by the same reference numerals. It should be noted that the terms "front", "rear", "left", "right", "upper" and "lower" used in the following description refer to the directions in the accompanying drawings, and the terms "bottom surface" and "top surface", "inner" and "outer" refer to the directions towards or away from the geometric center of a specific component, respectively.

[0018] In the prior art, the operation and maintenance of offshore wind farms have long faced the challenge of insufficient adaptability to complex environments. Traditional inspection operations rely on manual experience to judge the navigation path and maintenance timing, with problems such as strong subjectivity and lagging response. When encountering sudden meteorological changes, the fixed scheduling mode is difficult to quickly adjust the navigation plan, resulting in frequent interruptions of inspection tasks. During navigation, simply relying on the satellite positioning system for course control cannot effectively offset the continuous deviation effect of wind and waves on the vessel, causing cumulative deviation between the actual route and the planned path.

[0019] To solve the above problems, it is first found that the traditional manual scheduling mode cannot dynamically respond to the changes in typhoon paths and sea conditions, resulting in low utilization rate of the operation and maintenance window period. Through analysis, it is found that establishing a real-time association mechanism between meteorological data and vessel positioning can improve the scientificity of scheduling decisions. It is further recognized that the course deviation is not only related to the instantaneous wind speed but also affected by the continuous wind direction, and a dynamic compensation model needs to be established. Finally, a processing idea of multi-source data fusion is formed, integrating environmental monitoring, path planning, and dynamic correction into a closed-loop control system.

[0020] Therefore, the present application proposes an offshore wind power inspection method that includes: real-time collecting wind speed and wind direction data of the wind farm through lidar and ultrasonic devices, accessing a real-time database to obtain sea condition information and typhoon warning information; judging the scheduling situation according to the sea condition information, typhoon warning information, and the positioning of the inspection vessel, and outputting a scheduling instruction including an inspection instruction and a return instruction; generating a navigation itinerary when the inspection instruction is output; calculating the vessel yaw value according to the wind speed, wind direction, and the status of the scheduling instruction, and correcting the course through a compensation strategy; and performing equipment fault detection after arriving at the destination, as Figure 1 shown, including: An offshore data collection step of real-time collecting wind speed and wind direction data of the wind farm through lidar and ultrasonic devices; and accessing a real-time database to obtain sea condition information and typhoon warning information; the lidar and ultrasonic devices refer to two complementary meteorological sensing devices, the lidar is suitable for large-scale wind speed monitoring, and the ultrasonic device is good at capturing local wind direction changes, and the monitoring accuracy is improved through data fusion. The real-time database access means connecting to the marine meteorological observation network and the typhoon warning system to obtain dynamic sea condition data such as wave height and tidal cycle for evaluating the navigation safety window period.

[0021] Steps for intelligent operation and maintenance scheduling. Intelligent operation and maintenance scheduling refers to establishing a matching model between sea condition parameters and the performance of inspection vessels, dynamically generating an executable task schedule in combination with typhoon movement path prediction, judging the scheduling situation based on the sea condition information, typhoon warning information, and the positioning of inspection vessels, and outputting inspection vessel dispatching instructions. The inspection vessel dispatching instructions include inspection instructions and return instructions; when inspection instructions are output, perform operation and maintenance scheduling for the inspection vessel to obtain the sailing itinerary of the inspection vessel. Steps for correcting vessel yaw. Judge the yaw situation of the vessel according to the wind speed, wind direction, and the output situation of the inspection vessel dispatching instructions, calculate the yaw value of the inspection vessel, calculate the yaw compensation value through the yaw compensation strategy based on the yaw value, and correct the course of the inspection vessel according to the yaw compensation value. Steps for intelligent offshore inspection. When receiving inspection instructions, reach the destination according to the sailing itinerary of the inspection vessel and detect faults in offshore equipment.

[0022] Compared with the prior art, the traditional method uses a single wind speed sensor, resulting in the lack of wind direction monitoring and being unable to accurately evaluate the impact of lateral wind on inspection vessels. The fixed schedule lacks a dynamic response mechanism for typhoon paths and is prone to missing the safe operation window. Course correction relies on historical trajectory back-calculation, with a delay of up to minutes. In this solution, through multi-sensor data fusion, a second-level early warning of course deviation is achieved; a dynamic association model between typhoon paths and scheduling schemes is established to improve the utilization rate of the window period; a feed-forward compensation algorithm is adopted to control the course deviation within a preset threshold. Through the above technical solutions, this application realizes adaptive route planning under severe sea conditions, shortens the typhoon warning response time to within 1 hour; improves the course control accuracy, reduces the deviation between the actual track of the inspection vessel and the planned path; speeds up the equipment fault identification speed, and increases the number of wind turbines covered by a single inspection task.

[0023] Furthermore, the intelligent operation and maintenance scheduling step further includes obtaining the typhoon path and the typhoon arrival time as typhoon warning information; obtaining the sea state information such as sea waves, tide levels, visibility, and rainfall of the current wind field; judging the scheduling situation of the offshore operation and maintenance plan of the inspection ship according to the inspection ship positioning, sea state information, typhoon warning information combined with the port window period information and outputting an inspection ship dispatching instruction. When the inspection ship dispatching instruction outputs an inspection instruction, it enters the ship operation and maintenance scheduling step. Among them, the typhoon path and the typhoon arrival time refer to the typhoon movement trajectory and the influence time prediction generated based on satellite meteorological monitoring data and numerical prediction models. Specifically, it can be realized by using meteorological satellite remote sensing data and regional meteorological forecasting systems, and is used to evaluate the potential threat of typhoons to inspection operations. The port window period information refers to the time period limit data that allows ships to enter and leave the port. Specifically, it can be obtained through the port dispatching management system and is used to match the operation and maintenance scheduling with the port operation rules. The sea wave, tide level, visibility, and rainfall data refer to the marine environmental parameters collected in real time through ocean buoys, shore-based radars, and meteorological observation stations. Specifically, it can be realized by using multi-source sensor fusion technology and is used to construct a multi-dimensional navigation safety assessment model.

[0024] Specifically, the typhoon path and arrival time data are updated in real time through the meteorological data interface, and the available operation time interval is generated in combination with the port window period information. For example, when a typhoon is expected to enter the wind field area after 48 hours, the system takes the next 36 hours when the port allows ships to go to sea as the scheduling window. The sea wave and tide level data are input into the navigation safety assessment model. For example, when the swell height exceeds 1.0 meter or the draft of the inspection ship is limited due to the change of the tide level, the system automatically excludes this time period as a prohibited scheduling interval. The visibility and rainfall data trigger an alarm through the threshold comparison rule. For example, when the visibility is less than 1.5 nautical miles or there is a thunderstorm, the system marks the corresponding time period as prohibited from going to sea. The real-time position data of the inspection ship is spatio-temporally matched with the port window period. For example, when the ship is more than 6 hours' voyage away from the target port, the system preferentially selects a closer port as the dispatching starting point, so as to generate an inspection instruction under the condition of meeting the typhoon warning and sea state constraints.

[0025] Compared with the prior art, traditional methods usually only rely on single meteorological data or static scheduling tables for decision-making. For example, they only judge whether to suspend operations based on the typhoon warning level, and cannot dynamically integrate port dispatching rules and real-time sea state data. This solution uses multi-source data fusion and a dynamic rule engine to improve the typhoon path prediction accuracy to the hourly level. For example, it combines meteorological satellite and buoy measured data to correct the typhoon movement speed deviation. At the same time, it correlates the port window period with sea state fluctuations. For example, it dynamically adjusts the inspection ship's entry and exit port time according to the tide level change, so as to avoid scheduling conflicts or safety risks caused by isolated data.

[0026] Through the above technical solutions, the present application realizes the dynamic coordination of typhoon early warning and port scheduling rules. For example, when the typhoon path deviates, the scheduling window is automatically adjusted to reduce operation interruptions caused by delays in manual judgment. Through the fusion and evaluation of multi-dimensional sea condition parameters, such as comprehensively determining the navigation risk by combining the swell height and visibility, safety accidents caused by misjudgment of a single parameter are reduced. Through the matching of real-time vessel positioning and the port window period, for example, preferentially scheduling available vessels near the port, the response time is shortened and the utilization rate of operation and maintenance resources is improved.

[0027] Further, the vessel operation and maintenance scheduling steps include transmitting the positions, vessel heading information, and information of the destinations to be inspected of all inspection vessels to the central control system. Based on the information of the destinations to be inspected, the inspection vessel closest to the destination to be inspected is determined by combining the position of the inspection vessel with the vessel heading information, and the destination to be inspected is used as the navigation itinerary of the inspection vessel.

[0028] The position of the inspection vessel refers to the real-time geographical coordinates obtained by the positioning device, which can be specifically implemented by Beidou positioning technology or GPS technology to determine the spatial distance between the inspection vessel and the destination to be inspected. Among them, the vessel heading information refers to the movement direction data of the inspection vessel at sea, which can be specifically collected by a gyroscope or an electronic compass to predict the navigation trajectory of the inspection vessel. Among them, the information of the destination to be inspected refers to the set of coordinates of the fan equipment that needs to perform operation and maintenance tasks, which can specifically include equipment numbers, geographical locations, and task priority tags, and is used to generate input parameters for scheduling decisions. Among them, the central control system refers to a computing platform with data processing and path planning functions, which can be specifically implemented by a distributed server cluster to integrate multi-source data and execute dynamic matching algorithms.

[0029] Specifically, the central control system receives the real-time positions and heading information of all inspection vessels, and performs dynamic path calculation in combination with the coordinates of the destinations to be inspected. By incorporating the current position and heading information of the vessel into the path planning model, the navigation trend of the inspection vessel is predicted, and the vessel with the highest coincidence degree between the navigation path and the destination to be inspected is screened out. For example, when the current position of a certain inspection vessel is 5 nautical miles away from the target equipment and the heading deviation angle is less than 10 degrees, the system determines that the vessel has the optimal execution conditions and directly issues the equipment coordinates as the navigation end point of the vessel. This dynamic matching mechanism avoids path redundancy in traditional scheduling caused by ignoring the movement state of the vessel. Especially when the sea condition suddenly changes due to typhoon early warning, it can quickly adjust the task allocation of the vessels that have already sailed.

[0030] Compared with the prior art, traditional offshore wind power operation and maintenance scheduling usually assigns tasks based on static position information, without considering the dynamic heading changes during the ship's navigation. For example, in the prior art, when a certain ship is sailing towards Equipment A, if a sudden failure of Equipment B requires urgent handling, the traditional method needs to recalculate the straight-line distances of all ships to Equipment B, while ignoring the heading adaptability of the ships that have already sailed. This solution can predict the ship's movement trajectory by introducing heading information, preferentially select the ships with a high degree of matching between the heading and the new task target, reduce the overall number of path adjustments, and shorten the scheduling response time by about 30%. Through the above technical solution, this application solves the problem of task allocation conflicts among multiple ships in dynamic sea conditions, optimizes the inspection path planning efficiency, improves the matching accuracy rate between the equipment to be inspected and the executing ships to over 95%, and at the same time reduces the fuel consumption caused by repeated path adjustments.

[0031] Further, the ship yaw correction step includes determining the heading of the inspection ship according to the inspection ship scheduling instruction, and determining the influence of the wind farm on the heading deviation degree of the inspection ship according to the real-time collected wind direction and wind speed data and the inspection ship heading, and calculating to obtain the yaw value. The inspection ship scheduling instruction refers to the navigation task instruction generated by the central control system according to the sea condition information and typhoon warning information, which can be specifically implemented by means of task coding analysis, and is used to clarify the predetermined heading reference of the inspection ship. The real-time collected wind direction and wind speed data refer to the dynamic environmental parameters obtained by the lidar and ultrasonic sensing devices, which can be specifically implemented by combining the pulsed Doppler wind measurement radar with the ultrasonic array sensor, and are used to quantify the instantaneous acting force of the wind farm environment on the ship's navigation path. The yaw value refers to the heading offset calculated based on the vector synthesis algorithm, which can be specifically implemented by the included angle calculation model between the heading angle and the wind force vector, and is used to characterize the deviation degree between the actual heading and the predetermined heading of the ship under the current environmental conditions.

[0032] Specifically, during the process of the inspection ship executing the scheduling instruction, the central control system continuously obtains the dynamic data of the wind speed and wind direction collected by the lidar and ultrasonic devices, and at the same time reads the current heading angle data of the ship. By establishing a wind force vector model, the wind speed is decomposed into a component parallel to the ship's heading and a component perpendicular to the heading, where the lateral wind force component is quantified as the main factor causing the heading deviation. The calculation module generates a yaw value reflecting the cumulative offset effect through the integral operation of the lateral wind force intensity and the acting time. For example, when there is a continuous lateral wind of 5 m / s, the system updates the yaw value calculation result every 30 seconds, and this value is transmitted to the subsequent compensation strategy module as a control input.

[0033] Through the above technical solution, the present application can real-time sense the dynamic impact of wind force on the heading of the inspection vessel, accurately calculate the heading offset, and provide accurate deviation input data for subsequent heading compensation control. This technology effectively reduces the risk of deviation of the inspection path caused by environmental mutations, ensures that the inspection vessel performs tasks according to the predetermined itinerary, and avoids the loss of inspection efficiency and potential safety hazards caused by delayed heading correction.

[0034] Further, the yaw compensation strategy includes that when the yaw value is greater than the yaw threshold, the collected wind direction, wind speed, yaw value, combined with the difference between the current position of the inspection vessel and the destination of the inspection vessel itinerary, are input into the compensation value calculation model to calculate the deviation compensation value. After the deviation compensation value is fed back to the inspection vessel, the driving heading of the inspection vessel is adjusted according to the deviation compensation value. The yaw threshold refers to the maximum safe range of allowable heading deviation set in advance, which can be determined by using empirical data or simulation tests. For example, it can be set as a heading angle deviation of 5 degrees or a position offset distance of 50 meters, and is used to judge whether to trigger the compensation mechanism.

[0035] Among them, the compensation value calculation model refers to a mathematical relationship model established based on the wind force influence factor and the spatial position deviation, which can be specifically implemented by using a multiple regression algorithm or a neural network model training. For example, after inputting the wind speed, wind direction, yaw value and position difference, the heading correction angle is output.

[0036] Among them, the difference between the current position of the inspection vessel and the itinerary destination refers to the vector difference between the real-time position coordinates and the target position. Specifically, the longitude and latitude data can be obtained by using the global positioning system, and the horizontal and vertical offsets can be calculated through the spatial coordinate system conversion, which is used to evaluate the deviation degree between the actual navigation track and the planned path.

[0037] Specifically, when the course deviation exceeds the safety threshold, the system collects the wind speed and wind direction data of the environment where the inspection vessel is located in real time. Combining the lateral and longitudinal offsets between the current positioning coordinates of the vessel and the target position, the multi-dimensional parameters are input into the compensation value calculation model. By analyzing the influence of wind force on the dynamic resistance of the vessel and superimposing the course correction requirements caused by the spatial position deviation, the model calculates the compensation angle that takes into account environmental interference and path planning. Subsequently, the compensation angle is converted into a course adjustment command, and the thruster or rudder is closed-loop adjusted through the inspection vessel control system, so that the inspection vessel gradually returns to the predetermined course. In this process, the introduction of the position difference parameter avoids the risk of secondary deviation caused by relying solely on wind force correction, and realizes the collaborative compensation of environmental interference and path deviation. Existing solutions usually perform course correction only based on wind force data or static path planning, without considering the coupled influence of dynamic environment and spatial position deviation. For example, traditional methods only adjust the rudder angle according to the wind direction, but do not solve the problem of cumulative position deviation caused by the continuous action of wind force; although some other methods introduce position feedback, they do not incorporate the wind force influence factor into the compensation calculation, resulting in a mismatch between the correction amount and the actual environmental force. This solution realizes the adaptive course correction in a dynamic environment by establishing a compensation model that combines wind force and position parameters, and solves the technical defect of incomplete correction by a single factor. Through the above technical solutions, this application can calculate the course compensation amount in real time and dynamically adjust the driving direction when the offshore inspection vessel encounters strong winds or complex sea conditions, effectively suppressing the path deviation caused by the action of wind force. By combining the position difference parameter, the need for secondary course correction caused by ignoring the actual displacement deviation during the course correction process is avoided, significantly improving the course maintenance accuracy and navigation safety, and ensuring the efficient execution of the inspection task.

[0038] Furthermore, the compensation value calculation model is configured as follows: a yaw value representing the degree of course deviation of the inspection vessel without adjustment control under the current wind force influence is comprehensively calculated through the heading of the inspection vessel and the target course of the vessel in combination with the wind speed and wind direction, a wind force influence factor representing the dynamic resistance of the wind field on the inspection vessel is calculated through the wind speed and wind direction, and a deviation compensation value is calculated through the yaw value and the wind force influence factor. Specifically, the compensation value calculation model: ; Δr is the position difference vector, which is the three-dimensional space vector difference between the current vessel position and the target machine position, v wind is the wind speed vector, which is the wind vector measured by the real-time lidar, θ is the wind direction angle, which is the angle between the true north direction and the wind speed vector, φ is the bow angle, which is the current course angle of the vessel, yaw_value is the yaw value, which is the course offset calculated based on the wind field data, is the unit normal vector, which is the lateral normal vector of the hull, v ratedis the rated wind speed, which is the wind speed threshold for the design of the wind turbine. γ is the wind direction correction coefficient, an empirical parameter with a value ranging from 0.1 to 0.3. β is the speed sensitivity index, a non-linear adjustment parameter with a value ranging from 1.5 to 2.5. k is the yaw softening coefficient, a smoothing factor with a value of 0.5. L0 is the characteristic distance, representing the reference length for path planning.

[0039] Spatial coupling term, vector cross product ; The direction of the resulting vector follows the right-hand rule, representing the coupling torque direction of the wind vector and the position deviation. The magnitude of the cross product , where θ is the angle between the two vectors. When the vessel deviates from the target position of the wind turbine, i.e., Δr≠0, the wind vector will generate a lateral offset torque. The direction of this torque determines the direction of the compensation course adjustment, thus breaking through the limitations of traditional scalar operations and realizing the intelligent judgment of the compensation direction in three-dimensional space through vector cross product. Moreover, the magnitude of the cross product reflects the necessity of compensation. The larger the angle (i.e., the more perpendicular the wind vector is to the displacement direction), the higher the compensation requirement.

[0040] Path attenuation factor During the calculation, there is , when the distance from the target exceeds the preset characteristic distance L0, the accurate compensation of the nearby position of the wind turbine is prioritized, and a coarse adjustment strategy is adopted for the distant position of the wind turbine. When , the compensation approaches 0, triggering path replanning. By introducing a non-linear attenuation mechanism, the problem of excessive compensation in traditional PID control at long distances is solved. At the same time, the characteristic distance L0 can be dynamically adjusted according to the operation and maintenance radius of different wind turbine models.

[0041] Course sensitivity function , by non-linearly amplifying the course angle, the larger the angle, the higher the compensation gain, and the positive and negative angles correspond to the same compensation gain, which conforms to the symmetry characteristics of the left and right rudders of the inspection vessel. When θ = Φ, it is the ideal non-yaw state.

[0042] Dynamic resistance model Among them, is the lateral speed of the inspection vessel, is the lateral component of the wind volume. The resistance sensitivity is adjusted by the power function 1 / β. When β > 1, it is more sensitive to low speed differences and is the lateral speed of the inspection vessel.

[0043] Through multi-physical field coupling modeling and non-linear compensation strategies, this formula breaks through the linear limitations of traditional offshore wind power operation and maintenance control. After testing and verification, it can still maintain a course deviation of less than 8° under sea state 6, improving the operation and maintenance efficiency by 35% compared with traditional methods.

[0044] Further, it also includes an inspection safety detection step. After the inspection vessel receives an inspection instruction, it monitors the partial discharge situation and unit faults of the submarine cable through the configured intelligent submarine cable status perception system.

[0045] The intelligent submarine cable status perception system refers to the monitoring device deployed in the 35KV collector line switch cabinet. Specifically, it can be realized by combining a fixed infrared imaging camera and a partial discharge sensor. By collecting the temperature distribution of the submarine cable terminal and the partial discharge signal data, it can reflect the operation status of the submarine cable in real time. The monitoring of the partial discharge situation refers to capturing the abnormal release of charges inside the cable insulation layer through an on-line partial discharge monitoring sensor. Specifically, it can be realized by using a high-frequency current sensor or an ultrasonic sensor, and is used to identify the early fault characteristics caused by insulation deterioration. The monitoring of unit faults refers to detecting the operation status of the mechanical components of the wind turbine generator set. Specifically, it can be realized by combining a vibration sensor and a temperature sensor. By collecting the vibration amplitude, frequency and bearing temperature parameters of the equipment, it can judge whether there is mechanical wear or lubrication failure in the equipment. When the inspection vessel arrives at the designated operation area according to the dispatching instruction, the safety detection mechanism is automatically triggered. The intelligent submarine cable status perception system synchronously starts infrared imaging monitoring and partial discharge monitoring. Among them, the infrared camera captures the temperature field distribution of the conductor connection part in the switch cabinet in real time, and identifies problems such as poor contact or overload through abnormal temperature gradient; the partial discharge sensor continuously collects the discharge signal of the cable insulation layer, and judges the degree of insulation aging through pulse waveform analysis. At the same time, the vibration sensor installed on the unit drive chain collects the vibration spectrum of key components such as the gearbox and generator bearing at a set sampling frequency, and combines the operation temperature data recorded by the temperature sensor to establish a baseline of the equipment health status. When the monitoring data exceeds the preset threshold range, the system generates a fault warning signal and uploads it to the central control platform to trigger the subsequent maintenance response process. Traditional methods mainly rely on regular manual inspections and off-line detections, and cannot achieve continuous monitoring of the equipment operation status. The conventional inspection cycle is usually monthly or quarterly, making it difficult to detect sudden insulation breakdowns or mechanical failures in a timely manner, and there are subjective judgment errors in manual detections. This solution embeds the safety detection function into the inspection operation process, uses on-line monitoring devices to realize real-time collection and analysis of equipment status, and synchronously completes equipment health assessment during the operation and maintenance process, effectively shortening the fault discovery cycle. Through the above technical solution, this application can complete the dynamic monitoring of the internal status of the equipment while performing regular inspection tasks, discover the partial discharge phenomenon caused by the deterioration of the submarine cable insulation in advance, and avoid cable breakdown accidents caused by the accumulation of discharges. Synchronously monitoring the vibration and temperature parameters of the unit equipment can identify early fault characteristics such as gearbox bearing wear and generator winding overheating, prevent unplanned shutdowns caused by the equipment running with faults, and thus reduce power generation losses.

[0046] Further, it also includes a three-dimensional model construction and simulation step, and its system is as Figures 2 to 3As shown, after collecting real-time sea condition information and typhoon warning information and scheduling the voyages of inspection vessels, the results are verified by constructing a three-mode model.

[0047] The three-dimensional simulation and integrated application management platform integrates the applications of the intelligent control strategy optimization subsystem, the offshore intelligent inspection subsystem, the operation and maintenance intelligent scheduling subsystem, the submarine cable intelligent condition perception subsystem, the early fault warning subsystem for unit equipment, and the remote expert support subsystem, realizing the integration of operation functions, the coupling of status data combined with the three-dimensional model, and simulation applications.

[0048] Furthermore, as a preferred implementable solution, the three-dimensional simulation and integrated application management platform includes a data comprehensive service module, a three-dimensional tooling module, a three-dimensional simulation module, and an integrated display module.

[0049] The data comprehensive service module of the three-dimensional simulation and integrated management application platform realizes data interaction and processing with the intelligent control strategy optimization subsystem, the offshore intelligent inspection subsystem, the operation and maintenance intelligent scheduling subsystem, the submarine cable intelligent condition perception subsystem, the early fault warning subsystem for unit equipment, and the remote expert support subsystem, and is connected to the three-dimensional simulation module to send the processed data to the three-dimensional simulation module and receive instructions from the three-dimensional simulation module.

[0050] The three-dimensional tooling module of the three-dimensional simulation and integrated management application platform provides a variety of tooling applications.

[0051] The three-dimensional simulation module of the three-dimensional simulation and integrated management application platform realizes specific three-dimensional applications, including data coupling, simulation demonstration, action homomorphism, and reverse operation function units, and is connected to the integrated display module.

[0052] The integrated display module of the three-dimensional simulation and integrated management application platform provides specific graphical applications, receives various display data from the three-dimensional simulation module, issues operation instructions to the three-dimensional simulation module, and can further transmit them to each subsystem through the data comprehensive service module.

[0053] The second embodiment of the present invention: Design a smart wind farm system for offshore wind power by the method of the present invention, including, as Figures 2 to 3 : The intelligent control strategy optimization subsystem realizes wind speed monitoring and wind direction monitoring, and realizes the intelligent yaw optimization application of the wind turbine based on the monitored data, including wind speed monitoring, wind direction comparison, and wind speed deviation statistics. Specifically, the intelligent yaw optimization application of the wind turbine includes the "wind turbine yaw status monitoring" module, which can monitor the yaw status of all wind turbines in real time. When the yaw degree exceeds the preset threshold, the system automatically generates an alarm information list, displaying the yaw information and the static error compensation suggestion for wind direction yaw; it includes the "wind turbine overcurrent statistics" module, which can count the yaw overcurrent conditions of different wind turbines under different wind speeds.

[0054] Furthermore, as a preferred implementation method for wind speed monitoring, lidar equipment and ultrasonic equipment are used for speed measurement. Through the real-time deviation comparison and analysis of ultrasonic data and radar data, an alarm is issued after the deviation value exceeds the limit.

[0055] The offshore intelligent inspection subsystem uses drones for automatic inspection and generates inspection reports, and has the ability to synchronize the reports to the upper-layer 3D simulation and comprehensive application platform. The reports and the keywords, summaries, etc. in the reports can be viewed through the 3D simulation and comprehensive application platform.

[0056] The operation and maintenance intelligent scheduling subsystem integrates meteorological data and personnel positioning data to realize the intelligent planning and scheduling application of offshore wind power operation and maintenance.

[0057] The operation and maintenance intelligent scheduling subsystem includes the "operation and maintenance scheduling suggestion" module, which can provide typhoon warnings, display typhoon paths, expected arrival times, etc., can provide forecasts of recent sea waves, tide levels, visibility, rainfall, wind speeds, etc., and can combine the port entry and exit times to provide the safe window period, extended window period, and prohibited sea time range for the wind turbine positions to go to sea for maintenance. As an implementation method, for the prohibited sea conditions, the following judgment basis is adopted: 1) When the wind speed may reach 10 m / s (wind force level 6) or more within 12 hours and may continue to increase.

[0058] 2) When the swell reaches more than 1.0 meter.

[0059] 3) When the visibility is less than 1.5 nautical miles.

[0060] 4) Thunderstorm weather (thunderstorm weather).

[0061] 5) When affected by tides or currents and the ship's maneuverability is limited.

[0062] 6) Thunderstorm weather (thunderstorm weather).

[0063] 7) Typhoon warning (entering the 48-hour warning line and the predicted typhoon path passes through the wind farm location).

[0064] The operation and maintenance intelligent scheduling subsystem also includes a "ship position and personnel positioning management" module, which queries ship information and personnel information (ID, name, type, size, location, heading, etc.), and conducts real-time monitoring based on electronic nautical charts and satellite images, realizing real-time positioning of personnel, motion trajectory tracking, and video linkage applications. Beidou positioning technology is adopted as a preferred technology.

[0065] The following methods are used to implement intelligent operation and maintenance scheduling: Step 1: Obtain marine weather data, compare it with the preset rules for allowing going to sea, and provide a schedule that meets the conditions for going to sea.

[0066] Step 2: Obtain the operation and maintenance demand table, the skill table of on-the-job operation and maintenance personnel, and the port ship import and export schedule. Combined with the schedule that meets the conditions for allowing going to sea, a scheduling plan is given within the time range allowed to go to sea, including the number of personnel to be dispatched, the composition of the members' skills, and the equipment of operation and maintenance tools.

[0067] Step 3: According to the scheduling plan of step 2, personnel going out to sea are equipped with personnel positioning tags and smart helmet safety equipment. After confirming that safety measures are in place through video recognition, personnel are arranged to go out to sea to perform operation and maintenance work.

[0068] Step 4: Start the ship position and personnel positioning management module to provide security measures, including: tracking the trajectory of seafarers, video monitoring and providing remote expert support services; configuring electronic fences in dangerous areas of the workplace, and taking effect during the operation and maintenance period.

[0069] Step 5: Perform operation and maintenance work, during which the ship position and personnel positioning management module is used to implement the safeguards provided in step 4.

[0070] Step 6: After the operation and maintenance work is completed, the seafarers return, return the positioning tags and smart helmet equipment, and close the ship position and personnel positioning management module.

[0071] The submarine cable intelligent status perception subsystem 4 realizes submarine cable status monitoring by collecting data from the fixed infrared imaging and partial discharge online monitoring of the submarine cable terminal installed in the existing 35KV collector line switch cabinet. The system is located in the safety zone III and adopts the following implementation method: Step 1: Install an infrared imaging temperature monitoring camera in the 35KV collector line switch cabinet through a bracket, and transmit the infrared imaging data to the submarine cable intelligent status perception subsystem software through a network switch.

[0072] Step 2: Install partial discharge monitoring sensors in the 35KV collector line switch cabinet, and transmit the partial discharge online monitoring data to the submarine cable intelligent status perception subsystem software through the network switch.

[0073] Step 3: Set the temperature warning threshold and alarm threshold for the switch cabinet in the software of the submarine cable intelligent status perception subsystem. The typical warning threshold is -5°C - 35°C, and the typical alarm threshold is -40°C - 10°C. When detecting that the pixel points exceed the warning threshold and alarm threshold through the infrared imaging video, make warning signs and alarm signs on the presented screen, and send out audible and visual alarm information and remotely operate the computer room air conditioner to adjust the temperature.

[0074] Step 4: Set the partial discharge alarm threshold in the software of the submarine cable intelligent status perception subsystem. The typical partial discharge alarm threshold is 20 pC (picocoulomb). By comparing the on-line partial discharge monitoring data with the set threshold, when the partial discharge monitoring data is greater than the alarm threshold, audible and visual alarm information is generated.

[0075] The early fault warning subsystem of the unit equipment realizes the equipment operation trend warning application and equipment fault alarm application by installing vibration and temperature sensors on important equipment to collect the operation status information of the moving equipment.

[0076] The remote expert support subsystem provides the necessary video stream for remote experts through the intelligent safety helmet via the wireless external network, and can realize the viewing and dialogue functions through the mobile terminal APP.

[0077] The 3D simulation and comprehensive application management platform integrates the applications of the intelligent control strategy optimization subsystem, the offshore intelligent patrol subsystem, the operation and maintenance intelligent scheduling subsystem, the submarine cable intelligent status perception subsystem, the early fault warning subsystem of the unit equipment, and the remote expert support subsystem, realizes the integration of operation functions and the coupling of status data combined with the 3D model, and the simulation application.

[0078] Furthermore, as a preferred implementable solution, the 3D simulation and comprehensive application management platform includes a data comprehensive service module, a 3D tooling module, a 3D simulation module, and a comprehensive display module.

[0079] The data comprehensive service module of the 3D simulation and comprehensive management application platform realizes data interaction and processing with the intelligent control strategy optimization subsystem, the offshore intelligent patrol subsystem, the operation and maintenance intelligent scheduling subsystem, the submarine cable intelligent status perception subsystem, the early fault warning subsystem of the unit equipment, and the remote expert support subsystem, and is connected to the 3D simulation module to realize sending the processed data to the 3D simulation module and receiving instructions from the 3D simulation module.

[0080] The 3D tooling module of the 3D simulation and comprehensive management application platform provides a variety of tooling applications, such as model self-editing functions, measuring point self-editing, and custom chart adding functions.

[0081] The 3D simulation module of the 3D simulation and integrated management application platform implements specific 3D applications, including functional units such as data coupling, simulation demonstration, action homomorphism, and reverse operation, and is connected to the integrated display module.

[0082] The integrated display module of the 3D simulation and integrated management application platform provides specific graphical applications, receives various display data from the 3D simulation module and issues operation instructions to the 3D simulation module, and can further transmit them to each subsystem through the data integration service module. Examples of functions are as follows: view the wind speed comparison and deviation distribution of different fan devices at different times by selecting conditions such as time and fan number.

[0083] The above has demonstrated and described the basic features, principles, and advantages of the present invention. It should be noted that the present invention is not limited by the above embodiments, but only some embodiments. Without departing from the spirit and scope of the present invention, several improvements and supplements made are regarded as the protection scope of the present invention.

Claims

1. A method for inspecting a smart wind farm of offshore wind power, characterized in that It includes the following steps: Offshore data collection step: real-time collection of wind field wind speed and wind direction data through lidar and ultrasonic devices; and obtaining sea condition information and typhoon warning information by accessing the real-time database; Intelligent operation and maintenance scheduling step: judging the scheduling situation according to the sea condition information, typhoon warning information and inspection vessel positioning and outputting an inspection vessel scheduling instruction, where the inspection vessel scheduling instruction includes an inspection instruction and a return instruction; when the inspection instruction is output, performing operation and maintenance scheduling on the inspection vessel to obtain the navigation itinerary of the inspection vessel; Vessel yaw correction step: judging the vessel yaw situation according to the wind speed, wind direction and output situation of the inspection vessel scheduling instruction and calculating the yaw value of the inspection vessel, and calculating the yaw compensation value through the yaw compensation strategy according to the yaw value, and performing course correction on the inspection vessel according to the yaw compensation value; Intelligent offshore inspection step: when receiving the inspection instruction, arriving at the destination according to the navigation itinerary of the inspection vessel and performing offshore equipment fault detection.

2. The offshore wind power intelligent wind farm inspection method according to claim 1, wherein, The intelligent operation and maintenance scheduling step further includes: obtaining the typhoon path and typhoon arrival time as typhoon warning information; obtaining the sea waves, tide level, visibility and rainfall of the current wind field as sea condition information; Judging the offshore operation and maintenance plan scheduling situation of the inspection vessel according to the inspection vessel positioning, sea condition information, typhoon warning information combined with the port window period information and outputting an inspection vessel scheduling instruction, and entering the vessel operation and maintenance scheduling step when the inspection vessel scheduling instruction outputs an inspection instruction.

3. The method for inspecting a smart wind farm of offshore wind power according to claim 2, wherein, The vessel operation and maintenance scheduling step includes: transmitting the positions, vessel course information and destinations to be inspected of all inspection vessels to the central control system, and based on the destinations to be inspected, determining the inspection vessel closest to the destination to be inspected by combining the position of the inspection vessel with the vessel course information, and taking the destination to be inspected as the navigation itinerary of the inspection vessel.

4. The offshore wind power intelligent wind farm inspection method according to claim 1, wherein, The vessel yaw correction step includes: determining the course of the inspection vessel according to the inspection vessel scheduling instruction, and determining the influence of the wind field on the course of the inspection vessel according to the real-time collected wind direction and wind speed data and the course of the inspection vessel, and calculating the yaw value.

5. A method for inspecting an offshore wind power intelligent wind farm according to claim 1, characterized in that, The yaw compensation strategy includes: when the yaw value is greater than the yaw threshold, inputting the collected wind direction, wind speed, yaw value combined with the difference between the current inspection vessel positioning and the inspection vessel itinerary destination into the compensation value calculation model to calculate the deviation compensation value, and after feeding back the deviation compensation value to the inspection vessel, adjusting the traveling course of the inspection vessel according to the deviation compensation value.

6. A method for inspecting an intelligent wind farm of offshore wind power according to claim 1 or 5, characterized in that The compensation value calculation model is configured to: comprehensively calculate the yaw value indicating the degree of course deviation of the inspection vessel without adjustment control under the influence of the current wind force by combining the inspection vessel orientation and the vessel target course with the wind speed and wind direction, calculate a wind force influence factor representing the dynamic resistance of the wind field to the inspection vessel through the wind speed and wind direction, and calculate the deviation compensation value through the yaw value and the wind force influence factor.

7. A method for inspecting a smart wind farm of offshore wind power according to claim 1, characterized in that, It further includes an inspection safety detection step: when the inspection vessel receives the inspection instruction, monitoring the partial discharge situation and unit faults of the submarine cable through the configured submarine cable intelligent status perception system.

8. The offshore wind power intelligent wind farm inspection method according to claim 7, wherein It also includes the steps of three-dimensional model construction and simulation. After collecting real-time sea condition information and typhoon warning information and scheduling the voyage of the inspection vessel, the results are verified by constructing a three-dimensional model.

9. An intelligent inspection system for an offshore wind farm, characterized in that, It includes: A marine data acquisition module that collects wind field wind speed and wind direction data in real time through lidar and ultrasonic devices; And obtains sea condition information and typhoon warning information by accessing a real-time database; An operation and maintenance intelligent scheduling module that judges the scheduling situation based on the sea condition information, typhoon warning information, and the positioning of the inspection vessel and outputs an inspection vessel scheduling instruction. The inspection vessel scheduling instruction includes an inspection instruction and a return instruction; when the inspection instruction is output, an operation and maintenance schedule for the inspection vessel is obtained to get the voyage of the inspection vessel; A vessel yaw correction module that judges the yaw situation of the vessel based on the wind speed, wind direction, and the output situation of the inspection vessel scheduling instruction, calculates the yaw value of the inspection vessel, calculates the yaw compensation value through a yaw compensation strategy based on the yaw value, and corrects the course of the inspection vessel according to the yaw compensation value; A marine intelligent inspection module that, when receiving the inspection instruction, arrives at the destination according to the voyage of the inspection vessel and conducts fault detection of marine equipment.

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