A state monitoring based adaptive wind turbine survival control method and system

Abstract

The present application relates to the technical field of wind power generation control, and proposes a kind of adaptive wind turbine survival control method and system based on state monitoring, the adaptive wind turbine survival control method includes: obtaining the state monitoring data of offshore wind turbine, the survival threat type that wind turbine currently faces is identified based on state monitoring data;According to the survival threat type identified, the corresponding adaptive survival mode is matched in the preset survival mode library, the survival mode library includes the wind anchoring survival mode corresponding to the structure dynamic threat, the anticorrosion cycle survival mode corresponding to the corrosion acceleration threat and the electrical isolation survival mode corresponding to the function failure threat, wherein each survival mode is provided with the operating parameter boundary of wind turbine maintained in the safe operation boundary;The coping strategy corresponding to the adaptive survival mode matched is executed, including adjusting the mechanical control parameter, electrical control parameter and structure protection parameter of wind turbine, the operating state of wind turbine is constrained in the operating parameter boundary.

Description

Technical Field

[0001] This invention relates to the field of wind power generation control technology, and in particular to an adaptive wind turbine survival control method and system based on condition monitoring. Background Technology

[0002] Currently, the operation and control of offshore wind turbines under extreme environmental conditions mainly rely on the independent protection mechanisms of each subsystem. For example, the converter performs grid disconnection protection when the grid fails, the yaw system performs wind lock-in after the wind speed exceeds the limit, and the structural monitoring system only triggers an alarm after damage occurs. However, these decentralized protection strategies lack a systematic overall coordination of the overall survival status of the wind turbine: on the one hand, existing control methods have not established a unified survival threat identification mechanism based on multi-source status monitoring data. Mechanical, electrical, and environmental monitoring data are isolated, making it impossible for the wind turbine to have a global situational awareness when facing combined threats such as extreme wind loads from typhoons, accelerated corrosion from high salt spray, or failure of critical electrical components. On the other hand, existing technologies have not formed an adaptive survival mode library that matches specific threat types. The protection actions of each subsystem lack unified operating parameter boundary constraints, and it is difficult to achieve coordinated adjustment between mechanical control, electrical control, and structural protection parameters. As a result, under extreme conditions, the independent action of one subsystem often triggers a chain risk to other subsystems, making it impossible to effectively constrain the overall operating status of the turbine within a safe survival boundary. Summary of the Invention

[0003] To address the aforementioned shortcomings, the present invention aims to propose an adaptive wind turbine survival control method and system based on condition monitoring. This method constructs an adaptive survival mode library corresponding to structural dynamic threats, corrosion acceleration threats, and functional failure threats. Based on condition monitoring data, it identifies threat types and matches corresponding survival modes, collaboratively adjusting mechanical control parameters, electrical control parameters, and structural protection parameters. This constrains the wind turbine's operating state within preset operating parameter boundaries, thereby achieving systematic self-protection of offshore wind turbines under extreme environmental conditions.

[0004] To achieve this objective, the present invention adopts the following technical solution: An adaptive wind turbine survivability control method based on condition monitoring includes: Acquire status monitoring data of offshore wind turbines, and identify the types of survival threats currently faced by the wind turbines based on the status monitoring data; Based on the identified survival threat type, a corresponding adaptive survival mode is matched in a preset survival mode library. The survival mode library includes a wind-resistant anchoring survival mode corresponding to structural dynamic threats, an anti-corrosion cycle survival mode corresponding to corrosion acceleration threats, and an electrical isolation survival mode corresponding to functional failure threats. Each survival mode is equipped with operating parameter boundaries that keep the wind turbine within the safe operating boundary. The corresponding coping strategies for the matched adaptive survival mode are executed, including adjusting the mechanical control parameters, electrical control parameters, and structural protection parameters of the wind turbine, so as to constrain the wind turbine's operating state within the boundaries of the operating parameters.

[0005] Preferably, the types of survival threats currently faced by the wind turbine identified based on the condition monitoring data include: Based on the marine environmental field parameter dimension, the state monitoring data is screened at the first level to identify whether there are extreme environmental conditions, so as to determine whether a survival threat warning is triggered. From the state monitoring data that triggers the survival threat warning, a first subset of data that meets the dimensions of wind turbine operating state parameters is selected, and a second-level selection is performed based on the first subset of data to identify the threat category as structural dynamic threat, corrosion acceleration threat or functional failure threat. A second subset of data that conforms to the dimensions of wind turbine structural response parameters is selected from the first subset of data, and a third-level selection is performed based on the second subset of data to determine the threat level corresponding to the survival threat type; Set the priority of the third-level filter results to the highest, and set the priority of the first-level filter results to the lowest.

[0006] Preferably, matching the corresponding adaptive survival mode from a preset survival mode library based on the identified survival threat type includes: When the threat category identified by the second-level screening tends to be a structural dynamic threat, the corresponding survival mode is initially selected from the survival mode library; Based on the threat level determined by the third level of screening, the operational parameter boundary that matches the threat level is extracted from the initially selected survival mode, and the current survival mode is determined to be the wind-resistant anchored survival mode. Based on the highest priority judgment result of the third level, if the structural response parameters are found to exceed the preset safety deviation, the boundary of the operating parameters in the wind-resistant anchoring survival mode is reduced.

[0007] Preferably, the coping strategies corresponding to the matched adaptive survival mode include: According to the operating parameter boundaries of the wind-resistant anchoring survival mode, the yaw system of the wind turbine is adjusted to align the nacelle with the real-time wind direction, and the pitch system is driven to adjust the blade pitch angle to the preset feathering position. Based on the threat level and structural response parameters identified at the third level, the stiffness or damping coefficient of the active damping support components inside the tower is adjusted. The load feedback value of the actuator is monitored in real time, and when the load feedback value reaches the upper limit of the operating parameter boundary, the response frequency of the yaw system is reduced or the adjustment dead zone of the pitch system is increased.

[0008] Preferably, matching the corresponding adaptive survival mode from a preset survival mode library based on the identified survival threat type includes: When the threat category identified by the second-level screening tends to be a corrosion acceleration threat, the corresponding survival mode is initially selected from the survival mode library; Based on the threat level determined by the third-level screening, the operational parameter boundary that matches the threat level is extracted from the initially selected survival mode, and the current survival mode is determined to be the anti-corrosion cycle survival mode. Based on the highest priority judgment result of the third level, if a preset material performance degradation deviation is identified in the structural response parameters of the second data subset, the air quality control boundary in the anti-corrosion cycle survival mode is reduced.

[0009] Preferably, the coping strategies corresponding to the matched adaptive survival mode include: Prioritize the status monitoring data of each level that matches the corrosion protection cycle survival mode, and use the second data subset as the core comparison benchmark. The first data subset is compared with the core comparison benchmark by linkage feature comparison, including: extracting the association rules between marine environmental parameters and wind turbine structural response data, and calculating the degree of difference between the extraction results in corrosion-induced conditions and performance degradation response. The first data subset is compared with the core comparison benchmark by quantitative feature comparison, including: calculating the deviation of real-time statistical values ​​from the boundaries of the operating parameters for statistical indicators such as cabin salt spray concentration, temperature and humidity distribution under operating mode and sealing pressure. Perform auxiliary verification and comparison, comparing the first data subset with at least one other monitoring dimension data other than the core comparison benchmark, to verify whether the degree of difference and deviation are consistent in terms of environmental impact. Based on the degree of difference and the degree of deviation, valid differences are selected from the comparison results, and each valid difference is converted into a control command according to a preset mapping rule. The control commands include adjusting the positive pressure threshold of the cabin, adjusting the power of the temperature and humidity circulation device, and changing the dead zone of the actuator.

[0010] Preferably, matching the corresponding adaptive survival mode from a preset survival mode library based on the identified survival threat type includes: When the threat category identified by the second-level screening tends to be a functional failure threat, the corresponding survival mode is initially selected from the survival mode library; Based on the threat level determined by the third level of screening, the operating parameter boundary that matches the threat level is extracted from the initially selected survival mode, and the current survival mode is determined to be the electrical isolation survival mode. Based on the highest priority determination result of the third level, if a failure deviation is identified in the control loop response signal of the second data subset, the load distribution boundary in the electrical isolation survival mode is reduced.

[0011] Preferably, the coping strategies corresponding to the matched adaptive survival mode include: The objects consuming electricity are assigned corresponding priority logical tags according to their contribution to survival and operation, and the minimum priority threshold for maintaining operation is determined based on the threat level identified in the third level. Based on the real-time changes in the threat level, the on / off sequence of each power supply branch is dynamically adjusted: when the threat level rises, the corresponding branch circuit disconnection action is executed sequentially from low to high until the current operating load matches the load distribution boundary. During the process of executing the circuit disconnection, the output duty cycle or frequency parameter of the power conversion unit is synchronously adjusted to force the feedback of the electrical parameters of the core control circuit to be constrained within the numerical range defined by the boundary of the operating parameters. Based on the changing trend of the electrical parameter feedback value of the core control loop, the operating state of the protection actuator is adjusted in reverse. Through alternating step adjustments of electrical parameters and environmental protection parameters, the operating state of the fan is kept within the preset safety constraint range.

[0012] An adaptive wind turbine survivability control system based on condition monitoring includes: The threat identification module is used to acquire status monitoring data of offshore wind turbines and identify the types of survival threats currently faced by the wind turbines based on the status monitoring data. The pattern matching module is used to match the corresponding adaptive survival mode in the preset survival mode library according to the identified survival threat type. The survival mode library includes the wind-resistant anchoring survival mode corresponding to the structural dynamic threat, the anti-corrosion cycle survival mode corresponding to the corrosion acceleration threat, and the electrical isolation survival mode corresponding to the functional failure threat. Each survival mode is equipped with operating parameter boundaries that keep the wind turbine within the safe operating boundary. The strategy execution module is used to execute the response strategy corresponding to the matched adaptive survival mode, including adjusting the mechanical control parameters, electrical control parameters and structural protection parameters of the wind turbine, and constraining the wind turbine's operating state within the boundaries of the operating parameters.

[0013] One of the above technical solutions has the following advantages or beneficial effects: This invention acquires status monitoring data of offshore wind turbines and identifies the types of survival threats they currently face. It integrates scattered monitoring information into a global survival situation assessment, avoiding the threat identification lag and inaccurate response caused by isolated monitoring data from various subsystems. By matching corresponding adaptive survival modes from a preset survival mode library based on the identified threat type and setting operating parameter boundaries to keep the wind turbine within safe operating limits, it invokes differentiated survival strategy frameworks for different threat types, avoiding insufficient protection or over-response caused by mismatch between a single protection strategy and a specific threat type. By executing the response strategies corresponding to the matched adaptive survival modes, it coordinately adjusts the mechanical control parameters, electrical control parameters, and structural protection parameters of the wind turbine, constraining the overall operating state within the operating parameter boundaries. This achieves orderly linkage of mechanical, electrical, and structural protection actions under a unified survival objective, avoiding cascading risks caused by independent protection of each subsystem. Thus, under extreme operating conditions, offshore wind turbines can achieve systematic self-constraint and protection of the overall operating state based on global situational awareness and targeted strategy matching. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0015] Figure 1 This is a flowchart of the adaptive wind turbine survival control method based on state monitoring provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of the adaptive wind turbine survival control system based on state monitoring provided in an embodiment of the present invention. Detailed Implementation

[0016] Embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0017] In this invention, the terms "comprising," "including," or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0018] An adaptive wind turbine survivability control method based on condition monitoring is disclosed. Specifically, the adaptive wind turbine survivability control method based on condition monitoring described in this invention is applied to the entire offshore wind turbine system. This system includes a main mechanical structure consisting of a tower, nacelle, blades, and foundation platform, as well as a multi-type sensor network deployed at the bottom of the tower, the top of the nacelle, the blade roots, and key parts of the foundation platform. This network includes anemometers, accelerometers, strain gauges, temperature sensors, salt spray concentration sensors, and displacement sensors. The data collected by each sensor is aggregated to a central data processing unit via wired or wireless communication networks. The system has a built-in survival mode library for storing various adaptive survival modes and their corresponding operational parameter boundaries, and is also connected to a real-time controller for generating and distributing control commands to each actuator. The actuators include a yaw system installed between the top of the tower and the bottom of the nacelle for adjusting the nacelle's orientation, a pitch system installed at the root of each blade for adjusting the pitch angle, active damping support components installed inside the tower to suppress structural vibrations, an environmental control system installed inside the nacelle for regulating internal environmental parameters, and power conversion units and switching devices for power supply branch on / off control in the electrical system. Figure 1 As shown, a preferred embodiment of the present invention includes the following steps: S1: Acquire the status monitoring data of the offshore wind turbine, and identify the type of survival threat currently faced by the wind turbine based on the status monitoring data; It should be noted that condition monitoring data refers to a multi-dimensional collection of information reflecting the wind turbine's operating status, environmental conditions, and structural response, collected in real time through a sensor network deployed at key components of the offshore wind turbine. Condition monitoring data includes marine environmental field parameters, wind turbine operating status parameters, and wind turbine structural response parameters. Marine environmental field parameters include physical quantities characterizing the external environment such as wind speed, wind direction, wave height, air temperature, air pressure, and salt spray concentration. Their function is to provide real-time information on the wind turbine's environmental conditions, providing a basis for identifying extreme environmental conditions. Wind turbine operating status parameters include physical quantities characterizing the wind turbine's operating conditions such as generator speed, output power, pitch angle, yaw angle, converter temperature, and nacelle vibration acceleration. Their function is to reflect the real-time operating status of each subsystem of the wind turbine, providing a data foundation for identifying threat categories. Wind turbine structural response parameters include physical quantities characterizing the structural mechanical state, such as tower strain, foundation displacement, blade root bending moment, bolt preload, and weld stress. These parameters directly reflect the mechanical response of the wind turbine structure under environmental loads, providing a basis for quantitative assessment of threat severity. Survival threat types refer to the categories of operating conditions that, based on the analysis results of condition monitoring data, may pose a serious threat to the safe operation of the entire wind turbine. These include structural dynamic threats, accelerated corrosion threats, and functional failure threats. Structural dynamic threats refer to structural vibration, fatigue, or excessive stress response caused by extreme wind loads, wave impacts, or earthquakes, posing a direct risk of damage to the integrity of the wind turbine structure. Accelerated corrosion threats refer to material performance degradation or coating failure caused by environmental factors such as high salt spray concentrations, high humidity, or temperature cycling, posing a progressive damage risk to the durability of the wind turbine structure. Functional failure threats refer to the loss of system function caused by failures of critical electrical components, abnormal control loops, or communication interruptions, posing a sudden risk to the controllability of wind turbine operation.

[0019] Understandably, acquiring condition monitoring data from offshore wind turbines allows for a global situational awareness of the turbine's environmental conditions, operational status, and structural response, avoiding the delays in threat identification caused by isolated monitoring data from various subsystems. By comprehensively analyzing multi-dimensional condition monitoring data, the types of survival threats currently faced by the wind turbine can be identified, enabling a shift from fragmented, localized protection to unified threat identification. This allows for accurate threat type determination and global situational awareness when facing complex threats such as extreme wind loads from typhoons, accelerated corrosion from high salt spray, or failure of critical electrical components. This provides accurate decision-making basis for subsequent adaptive survival mode matching and response strategy execution.

[0020] S2: Based on the identified survival threat type, match the corresponding adaptive survival mode in the preset survival mode library. The survival mode library includes the wind-resistant anchoring survival mode corresponding to the structural dynamic threat, the anti-corrosion cycle survival mode corresponding to the corrosion acceleration threat, and the electrical isolation survival mode corresponding to the functional failure threat. Each survival mode is equipped with operating parameter boundaries that keep the wind turbine within the safe operating boundary. It should be noted that the survival mode library refers to a pre-built structured database containing various adaptive survival modes and their corresponding operational parameter boundaries. Its function is to provide differentiated strategy frameworks for different types of survival threats. The wind-resistant anchoring survival mode is a survival strategy framework designed for structural dynamic threats, with the core objectives of suppressing structural vibration and reducing wind load impact. Its function is to constrain the wind turbine structural response within safe operating boundaries by adjusting mechanical control parameters such as the yaw system, pitch system, and active damping support components. The corrosion-resistant cyclic survival mode is a survival strategy framework designed for accelerated corrosion threats, with the core objectives of controlling internal nacelle environmental parameters and delaying material performance degradation. Its function is to constrain corrosion-inducing conditions within safe operating boundaries by adjusting structural protection parameters such as nacelle positive pressure, temperature and humidity circulation device power, and sealing performance. Electrical isolation survival mode refers to a survival strategy framework designed to address functional failure threats, with the core objective of ensuring power supply to the core control circuit and maintaining minimum survivability. Its function is to constrain the electrical system's operating state within safe operating boundaries by adjusting electrical control parameters such as the on / off timing of power supply branches, output parameters of power conversion units, and load allocation priorities. Operating parameter boundaries refer to the operational value ranges of various control parameters set under a specific survival mode to ensure the wind turbine remains within safe operating boundaries. These include mechanical control parameter boundaries, electrical control parameter boundaries, and structural protection parameter boundaries. Their function is to provide clear numerical constraints for the execution of coping strategies, preventing secondary risks caused by excessive or insufficient parameter adjustments. Safe operating boundaries refer to the set of operating states under extreme conditions that allow the wind turbine to maintain structural integrity, functional control, and prevent catastrophic failure. Their function is to provide the ultimate state constraint target for the overall turbine's survival.

[0021] Understandably, by matching the identified survival threat type with the corresponding adaptive survival mode from a pre-defined survival mode library, a precise match between threat type and protection strategy is achieved, avoiding insufficient protection or over-response caused by a mismatch between a single protection strategy and a specific threat type. By setting operating parameter boundaries for each survival mode to keep the wind turbine within safe operating limits, a unified numerical constraint framework is provided for the coordinated adjustment of mechanical control, electrical control, and structural protection parameters. This allows for the invocation of differentiated survival strategy frameworks when facing different threat types, achieving a balance between targeted protection and overall safety.

[0022] S3: Execute the corresponding response strategy for the matched adaptive survival mode, including adjusting the mechanical control parameters, electrical control parameters and structural protection parameters of the wind turbine, and constraining the wind turbine's operating state within the boundaries of the operating parameters.

[0023] It should be noted that the response strategy refers to a set of control actions formulated to constrain the wind turbine's operating state within the boundaries of operating parameters under a specific adaptive survival mode. Mechanical control parameters refer to physical quantities used to adjust the operating state of the wind turbine's mechanical system, including the yaw system alignment angle, pitch system pitch angle, stiffness coefficient of active damping support components, and pitch system dead zone. Their function is to reduce the impact of external loads on the wind turbine structure through attitude adjustment and dynamic characteristic regulation of the mechanical structure. Electrical control parameters refer to physical quantities used to adjust the operating state of the wind turbine's electrical system, including the on / off sequence of power supply branches, duty cycle of the power conversion unit output, core control loop voltage threshold, and load allocation priority. Their function is to ensure the continuous operation of core functions through energy management and loop control of the electrical system. Structural protection parameters refer to physical quantities used to adjust the operating state of the wind turbine's structural protection system, including the nacelle positive pressure threshold, power of the temperature and humidity circulation device, sealing pressure, and air quality control boundaries. Their function is to delay the performance degradation of structural materials through active control of environmental parameters.

[0024] Understandably, by executing the corresponding coping strategies of the matched adaptive survival mode, the mechanical control parameters, electrical control parameters, and structural protection parameters of the wind turbine are adjusted in a coordinated manner. This achieves orderly linkage of mechanical, electrical, and structural protection actions under a unified survival objective, avoiding the chain risks caused by the independent protection of each subsystem. By constraining the wind turbine's operating state within the boundaries of its operating parameters, the overall operating state is effectively limited within a safe survival boundary, thereby achieving a systematic self-restraint and protection effect for offshore wind turbines under extreme operating conditions.

[0025] Preferably, the types of survival threats currently faced by the wind turbine identified based on the condition monitoring data include: Based on the marine environmental field parameter dimension, the state monitoring data is screened at the first level to identify whether there are extreme environmental conditions, so as to determine whether a survival threat warning is triggered. From the state monitoring data that triggers the survival threat warning, a first subset of data that meets the dimensions of wind turbine operating state parameters is selected, and a second-level selection is performed based on the first subset of data to identify the threat category as structural dynamic threat, corrosion acceleration threat or functional failure threat. A second subset of data that conforms to the dimensions of wind turbine structural response parameters is selected from the first subset of data, and a third-level selection is performed based on the second subset of data to determine the threat level corresponding to the survival threat type; Set the priority of the third-level filter results to the highest, and set the priority of the first-level filter results to the lowest.

[0026] It should be noted that the marine environmental field parameter dimension refers to the set of parameters selected from the condition monitoring data to characterize the external environmental conditions of the offshore wind turbine, including wind speed, wind direction, wave height, air temperature, air pressure, and salt spray concentration. Its function is to provide direct external environmental evidence for identifying extreme environmental conditions. This data is acquired in real-time by environmental monitoring sensors deployed on the wind turbine foundation platform, the top of the tower, and the exterior of the nacelle. The first-level screening refers to a preliminary filtering process that compares and judges each piece of condition monitoring data against preset extreme environmental thresholds, using the marine environmental field parameter dimension as the object. Its function is to quickly identify whether there are external extreme conditions that may endanger the survival of the wind turbine. The judgment criterion is whether each environmental parameter exceeds the corresponding safe operating threshold. Extreme environmental conditions refer to the state where the external environmental conditions of the offshore wind turbine exceed the design safe operating range, including continuous wind speed exceeding the cut-out wind speed, significant wave height exceeding the design wave height, and salt spray concentration exceeding the corrosion acceleration critical value. Their function is to serve as the initial condition for triggering a survival threat warning. Survival threat early warning refers to an alarm signal generated by the central data processing unit after extreme environmental conditions are identified. This signal activates the subsequent refined threat identification process, initiating the second and third-level screening processes and switching the identification mode from routine monitoring to survival threat analysis mode. The wind turbine operating status parameter dimension refers to the set of parameters selected from the condition monitoring data to characterize the operating conditions of each subsystem of the wind turbine. These parameters include generator speed, output power, pitch angle, yaw angle, converter temperature, and nacelle vibration acceleration. Their function is to provide evidence of the internal operating status of the wind turbine for threat category identification. This data is acquired through the sensor network built into the wind turbine main control system and the controllers of each subsystem. The first data subset refers to the data set containing only the wind turbine operating status parameter dimension information, filtered from all condition monitoring data after the survival threat early warning is triggered. Its function is to provide a focused analysis object for the second-level screening, avoiding interference from environmental parameters in threat category identification. The second-level filtering refers to an intermediate filtering process that uses the first subset of data as the object and extracts features and identifies patterns from the wind turbine operating status parameters through a threat category classification model to determine the threat category tendency. Its function is to further subdivide the survival threat warning into three main categories: structural dynamic threats, corrosion acceleration threats, and functional failure threats. Threat category tendency refers to the main category direction of the current survival threat determined based on the second-level filtering results, including structural dynamic threats, corrosion acceleration threats, and functional failure threats. Its function is to provide a category index for the initial selection of patterns in the subsequent survival pattern library.The structural response parameter dimension of a wind turbine refers to the set of parameters selected from condition monitoring data to characterize the mechanical response of the wind turbine structure under load. These parameters include tower strain, foundation displacement, blade root bending moment, bolt preload, and weld stress. Their purpose is to provide direct structural mechanical basis for the quantitative assessment of threat severity. Data is acquired through strain gauges, displacement gauges, and force sensors deployed in the middle of the tower, foundation ring, blade roots, and key connection nodes. The second data subset refers to the data set further filtered from the first data subset after the second-level screening. This subset contains only information on the structural response parameter dimension and provides a refined structural analysis object for the third-level screening. The third-level screening is an advanced filtering process that uses the second data subset as the object and compares the structural response parameters with preset safety deviation thresholds to determine the severity of the threat. Its purpose is to provide a basis for the quantitative assessment of threat levels. Threat level refers to the severity level of the current survival threat determined based on the third-level screening results. It is usually divided into low, medium, and high levels, and its function is to provide a level index for the accurate extraction of operational parameter boundaries in the survival mode library. Priority refers to the order of decision weight assigned to each level of screening results when there is a conflict or when a comprehensive decision needs to be made. The third-level screening results are given the highest priority, and the first-level screening results are given the lowest priority. Its function is to ensure that the direct response at the structural level plays a dominant role in the final threat identification result, and to avoid the distortion of threat identification caused by the instantaneous fluctuation of external environmental parameters or the indirect representation of operational status parameters.

[0027] Understandably, by sequentially performing a first-level screening based on marine environmental field parameters, a second-level screening based on wind turbine operating status parameters, and a third-level screening based on wind turbine structural response parameters on the status monitoring data, a progressive threat identification process is achieved, moving from external environmental assessment to internal state classification and then to structural response quantification. The first-level screening identifies extreme environmental conditions and triggers survival threat warnings, focusing the analysis scope from routine monitoring data to operating periods that may face survival threats, avoiding meaningless analysis of normal operating data. The second-level screening identifies threat category tendencies from the first data subset, refining the broad survival threat warning into specific threat category directions, providing an accurate category index for subsequent survival mode matching. The third-level screening determines the threat level from the second data subset, further quantifying the threat category tendency into severity levels, providing a level-based basis for the precise extraction of operating parameter boundaries. By setting the third-level screening results as the highest priority and the first-level screening results as the lowest priority, the analysis results of structural response parameters are ensured to dominate the final decision during the comprehensive judgment process, avoiding misjudgments caused by instantaneous fluctuations in the external environment. This achieves a progressive analysis from global situational awareness to precise threat identification, resulting in a dual accurate determination of threat type and threat level.

[0028] Specifically, the central data processing unit receives status monitoring data uploaded by each sensor according to a preset data acquisition cycle, and stores the data in different data caches according to parameter dimensions. In the first-level screening stage, the central data processing unit extracts the current marine environmental field parameters from the environmental parameter cache, including wind speed, wind direction, wave height, air temperature, air pressure, and salt spray concentration. Each parameter is compared with preset extreme environment judgment thresholds: when the continuous wind speed exceeds 25 meters per second, the gust wind speed exceeds 35 meters per second, the significant wave height exceeds 6 meters, the salt spray concentration exceeds 5 milligrams per cubic meter, or the air temperature is below -10 degrees Celsius, an extreme environmental condition is determined to exist, triggering a survival threat warning and generating a warning identification code. After triggering the survival threat warning, the central data processing unit extracts the wind turbine operating status parameters corresponding to the warning time from the operating status parameter cache, including generator speed, output power, pitch angle, yaw angle, converter temperature, and nacelle vibration acceleration, forming the first data subset. In the second-level screening stage, the central data processing unit inputs the first data subset into a pre-trained threat category classification model. This model is built based on the support vector machine algorithm. The input features include generator speed fluctuation rate, pitch system response delay, yaw system tracking error, converter temperature rise rate, and nacelle vibration spectrum characteristics. The model output is a threat category tendency probability distribution. When the probability of structural dynamic threat exceeds 0.6, the threat category is determined to be structural dynamic threat; when the probability of corrosion acceleration threat exceeds 0.6, it is determined to be corrosion acceleration threat; and when the probability of functional failure threat exceeds 0.6, it is determined to be functional failure threat. In the third-level screening stage, the central data processing unit extracts a second data subset synchronized with the first data subset from the structural response parameter buffer. This second subset includes tower strain, foundation displacement, blade root bending moment, and bolt preload. It calculates the safety deviation of each structural response parameter relative to the normal operating baseline value. The safety deviation is calculated by subtracting the normal operating baseline value from the current measured value and then dividing by the normal operating baseline value. When the safety deviation of tower strain exceeds 0.5, the safety deviation of foundation displacement exceeds 0.3, or the safety deviation of blade root bending moment exceeds 0.4, the threat level is determined to be high. When the safety deviation is between 0.2 and the above thresholds, it is determined to be medium-level; and when it is below 0.2, it is determined to be low-level. In the comprehensive judgment stage, the central data processing unit assigns priority according to the principle that the third-level screening results have the highest priority and the first-level screening results have the lowest priority. If the third-level judgment indicates a high-level structural dynamic threat, the final identification result is a high-level structural dynamic threat, even if the first-level screening results show that the environmental parameters have returned to normal. The third-level result is still taken as the standard.

[0029] Preferably, matching the corresponding adaptive survival mode from a preset survival mode library based on the identified survival threat type includes: When the threat category identified by the second-level screening tends to be a structural dynamic threat, the corresponding survival mode is initially selected from the survival mode library; Based on the threat level determined by the third level of screening, the operational parameter boundary that matches the threat level is extracted from the initially selected survival mode, and the current survival mode is determined to be the wind-resistant anchored survival mode. Based on the highest priority judgment result of the third level, if the structural response parameters are found to exceed the preset safety deviation, the boundary of the operating parameters in the wind-resistant anchoring survival mode is reduced.

[0030] It should be noted that the initial selection refers to the process of initially searching and extracting from the survival pattern database based on threat category tendencies. Its purpose is to quickly locate candidate survival patterns corresponding to the current threat category from the complete survival pattern database, providing a foundation for subsequent extraction of precise operational parameter boundaries based on threat levels. Safety deviation refers to the degree of deviation of the current measured value of the structural response parameter from the normal operating baseline value, expressed as a relative percentage. Its calculation formula is the current measured value minus the normal operating baseline value, divided by the normal operating baseline value. Its purpose is to quantitatively assess the severity of structural response parameters exceeding the normal range, providing numerical basis for threat level assessment and dynamic reduction of operational parameter boundaries. Operating parameter boundary reduction refers to the process of tightening and adjusting the operating parameter boundaries set in the original survival mode after identifying that the structural response parameters exceed the preset safety deviation. This includes narrowing the allowable range of alignment accuracy of the yaw system, lowering the lower limit of the feathering angle of the pitch system, raising the lower limit of the stiffness adjustment of the active damping support components, or lowering the upper limit of the tower strain safety. Its function is to provide a more conservative safety constraint for the wind turbine by tightening the allowable operating range of the control parameters when the structural response deviates significantly from the normal state, so as to avoid the aggravation of structural damage caused by excessive parameter adjustment margin.

[0031] Understandably, when a structural dynamic threat is identified through the second-level screening, a corresponding wind-anchored survival mode is initially selected from the survival mode library. This achieves a preliminary correspondence between the threat category and the survival mode framework, ensuring that subsequent parameter extraction is performed under the correct mode category. By combining the threat level determined by the third-level screening, operational parameter boundaries matching the threat level are extracted from the initially selected survival modes. This achieves dynamic adaptation between threat severity and parameter constraint precision. Higher-level threats correspond to stricter operational parameter boundaries, while lower-level threats correspond to relatively looser operational parameter boundaries, thus avoiding insufficient protection or over-response caused by uniform parameter boundaries. Based on the highest priority judgment result of the third level, when structural response parameters are identified as exceeding a preset safety deviation, the operational parameter boundaries in the wind-anchored survival mode are reduced. This achieves dynamic tightening of parameter boundaries when the structural response is abnormal, providing additional safety margins for the wind turbine and achieving refined mode matching and dynamic safety constraint effects under structural dynamic threats.

[0032] Specifically, after completing the second-level screening and identifying the threat category as structural dynamic threat, the central data processing unit sends a category query command to the survival mode database. The search criteria are that the threat category identifier equals structural dynamic threat. The survival mode database returns a complete record of wind-resistant anchoring survival modes, including the mode name, mode identifier, default operating parameter boundary set, and boundary reduction rule set, completing the initial selection process. The central data processing unit then reads the threat level determined by the third-level screening. If the threat level is low, it extracts the corresponding operating parameter boundaries from the wind-resistant anchoring survival mode record. These boundaries include: yaw system alignment accuracy threshold of ±8 degrees; pitch system feathering angle range of 82 to 90 degrees; active damping support component stiffness adjustment range of 1.0 to 1.5 times the reference stiffness; and tower strain safety upper limit of 1500. If the threat level is medium, then extract the corresponding operational parameter boundaries, including: yaw system alignment accuracy threshold of ±5 degrees; pitch system feathering angle range of 85 to 90 degrees; active damping support component stiffness adjustment range of 1.2 to 2.0 times the reference stiffness; and tower strain safety upper limit of 1200. If the threat level is high, then the corresponding operational parameter boundaries are extracted, including: yaw system alignment accuracy threshold of ±3 degrees; pitch system feathering angle range of 87 to 90 degrees; active damping support component stiffness adjustment range of 1.5 to 2.5 times the reference stiffness; and tower strain safety upper limit of 1000. After extracting the operational parameter boundaries, the central data processing unit, based on the highest priority judgment result of the third level, verifies the safety deviation of the structural response parameters in the second data subset. If the verification result shows that the tower strain safety deviation exceeds 0.6, the foundation displacement safety deviation exceeds 0.5, or the blade root bending moment safety deviation exceeds 0.5, the operational parameter boundary reduction program is initiated. The extracted operational parameter boundaries are tightened according to preset reduction rules: the yaw system alignment accuracy threshold is reduced by ±1 degree, the lower limit of the pitch system feathering angle is increased by 1 degree, the lower limit of the active damping support component stiffness adjustment is increased by 0.3 times, and the upper limit of the tower strain safety deviation is reduced by 200 degrees. The reduced operating parameter boundaries are marked as compressed mode and loaded into the parameter register of the real-time controller.

[0033] Preferably, the coping strategies corresponding to the matched adaptive survival mode include: According to the operating parameter boundaries of the wind-resistant anchoring survival mode, the yaw system of the wind turbine is adjusted to align the nacelle with the real-time wind direction, and the pitch system is driven to adjust the blade pitch angle to the preset feathering position. Based on the threat level and structural response parameters identified at the third level, the stiffness or damping coefficient of the active damping support components inside the tower is adjusted. The load feedback value of the actuator is monitored in real time, and when the load feedback value reaches the upper limit of the operating parameter boundary, the response frequency of the yaw system is reduced or the adjustment dead zone of the pitch system is increased.

[0034] It should be noted that the yaw system refers to the electromechanical device installed between the top of the wind turbine tower and the bottom of the nacelle, used to drive the nacelle to rotate around the vertical axis of the tower to align with the wind direction. It includes a yaw motor, yaw bearing, yaw brake, and wind direction tracking controller. Its function is to adjust the nacelle azimuth angle so that the rotor plane faces the oncoming wind direction, reducing the asymmetric impact of lateral wind loads on the tower. This is obtained by the wind turbine main control system sending angle adjustment commands to the yaw drive and receiving position feedback from the yaw encoder. The pitch angle, measured in degrees, is the angle between the airfoil chord of the wind turbine blades and the plane of rotation of the rotor. Its function is to adjust the aerodynamic power captured by the rotor by changing the blade's angle of attack. In extreme conditions, increasing the pitch angle can reduce the lift and thrust on the blades. This is obtained in real time through an angle encoder within the pitch system. The feathering position refers to the state where the blade pitch angle is adjusted to close to 90 degrees. At this position, the blade airfoil chord is approximately parallel to the wind direction, the aerodynamic power captured by the rotor is minimized, and the wind load on the blades is significantly reduced. Its function is to provide maximum load unloading protection for the wind turbine under extreme wind load conditions. Active damping support components refer to electromechanical or hydraulic devices installed inside the tower to provide controllable damping force to suppress tower vibration. These include magnetorheological dampers, eddy current dampers, or servo hydraulic actuators. Their function is to counteract the tower vibration energy caused by external wind loads and wave excitation by adjusting the damping force or stiffness characteristics in real time. This is obtained by receiving adjustment commands and feeding back actuator displacement and output through the actuator controller within the structural health monitoring system. Stiffness refers to the ability of the active damping support component to resist deformation, expressed in Newtons per meter (N / m). It characterizes the magnitude of the restoring force generated by the component under a unit deformation. Its function is to enhance the tower's bending stiffness by providing sufficient restoring force to constrain lateral displacement. This is obtained by calculating using force and displacement sensors built into the actuator. The damping coefficient refers to the ability of an active damping support component to dissipate vibration energy, measured in Newton-seconds per meter. It characterizes the damping force generated by the component at a unit vibration velocity. Its function is to dissipate the kinetic energy of tower vibration by converting it into heat energy, thus suppressing the amplification of the tower's resonance response. It is obtained by real-time calculation of the ratio of actuator output force to velocity. The actuator refers to the terminal device that responds to real-time controller commands and executes specific physical actions. This includes yaw motors, pitch motors, and actuators of the active damping support component. Its function is to convert control commands into mechanical motion, thereby adjusting the wind turbine's attitude and structural characteristics. It is obtained by the drivers of each subsystem receiving control signals and driving the motors or actuators. Load feedback value refers to the actual mechanical load borne by the actuator during operation, including the yaw torque of the yaw system, the pitch torque of the pitch system, and the support reaction force of the active damping support component, etc., in kilonewton-meters or kilonewtons. Its function is to reflect the current working load status of the actuator and provide real-time basis for judging the boundary of operating parameters. It is obtained in real time through the torque sensor or force sensor built into each actuator.Response frequency refers to the number or rate at which the yaw system completes azimuth adjustment per unit time, measured in degrees per second. It characterizes the yaw system's agility in tracking wind direction changes and is obtained through calculations using the yaw motor speed and transmission ratio. Dead zone refers to the non-responsive angle range of the pitch system during pitch angle adjustment, measured in degrees, due to mechanical clearance, sensor accuracy, or control strategy settings. Its function is to prevent frequent pitch system actions during minor fluctuations in wind direction or load, reducing mechanical wear and additional vibration. It is obtained through a dead zone compensation algorithm set within the pitch controller.

[0035] Understandably, by adjusting the yaw system according to the operating parameter boundaries under the wind-resistant anchoring survival mode, the nacelle is aligned with the real-time wind direction, and the pitch system is driven to adjust the blade pitch angle to the feathering position. This enables rapid attitude unloading of the wind turbine under extreme wind load conditions, reducing the aerodynamic power captured by the rotor and the blade thrust, thereby alleviating the load burden on the tower and foundation. By adjusting the stiffness or damping coefficient of the active damping support components within the tower based on the threat level and structural response parameters identified at the third level, the vibration characteristics of the tower are actively controlled, enhancing the tower's vibration resistance under extreme conditions and suppressing the amplification of structural resonance response. By monitoring the load feedback value of the actuator in real time, and reducing the response frequency of the yaw system or increasing the adjustment dead zone of the pitch system when the load feedback value reaches the upper limit of the operating parameter boundaries, the actuator is protected by speed reduction and frequency reduction. This avoids the actuator from frequently adjusting near the full load boundary, which could lead to additional dynamic loads or mechanical fatigue, thus achieving multi-parameter collaborative protection and actuator safety protection under structural dynamic threats.

[0036] Specifically, the real-time controller reads the operating parameter boundaries for the wind-resistant anchoring survival mode from the parameter register, generates and sends alignment commands to the yaw system. The wind direction tracking controller within the yaw system analyzes the real-time wind direction data and drives the yaw motors to adjust the nacelle azimuth at a rate of 2 degrees per second until the deviation between the nacelle centerline and the real-time wind direction is controlled within the alignment accuracy threshold specified by the operating parameter boundaries. Simultaneously, the real-time controller sends feathering commands to the pitch system, and the pitch controller drives the pitch motors of each blade to synchronously increase the pitch angle at a rate of 8 degrees per second until the pitch angle of each blade reaches the feathering position range specified by the operating parameter boundaries. During yaw and pitch control, the real-time controller receives the threat level and structural response parameters determined by the third-level screening. If the threat level is high and the tower vibration acceleration exceeds 0.1g, a stiffness enhancement command is sent to the active damping support component inside the tower, increasing the excitation current of the magnetorheological damper from the reference value of 2 amperes to 4 amperes, thereby increasing the damper stiffness from 1.5 times to 2.0 times the reference stiffness, and simultaneously increasing the damping coefficient from 5000 N / s / m to 8000 N / s / m. If the tower vibration acceleration is between 0.05g and 0.1g, only the damping coefficient is increased to 6000 N / s / m while keeping the stiffness unchanged. The real-time controller continuously collects load feedback values, including yaw moment, pitch moment, and support reaction force, through sensors built into each actuator. When the yaw moment reaches the upper limit of 1500 kNm specified by the operating parameter boundary, the real-time controller reduces the yaw system response frequency from 2 degrees per second to 0.5 degrees per second, slowing down the nacelle alignment adjustment rate. When the pitch moment reaches the upper limit of 800 kNm specified by the operating parameter boundary, the real-time controller increases the pitch system dead zone from ±0.5 degrees to ±2 degrees, reducing the frequency of pitch actions. During the above adjustment process, the real-time controller continuously compares the load feedback values ​​with the upper limit of the operating parameter boundary, dynamically adjusting the response frequency and dead zone to ensure that the actuator workload is always within a safe range.

[0037] Preferably, matching the corresponding adaptive survival mode from a preset survival mode library based on the identified survival threat type includes: When the threat category identified by the second-level screening tends to be a corrosion acceleration threat, the corresponding survival mode is initially selected from the survival mode library; Based on the threat level determined by the third-level screening, the operational parameter boundary that matches the threat level is extracted from the initially selected survival mode, and the current survival mode is determined to be the anti-corrosion cycle survival mode. Based on the highest priority judgment result of the third level, if a preset material performance degradation deviation is identified in the structural response parameters of the second data subset, the air quality control boundary in the anti-corrosion cycle survival mode is reduced.

[0038] It should be noted that the material performance degradation deviation refers to the degree of deviation of the structural response parameters reflecting the decline in the mechanical properties of the wind turbine structural materials due to corrosion. It is characterized as a relative percentage and is calculated by subtracting the material performance design benchmark value from the current measured value of the material performance index and then dividing by the material performance design benchmark value. The material performance indexes include the yield strength of the tower steel, the interlaminar shear strength of the blade composite material, the tensile strength of the bolts, and the adhesion of the coating, etc. Its function is to quantitatively assess the degree of corrosion on the mechanical properties of the structural materials and provide a basis for the dynamic reduction of the boundary of the operating parameters under the anti-corrosion cycle survival mode. It is obtained through material performance sensors deployed in the structural health monitoring system or through inversion calculation based on the structural response parameters. Air quality control boundaries refer to the allowable operating range of environmental parameters set under the anti-corrosion cycle survival mode to control the air quality inside the engine room and delay the corrosion process. These include the lower limit of the positive pressure threshold of the engine room, the upper limit of the power of the temperature and humidity circulation device, the lower limit of the sealing pressure, and the target value of salt spray concentration control. Their function is to provide numerical constraints for the operation of the engine room environmental control system and ensure that the engine room maintains a gaseous environment that is conducive to inhibiting corrosion. The method of obtaining these boundaries is to extract them from the anti-corrosion cycle survival mode records in the survival mode library and dynamically reduce them according to the material performance degradation deviation.

[0039] Understandably, when the second-level screening identifies an accelerated corrosion threat, an initial anti-corrosion cycle survival mode is selected from the survival mode library, achieving a preliminary correspondence between corrosion threat categories and the cabin environmental control strategy framework. By combining the threat level determined by the third-level screening to extract matching operational parameter boundaries, dynamic adaptation between corrosion severity and environmental control precision is achieved, with higher-level corrosion threats corresponding to stricter air quality control boundaries. Based on the highest priority judgment result of the third level, when material performance degradation deviations are identified in the structural response parameters of the second data subset, the air quality control boundary is reduced, achieving dynamic tightening of environmental control parameters when material performance is abnormal. This provides additional corrosion protection margin for the wind turbine, achieving refined mode matching and dynamic environmental constraint effects under accelerated corrosion threats.

[0040] Specifically, after completing the second-level screening and identifying the threat category as corrosion acceleration threat, the central data processing unit sends a category query command to the survival pattern database. The search criteria are that the threat category identifier equals corrosion acceleration threat. The survival pattern database returns a complete record of the anti-corrosion cycle survival patterns, completing the initial selection process. The central data processing unit then reads the threat level determined by the third-level screening. If the threat level is low, it extracts the corresponding operational parameter boundaries from the anti-corrosion cycle survival pattern records, including a lower limit of 100 Pa for positive pressure in the engine room, a power upper limit of 5 kW for the temperature and humidity circulation device, a lower limit of 0.05 MPa for sealing pressure, a salt spray concentration control target of 3 mg / m³, and a normal air quality control boundary. If the threat level is medium, it extracts the corresponding operational parameter boundaries, including the engine room positive pressure... The lower limit of the threshold is 150 Pa, the upper limit of the power of the temperature and humidity circulation device is 8 kW, the lower limit of the sealing pressure is 0.08 MPa, the target value of salt spray concentration control is 2 mg / m³, and the air quality control boundary is strict. If the threat level is high, the corresponding operating parameter boundaries are extracted, including the lower limit of the positive pressure threshold of the cabin is 200 Pa, the upper limit of the power of the temperature and humidity circulation device is 12 kW, the lower limit of the sealing pressure is 0.12 MPa, the target value of salt spray concentration control is 1 mg / m³, and the air quality control boundary is severe. After completing the extraction of operating parameter boundaries, the central data processing unit, based on the highest priority judgment result of the third level, performs a material performance degradation deviation check on the structural response parameters in the second data subset. If the check result shows that the degradation deviation of the tower steel yield strength exceeds 0.15, the degradation deviation of the blade composite interlaminar shear strength exceeds 0.12, or the degradation deviation of the bolt tensile strength exceeds 0.10, the air quality control boundary reduction program is initiated. The currently extracted air quality control boundary is tightened according to the preset reduction rules: the lower limit of the positive pressure threshold of the nacelle is increased by 50 Pa, the upper limit of the power of the temperature and humidity circulation device is increased by 2 kW, the lower limit of the sealing pressure is increased by 0.02 MPa, and the target value of salt spray concentration control is reduced by 0.5 mg / m³. The reduced air quality control boundary is marked as the tightened mode and loaded into the parameter register of the real-time controller.

[0041] Preferably, the coping strategies corresponding to the matched adaptive survival mode include: Prioritize the status monitoring data of each level that matches the corrosion protection cycle survival mode, and use the second data subset as the core comparison benchmark. The first data subset is compared with the core comparison benchmark by linkage feature comparison, including: extracting the association rules between marine environmental parameters and wind turbine structural response data, and calculating the degree of difference between the extraction results in corrosion-induced conditions and performance degradation response. The first data subset is compared with the core comparison benchmark by quantitative feature comparison, including: calculating the deviation of real-time statistical values ​​from the boundaries of the operating parameters for statistical indicators such as cabin salt spray concentration, temperature and humidity distribution under operating mode and sealing pressure. Perform auxiliary verification and comparison, comparing the first data subset with at least one other monitoring dimension data other than the core comparison benchmark, to verify whether the degree of difference and deviation are consistent in terms of environmental impact. Based on the degree of difference and the degree of deviation, valid differences are selected from the comparison results, and each valid difference is converted into a control command according to a preset mapping rule. The control commands include adjusting the positive pressure threshold of the cabin, adjusting the power of the temperature and humidity circulation device, and changing the dead zone of the actuator.

[0042] It should be noted that priority refers to the processing order and decision weight assigned to the state monitoring data at each level during comparative analysis under the corrosion-resistant cyclic survival mode. The second data subset, as the core comparison benchmark, is given the highest priority, the first data subset is given a secondary priority, and other monitoring dimensions are given auxiliary priorities. Its role is to ensure that structural response parameters play a dominant role in corrosion state assessment, environmental parameters play a role in inducing conditions, and other parameters play a supporting role in verification. The core comparison benchmark, the second data subset, serves as the reference standard in the comparative analysis process of the corrosion-resistant cyclic survival mode. It includes structural response parameters such as tower strain, foundation displacement, blade root bending moment, and bolt preload. Its role is to provide a structural-level benchmark for linkage feature comparison and quantitative feature comparison, measuring the correlation between corrosion inducing conditions and structural performance degradation. It is obtained by extracting data from the first data subset through a third-level screening process. Linkage feature comparison refers to the process of performing correlation analysis between a first subset of data and a core comparison benchmark. By extracting association rules between marine environmental parameters and wind turbine structural response data, the degree of difference between corrosion-induced conditions and performance degradation responses is calculated. Its purpose is to reveal the strength of the causal relationship between environmental factors and structural degradation, providing a correlational basis for the generation of control commands. Association rules refer to statistically significant conditional dependencies between marine environmental parameters and wind turbine structural response data, such as the co-occurrence relationship between high salt spray concentration and high tower strain rate. Their purpose is to extract these rules from historical monitoring data using data mining algorithms, providing a rule base for linkage feature comparison. The degree of difference refers to the deviation between the real-time state of corrosion-induced conditions and the expected performance degradation response state based on association rules, characterized by standardized distance or probability difference. Its purpose is to quantify the deviation between the current corrosion process and historical typical corrosion patterns, providing a numerical basis for screening effective differences. Quantitative feature comparison refers to the process of numerically measuring the first subset of data against the core comparison benchmark. For statistical indicators such as cabin salt spray concentration, temperature and humidity distribution under operating conditions, and sealing pressure, the deviation of real-time statistical values ​​from the boundaries of operating parameters is calculated. Its purpose is to assess the urgency of accelerated corrosion through the numerical deviation of specific environmental parameters. Statistical indicators refer to characteristic quantities obtained after statistical analysis of environmental parameters such as cabin salt spray concentration, temperature and humidity distribution, and sealing pressure, including mean, standard deviation, maximum value, and duration exceeding thresholds. Their function is to transform raw sensor data into comparable statistical features, providing input for the calculation of deviation. Deviation refers to the amount of deviation of the real-time statistical value of the environmental parameter from the boundaries of the operating parameters, characterized by absolute difference or relative percentage. Its function is to quantify the severity of the current cabin environmental state exceeding the safe corrosion control range, providing a basis for adjusting the intensity of control commands.Auxiliary verification and comparison refers to the process of cross-validating the first data subset with at least one other monitoring dimension data besides the core comparison benchmark. For example, comparing marine environmental parameters with electrical system insulation resistance data. Its purpose is to verify whether the degree of difference obtained from the linkage feature comparison and the degree of deviation obtained from the quantitative feature comparison are consistent in terms of environmental impact, and to eliminate misjudgments caused by anomalies in single-dimensional data. Effective difference refers to significant deviations with control value selected from the degree of difference and deviation after the linkage feature comparison, quantitative feature comparison, and auxiliary verification and comparison have all passed consistency verification. Its purpose is to serve as input for mapping rules, ensuring that only information truly reflecting the corrosion acceleration state is converted into control actions. Mapping rules refer to a pre-defined correspondence table between effective differences and control commands, including the mapping relationship between the degree of difference range and the positive pressure threshold adjustment amount of the engine room, and the degree of deviation range and the power adjustment amount of the temperature and humidity circulation device and the dead zone adjustment amount of the actuator. Its purpose is to convert the selected effective differences into specific control parameter adjustment commands. Control commands refer to the set of commands generated by the real-time controller according to the mapping rules, which are used to drive the cabin environmental control system to perform specific actions. These commands include adjusting the cabin positive pressure threshold, adjusting the power of the temperature and humidity circulation device, and changing the dead zone of the actuator. Their function is to transform the corrosion status assessment results into actual environmental control actions, thereby achieving active regulation of the air quality inside the cabin.

[0043] Understandably, by prioritizing state monitoring data at each level that matches the corrosion-resistant cycle survival mode and using the second data subset as the core comparison benchmark, the dominant role of structural response parameters in corrosion assessment is achieved, ensuring the structural reliability of corrosion state determination. By performing a linked feature comparison between the first data subset and the core comparison benchmark, the correlation rules between marine environmental parameters and wind turbine structural response data are extracted, and the degree of difference is calculated, revealing the causal relationship between corrosion-inducing conditions and performance degradation responses. By performing a quantitative feature comparison between the first data subset and the core comparison benchmark, the deviation of statistical indicators such as computer cabin salt spray concentration, temperature and humidity distribution, and sealing pressure from the operating parameter boundaries is quantified, thus quantifying the urgency of accelerated corrosion. Through auxiliary verification comparison, the first data subset is cross-validated with data from other monitoring dimensions to ensure consistency of the degree of difference and deviation at the environmental impact level, eliminating data anomalies. By filtering effective differences based on the degree of difference and deviation and converting them into control commands according to mapping rules, the corrosion state assessment results are accurately mapped to environmental control actions, achieving multi-dimensional state assessment and precise environmental control effects under the threat of accelerated corrosion.

[0044] Specifically, the real-time controller reads the operational parameter boundaries and priority configurations of the compressed version of the anti-corrosion cycle survival mode from the parameter register, sets the second data subset as the core comparison benchmark and assigns it the highest processing priority, assigns the first data subset a secondary priority, and assigns auxiliary verification priority to the electrical system insulation resistance data. The real-time controller performs linkage feature comparison: extracts the current marine environmental parameters from the first data subset, including a salt spray concentration of 6 mg / m³, an external relative humidity of 85% for the engine room, and an air temperature of 35 degrees Celsius; and extracts the structural response parameters at the synchronous moment from the core comparison benchmark, including a tower strain of 650... The base displacement is 12 mm. Using a pre-stored rule base, the expected growth rate of tower strain under conditions of coexisting high salt spray concentration and high relative humidity is 5 mm per hour. The actual tower strain growth rate is calculated to be 8 per hour. The difference is calculated as the actual growth rate of 8 minus the expected growth rate of 5, divided by the expected growth rate of 5, which equals 0.6. The real-time controller performs quantitative feature comparisons: For the cabin salt spray concentration, the statistical indicators for the past hour are calculated, with a mean of 5.5 mg / m³, a standard deviation of 1.2 mg / m³, and a maximum of 7 mg / m³; for temperature and humidity distribution, the statistical indicators for the past hour are calculated, with a mean cabin temperature of 45 degrees Celsius and a mean relative humidity of 70%; for sealing pressure, the statistical indicators for the past hour are calculated, with a mean of 0.06 MPa. Comparing these statistical indicators with the operating parameter boundaries, the deviation of the mean salt spray concentration of 5.5 exceeding the control target value of 1.5 is 4.0; the relative humidity of 70% inside the cabin is within the normal operating range; and the deviation of the sealing pressure of 0.06 below the lower limit of 0.10 is -0.04. The real-time controller performs auxiliary verification and comparison: It compares the salt spray concentration data in the first data subset with the electrical system insulation resistance data. Historical correlation rules show that for every 1 mg / m³ increase in salt spray concentration, the insulation resistance decreases by 5 megohms. The current salt spray concentration is 6 mg / m³, and the expected insulation resistance decrease is 30 megohms. The measured insulation resistance decrease is 28 megohms, a deviation of 2 megohms, within the allowable error range. This verifies that the difference degree of 0.6 and the salt spray concentration deviation degree of 4.0 are consistent in terms of environmental impact. The real-time controller filters valid differences based on the difference degree of 0.6 and the deviation degree of 4.0: the difference degree of 0.6 exceeds the effective threshold of 0.3, the salt spray concentration deviation degree of 4.0 exceeds the effective threshold of 1.0, and the absolute value of the sealing pressure deviation degree of 0.04 is lower than the absolute value of the effective threshold of 0.02. Therefore, valid differences in salt spray concentration and the difference degree of 4.0 are selected. The real-time controller invokes the mapping rules: a difference of 0.6 corresponds to an increase of 100 Pa in the positive pressure threshold adjustment of the cabin, an increase of 3 kW in the power adjustment of the temperature and humidity circulation device, and a salt spray concentration deviation of 4.0 corresponds to an increase of ±1 degree in the dead zone adjustment of the actuator. Control commands are generated and distributed to the cabin environmental control system.

[0045] Preferably, matching the corresponding adaptive survival mode from a preset survival mode library based on the identified survival threat type includes: When the threat category identified by the second-level screening tends to be a functional failure threat, the corresponding survival mode is initially selected from the survival mode library; Based on the threat level determined by the third level of screening, the operating parameter boundary that matches the threat level is extracted from the initially selected survival mode, and the current survival mode is determined to be the electrical isolation survival mode. Based on the highest priority determination result of the third level, if a failure deviation is identified in the control loop response signal of the second data subset, the load distribution boundary in the electrical isolation survival mode is reduced.

[0046] It should be noted that control loop response signals refer to the feedback signals generated by each control loop in the wind turbine electrical control system after receiving control commands. These include converter output current response signals, pitch motor position loop feedback signals, yaw motor speed loop feedback signals, and main control system communication response signals. Their function is to characterize the real-time response status and functional integrity of each control loop, and they are acquired in real-time through the built-in feedback channels or communication buses of each controller. Failure deviation refers to the degree of deviation between the actual characteristics of the control loop response signal and its normal functional characteristics. It is characterized by deviations in indicators such as response time delay, signal amplitude attenuation, signal waveform distortion, or communication packet loss rate. Its function is to quantitatively assess whether there is functional failure or performance degradation in the control loop, providing a triggering basis for the dynamic reduction of the load distribution boundary in electrical isolation survival mode. The load distribution boundary refers to the maximum allowable load of each power supply branch in the electrical isolation survival mode to maintain the minimum survival operation function of the wind turbine. This includes the upper limit of the converter branch load, the upper limit of the yaw system branch load, the upper limit of the pitch system branch load, and the upper limit of the auxiliary system branch load. Its function is to prevent the spread of faults by limiting the load of each branch under the threat of functional failure, and to ensure the power supply safety of the core control circuit. It is obtained by extracting the electrical isolation survival mode records from the survival mode library and dynamically reducing them according to the failure deviation.

[0047] Understandably, when a functional failure threat is identified by the second-level screening, an electrical isolation survival mode is initially selected from the survival mode library, achieving a preliminary correspondence between the functional failure threat category and the electrical system protection strategy framework. By combining the threat level determined by the third-level screening to extract matching operating parameter boundaries, dynamic adaptation between the severity of functional failure and the accuracy of electrical protection is achieved, with higher-level functional failures corresponding to stricter load allocation boundaries. Based on the highest priority judgment result of the third level, when a failure deviation is identified in the control loop response signal in the second data subset, the load allocation boundary is reduced, achieving dynamic tightening of load limits when the control loop is abnormal, providing additional electrical safety margin for the wind turbine, and achieving refined pattern matching and dynamic electrical constraint effects under functional failure threats.

[0048] Specifically, after completing the second-level screening and identifying threats that tend to be functional failure threats, the central data processing unit sends a category query command to the survival mode database. The search criteria are that the threat category identifier equals the functional failure threat. The survival mode database returns a complete record of electrical isolation survival modes, completing the initial selection process. The central data processing unit then reads the threat levels determined by the third-level screening. If the threat level is low, it extracts the corresponding operating parameter boundaries from the electrical isolation survival mode records, including the converter branch load limit being 80% of rated power, the yaw system branch load limit being 60% of rated power, the pitch system branch load limit being 70% of rated power, the auxiliary system branch load limit being 50% of rated power, and the load distribution boundary being at the normal level. If the threat level is medium, it extracts the corresponding operating parameter boundaries, including the converter branch load limit being... The load distribution boundary is set at 60% of the rated power, 40% for the yaw system branch load, 50% for the pitch system branch load, 30% for the auxiliary system branch load, and is at a strict level. If the threat level is high, the corresponding operating parameter boundaries are extracted, including 40% for the converter branch load, 20% for the yaw system branch load, 30% for the pitch system branch load, 10% for the auxiliary system branch load, and is at a severe level. After completing the extraction of operating parameter boundaries, the central data processing unit performs a failure deviation check on the control loop response signals in the second data subset based on the highest priority judgment result of the third level. If the check result shows that the converter output current response signal delay exceeds 50 milliseconds, the pitch motor position loop feedback signal amplitude attenuation exceeds 20%, the yaw motor speed loop feedback signal waveform distortion rate exceeds 15%, or the main control system communication packet loss rate exceeds 5%, then the load distribution boundary reduction program is started. The currently extracted load distribution boundary is tightened according to the preset reduction rules: the upper limit of the load of each power supply branch is reduced by 10% of the rated power, and the upper limit of the load of the auxiliary system branch is further reduced by 5% of the rated power. The reduced load distribution boundary is marked as the tightened mode and loaded into the parameter register of the real-time controller.

[0049] Preferably, the coping strategies corresponding to the matched adaptive survival mode include: The objects consuming electricity are assigned corresponding priority logical tags according to their contribution to survival and operation, and the minimum priority threshold for maintaining operation is determined based on the threat level identified in the third level. Based on the real-time changes in the threat level, the on / off sequence of each power supply branch is dynamically adjusted: when the threat level rises, the corresponding branch circuit disconnection action is executed sequentially from low to high until the current operating load matches the load distribution boundary. During the process of executing the circuit disconnection, the output duty cycle or frequency parameter of the power conversion unit is synchronously adjusted to force the feedback of the electrical parameters of the core control circuit to be constrained within the numerical range defined by the boundary of the operating parameters. Based on the changing trend of the electrical parameter feedback value of the core control loop, the operating state of the protection actuator is adjusted in reverse. Through alternating step adjustments of electrical parameters and environmental protection parameters, the operating state of the fan is kept within the preset safety constraint range.

[0050] It should be noted that the energy-consuming objects refer to the functional units in the wind turbine electrical system that consume electrical energy to maintain operation, including converters, yaw motors, pitch motors, nacelle heaters, communication equipment, and condition monitoring sensors. Their role is to serve as load management objects in the electrical isolation survival mode, and to implement graded control based on their importance to the wind turbine's survival and operation. Contribution refers to the assessment value of the necessity of each energy-consuming object in maintaining the minimum survival and operation functions of the wind turbine, expressed as a percentage or grade system. Converters and the core controller have the highest contribution, followed by auxiliary systems and communication equipment, while non-essential heating and lighting equipment have the lowest contribution. Their role is to provide a quantitative basis for the allocation of priority logical labels. Priority logical labels are level identifiers assigned to each energy-consuming object based on the contribution assessment results, used for power supply branch on / off decisions, including core level, important level, general level, and disconnectable level. Their role is to establish the order rules for power supply branch disconnection. The minimum priority threshold refers to the minimum contribution threshold of an energy-consuming object that is allowed to maintain operation under a specific threat level. When the priority logic label of an energy-consuming object is lower than this threshold, its power supply branch will be disconnected. Its function is to dynamically define the core functional scope that must be retained under the current operating conditions. A power supply branch refers to an independent electrical circuit that runs from the main distribution cabinet of the wind turbine and supplies power to a specific energy-consuming object or functional unit. This includes converter branches, yaw system branches, pitch system branches, and auxiliary system branches, etc. Its function is to act as an electrical isolation unit, achieving fine-grained load shedding through independent switching. The switching sequence refers to the time order and interval arrangement of the switching or closing actions of each power supply branch, measured in seconds or milliseconds. Its function is to avoid voltage surges and current surges caused by the simultaneous disconnection of multiple high-power branches during load shedding. A circuit disconnection action refers to the operation of cutting off the electrical connection of a power supply branch through switching devices such as circuit breakers, contactors, or solid-state relays. Its function is to isolate a specific energy-consuming object from the power grid, stop its power supply, and reduce the overall operating load. A power conversion unit (PCU) refers to the device in a wind turbine electrical system used to convert electrical energy into its form. This includes rectifiers, inverters, and DC choppers in the converter. Its function is to maintain the stability of the electrical parameters of the core control circuit by adjusting the duty cycle or frequency of the output voltage and current. The output duty cycle is the ratio of the PCU's on-time to the switching cycle, expressed as a percentage. Its function is to control the average value of the output voltage by adjusting the duty cycle, thereby achieving fine-tuning of the supply voltage to the core control circuit. The frequency parameter refers to the frequency of the AC output from the PCU or the switching frequency of the switching devices, measured in Hertz. Its function is to control the motor speed or filtering characteristics by adjusting the frequency to adapt to the electrical performance requirements under different load conditions.Electrical parameter feedback refers to the real-time measurement values ​​of electrical quantities such as voltage, current, and power in the core control loop, including DC bus voltage feedback, phase current feedback, and active power feedback. Its function is to characterize the real-time electrical state of the core control loop and provide closed-loop feedback for the adjustment of the power conversion unit. Protective actuators refer to physical actuators that participate in wind turbine safety protection in the electrical isolation survival mode, in addition to electrical regulation. These include nacelle sealing actuators, temperature and humidity regulating actuators, and structural protection actuators. Their function is to assist the safe operation of the electrical system by adjusting environmental protection parameters. Alternating step regulation refers to a control method in which electrical parameter regulation and protective actuator regulation alternate at preset time intervals. That is, first, a first-level electrical parameter regulation is executed, and after the system stabilizes, a first-level protective actuator regulation is executed, and so on, alternating progressively. Its function is to avoid system oscillations caused by simultaneous large changes in electrical parameter regulation and mechanical protection regulation, ensuring a smooth transition of the wind turbine's operating state to the safe constraint range. The safety constraint range refers to the multi-dimensional safe operating space formed by the wind turbine's electrical parameters and structural protection parameters under the electrical isolation survival mode. It includes the allowable voltage range, allowable current range, allowable temperature range, and allowable vibration range, etc. Its function is to serve as the final state constraint target for the execution of the electrical isolation survival mode.

[0051] Understandably, by assigning priority logical tags to energy-consuming objects according to their contribution to survival and operation, and determining the minimum priority threshold based on the threat level identified at the third level, hierarchical management of load shedding is achieved, ensuring the priority preservation of core functions. By dynamically adjusting the on / off sequence of each power supply branch according to real-time changes in threat level, and sequentially executing circuit disconnection actions from low to high as the threat level increases until the current operating load matches the load distribution boundary, a gradual load shedding is achieved, avoiding electrical shocks caused by simultaneously disconnecting multiple high-power loads. By synchronously adjusting the output duty cycle or frequency parameters of the power conversion unit during circuit disconnection, the electrical parameter feedback of the core control circuit is forcibly constrained within the numerical range defined by the operating parameter boundaries, ensuring the stability of the core circuit power supply. By reversely adjusting the operating state of the protection actuator based on the changing trend of the electrical parameter feedback value of the core control circuit, and through alternating step adjustments of electrical parameters and environmental protection parameters, the wind turbine operating state is kept within the safe constraint range, achieving coordinated safety constraints between the electrical system and the structural protection system, and achieving the effect of gradual load isolation and stable maintenance of core functions under the threat of functional failure.

[0052] Specifically, the real-time controller reads the operating parameter boundaries and load allocation boundaries of the compressed version of the electrical isolation survival mode from the parameter register, including the load upper limit and minimum priority threshold for each power supply branch. The real-time controller assesses the contribution of each power consumption object of the wind turbine: converter and main control system contribute 95%, yaw system 70%, pitch system 75%, nacelle heater 30%, communication equipment 50%, and condition monitoring sensors 60%, and assigns priority logical labels accordingly: converter and main control system are core level, yaw system and pitch system are important level, condition monitoring sensors and communication equipment are general level, and nacelle heater is disconnectable level. The threat level identified at the third level is high, and the real-time controller determines the minimum priority threshold to be important level, that is, only core level and important level power consumption objects are allowed to continue operating, and general level and disconnectable level will be cut off. The real-time controller detects that the current total operating load is 65% of the rated power, exceeding the total rated power specified by the compressed version load allocation boundary by 50%, and initiates the load shedding procedure. The real-time controller, following the on / off timing rules, first waits 100 milliseconds to ensure system stability, then executes the disconnectable circuit disconnection action, cutting off the power supply branch for the nacelle heaters, reducing the load by 10% to 55% of the rated power; after another 100 milliseconds, it executes the general circuit disconnection action, cutting off the power supply branch for the communication equipment, reducing the load by 5% to 50% of the rated power, matching the load distribution boundary. During the above circuit disconnection process, the real-time controller synchronously monitors the DC bus voltage feedback value of the core control circuit. When it detects that the voltage fluctuation exceeds ±5% at the moment of disconnection, it immediately adjusts the output duty cycle of the DC chopper in the converter, adjusting the duty cycle from 50% to 55% to increase the DC bus voltage, or adjusting the duty cycle from 50% to 45% to decrease the DC bus voltage, forcibly constraining the DC bus voltage within the value range of 540V to 660V defined by the operating parameter boundary; simultaneously, it adjusts the inverter output frequency, increasing the switching frequency from 2kHz to 2.5kHz to enhance the filtering effect and adapt to the current harmonic characteristics after load changes. The real-time controller continuously monitors the changing trends of electrical parameter feedback values ​​in the core control loop. When a downward trend is detected in the DC bus voltage, the nacelle sealing actuator in the protection actuator is adjusted in reverse to increase the sealing pressure by 0.02 MPa to reduce the intrusion of the external environment into the electrical compartment and reduce the risk of insulation degradation. When an upward trend in the current harmonic content is detected, the temperature and humidity regulating actuator is adjusted in reverse to reduce the internal temperature of the nacelle by 5 degrees Celsius to improve the heat dissipation conditions of electrical components.The aforementioned electrical parameter adjustments and protective actuator adjustments are performed alternately at 200-millisecond intervals. That is, the first-level duty cycle adjustment is performed first, followed by a 200-millisecond wait before the first-level sealing pressure adjustment is performed, and then a 200-millisecond wait before the first-level frequency adjustment is performed. This alternating process avoids system oscillations caused by simultaneous large adjustments, until the fan operation is within the safe constraint range of 540V to 660V, current 0 to rated value, temperature -10°C to 50°C, and vibration 0 to 0.05g.

[0053] An adaptive wind turbine survivability control system based on condition monitoring, such as Figure 2 As shown, it includes: The threat identification module is used to acquire status monitoring data of offshore wind turbines and identify the types of survival threats currently faced by the wind turbines based on the status monitoring data. The pattern matching module is used to match the corresponding adaptive survival mode in the preset survival mode library according to the identified survival threat type. The survival mode library includes the wind-resistant anchoring survival mode corresponding to the structural dynamic threat, the anti-corrosion cycle survival mode corresponding to the corrosion acceleration threat, and the electrical isolation survival mode corresponding to the functional failure threat. Each survival mode is equipped with operating parameter boundaries that keep the wind turbine within the safe operating boundary. The strategy execution module is used to execute the response strategy corresponding to the matched adaptive survival mode, including adjusting the mechanical control parameters, electrical control parameters and structural protection parameters of the wind turbine, and constraining the wind turbine's operating state within the boundaries of the operating parameters.

[0054] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0055] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims

1. An adaptive wind turbine survivability control method based on condition monitoring, characterized in that, include: Acquire status monitoring data of offshore wind turbines, and identify the types of survival threats currently faced by the wind turbines based on the status monitoring data; Based on the identified survival threat type, a corresponding adaptive survival mode is matched in a preset survival mode library. The survival mode library includes a wind-resistant anchoring survival mode corresponding to structural dynamic threats, an anti-corrosion cycle survival mode corresponding to corrosion acceleration threats, and an electrical isolation survival mode corresponding to functional failure threats. Each survival mode is equipped with operating parameter boundaries that keep the wind turbine within the safe operating boundary. The corresponding coping strategies for the matched adaptive survival mode are executed, including adjusting the mechanical control parameters, electrical control parameters, and structural protection parameters of the wind turbine, so as to constrain the wind turbine's operating state within the boundaries of the operating parameters.

2. The adaptive wind turbine survivability control method based on condition monitoring according to claim 1, characterized in that, Based on the aforementioned condition monitoring data, the types of survival threats currently faced by the wind turbine include: Based on the marine environmental field parameter dimension, the state monitoring data is screened at the first level to identify whether there are extreme environmental conditions, so as to determine whether a survival threat warning is triggered. From the state monitoring data that triggers the survival threat warning, a first subset of data that meets the dimensions of wind turbine operating state parameters is selected, and a second-level selection is performed based on the first subset of data to identify the threat category as structural dynamic threat, corrosion acceleration threat or functional failure threat. A second subset of data that conforms to the dimensions of wind turbine structural response parameters is selected from the first subset of data, and a third-level selection is performed based on the second subset of data to determine the threat level corresponding to the survival threat type. Set the priority of the third-level filter results to the highest, and set the priority of the first-level filter results to the lowest.

3. The adaptive wind turbine survivability control method based on condition monitoring according to claim 2, characterized in that, Based on the identified survival threat type, the corresponding adaptive survival mode is matched from the preset survival mode library, including: When the threat category identified by the second-level screening tends to be a structural dynamic threat, the corresponding survival mode is initially selected from the survival mode library; Based on the threat level determined by the third level of screening, the operational parameter boundary that matches the threat level is extracted from the initially selected survival mode, and the current survival mode is determined to be the wind-resistant anchored survival mode. Based on the highest priority judgment result of the third level, if the structural response parameters are found to exceed the preset safety deviation, the boundary of the operating parameters in the wind-resistant anchoring survival mode is reduced.

4. The adaptive wind turbine survivability control method based on condition monitoring according to claim 3, characterized in that, The corresponding coping strategies for the matched adaptive survival mode include: According to the operating parameter boundaries of the wind-resistant anchoring survival mode, the yaw system of the wind turbine is adjusted to align the nacelle with the real-time wind direction, and the pitch system is driven to adjust the blade pitch angle to the preset feathering position. Based on the threat level and structural response parameters identified at the third level, the stiffness or damping coefficient of the active damping support components inside the tower is adjusted. The load feedback value of the actuator is monitored in real time, and when the load feedback value reaches the upper limit of the operating parameter boundary, the response frequency of the yaw system is reduced or the adjustment dead zone of the pitch system is increased.

5. The adaptive wind turbine survivability control method based on condition monitoring according to claim 2, characterized in that, Based on the identified survival threat type, the corresponding adaptive survival mode is matched from the preset survival mode library, including: When the threat category identified by the second-level screening tends to be a corrosion acceleration threat, the corresponding survival mode is initially selected from the survival mode library; Based on the threat level determined by the third-level screening, the operational parameter boundary that matches the threat level is extracted from the initially selected survival mode, and the current survival mode is determined to be the anti-corrosion cycle survival mode. Based on the highest priority judgment result of the third level, if a preset material performance degradation deviation is identified in the structural response parameters of the second data subset, the air quality control boundary in the anti-corrosion cycle survival mode is reduced.

6. The adaptive wind turbine survivability control method based on state monitoring according to claim 5, characterized in that, The corresponding coping strategies for the matched adaptive survival mode include: Prioritize the status monitoring data of each level that matches the corrosion protection cycle survival mode, and use the second data subset as the core comparison benchmark. The first data subset is compared with the core comparison benchmark by linkage feature comparison, including: extracting the association rules between marine environmental parameters and wind turbine structural response data, and calculating the degree of difference between the extraction results in corrosion-induced conditions and performance degradation response. The first data subset is compared with the core comparison benchmark by quantitative feature comparison, including: calculating the deviation of real-time statistical values ​​from the boundaries of the operating parameters for statistical indicators such as cabin salt spray concentration, temperature and humidity distribution under operating mode and sealing pressure. Perform auxiliary verification and comparison, comparing the first data subset with at least one other monitoring dimension data other than the core comparison benchmark, to verify whether the degree of difference and deviation are consistent in terms of environmental impact. Based on the degree of difference and the degree of deviation, valid differences are selected from the comparison results, and each valid difference is converted into a control command according to a preset mapping rule. The control commands include adjusting the positive pressure threshold of the cabin, adjusting the power of the temperature and humidity circulation device, and changing the dead zone of the actuator.

7. The adaptive wind turbine survivability control method based on condition monitoring according to claim 2, characterized in that, Based on the identified survival threat type, the corresponding adaptive survival mode is matched from the preset survival mode library, including: When the threat category identified by the second-level screening tends to be a functional failure threat, the corresponding survival mode is initially selected from the survival mode library; Based on the threat level determined by the third level of screening, the operating parameter boundary that matches the threat level is extracted from the initially selected survival mode, and the current survival mode is determined to be the electrical isolation survival mode. Based on the highest priority determination result of the third level, if a failure deviation is identified in the control loop response signal of the second data subset, the load distribution boundary in the electrical isolation survival mode is reduced.

8. The adaptive wind turbine survivability control method based on state monitoring according to claim 7, characterized in that, The corresponding coping strategies for the matched adaptive survival mode include: The objects consuming electricity are assigned corresponding priority logical tags according to their contribution to survival and operation, and the minimum priority threshold for maintaining operation is determined based on the threat level identified in the third level. Based on the real-time changes in the threat level, the on / off sequence of each power supply branch is dynamically adjusted: when the threat level rises, the corresponding branch circuit disconnection action is executed sequentially from low to high until the current operating load matches the load distribution boundary. During the process of executing the circuit disconnection, the output duty cycle or frequency parameter of the power conversion unit is adjusted synchronously to force the feedback of the electrical parameters of the core control circuit to be constrained within the numerical range defined by the boundary of the operating parameters. Based on the changing trend of the electrical parameter feedback value of the core control loop, the operating state of the protection actuator is adjusted in reverse. Through alternating step adjustments of electrical parameters and environmental protection parameters, the operating state of the fan is kept within the preset safety constraint range.

9. An adaptive wind turbine survival control system based on condition monitoring, characterized in that, include: The threat identification module is used to acquire status monitoring data of offshore wind turbines and identify the types of survival threats currently faced by the wind turbines based on the status monitoring data. The pattern matching module is used to match the corresponding adaptive survival mode in the preset survival mode library according to the identified survival threat type. The survival mode library includes the wind-resistant anchoring survival mode corresponding to the structural dynamic threat, the anti-corrosion cycle survival mode corresponding to the corrosion acceleration threat, and the electrical isolation survival mode corresponding to the functional failure threat. Each survival mode is equipped with operating parameter boundaries that keep the wind turbine within the safe operating boundary. The strategy execution module is used to execute the response strategy corresponding to the matched adaptive survival mode, including adjusting the mechanical control parameters, electrical control parameters and structural protection parameters of the wind turbine, and constraining the wind turbine's operating state within the boundaries of the operating parameters.

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