Method for evaluating the safety state of offshore wind power equipment

Abstract

This invention discloses a method for assessing the safety status of offshore wind power equipment, comprising the following steps: acquiring basic structural data and historical operational data of the offshore wind power equipment, and constructing a structural safety knowledge graph and a structural safety assessment index system based on the acquired data; determining the subjective, objective, and comprehensive weights of each safety assessment index in the overall structural safety status assessment of the offshore wind power equipment based on the structural safety assessment index system; and quantitatively assessing the safety status based on the acquired structural safety assessment index system and comprehensive weights to obtain its corresponding safety level. This invention constructs a knowledge graph-based structural safety assessment index system for offshore wind power equipment, integrates the optimal / worst-case method and the CRITIC method to extract the subjective and objective weights of the indicators, utilizes a game theory-based combined weighting model to achieve weight balance optimization, and finally combines a multi-index state distance method to quantitatively classify and grade the structural safety status of the equipment.

Description

Technical Field

[0001] This invention relates to the field of overall safety assessment technology for offshore wind power equipment, and in particular to a method for assessing the safety status of offshore wind power equipment. Background Technology

[0002] With the rapid development of the offshore wind power industry, offshore wind power equipment, due to its large installed capacity and complex operating environment, has become an important infrastructure for the development of clean energy at sea. Typical offshore wind power equipment usually consists of key structural units such as upper functional components, load-bearing cylinder structure, and foundation structure. It operates for a long time in complex marine environments such as high salt spray, high humidity, strong winds and waves, and cyclic loads. During long-term service, the structure inevitably experiences problems such as material performance degradation, abnormal structural response, and deterioration of connection performance, which adversely affect the overall operational safety and power generation reliability of the equipment, and in severe cases, may even lead to safety accidents.

[0003] In current engineering practice, the safety assessment of offshore wind power structures still mainly relies on manual inspections, periodic testing, or analysis of single structural parameters. For example, it involves visually inspecting the structural appearance or using local monitoring and testing methods to assess the operational status of individual structural components. These methods typically suffer from drawbacks such as long inspection cycles, reliance on experience-based judgment for assessment results, and difficulty in systematically reflecting the overall safety status of the structure. Furthermore, they struggle to achieve comprehensive analysis and unified assessment of multiple structural units and various types of status information.

[0004] In addition, existing assessment methods still have significant limitations in distinguishing the operation and maintenance requirements corresponding to different safety states, which can easily lead to inaccurate judgments on structural safety status. On the one hand, excessive maintenance or operation restriction measures are taken for structures that still have the ability to serve safely, increasing unnecessary operation and maintenance costs. On the other hand, structures that have shown abnormal state evolution trends or potential safety risks are not identified and warned in a timely manner, thereby increasing operational risks and affecting the long-term safe and stable operation of offshore wind farms.

[0005] Therefore, there is an urgent need for a structural safety status assessment and early warning method that can comprehensively consider multiple structural units, multiple safety assessment indicators and multiple source status data of offshore wind power equipment, so as to achieve objective assessment, reasonable classification and scientific management of structural safety status. Summary of the Invention

[0006] This invention addresses the problems existing in the prior art by proposing a method for assessing the safety status of offshore wind power equipment.

[0007] The technical means employed in this invention are as follows: A method for assessing the safety status of offshore wind power equipment includes the following steps: Step 1: Obtain the structural foundation data and historical operation data of the offshore wind power equipment; Step 2: Based on the acquired structural basic data and historical operation data, construct a structural safety knowledge graph of offshore wind power equipment, and construct a structural safety assessment index system based on the structural safety knowledge graph; Step 3: Based on the aforementioned structural safety assessment index system, determine the subjective weight of each safety assessment index in the overall safety status assessment of offshore wind power equipment structure using the optimal and worst-case method. Step 4: Based on the aforementioned structural safety assessment index system, the CRITIC method is used to determine the objective weight of each safety assessment index in the overall safety status assessment of offshore wind power equipment structures. Step 5: Based on the subjective weights and the objective weights, a game theory approach is used to determine the comprehensive weights for assessing the overall safety status of offshore wind power equipment structures. Step 6: Based on the obtained structural safety assessment index system and comprehensive weight of offshore wind power equipment, the multi-index state distance method is used to quantitatively assess the overall safety status of the offshore wind power equipment structure in order to obtain its corresponding safety level.

[0008] Furthermore, step 1 is specifically as follows: Define the structural units and monitoring locations in the offshore wind power equipment structure, and collect historical operation data for each structural unit and monitoring location of the corresponding offshore wind power equipment. The historical operational data includes structural feature data and structural status data; The structural status data refers to the operational data measured at each monitoring point during equipment operation; The structural feature data includes environmental condition data, structural material property data, structural load feature data, and structural foundation data. The environmental condition data includes the effective wave height, wave period, wind field turbulence intensity, wind shear index, and ocean current velocity vectors at different water depths in the site area. The structural material property data includes constitutive parameters of the steel used in the structure, including material density, elastic modulus, Poisson's ratio, yield strength, and annual average corrosion rate in the corresponding marine environment. The structural load characteristic data includes the static load generated by the structure's self-weight and the dynamic load distribution characteristics generated by wind turbine blade rotation, emergency shutdown, and extreme wave impact. The structural basic data is constructed by integrating geometric structural parameters and structural material property data; wherein, the geometric structural parameters define the physical spatial configuration of the structure, and the structural material property data endow the physical spatial configuration with mechanical constitutive characteristics through parameter mapping; The geometric structural parameters include the pile-supported foundation structure, the load-bearing cylindrical structure, and the superstructure functional components, as well as their diameter, thickness, cross-sectional dimensions, and connection methods.

[0009] Furthermore, step 2 includes the following steps: Step 21, Data Preprocessing and Knowledge Abstraction: The acquired structural foundation data and historical operation data are subjected to data preprocessing, which includes abnormal data removal, missing data filling, and data normalization to obtain the processed structural foundation data and historical operation data. The processed structural foundation data and historical operation data are subjected to structured abstraction to form structural nodes, state anomaly feature nodes, and security assessment indicator nodes for constructing a knowledge graph. Step 22: Construction of a knowledge graph relating structure, damage, and indicators: Based on the obtained structural nodes, abnormal state feature nodes, and safety assessment index nodes, a knowledge graph of structure-damage-index association is constructed using correlation analysis methods and combined with expert experience. Step 23: Screening of key safety assessment indicators and construction of a safety status assessment indicator system: Based on the path association strength between nodes in the knowledge graph of structure-damage-index association, safety assessment indicators that meet the preset association threshold for their impact on the structural safety status of offshore wind power equipment are selected as key safety assessment indicators, and a safety status assessment indicator system table for offshore wind power equipment structures is formed.

[0010] Furthermore, step 3 includes the following steps: Step 31: Determine the set of safety assessment indicators and select the optimal and worst indicators: A set of safety assessment indicators is constructed based on the aforementioned offshore wind power equipment structural safety status assessment index system table. : (1) Based on expert experience and engineering practice, from the aforementioned set of safety assessment indicators The indicator that has the greatest impact on the overall safety status of the structure is selected as the optimal indicator. The index with the least impact on the overall structural safety status is selected as the worst-case index. ; Step 32: Construct a comparison vector of the importance of the best and worst indicators relative to other indicators: With the aforementioned optimal index Based on this, construct the optimal index. Importance comparison vector relative to other safety assessment indicators : (2) in, Indicates the optimal index relative to indicators The degree of importance; when hour, =1; With the worst-case indicator Based on this benchmark, construct the remaining security assessment indicators relative to the worst-case indicator. Importance comparison vector : (3) in, Indicators Compared to the worst-case indicator The degree of importance; when hour, =1; in, and The value range is 1 to 9, and the specific meanings of the values ​​are as follows: When the value is 1, it indicates that they have the same priority. When the value is 2, it indicates that the priority is between 1 and 3; When the value is 3, it indicates medium priority; When the value is 4, it indicates that the priority is between 3 and 5; When the value is 5, it indicates priority; When the value is 6, it indicates that the priority is between 5 and 7; When the value is 7, it indicates very high priority; When the value is 8, it indicates that the priority is between 7 and 9; When the value is 9, it indicates the highest priority; Step 33: Construct the BWM subjective weight optimization model: Construct subjective weights for each security assessment indicator. for: (4) in, Indicates the first The subjective weights of each security assessment indicator to be solved. And it satisfies the normalization constraint: (5) Based on the consistency principle of BWM, construct an optimization model: (6) Make it satisfy the constraints: (7) (8) (9) in, Indicates the consistency deviation variable; Step 34: Subjective weight calculation and consistency check: Solving the aforementioned BWM subjective weight optimization model yields the subjective weight vector of the safety assessment indicators: (10) in, Indicates the first The subjective weights obtained from solving each security assessment indicator are used, and the consistency deviation values ​​obtained from the solution are used as a basis. Determine the consistency deviation value Does it meet the preset consistency threshold? (11) in, Indicates the preset consistency threshold; If the above conditions are met, the subjective weighting result is deemed to have consistent validity; otherwise, the importance comparison vector is adjusted and steps S32 to S34 are repeated.

[0011] Furthermore, step 4 includes the following steps: Step 41: Construct the original data matrix for the evaluation indicators: Suppose that the safety assessment index system for offshore wind power equipment structures contains n safety assessment indicators, corresponding to m assessment samples, and construct the original data matrix of the assessment indicators. (12) in, Indicates the first The evaluation sample in the first Original indicator values ​​under each safety assessment indicator; Step 42: Standardization of the evaluation index data matrix: The original evaluation index data matrix is ​​standardized to obtain a standardized evaluation index matrix: (13) The standardized evaluation index matrix is ​​then processed to make the positive indicators dimensionless: (14) The standardized evaluation index matrix is ​​then processed to make the negative indicators dimensionless: (15) in, and These represent the nth elements in the original data matrix. List the maximum and minimum values ​​of the security assessment indicators; Step 43: Calculate the comparative strength of each safety assessment indicator: For each safety assessment indicator in the standardized assessment indicator matrix, its comparative strength is calculated using the standard deviation: (16) in, (17) Step 44: Calculate the correlation matrix between the indicators: Based on the standardized indicator matrix, the correlation coefficients between the various safety assessment indicators are calculated, and an indicator correlation matrix is ​​constructed: (18) Among them, the The first security assessment indicator and the first The formula for calculating the correlation coefficient between the safety assessment indicators is as follows: (19) Step 45: Calculate the amount of information in the indicators: Based on the comparative strength of each safety assessment indicator and the conflict between the indicators, the calculation of the first... The total amount of information contained in each security assessment indicator: (20) in, Indicates the first The comprehensive amount of information contained in each security assessment indicator; Step 46: Determine the objective weights: The overall information content of each safety assessment indicator is normalized to obtain the objective weight of each safety assessment indicator: (twenty one) in, Indicates the first The objective weights corresponding to each security assessment indicator; Step 47: Construct the objective weight vector: Construct an objective weight vector based on the objective weights of each obtained security assessment indicator: (twenty two) in, This represents the objective weight vector of the safety assessment indicators.

[0012] Furthermore, step 5 includes the following steps: Step 51: Construct a game theory combined weight model: Based on the subjective weight vector and the objective weight vector, construct a comprehensive weight vector in the form of a linear combination: (twenty three) in: The combination coefficients are to be determined, and the constraints must be met. (twenty four) Step 52: Construct a minimum deviation game optimization model: (25) in, , ; Represents the vector norm; Represents the combination coefficients. ; Step 53: Solve for the game theory combination coefficients: Substituting the comprehensive weight vector into the minimum deviation game optimization model, we obtain information about the combination coefficients. Optimization solution model: (26) The constraints are satisfied: (27) For the combined coefficients The optimal solution model is used to solve the problem and obtain the optimal combination coefficients. and ; Step 54: Determine the comprehensive weight vector: right and Normalization is performed: (28) (28) Substitute the normalized weight coefficients into the comprehensive weight vector to obtain the final comprehensive weight: (29) This leads to the comprehensive weight vector of the structural safety assessment indicators for offshore wind power equipment: (30) in, , Indicates the first The overall weight of each security assessment indicator.

[0013] Furthermore, step 6 includes the following steps: Step 61: Construct a standard state reference interval table for security levels and classify security levels: A standard state reference interval table for safety levels is constructed, and based on the degree of change in structural state response characteristics and its impact on the safe operation of the structure, the safety status of offshore wind power equipment is divided into four levels: I, II, III, and IV, corresponding to "good condition", "relatively good condition", "poor condition" and "dangerous condition". Step 62: Construct standard state reference vectors for each security level: Based on structural design specifications, operation control requirements, and historical operation statistics, a corresponding standard state reference vector is constructed for each safety level. (31) in, Indicates the first Under the first security level The standard state characteristic values ​​corresponding to each safety assessment indicator; the values ​​of each component of the standard state reference vector are determined according to the state reference interval of the corresponding safety level in the standard state reference interval table of the safety level; Step 63: Construct a multi-index state feature vector of the current state of the offshore wind power equipment structure: Based on the safety assessment data collected under the current operating conditions, and after standardization according to a unified dimensionless rule, a multi-index state feature vector corresponding to the current state of the offshore wind power equipment structure is constructed: (32) in, This indicates the current state of the offshore wind power equipment structure. The status characteristic values ​​corresponding to each security assessment indicator; Step 64: Construct a weighted state distance metric model: Based on the comprehensive weight vector The current status and first phase of offshore wind power equipment structure construction Weighted state distance metric model between security levels: (33) The following conditions must be met: (34) Step 65: Calculate the state distance between the current state of the offshore wind power equipment structure and each safety level: Based on the weighted state distance metric model, the state distances between the current state of the offshore wind power equipment structure and each safety level are calculated to obtain a set of state distances. : (35) in: Indicates the current state of the offshore wind power equipment structure and the first Distance values ​​between standard states of each security level; Step 66: Determine the overall safety level of offshore wind power equipment structure based on the minimum state distance criterion. The state distance set is analyzed based on the minimum state distance criterion. Each element is compared to determine the overall structural safety level: (36) in, This indicates the overall safety level assessment result corresponding to the current operating status of the offshore wind power equipment structure. Step 67: Output the structural safety assessment results: The overall safety level of the offshore wind power equipment structure will be determined. The corresponding state distance calculation results are used as the final output of the structural safety status assessment of offshore wind power equipment, and are used for structural safety early warning, operation status assessment and operation and maintenance decision support.

[0014] Furthermore, the standard state reference interval table for the security level includes: The four levels are: I, II, III, and IV. The four levels correspond to the status descriptions of "Good Status", "Fair Status", "Poor Status" and "Dangerous Status". Safety indicators include vertical deformation response, horizontal displacement response, attitude deviation characteristics, continuity anomaly characteristics, and vibration response change characteristics; Each safety indicator corresponds to four levels, meanings of which are: within the reference range of the baseline state, deviating from the baseline state but not exceeding the allowable reference range, exceeding the allowable reference range and showing a continuous increasing trend, and significantly deviating from the baseline state and exceeding the safety control threshold. The baseline state reference range is obtained by analyzing the safety status response index data collected during the initial commissioning or historical stable operation phase of offshore wind power equipment and the statistical distribution characteristics of the corresponding index data. The allowable reference range is determined by expanding the baseline state reference range based on structural design parameters, allowable ranges in specifications, and operational experience. The safety control threshold is set according to the structural design safety requirements or operational control requirements and is used to distinguish between acceptable and dangerous structural states.

[0015] Furthermore, the safety status of offshore wind power equipment is classified into four levels: I, II, III, and IV, and the classification criteria are as follows: Level I indicates that the overall structural condition is within the allowable range of the design conditions, the state response of each structural unit is stable, and the superstructure and pile foundation structure meet the requirements for long-term safe service, and no structural treatment measures are required. Level II indicates that the overall structural condition is basically within the design allowable range, with slight abnormalities in the condition response of individual structural units, but without substantial impact on the overall load-bearing capacity. The structure can continue to be in service, but operational monitoring should be strengthened. Level III indicates that the state response of key structural units deviates from the design reference range, the structural load-bearing capacity shows a significant downward trend, which has an adverse impact on operational safety, and targeted maintenance or operation control measures are required. Level IV indicates that the overall structural condition significantly exceeds the design allowable range, key structural units have significant abnormal response or failure risk, and do not meet the requirements for safe operation. Structural treatment or shutdown measures should be taken in a timely manner.

[0016] Furthermore, the safety status assessment index system table for offshore wind power equipment structures includes structural units, primary indicators, and secondary safety assessment indicators: The structural unit includes: pile-bearing foundation structure, load-bearing cylindrical structure, and superstructure functional components; Among them, the primary indicators corresponding to pile-bearing foundation structures include: geometric state response and structural integrity state; The primary indicators for load-bearing cylindrical structures include: overall deformation state and local deformation characteristics; The primary indicators corresponding to the upper functional components include: dynamic response characteristics and operational status characteristics; Among them, the secondary safety assessment indicators corresponding to the geometric state response include: the vertical deformation response of the foundation and the horizontal displacement response of the foundation; The secondary safety assessment indicators corresponding to the structural integrity status include: pile-soil interaction stiffness variation characteristics and overall foundation attitude offset characteristics; The secondary safety assessment indicators corresponding to the overall deformation state include: the axial deformation response of the bearing cylinder and the lateral displacement response of the bearing cylinder; The secondary safety assessment indicators corresponding to local state characteristics include: abnormal characteristics of local continuity of the load-bearing cylinder and stiffness degradation characteristics of the cylinder connection parts; The secondary safety assessment indicators corresponding to the dynamic response characteristics include: the vibration response change characteristics of the superstructure; The secondary safety assessment indicators corresponding to the operational status characteristics include: the operational stability change characteristics of the superstructure.

[0017] Compared with existing technologies, the method for assessing the safety status of offshore wind power equipment disclosed in this invention has the following beneficial effects: This invention constructs a knowledge graph-based structural safety assessment index system for offshore wind power equipment, integrates the best-worst method (BWM) and the CRITIC method to extract the subjective and objective weights of the indicators respectively, and uses a game theory-based combined weighting model to achieve balanced optimization of the weights. Finally, it combines a multi-indicator state distance method to quantify and classify the structural safety status of the equipment. The knowledge graph technology effectively solves the problems of complex and hidden correlations in offshore wind power structural failure modes, improving the completeness and scientific nature of the assessment index system. The game theory model, combined with subjective engineering experience and objective data distribution characteristics, eliminates the bias of a single weighting method, ensuring the credibility and robustness of the safety weight allocation. The state distance method accurately characterizes the deviation between the real-time operating status and the standard safety level, effectively capturing the subtle deterioration trends of key indicators, providing precise decision support for preventive maintenance and life-cycle safety management of offshore wind power equipment. Attached Figure Description

[0018] Figure 1 This is a flowchart of the method for assessing the safety status of offshore wind power equipment disclosed in this invention; Figure 2 This is a structural diagram of the knowledge graph constructed in the method for assessing the safety status of offshore wind power equipment disclosed in this invention; Detailed Implementation like Figure 1 As shown, the method for assessing the safety status of offshore wind power equipment disclosed in this invention includes the following steps: Step 1: Obtain the structural foundation data and historical operation data of the offshore wind power equipment; Step 2: Based on the acquired structural basic data and historical operation data, construct a structural safety knowledge graph of offshore wind power equipment, and construct a structural safety assessment index system based on the structural safety knowledge graph; Step 3: Based on the aforementioned structural safety assessment index system, determine the subjective weight of each safety assessment index in the overall safety status assessment of offshore wind power equipment structure using the optimal and worst-case method. Step 4: Based on the aforementioned structural safety assessment index system, the CRITIC method is used to determine the objective weight of each safety assessment index in the overall safety status assessment of offshore wind power equipment structures. Step 5: Based on the subjective weights and the objective weights, a game theory approach is used to determine the comprehensive weights for assessing the overall safety status of offshore wind power equipment structures. Step 6: Based on the obtained structural safety assessment index system and comprehensive weight of offshore wind power equipment, the multi-index state distance method is used to quantitatively assess the overall safety status of the offshore wind power equipment structure in order to obtain its corresponding safety level.

[0019] This invention constructs a knowledge graph-based structural safety assessment index system for offshore wind power equipment, integrates the best-worst method (BWM) and the CRITIC method to extract the subjective and objective weights of the indicators respectively, and uses a game theory combined weighting model to achieve balanced optimization of the weights. Finally, it combines the multi-index state distance method to quantify and classify the structural safety status of the equipment.

[0020] The present invention has the following beneficial effects: Knowledge graph technology effectively addresses the complex and hidden correlations of failure modes in offshore wind power structures, enhancing the completeness and scientific rigor of the evaluation index system. Game theory models, combined with subjective engineering experience and objective data distribution characteristics, eliminate the bias of single weighting methods, ensuring the credibility and robustness of safety weight allocation. The state distance method precisely characterizes the deviation between real-time operating status and standard safety levels, effectively capturing subtle deterioration trends in key indicators, and providing accurate decision support for preventative maintenance and life-cycle safety management of offshore wind power equipment.

[0021] Furthermore, step 1 is specifically as follows: Define the structural units and monitoring locations in the offshore wind power equipment structure, and collect historical operation data for each structural unit and monitoring location of the corresponding offshore wind power equipment. The historical operational data includes structural feature data and structural status data; The structural status data refers to the operational data measured at each monitoring point during equipment operation; The structural feature data includes environmental condition data, structural material property data, structural load feature data, and structural foundation data. The environmental condition data includes the effective wave height, wave period, wind field turbulence intensity, wind shear index, and ocean current velocity vectors at different water depths in the site area. The structural material property data includes constitutive parameters of the steel used in the structure, including material density, elastic modulus, Poisson's ratio, yield strength, and annual average corrosion rate in the corresponding marine environment. The structural load characteristic data includes the static load generated by the structure's self-weight and the dynamic load distribution characteristics generated by wind turbine blade rotation, emergency shutdown, and extreme wave impact. The structural basic data is constructed by integrating geometric structural parameters and structural material property data; wherein, the geometric structural parameters define the physical spatial configuration of the structure, and the structural material property data endow the physical spatial configuration with mechanical constitutive characteristics through parameter mapping; The geometric structural parameters include the pile-supported foundation structure, the load-bearing cylindrical structure, and the superstructure functional components, as well as their diameter, thickness, cross-sectional dimensions, and connection methods.

[0022] This step establishes the data foundation, which serves as the physical source for all subsequent analyses, ensuring the original authenticity of the evaluation model. By integrating multi-source data, the limitations of single-source monitoring data being susceptible to environmental noise interference are overcome, providing underlying support for constructing an accurate knowledge graph. Furthermore, step 2 includes the following steps: Step 2 involves constructing a knowledge graph related to the structural safety of offshore wind power equipment based on the structural foundation data and historical operation data. Then, based on the knowledge graph, the correlation between abnormal structural features and safety assessment indicators is analyzed to identify key safety assessment indicators that have a significant impact on the structural safety status of offshore wind power equipment, thereby forming an indicator system for structural safety assessment. The knowledge graph is used to describe the relationships between different structural zones, typical structural anomaly characteristics, and safety assessment indicators of offshore wind power equipment, specifically including the following steps: Step 21, Data Preprocessing and Knowledge Abstraction: The acquired structural foundation data and historical operation data are subjected to data preprocessing, which includes abnormal data removal, missing data filling, and data normalization to obtain the processed structural foundation data and historical operation data. The processed structural foundation data and historical operation data are subjected to structured abstraction to form structural nodes, state anomaly feature nodes, and security assessment indicator nodes for constructing a knowledge graph. Among them, structural nodes correspond to the physical composition of offshore wind power equipment, including upper functional components, load-bearing cylinder structure and foundation structure; abnormal condition characteristic nodes correspond to physical damage or performance degradation characteristics that occur in the structure during service, including but not limited to blade instability, stiffness degradation of connection parts, local continuity anomalies of the cylinder and pile scour; safety assessment index nodes correspond to observable or calculable physical quantities, including quantitative indicators generated by real-time monitoring and qualitative indicators generated based on inspection status scores. Step 22: Construction of a knowledge graph relating structure, damage, and indicators: Based on the obtained structural nodes, abnormal state feature nodes, and safety assessment index nodes, a knowledge graph of structure-damage-index association is constructed using correlation analysis methods and combined with expert experience. Specifically, this step analyzes the correlation between the structural feature data and structural state data obtained in step 1 (calculated using the Pearson correlation coefficient) to determine typical structural state anomalies that are prone to occur in different structural zones under specific working conditions. Furthermore, a weighted connection is established between "state anomaly feature nodes" and "safety assessment index nodes" to characterize the sensitivity of index changes to damage evolution. For qualitative indicators, they are mapped to quantitative scores using a pre-defined grading standard, thus achieving a unified expression of qualitative and quantitative indicators in the knowledge graph. The knowledge graph established in this application is as follows: Figure 2 As shown; Step 23: Screening of key safety assessment indicators and construction of a safety status assessment indicator system: Based on the path association strength between nodes in the knowledge graph of structure-damage-index association, safety assessment indicators that meet the preset association threshold (set ranking threshold, for example, the ranking threshold set in this application is the top ten) are selected as key safety assessment indicators and form a safety status assessment indicator system table for offshore wind power equipment structure. Specifically, the safety assessment index selection logic is as follows: Indicators with the highest correlation to abnormal state characteristic nodes are selected from the candidate indicators, and these indicators are categorized and constructed to form a safety assessment index system applicable to the superstructure, load-bearing cylindrical structure, and foundation structure. These key safety assessment indicators are used as input indicators in the subsequent overall structural safety assessment process. The final structural safety assessment index system is shown in Table 1. Table 1. Overall Safety Status Assessment Index System for Offshore Pile-Bearing Structures

[0023] In other words, in this application, the safety status assessment index system table for offshore wind power equipment structures includes structural units, primary indicators, and secondary safety assessment indicators: The structural unit includes: pile-bearing foundation structure, load-bearing cylindrical structure, and superstructure functional components; Among them, the primary indicators corresponding to pile-bearing foundation structures include: geometric state response and structural integrity state; The primary indicators for load-bearing cylindrical structures include: overall deformation state and local deformation characteristics; The primary indicators corresponding to the upper functional components include: dynamic response characteristics and operational status characteristics; Among them, the secondary safety assessment indicators corresponding to the geometric state response include: the vertical deformation response of the foundation and the horizontal displacement response of the foundation; The secondary safety assessment indicators corresponding to the structural integrity status include: pile-soil interaction stiffness variation characteristics and overall foundation attitude offset characteristics; The secondary safety assessment indicators corresponding to the overall deformation state include: the axial deformation response of the bearing cylinder and the lateral displacement response of the bearing cylinder; The secondary safety assessment indicators corresponding to local state characteristics include: abnormal characteristics of local continuity of the load-bearing cylinder and stiffness degradation characteristics of the cylinder connection parts; The secondary safety assessment indicators corresponding to the dynamic response characteristics include: the vibration response change characteristics of the superstructure; The secondary safety assessment indicators corresponding to the operational status characteristics include: the operational stability change characteristics of the superstructure.

[0024] In this application, the meanings of each safety indicator are as follows: (1) The vertical deformation response of the foundation is determined by the displacement of the monitoring point of the pile foundation in the vertical direction. The cumulative change of vertical displacement within a specified time period is taken as the quantitative value of the index. (2) The horizontal displacement response of the foundation is determined by the displacement of the pile-supported foundation in the horizontal direction. The displacement change of the foundation monitoring point in the horizontal direction is taken as the quantitative value of this index. (3) The variation characteristics of pile-soil interaction stiffness are obtained by inverting the displacement response of the pile foundation under known external loads. The value of this index is determined by comparing the changes in the equivalent stiffness parameters of pile-soil in different time periods. (4) The overall attitude deviation characteristics of the foundation are determined by the overall inclination angle of the pile-supported foundation. The change in inclination angle of the foundation in two orthogonal directions is taken as the quantitative value of this index. (5) The axial deformation response of the bearing cylinder is determined by the axial displacement of the bearing cylinder, and the change in axial displacement is used as the quantitative value of this index; (6) The lateral displacement response of the bearing cylinder is determined by the displacement of the bearing cylinder in the lateral direction. The change in lateral displacement of the bearing cylinder is taken as the quantitative value of this index. (7) The local continuity anomaly characteristics of the bearing cylinder are determined by the strain distribution anomaly in the local area of ​​the bearing cylinder, and the strain difference between adjacent measuring points is calculated as the quantitative value of this index; (8) The stiffness degradation characteristics of the cylinder connection are determined by the deformation response of the connection under the same conditions. The change in the equivalent stiffness parameter of the connection in different time periods is used as the quantitative value of this index. (9) The vibration response variation characteristics of the superstructure are determined by the vibration amplitude of the superstructure functional components under operating conditions. The root mean square value of the vibration acceleration signal within the preset time window is taken as the quantization value of this index.

[0025] This step achieves semantic integration of heterogeneous data. Fragmented engineering data is transformed into a logically connected knowledge network, from which evaluation indicators are derived. This solves the problems of complex offshore wind power structures and strong correlations between failure modes. By utilizing the association mining capabilities of knowledge graphs, the comprehensiveness and scientific nature of the indicator system are ensured, avoiding subjective omissions caused by manually setting indicators in traditional methods.

[0026] Furthermore, step 3 includes the following steps: Step 3 involves using the best-worst method (BWM) to determine the subjective weight of each safety assessment index in the overall safety status assessment of offshore wind power equipment structures, based on the structural safety assessment index system constructed from the knowledge graph. This involves incorporating expert judgment information to quantify and compare the importance of different safety assessment indicators, thereby obtaining subjective weight results that reflect engineering experience and professional knowledge. The specific process is as follows: Step 31: Determine the set of safety assessment indicators and select the optimal and worst indicators: A set of safety assessment indicators is constructed based on the aforementioned offshore wind power equipment structural safety status assessment index system table. : (1) Based on expert experience and engineering practice, from the aforementioned set of safety assessment indicators The indicator that has the greatest impact on the overall safety status of the structure is selected as the optimal indicator. The index with the least impact on the overall structural safety status is selected as the worst-case index. The expert experience mentioned above comes from professionals in the fields of offshore wind power structure design, operation and maintenance and testing. Step 32: Construct a comparison vector of the importance of the best and worst indicators relative to other indicators: With the aforementioned optimal index Based on this, construct the optimal index. Importance comparison vector relative to other safety assessment indicators : (2) in, Indicates the optimal index relative to indicators The degree of importance; when hour, =1; With the worst-case indicator Based on this benchmark, construct the remaining security assessment indicators relative to the worst-case indicator. Importance comparison vector : (3) in, Indicators Compared to the worst-case indicator The degree of importance; when hour, =1; in, and The value range is a preset integer scale interval, used to quantify experts' judgment on the importance of the indicator. In this application... and The value range is 1 to 9, and the specific meanings of the values ​​are as follows: When the value is 1, it indicates that they have the same priority. When the value is 2, it indicates that the priority is between 1 and 3; When the value is 3, it indicates medium priority; When the value is 4, it indicates that the priority is between 3 and 5; When the value is 5, it indicates priority; When the value is 6, it indicates that the priority is between 5 and 7; When the value is 7, it indicates very high priority; When the value is 8, it indicates that the priority is between 7 and 9; When the value is 9, it indicates the highest priority; The specific preset integer scale intervals can be found in Table 2: Table 2. Schematic diagram of relative importance

[0027] Step 33: Construct the BWM subjective weight optimization model: Construct subjective weights for each security assessment indicator. for: (4) in, Indicates the first The subjective weights of each security assessment indicator to be solved. And it satisfies the normalization constraint: (5) Based on the consistency principle of BWM, construct an optimization model: (6) Make it satisfy the constraints: (7) (8) (9) in, The variable representing consistency deviation is used; the optimization model is used to solve for the optimal subjective weights of each safety assessment index while ensuring the consistency of expert judgment. Step 34: Subjective weight calculation and consistency check: Solving the aforementioned BWM subjective weight optimization model yields the subjective weight vector of the safety assessment indicators: (10) in, Indicates the first The subjective weights obtained from solving each security assessment indicator are used, and the consistency deviation values ​​obtained from the solution are used as a basis. Determine the consistency deviation value Does it meet the preset consistency threshold? (11) in, Indicates the preset consistency threshold; If the above conditions are met, the subjective weighting results are deemed to have consistent validity; otherwise, the importance comparison vector is adjusted and steps S32 to S34 are repeated. The subjective weights of each safety assessment index determined by the BWM method will be used as the subjective weight inputs in the overall safety status assessment of offshore wind power equipment structures, and will be used for subsequent comprehensive weight calculation with objective weights and determination of structural safety level.

[0028] In this step, by quantifying expert experience, Business Modeling (BWM) demonstrates higher comparative consistency compared to the traditional Analytic Hierarchy Process (AHP) in multi-criteria decision-making. By reducing the number of comparisons, consistency bias in the evaluation process is significantly reduced, ensuring that the evaluation results align with engineering realities.

[0029] Furthermore, step 4 includes the following steps: Step 4, based on the offshore wind power equipment structural safety assessment index system determined in Step 2 and the corresponding raw index data, uses the CRITIC (Criteria Importance Through Intercriteria Correlation) method to determine the objective weights of each safety assessment index. The CRITIC method comprehensively considers the comparative strength of each safety assessment index and the correlation between the indicators to reduce the influence of subjective human factors on the weight determination results. The specific steps are as follows: Step 41: Construct the original data matrix for the evaluation indicators: Suppose that the safety assessment index system for offshore wind power equipment structures contains n safety assessment indicators, corresponding to m assessment samples, and construct the original data matrix of the assessment indicators. (12) in, Indicates the first The evaluation sample in the first Original indicator values ​​under each safety assessment indicator; Step 42: Standardization of the evaluation index data matrix: To eliminate the influence of different indicator units and numerical ranges, the original evaluation indicator data matrix is ​​standardized to obtain a standardized evaluation indicator matrix: (13) The standardized evaluation index matrix is ​​then processed to make the positive indicators dimensionless: (14) The standardized evaluation index matrix is ​​then processed to make the negative indicators dimensionless: (15) in, and These represent the nth elements in the original data matrix. List the maximum and minimum values ​​of the security assessment indicators; Step 43: Calculate the comparative strength of each safety assessment indicator: For each safety assessment indicator in the standardized assessment indicator matrix, its comparative strength is calculated using the standard deviation: (16) in, (17) Step 44: Calculate the correlation matrix between the indicators: Based on the standardized indicator matrix, the correlation coefficients between the various safety assessment indicators are calculated, and an indicator correlation matrix is ​​constructed: (18) Among them, the The first security assessment indicator and the first The formula for calculating the correlation coefficient between the safety assessment indicators is as follows: (19) Step 45: Calculate the amount of information in the indicators: Based on the comparative strength of each safety assessment indicator and the conflict between the indicators, the calculation of the first... The total amount of information contained in each security assessment indicator: (20) in, Indicates the first The comprehensive amount of information contained in each security assessment indicator; Step 46: Determine the objective weights: The overall information content of each safety assessment indicator is normalized to obtain the objective weight of each safety assessment indicator: (twenty one) in, Indicates the first Each safety assessment indicator has its own objective weight; the objective weight reflects the objective importance of the indicator in the structural safety assessment. Step 47: Construct the objective weight vector: Construct an objective weight vector based on the objective weights of each obtained security assessment indicator: (twenty two) in, This represents the objective weight vector of the safety assessment indicators.

[0030] This step involves mining the intrinsic characteristics of the data. The CRITIC method balances the variability of indicators and the correlation between them, enabling self-correction of weights. It can extract information from objective data, effectively identify and process data features that fluctuate greatly or are highly redundant with other indicators, and compensate for implicit data trends that may be overlooked by subjective evaluations.

[0031] Furthermore, step 5 includes the following steps: Step 5 involves introducing game theory to coordinate and combine the subjective and objective weights, based on the BRIM method and the CRITIC method, to determine a comprehensive weight that balances expert experience and objective data characteristics. This comprehensive weight is then used for the overall safety status assessment of offshore wind power equipment structures. The specific steps are as follows: Step 51: Construct a game theory combined weight model: Based on the subjective weight vector and the objective weight vector, construct a comprehensive weight vector in the form of a linear combination: (twenty three) in: The combination coefficients are to be determined, and the constraints must be met. (twenty four) Step 52: Construct a minimum deviation game optimization model: To minimize the deviation between the overall weight and each individual weight scheme, a minimum deviation criterion is introduced, and the following game theory optimization model is constructed. (25) in, , ; The vector norm is used to measure the deviation between weight vectors. Represents the combination coefficients. ; Step 53: Solve for the game theory combination coefficients: Substituting the comprehensive weight vector into the minimum deviation game optimization model, we obtain information about the combination coefficients. Optimization solution model: (26) The constraints are satisfied: (27) For the combined coefficients The optimal solution model is used to solve the problem and obtain the optimal combination coefficients. and ; Step 54: Determine the comprehensive weight vector: right and Normalization is performed: (28) (28) Substitute the normalized weight coefficients into the comprehensive weight vector to obtain the final comprehensive weight: (29) This leads to the comprehensive weight vector of the structural safety assessment indicators for offshore wind power equipment: (30) in, , Indicates the first The overall weight of each security assessment indicator.

[0032] This step resolves the conflict between subjective and objective weights. The game theory model achieves the optimal combination of weights by finding a "Nash equilibrium" between subjective intentions and objective laws. It effectively avoids the bias that may be caused by a single weighting method, significantly improves the robustness and credibility of the evaluation model, and makes the final weight allocation more fair and robust.

[0033] Furthermore, step 6 includes the following steps: Step 6 is the determination of the overall structural safety level based on multi-index state distance discrimination. This involves obtaining the offshore wind turbine structural safety assessment index system and its corresponding comprehensive weight vector, then using the multi-index state distance method to quantitatively assess the overall safety status of the offshore wind turbine structure and determine its corresponding safety level. The specific process is as follows: Step 61: Construct a standard state reference interval table for security levels and classify security levels: The offshore wind power equipment structural safety assessment index system obtained in step 24 includes... A safety assessment index is established, and a standard state reference interval table for safety levels is constructed (see Table 3 for details). The baseline state reference interval is determined based on the safety state response index data collected during the initial commissioning phase or the historical stable operation phase of the offshore pile-supported structure. Specifically, it is obtained by analyzing the statistical distribution characteristics of the corresponding indexes. The allowable reference interval is determined by expanding upon the baseline state reference interval, combined with structural design parameters, allowable ranges in specifications, and operational experience. The safety control threshold is set according to the structural design safety requirements or operational control requirements, and is used to distinguish between acceptable and dangerous structural states. Table 3. Standard State Reference Range for Overall Structural Safety Level of Offshore Wind Turbine Units

[0034] Then, based on the degree of change in structural state response characteristics and its impact on the safe operation of the structure, the safety status of offshore wind power equipment is divided into four levels: I, II, III, and IV, corresponding to the four levels of "good condition", "relatively good condition", "poor condition" and "dangerous condition", as detailed in Table 4. Table 4. Standards for Classification of Overall Safety Levels of Offshore Wind Turbine Units

[0035] That is, the standard state reference interval table for the aforementioned security level includes: The four levels are: I, II, III, and IV. The four levels correspond to the status descriptions of "Good Status", "Fair Status", "Poor Status" and "Dangerous Status". Safety indicators include vertical deformation response, horizontal displacement response, attitude deviation characteristics, continuity anomaly characteristics, and vibration response change characteristics; Each safety indicator corresponds to four levels, meanings of which are: within the reference range of the baseline state, deviating from the baseline state but not exceeding the allowable reference range, exceeding the allowable reference range and showing a continuous increasing trend, and significantly deviating from the baseline state and exceeding the safety control threshold. The baseline state reference range is obtained by analyzing the safety status response index data collected during the initial commissioning or historical stable operation phase of offshore wind power equipment and the statistical distribution characteristics of the corresponding index data. The allowable reference range is determined by expanding the baseline state reference range based on structural design parameters, allowable ranges in specifications, and operational experience. The safety control threshold is set according to the structural design safety requirements or operational control requirements and is used to distinguish between acceptable and dangerous structural states. Step 62: Construct standard state reference vectors for each security level: Based on structural design specifications, operation control requirements, and historical operation statistics, a corresponding standard state reference vector is constructed for each safety level. (31) in, Indicates the first Under the first security level The standard state characteristic values ​​corresponding to each safety assessment indicator; the values ​​of each component of the standard state reference vector are determined according to the state reference interval of the corresponding safety level in the standard state reference interval table of the safety level; Step 63: Construct a multi-index state feature vector of the current state of the offshore wind power equipment structure: Based on the safety assessment data collected under the current operating conditions, and after standardization according to a unified dimensionless rule, a multi-index state feature vector corresponding to the current state of the offshore wind power equipment structure is constructed: (32) in, This indicates the current state of the offshore wind power equipment structure. The status characteristic values ​​corresponding to each security assessment indicator; Step 64: Construct a weighted state distance metric model: Based on the comprehensive weight vector The current status and first phase of offshore wind power equipment structure construction Weighted state distance metric model between security levels: (33) The following conditions must be met: (34) Step 65: Calculate the state distance between the current state of the offshore wind power equipment structure and each safety level: Based on the weighted state distance metric model, the state distances between the current state of the offshore wind power equipment structure and each safety level are calculated to obtain a set of state distances. : (35) in: Indicates the current state of the offshore wind power equipment structure and the first Distance values ​​between standard states of each security level; Step 66: Determine the overall safety level of offshore wind power equipment structure based on the minimum state distance criterion. The state distance set is analyzed based on the minimum state distance criterion. Each element is compared to determine the overall structural safety level: (36) in, This indicates the overall safety level assessment result corresponding to the current operating status of the offshore wind power equipment structure. Step 67: Output the structural safety assessment results: The overall safety level of the offshore wind power equipment structure will be determined. The corresponding state distance calculation results are used as the final output of the structural safety status assessment of offshore wind power equipment, and are used for structural safety early warning, operation status assessment and operation and maintenance decision support.

[0036] This step enables the mapping of status levels, that is, the safety level is determined by calculating the "distance" between the status to be evaluated and the standard level, providing a direct and clear scientific basis for the operation and maintenance decisions of offshore wind power.

[0037] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for assessing the safety status of offshore wind power equipment, characterized in that, Includes the following steps: Step 1: Obtain the structural foundation data and historical operation data of the offshore wind power equipment; Step 2: Based on the acquired structural basic data and historical operation data, construct a structural safety knowledge graph of offshore wind power equipment, and construct a structural safety assessment index system based on the structural safety knowledge graph; Step 3: Based on the aforementioned structural safety assessment index system, determine the subjective weight of each safety assessment index in the overall safety status assessment of offshore wind power equipment structure using the optimal and worst-case method. Step 4: Based on the aforementioned structural safety assessment index system, the CRITIC method is used to determine the objective weight of each safety assessment index in the overall safety status assessment of offshore wind power equipment structures. Step 5: Based on the subjective weights and the objective weights, a game theory approach is used to determine the comprehensive weights for assessing the overall safety status of offshore wind power equipment structures. Step 6: Based on the obtained structural safety assessment index system and comprehensive weight of offshore wind power equipment, the multi-index state distance method is used to quantitatively assess the overall safety status of the offshore wind power equipment structure in order to obtain its corresponding safety level.

2. The method for assessing the safety status of offshore wind power equipment according to claim 1, characterized in that: Step 1 is described in detail as follows: Define the structural units and monitoring locations in the offshore wind power equipment structure, and collect historical operation data for each structural unit and monitoring location of the corresponding offshore wind power equipment. The historical operational data includes structural feature data and structural status data; The structural status data refers to the operational data measured at each monitoring point during equipment operation; The structural feature data includes environmental condition data, structural material property data, structural load feature data, and structural foundation data. The environmental condition data includes the effective wave height, wave period, wind field turbulence intensity, wind shear index, and ocean current velocity vectors at different water depths in the site area. The structural material property data includes constitutive parameters of the steel used in the structure, including material density, elastic modulus, Poisson's ratio, yield strength, and annual average corrosion rate in the corresponding marine environment. The structural load characteristic data includes the static load generated by the structure's self-weight and the dynamic load distribution characteristics generated by wind turbine blade rotation, emergency shutdown, and extreme wave impact. The structural basic data is constructed by integrating geometric structural parameters and structural material property data; wherein, the geometric structural parameters define the physical spatial configuration of the structure, and the structural material property data endow the physical spatial configuration with mechanical constitutive characteristics through parameter mapping; The geometric structural parameters include the pile-supported foundation structure, the load-bearing cylindrical structure, and the superstructure functional components, as well as their diameter, thickness, cross-sectional dimensions, and connection methods.

3. The method for assessing the safety status of offshore wind power equipment according to claim 1, characterized in that: Step 2 includes the following steps: Step 21, Data Preprocessing and Knowledge Abstraction: The acquired structural foundation data and historical operation data are subjected to data preprocessing, which includes abnormal data removal, missing data filling, and data normalization to obtain the processed structural foundation data and historical operation data. The processed structural foundation data and historical operation data are subjected to structured abstraction to form structural nodes, state anomaly feature nodes, and security assessment indicator nodes for constructing a knowledge graph. Step 22: Construction of a knowledge graph relating structure, damage, and indicators: Based on the obtained structural nodes, abnormal state feature nodes, and safety assessment index nodes, a knowledge graph of structure-damage-index association is constructed using correlation analysis methods and combined with expert experience. Step 23: Screening of key safety assessment indicators and construction of a safety status assessment indicator system: Based on the path association strength between nodes in the knowledge graph of structure-damage-index association, safety assessment indicators that meet the preset association threshold for their impact on the structural safety status of offshore wind power equipment are selected as key safety assessment indicators, and a safety status assessment indicator system table for offshore wind power equipment structures is formed.

4. The method for assessing the safety status of offshore wind power equipment according to claim 3, characterized in that: Step 3 includes the following steps: Step 31: Determine the set of safety assessment indicators and select the optimal and worst indicators: A set of safety assessment indicators is constructed based on the aforementioned offshore wind power equipment structural safety status assessment index system table. : （1） Based on expert experience and engineering practice, from the aforementioned set of safety assessment indicators The indicator that has the greatest impact on the overall safety status of the structure is selected as the optimal indicator. The index with the least impact on the overall structural safety status is selected as the worst-case index. ; Step 32: Construct a comparison vector of the importance of the best and worst indicators relative to other indicators: With the aforementioned optimal index Based on this, construct the optimal index. Importance comparison vector relative to other safety assessment indicators : （2） in, Indicates the optimal index relative to indicators The degree of importance; when hour, =1; With the worst-case indicator Based on this benchmark, construct the remaining security assessment indicators relative to the worst-case indicator. Importance comparison vector : （3） in, Indicators Compared to the worst-case indicator The degree of importance; when hour, =1; in, and The value range is 1 to 9, and the specific meanings of the values ​​are as follows: When the value is 1, it indicates that they have the same priority. When the value is 2, it indicates that the priority is between 1 and 3; When the value is 3, it indicates medium priority; When the value is 4, it indicates that the priority is between 3 and 5; When the value is 5, it indicates priority; When the value is 6, it indicates that the priority is between 5 and 7; When the value is 7, it indicates very high priority; When the value is 8, it indicates that the priority is between 7 and 9; When the value is 9, it indicates the highest priority; Step 33: Construct the BWM subjective weight optimization model: Construct subjective weights for each security assessment indicator. for: （4） in, Indicates the first The subjective weights of each security assessment indicator to be solved. And it satisfies the normalization constraint: （5） Based on the consistency principle of BWM, construct an optimization model: （6） Make it satisfy the constraints: （7） （8） （9） in, Indicates the consistency deviation variable; Step 34: Subjective weight calculation and consistency check: Solving the aforementioned BWM subjective weight optimization model yields the subjective weight vector of the safety assessment indicators: （10） in, Indicates the first The subjective weights obtained from solving each security assessment indicator are used, and the consistency deviation values ​​obtained from the solution are used as a basis. Determine the consistency deviation value Does it meet the preset consistency threshold? （11） in, Indicates the preset consistency threshold; If the above conditions are met, the subjective weighting result is deemed to have consistent validity; otherwise, the importance comparison vector is adjusted and steps S32 to S34 are repeated.

5. The method for assessing the safety status of offshore wind power equipment according to claim 4, characterized in that: Step 4 includes the following steps: Step 41: Construct the original data matrix for the evaluation indicators: Suppose that the safety assessment index system for offshore wind power equipment structures contains n safety assessment indicators, corresponding to m assessment samples, and construct the original data matrix of the assessment indicators. （12） in, Indicates the first The evaluation sample in the first Original indicator values ​​under each safety assessment indicator; Step 42: Standardization of the evaluation index data matrix: The original evaluation index data matrix is ​​standardized to obtain a standardized evaluation index matrix: （13） The standardized evaluation index matrix is ​​then processed to make the positive indicators dimensionless: （14） The standardized evaluation index matrix is ​​then processed to make the negative indicators dimensionless: （15） in, and These represent the nth elements in the original data matrix. List the maximum and minimum values ​​of the security assessment indicators; Step 43: Calculate the comparative strength of each safety assessment indicator: For each safety assessment indicator in the standardized assessment indicator matrix, its comparative strength is calculated using the standard deviation: （16） in, （17） Step 44: Calculate the correlation matrix between the indicators: Based on the standardized indicator matrix, the correlation coefficients between the various safety assessment indicators are calculated, and an indicator correlation matrix is ​​constructed: （18） Among them, the The first security assessment indicator and the first The formula for calculating the correlation coefficient between the safety assessment indicators is as follows: （19） Step 45: Calculate the amount of information in the indicators: Based on the comparative strength of each safety assessment indicator and the conflict between the indicators, the calculation of the first... The total amount of information contained in each security assessment indicator: （20） in, Indicates the first The comprehensive amount of information contained in each security assessment indicator; Step 46: Determine the objective weights: The overall information content of each safety assessment indicator is normalized to obtain the objective weight of each safety assessment indicator: （21） in, Indicates the first The objective weights corresponding to each security assessment indicator; Step 47: Construct the objective weight vector: Construct an objective weight vector based on the objective weights of each obtained security assessment indicator: （22） in, This represents the objective weight vector of the safety assessment indicators.

6. The method for assessing the safety status of offshore wind power equipment according to claim 5, characterized in that: Step 5 includes the following steps: Step 51: Construct a game theory combined weight model: Based on the subjective weight vector and the objective weight vector, construct a comprehensive weight vector in the form of a linear combination: （23） in: The combination coefficients are to be determined, and the constraints must be met. （24） Step 52: Construct a minimum deviation game optimization model: （25） in, , ; Represents the vector norm; Represents the combination coefficients. ; Step 53: Solve for the game theory combination coefficients: Substituting the comprehensive weight vector into the minimum deviation game optimization model, we obtain information about the combination coefficients. Optimization solution model: （26） The constraints are satisfied: （27） For the combined coefficients The optimal solution model is used to solve the problem and obtain the optimal combination coefficients. and ; Step 54: Determine the comprehensive weight vector: right and Normalization is performed: （28） （28） Substitute the normalized weight coefficients into the comprehensive weight vector to obtain the final comprehensive weight: （29） This leads to the comprehensive weight vector of the structural safety assessment indicators for offshore wind power equipment: （30） in, , Indicates the first The overall weight of each security assessment indicator.

7. The method for assessing the safety status of offshore wind power equipment according to claim 6, characterized in that: Step 6 includes the following steps: Step 61: Construct a standard state reference interval table for security levels and classify security levels: A standard state reference interval table for safety levels is constructed, and based on the degree of change in structural state response characteristics and its impact on the safe operation of the structure, the safety status of offshore wind power equipment is divided into four levels: I, II, III, and IV, corresponding to "good condition", "relatively good condition", "poor condition" and "dangerous condition". Step 62: Construct standard state reference vectors for each security level: Based on structural design specifications, operation control requirements, and historical operation statistics, a corresponding standard state reference vector is constructed for each safety level. （31） in, Indicates the first Under the first security level The standard state characteristic values ​​corresponding to each safety assessment indicator; the values ​​of each component of the standard state reference vector are determined according to the state reference interval of the corresponding safety level in the standard state reference interval table of the safety level; Step 63: Construct a multi-index state feature vector of the current state of the offshore wind power equipment structure: Based on the safety assessment data collected under the current operating conditions, and after standardization according to a unified dimensionless rule, a multi-index state feature vector corresponding to the current state of the offshore wind power equipment structure is constructed: （32） in, This indicates the current state of the offshore wind power equipment structure. The status characteristic values ​​corresponding to each security assessment indicator; Step 64: Construct a weighted state distance metric model: Based on the comprehensive weight vector The current status and first phase of offshore wind power equipment structure construction Weighted state distance metric model between security levels: （33） The following conditions must be met: （34） Step 65: Calculate the state distance between the current state of the offshore wind power equipment structure and each safety level: Based on the weighted state distance metric model, the state distances between the current state of the offshore wind power equipment structure and each safety level are calculated to obtain a set of state distances. : （35） in: Indicates the current state of the offshore wind power equipment structure and the first Distance values ​​between standard states of each security level; Step 66: Determine the overall safety level of offshore wind power equipment structure based on the minimum state distance criterion. The state distance set is analyzed based on the minimum state distance criterion. Each element is compared to determine the overall structural safety level: （36） in, This indicates the overall safety level assessment result corresponding to the current operating status of the offshore wind power equipment structure. Step 67: Output the structural safety assessment results: The overall safety level of the offshore wind power equipment structure will be determined. The corresponding state distance calculation results are used as the final output of the structural safety status assessment of offshore wind power equipment, and are used for structural safety early warning, operation status assessment and operation and maintenance decision support.

8. The method for assessing the safety status of offshore wind power equipment according to claim 7, characterized in that: The standard state reference interval table for the security level includes: The four levels are: I, II, III, and IV. The four levels correspond to the status descriptions of "Good Status", "Fair Status", "Poor Status" and "Dangerous Status". Safety indicators include vertical deformation response, horizontal displacement response, attitude deviation characteristics, continuity anomaly characteristics, and vibration response change characteristics; Each safety indicator corresponds to four levels, meanings of which are: within the reference range of the baseline state, deviating from the baseline state but not exceeding the allowable reference range, exceeding the allowable reference range and showing a continuous increasing trend, and significantly deviating from the baseline state and exceeding the safety control threshold. The baseline state reference range is obtained by analyzing the safety status response index data collected during the initial commissioning or historical stable operation phase of offshore wind power equipment and the statistical distribution characteristics of the corresponding index data. The allowable reference range is determined by expanding the baseline state reference range based on structural design parameters, allowable ranges in specifications, and operational experience. The safety control threshold is set according to the structural design safety requirements or operational control requirements and is used to distinguish between acceptable and dangerous structural states.

9. The method for assessing the safety status of offshore wind power equipment according to claim 8, characterized in that: Offshore wind power equipment safety status is classified into four levels: I, II, III, and IV. The classification criteria are as follows: Level I indicates that the overall structural condition is within the allowable range of the design conditions, the state response of each structural unit is stable, and the superstructure and pile foundation structure meet the requirements for long-term safe service, and no structural treatment measures are required. Level II indicates that the overall structural condition is basically within the design allowable range, with slight abnormalities in the condition response of individual structural units, but without substantial impact on the overall load-bearing capacity. The structure can continue to be in service, but operational monitoring should be strengthened. Level III indicates that the state response of key structural units deviates from the design reference range, the structural load-bearing capacity shows a significant downward trend, which has an adverse impact on operational safety, and targeted maintenance or operation control measures are required. Level IV indicates that the overall structural condition significantly exceeds the design allowable range, key structural units have significant abnormal response or failure risk, and do not meet the requirements for safe operation. Structural treatment or shutdown measures should be taken in a timely manner.

10. The method for assessing the safety status of offshore wind power equipment according to claim 3, characterized in that: The safety status assessment index system table for offshore wind power equipment structures includes structural units, primary indicators, and secondary safety assessment indicators: The structural unit includes: pile-bearing foundation structure, load-bearing cylindrical structure, and superstructure functional components; Among them, the primary indicators corresponding to pile-bearing foundation structures include: geometric state response and structural integrity state; The primary indicators for load-bearing cylindrical structures include: overall deformation state and local deformation characteristics; The primary indicators corresponding to the upper functional components include: dynamic response characteristics and operational status characteristics; Among them, the secondary safety assessment indicators corresponding to the geometric state response include: the vertical deformation response of the foundation and the horizontal displacement response of the foundation; The secondary safety assessment indicators corresponding to the structural integrity status include: pile-soil interaction stiffness variation characteristics and overall foundation attitude offset characteristics; The secondary safety assessment indicators corresponding to the overall deformation state include: the axial deformation response of the bearing cylinder and the lateral displacement response of the bearing cylinder; The secondary safety assessment indicators corresponding to local state characteristics include: abnormal characteristics of local continuity of the load-bearing cylinder and stiffness degradation characteristics of the cylinder connection parts; The secondary safety assessment indicators corresponding to the dynamic response characteristics include: the vibration response change characteristics of the superstructure; The secondary safety assessment indicators corresponding to the operational status characteristics include: the operational stability change characteristics of the superstructure.

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