Method for calculating and optimizing steel consumption demand of offshore photovoltaic bracket

Abstract

The invention discloses a method for calculating and optimizing the steel consumption demand of an offshore photovoltaic support, relates to the technical field of offshore photovoltaic supports, and aims to solve the problem that the steel consumption of the support is not accurately obtained when the offshore photovoltaic support is installed. According to the method, the performance of the offshore photovoltaic support under different working conditions can be comprehensively evaluated through multiple finite element analysis methods, the bearing capacity and fatigue life of the support under extreme conditions can be evaluated through buckling analysis and fatigue analysis, and therefore the safety problems such as buckling instability or fatigue damage of the support in the using process are avoided, and the service life of the support is prolonged. By accurately analyzing the performance of the support under different working conditions, the using amount of steel can be more reasonably determined, cost waste caused by excessive design is avoided, material attributes in a geometric model are set according to material data, the mechanical performance of a support material can be truly reflected, the geometric model is divided into hexahedron elements, and the performance of the support is improved. And the deformation and stress distribution conditions of the structure under the load effect can be better captured.

Description

Technical Field

[0001] The present invention relates to the technical field of offshore photovoltaic brackets, and in particular to a method for optimizing calculation of steel demand for offshore photovoltaic brackets. Background Art

[0002] Offshore photovoltaic support refers to the structural system used to support and fix photovoltaic components (such as solar panels) in the marine environment.

[0003] The patent application with publication number CN118094665A discloses a method for optimizing the reduction of photovoltaic support structure. The method mainly optimizes the purlins, diagonal beams, columns, and diagonal braces in the first round, optimizes the layout of connectors and columns in the second round, and optimizes the photovoltaic direct structure by adjusting the value of the structural importance coefficient and thus adjusting the calculated load in the third round. The optimization is hierarchical, step-by-step, and focused. The optimized photovoltaic support column layout, force structure, and component selection are more reasonable. While satisfying the support force structure, the amount of steel used in the photovoltaic support can be controlled to the maximum extent, thereby saving the material cost of the photovoltaic support. Although the above patent solves the problem of reduction optimization, the following problems still exist in actual operation: 1. The material data and offshore data of the photovoltaic bracket were not accurately obtained, resulting in inaccurate steel quantity of the photovoltaic bracket.

[0004] 2. Failure to accurately construct a model based on the photovoltaic bracket data and marine environment data resulted in uneven stress distribution after the photovoltaic bracket was installed.

[0005] 3. The photovoltaic bracket installation process was not simulated, making it impossible to understand the performance of the photovoltaic bracket installation under different conditions, resulting in inaccurate acquisition of the photovoltaic bracket steel quantity. Summary of the invention

[0006] The purpose of the present invention is to provide a method for optimizing the calculation of the steel demand for offshore photovoltaic brackets. Through a variety of finite element analysis methods, the performance of offshore photovoltaic brackets under different working conditions can be comprehensively evaluated. Through buckling analysis and fatigue analysis, the bearing capacity and fatigue life of the bracket under extreme conditions can be evaluated, thereby avoiding safety problems such as buckling instability or fatigue damage of the bracket during use. By accurately analyzing the performance of the bracket under different working conditions, the amount of steel can be determined more reasonably to avoid cost waste caused by over-design. The material properties in the geometric model are set according to the material data, which can truly reflect the mechanical properties of the bracket material. The geometric model is divided into hexahedral elements, which can better capture the deformation and stress distribution of the structure under load, and can solve the problems in the prior art.

[0007] To achieve the above object, the present invention provides the following technical solutions: The method for calculating and optimizing the steel demand for offshore photovoltaic brackets includes the following steps: S1: Photovoltaic support data confirmation: confirm the basic data and load data of the photovoltaic support, and obtain the support data after confirmation, wherein the basic data and load data of the photovoltaic support are retrieved from the database; S2: Confirmation of offshore environmental data: Confirm the offshore location where the photovoltaic bracket is installed, and confirm the offshore environmental data according to the offshore location, and obtain the environmental data after confirmation; S3: Construction of simulation structure model: The structure model of offshore photovoltaic support installation is constructed according to the support data and environmental data, and the simulation structure model is obtained after the construction; S4: Structural model analysis: Perform finite element analysis on the simulated structural model, obtain the load data of the bracket in the simulated structural model, optimize the steel usage based on the finite element analysis and load data, and obtain the steel quantity data of the offshore photovoltaic bracket after optimization; S5: Steel quantity data output: The demand is summarized and optimized based on the steel quantity data of the offshore photovoltaic bracket, and after summary and optimization, it is transmitted to the display terminal for display.

[0008] Preferably, the basic data and load data of the photovoltaic support are confirmed in S1, including: The photovoltaic support is made of steel pipe columns and steel trusses; The steel pipe column adopts a variable diameter steel pipe column, with a diameter of 1m below the mud surface and a wall thickness of 10-20mm, and a diameter of 0.4m above the mud surface and a wall thickness of 10-20mm; The basic data of photovoltaic brackets include size data, material data, connection method and surface treatment data; Among them, the dimensional data are the structural dimensions and floating body dimensions of the bracket; the material data are the material type, specifications and mechanical properties of the bracket; the connection methods are bolt connection and welding connection; the surface treatment data are the anti-corrosion treatment and anti-corrosion layer thickness data of the bracket.

[0009] Preferably, the basic data and load data of the photovoltaic support are confirmed in S1, and further includes: The load data of photovoltaic bracket includes constant load, live load, special load and other loads; Dead loads include deadweight loads and static loads; live loads include wind loads, wave loads, flow loads and tidal loads; special loads include sea ice loads, earthquake loads and temperature loads; other loads include biological attachment loads and drifting objects loads; The acquired load data and basic data are marked as support data.

[0010] Preferably, the sea area location where the photovoltaic bracket is installed in S2 is confirmed, and the marine environment data is confirmed according to the sea area location, including: Obtain the photovoltaic bracket installation position from the database, wherein the photovoltaic bracket installation position is located by GPS; Use sonar to conduct topographic mapping of the installation location and perform simulated installation verification, and confirm the installation location of the photovoltaic bracket based on the verification results.

[0011] Preferably, the sea area location where the photovoltaic bracket is installed in S2 is confirmed, and the marine environment data is confirmed according to the sea area location, further comprising: Confirm offshore environmental data according to the installation location of the photovoltaic bracket; Marine environmental data include meteorological data, oceanographic data, ecological data, engineering-related data, geological and topographic data; Among them, marine environmental data are obtained using satellite remote sensing technology; And mark the marine environmental data as environmental data.

[0012] Preferably, the construction of a structural model for installing an offshore photovoltaic support according to the support data and environmental data in S3 includes: Confirm the bracket data and environmental data, and perform data preprocessing after confirmation; After data preprocessing, a geometric model is established according to the stent dimensions in the stent data; Set material properties in the geometric model according to material data; The connection conditions of the geometric model are defined based on geological, topographic data and connection methods.

[0013] Preferably, preprocessing the environmental data includes: Monitor the invalid values ​​of the collected environmental data and obtain the data collection time corresponding to the invalid data; Extracting the valid data that is closest to and adjacent to the data collection time corresponding to the invalid data and corresponds to the data type of the invalid data; Acquire replacement data corresponding to the invalid data by using the valid data corresponding to the data type of the invalid data that is closest to and adjacent to the data collection time; The replacement data corresponding to the invalid data is obtained by the following formula:

[0014] Among them, X t Indicates the replacement data corresponding to the invalid data; n indicates the number of valid data collected before and after the data collection time corresponding to the data type of the invalid data, and the value range of the number of valid data collected is 3-5; X 01The data type indicating invalid data corresponds to the valid data value collected earlier in the two adjacent data; X 02 The data type indicating invalid data corresponds to the data value of the later data collected in the two adjacent data; X 01i The data type representing invalid data corresponds to the data value of the ith valid data corresponding to the valid data collected earlier in the two adjacent data before and after, and the data value of the i-th valid data corresponding to the n consecutive collected data before; X 02i The data type representing invalid data corresponds to the data value of the ith valid data corresponding to the data collected at the later time in the two adjacent data before and after; The invalid data is replaced by replacement data corresponding to the invalid data.

[0015] Preferably, performing data preprocessing on the environmental data further includes: Monitor the missing data of the collected environmental data and obtain the data collection time corresponding to the missing data; Extract the valid data closest to the data collection time corresponding to the missing data; Acquire first replacement data corresponding to the missing data using the nearest valid data before and after the data collection time corresponding to the missing data; The first replacement data corresponding to the missing data is obtained by the following formula:

[0016] Among them, W t01 represents the first replacement data corresponding to the missing data; m represents the number of valid data collected before and after the data collection time corresponding to the two adjacent data before and after the data type of the missing data, and the value range of the number of valid data collected is 3-5; W 01 The data type indicating missing data corresponds to the valid data value collected earlier in the two adjacent data. 02 The data type indicating missing data corresponds to the data value of the later data collected in the two adjacent data. 01i The data type representing missing data corresponds to the data value of the i-th valid data corresponding to the valid data collected earlier in the two adjacent data before and after, and the m consecutive data collected earlier in time; W 02i The data type representing missing data corresponds to the data value of the i-th valid data corresponding to the data collected at the later time in the two adjacent data before and after; Using all valid data in the environmental data corresponding to the data type of the missing data to compensate and adjust the first replacement data, to obtain second replacement data; The second replacement data corresponding to the missing data is obtained by the following formula:

[0017] Among them, W t02 W represents the second replacement data corresponding to the missing data; t01 represents the first replacement data corresponding to the missing data; W 01 The data type indicating missing data corresponds to the valid data value collected earlier in the two adjacent data. 02 The data type of the missing data corresponds to the data value of the later data collected in the two adjacent data; k represents the total number of all valid data corresponding to the data type of the missing data; W i represents the data value of the i-th valid data among all valid data corresponding to the data type of the missing data; z Represents the data middle value of all valid data corresponding to the data type of the missing data; The missing data is replaced by second replacement data corresponding to the missing data.

[0018] Preferably, the construction of a structural model for installing an offshore photovoltaic bracket according to bracket data and environmental data in S3 further includes: After the connection conditions of the geometric model are defined, loads are applied; Among them, the geometric model is meshed into hexahedral elements; After the model mesh is divided, the load is applied to the model mesh by the distributed load application method; After the load is applied, the simulated structural model of the offshore photovoltaic support installation is obtained.

[0019] Preferably, in S4, the simulated structural model is subjected to finite element analysis, and the load data of the bracket in the simulated structural model is obtained, and the steel usage is optimized according to the finite element analysis and the load data, including: The simulated structural model is subjected to static analysis, modal analysis, buckling analysis and fatigue analysis using finite element software; Among them, the static analysis is to calculate the static balance data according to the connection and load data between the bracket and the floating body in the simulated structural model, and obtain the displacement, stress, strain, reaction force and deformation shape data of the simulated structural model after calculation; Modal analysis is to perform operation analysis based on the connection between the bracket and the floating body in the simulated structural model. After the operation analysis, the natural frequency, vibration mode, damping ratio and mass participation coefficient of the simulated structural model are obtained. Buckling analysis is to perform operation analysis based on the connection and load data between the bracket and the floating body in the simulated structural model, and after the operation analysis, the buckling load factor, buckling mode, critical stress and buckling load of the simulated structural model are obtained; Fatigue analysis is performed based on the static analysis results of the simulated structural model. After fatigue analysis, the stress range, stress amplitude, average stress, fatigue life, damage accumulation, fatigue safety factor and SN curve of the simulated structural model are obtained.

[0020] Preferably, in S4, the simulated structural model is subjected to finite element analysis, and the load data of the bracket in the simulated structural model is obtained, and the steel usage is optimized according to the finite element analysis and the load data, and further includes: Determine whether the types of steel pipe columns and steel trusses meet the standards based on the load data and finite element analysis data. If they do not meet the standards, reselect the steel pipe columns and steel trusses. According to the finite element analysis data, the cross-sectional dimensions of the steel pipe columns and steel trusses are adjusted, and the structural stiffness is adjusted after the cross-sectional dimensions are adjusted; After the structural stiffness adjustment is completed, the support optimization and connection design are carried out according to the load data; After the support optimization and connection design are completed, the volume data of the steel pipe column and steel truss are confirmed, and the density of the steel pipe column and steel truss is multiplied by the volume data to obtain the optimized amount of steel; At the same time, the optimized dosage includes cutting loss and welding joint loss; The optimized usage of steel is marked as offshore photovoltaic support steel quantity data.

[0021] Preferably, in S5, the demand is summarized and optimized according to the steel quantity data of the offshore photovoltaic support, and the summary and optimization are transmitted to the display terminal for display, including: The steel quantity demand data, bearing capacity data and constructed model data in the offshore photovoltaic bracket steel quantity data are summarized respectively; After the aggregation, text data and image data are generated, and the generated text data and image data are converted into visual data; After visualization conversion, it is transmitted to the display terminal for display.

[0022] Compared with the prior art, the present invention has the following beneficial effects: 1. The method for calculating and optimizing the steel demand for offshore photovoltaic brackets provided by the present invention fully considers various load conditions, including special loads under extreme conditions, such as sea ice loads, earthquake loads, etc., can improve the risk resistance of the bracket and reduce damage caused by natural disasters and the like, and comprehensively considers various environmental factors such as meteorological data, ocean data, ecological data, engineering-related data, geological and topographic data, etc. These data are important bases for evaluating the design and material requirements of photovoltaic brackets.

[0023] 2. The method for optimizing the calculation of the steel demand for offshore photovoltaic brackets provided by the present invention sets the material properties in the geometric model according to the material data, can truly reflect the mechanical properties of the bracket material, and divides the geometric model into hexahedral elements. This grid division method can not only improve the calculation efficiency, but also better capture the deformation and stress distribution of the structure under load, thereby improving the accuracy of the simulation results.

[0024] 3. The method for optimizing calculation of steel demand for offshore photovoltaic brackets provided by the present invention can comprehensively evaluate the performance of offshore photovoltaic brackets under different working conditions through a variety of finite element analysis methods. Through buckling analysis and fatigue analysis, the bearing capacity and fatigue life of the bracket under extreme conditions can be evaluated, thereby avoiding safety problems such as buckling instability or fatigue damage of the bracket during use. By accurately analyzing the performance of the bracket under different working conditions, the amount of steel can be determined more reasonably, avoiding cost waste caused by excessive design, and ensuring the safety and stability of the bracket. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 A schematic diagram of the calculation steps of the steel quantity demand for the offshore photovoltaic support of the present invention; Figure 2 It is a schematic diagram of the calculation process of the steel demand for the offshore photovoltaic support of the present invention. DETAILED DESCRIPTION

[0026] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] In order to solve the problem that the existing technology does not accurately obtain the material data and offshore data of the photovoltaic bracket, resulting in inaccurate steel quantity acquisition of the photovoltaic bracket, please refer to Figure 1 and Figure 2 , this embodiment provides the following technical solutions: The method for calculating and optimizing the steel demand for offshore photovoltaic brackets includes the following steps: S1: Photovoltaic support data confirmation: confirm the basic data and load data of the photovoltaic support, and obtain the support data after confirmation, wherein the basic data and load data of the photovoltaic support are retrieved from the database; Among them, by optimizing the design to reduce the use of steel, energy consumption and carbon emissions; S2: Confirmation of offshore environmental data: Confirm the offshore location where the photovoltaic bracket is installed, and confirm the offshore environmental data according to the offshore location, and obtain the environmental data after confirmation; Among them, based on accurate understanding of the installation location of the photovoltaic bracket and comprehensive grasp of the offshore environmental data, the steel demand for the photovoltaic bracket can be calculated more accurately; S3: Construction of simulation structure model: The structure model of offshore photovoltaic support installation is constructed according to the support data and environmental data, and the simulation structure model is obtained after the construction; Among them, based on the constructed simulation structural model, further structural analysis and optimization can be carried out to reduce unnecessary steel usage; S4: Structural model analysis: Perform finite element analysis on the simulated structural model, obtain the load data of the bracket in the simulated structural model, optimize the steel usage based on the finite element analysis and load data, and obtain the steel quantity data of the offshore photovoltaic bracket after optimization; Among them, by accurately analyzing the performance of the bracket under different working conditions, the amount of steel can be determined more reasonably; S5: Steel quantity data output: According to the steel quantity data of offshore photovoltaic brackets, demand is summarized and optimized, and after summary and optimization, it is transmitted to the display terminal for display; Among them, publicly displaying key data such as steel demand in a visual form will help enhance the transparency and credibility of the project.

[0028] Confirm the basic data and load data of the photovoltaic bracket in S1, including: The photovoltaic support is made of steel pipe columns and steel trusses; The steel pipe column adopts a variable diameter steel pipe column, with a diameter of 1m below the mud surface and a wall thickness of 10-20mm, and a diameter of 0.4m above the mud surface and a wall thickness of 10-20mm; The basic data of photovoltaic brackets include size data, material data, connection method and surface treatment data; Among them, the dimensional data are the structural dimensions and floating body dimensions of the bracket; the material data are the material type, specifications and mechanical properties of the bracket; the connection methods are bolt connection and welding connection; the surface treatment data are the anti-corrosion treatment and anti-corrosion layer thickness data of the bracket.

[0029] The load data of photovoltaic bracket includes constant load, live load, special load and other loads; Dead loads include deadweight loads and static loads; live loads include wind loads, wave loads, flow loads and tidal loads; special loads include sea ice loads, earthquake loads and temperature loads; other loads include biological attachment loads and drifting objects loads; The acquired load data and basic data are marked as support data.

[0030] Specifically, by confirming the dimensional data of the support in detail (including structural dimensions and floating body dimensions), it can be ensured that the data used in the calculation is accurate, thereby improving the accuracy and reliability of the entire calculation process. The accuracy of material data (such as material type, specifications and mechanical properties) directly affects the bearing capacity and safety of the support. Detailed confirmation of these data can avoid safety problems caused by improper material selection or incorrect specifications. Understanding the connection method and surface treatment data will help optimize the support structure in the design stage and select appropriate connection methods and anti-corrosion treatments to improve the stability and durability of the support. Accurate load data (including dead loads, live loads, special loads and other loads) provides comprehensive and accurate load conditions for the design, which helps to design a support structure that is both economical and safe. Fully considering various load conditions, including special loads under extreme conditions, such as sea ice loads, earthquake loads, etc., can improve the risk resistance of the support and reduce damage caused by natural disasters and other reasons. By optimizing the design, reducing the use of steel, reducing energy consumption and carbon emissions, it will help achieve green building and sustainable development goals.

[0031] Confirm the sea area where the photovoltaic bracket will be installed in S2, and confirm the marine environmental data according to the sea area location, including: Obtain the photovoltaic bracket installation position from the database, wherein the photovoltaic bracket installation position is located by GPS; Use sonar to conduct topographic mapping of the installation location and perform simulated installation verification, and confirm the installation location of the photovoltaic bracket based on the verification results.

[0032] Confirm offshore environmental data according to the installation location of the photovoltaic bracket; Marine environmental data include meteorological data, oceanographic data, ecological data, engineering-related data, geological and topographic data; Among them, marine environmental data are obtained using satellite remote sensing technology; And mark the marine environmental data as environmental data.

[0033] Specifically, using GPS to accurately locate the installation position of the photovoltaic bracket ensures the accuracy of the installation position and avoids subsequent problems caused by position errors. Using sonar to map the installation position can provide a more detailed understanding of the seabed topography, which is crucial for the stable installation of the photovoltaic bracket. Through simulated installation verification, the rationality and safety of the installation position are further ensured. Comprehensive consideration is given to various environmental factors such as meteorological data, ocean data, ecological data, engineering-related data, geological and topographic data. These data are important bases for evaluating the design and material requirements of photovoltaic brackets. Based on an accurate understanding of the installation position of the photovoltaic bracket and a comprehensive grasp of the offshore environmental data, the steel demand for the photovoltaic bracket can be more accurately calculated. This helps to avoid material waste and cost overruns and improve the economic benefits of the project.

[0034] In order to solve the problem that the existing technology does not accurately build a model based on the data of the photovoltaic bracket and the marine environment data, resulting in uneven stress distribution after the photovoltaic bracket is installed, please refer to Figure 1 and Figure 2 , this embodiment provides the following technical solutions: The structural model of offshore photovoltaic bracket installation is constructed according to bracket data and environmental data in S3, including: Confirm the bracket data and environmental data, and perform data preprocessing after confirmation; After data preprocessing, a geometric model is established according to the stent dimensions in the stent data; Set material properties in the geometric model according to material data; The connection conditions of the geometric model are defined based on geological, topographic data and connection methods.

[0035] After the connection conditions of the geometric model are defined, loads are applied; Among them, the geometric model is meshed into hexahedral elements; After the model mesh is divided, the load is applied to the model mesh by the distributed load application method; After the load is applied, the simulated structural model of the offshore photovoltaic support installation is obtained.

[0036] Specifically, by confirming and preprocessing the bracket data and environmental data, the accuracy and completeness of the model input data are ensured. This helps to reduce the deviation of simulation results caused by data errors, thereby improving the accuracy of the entire simulation process. The accurate geometric model is established based on the bracket size, which can accurately reflect the actual shape and size of the photovoltaic bracket. This refined modeling method is crucial for subsequent structural analysis and optimization. Setting the material properties in the geometric model according to the material data can truly reflect the mechanical properties of the bracket material (such as elastic modulus, yield strength, etc.), which plays a key role in simulating the response of the structure under load. The geometric model is divided into hexahedral elements. This grid division method can not only improve the calculation efficiency, but also better capture the deformation and stress distribution of the structure under load, thereby improving the accuracy of the simulation results. The load is accurately applied to the model grid through the distributed load application method, which can simulate the various loads (such as wind load, wave load, etc.) on the photovoltaic bracket in the actual environment, ensuring the accuracy of the simulation results. Based on the constructed simulation structure model, further structural analysis and optimization can be carried out to reduce unnecessary steel use and reduce construction costs. For example, by simulating the structural response under different steel usage, the steel configuration scheme that meets safety requirements and has the lowest cost can be found.

[0037] Specifically, data preprocessing of environmental data includes: Monitor the invalid values ​​of the collected environmental data and obtain the data collection time corresponding to the invalid data; Extracting the valid data that is closest to and adjacent to the data collection time corresponding to the invalid data and corresponds to the data type of the invalid data; Acquire replacement data corresponding to the invalid data by using the valid data corresponding to the data type of the invalid data that is closest to and adjacent to the data collection time; The replacement data corresponding to the invalid data is obtained by the following formula:

[0038] Among them, X t Indicates the replacement data corresponding to the invalid data; n indicates the number of valid data collected before and after the data collection time corresponding to the data type of the invalid data, and the value range of the number of valid data collected is 3-5; X 01 The data type indicating invalid data corresponds to the valid data value collected earlier in the two adjacent data; X 02 The data type indicating invalid data corresponds to the data value of the later data collected in the adjacent two data; X 01iThe data type representing invalid data corresponds to the data value of the ith valid data corresponding to the valid data collected earlier in the two adjacent data before and after, and the data value of the i-th valid data corresponding to the n consecutive collected data before; X 02i The data type representing invalid data corresponds to the data value of the ith valid data corresponding to the data collected at the later time in the two adjacent data before and after; The invalid data is replaced by replacement data corresponding to the invalid data.

[0039] The technical effect of the above technical solution is: by monitoring the invalid values ​​of the collected environmental data and identifying the invalid data and its corresponding data collection time, the abnormal or invalid data generated due to various reasons (such as sensor failure, data transmission error, etc.) can be effectively eliminated or replaced. This significantly improves the accuracy and reliability of the data and provides a more solid foundation for subsequent data analysis and decision-making.

[0040] The above technical solution maintains the continuity of the data by extracting the valid data corresponding to the invalid data type that is closest to the data collection time corresponding to the invalid data, and using this data to estimate the replacement value of the invalid data. This is particularly important for application scenarios that require continuous data support, such as time series analysis and trend forecasting. The replacement data calculation formula proposed in the solution takes into account the information of multiple valid data points before and after the invalid data (n continuous times of collected data before and n continuous times of collected data after), and allows the value range of the number of valid data collection n to be adjusted (3-5) according to the data type and actual situation. This flexibility enables the replacement data to more accurately reflect the actual situation of the invalid data point and reduce the deviation caused by a single data point.

[0041] The entire data preprocessing process, including the monitoring of invalid data, the extraction of valid data, the calculation of replacement data, and the replacement of invalid data, can all be automated through programming. This not only improves processing efficiency, but also reduces errors caused by human intervention, making the data preprocessing process more intelligent and standardized. Since the collection and analysis of environmental data are widely used in many fields such as environmental monitoring, climate change research, agricultural production, and urban planning, this technical solution has a wide range of applicability. By improving data quality and continuity, more accurate and reliable data support can be provided for these fields, promoting the development and progress of related fields.

[0042] In summary, this technical solution effectively improves the quality and continuity of environmental data through a series of scientific and reasonable data preprocessing steps, providing strong data support for research and applications in related fields.

[0043] Specifically, the data preprocessing of the environmental data also includes: Monitor the missing data of the collected environmental data and obtain the data collection time corresponding to the missing data; Extract the valid data closest to the data collection time corresponding to the missing data; Acquire first replacement data corresponding to the missing data using the nearest valid data before and after the data collection time corresponding to the missing data; The first replacement data corresponding to the missing data is obtained by the following formula:

[0044] Among them, W t01 represents the first replacement data corresponding to the missing data; m represents the number of valid data collected before and after the data collection time corresponding to the two adjacent data before and after the data type of the missing data, and the value range of the number of valid data collected is 3-5; W 01 The data type indicating missing data corresponds to the valid data value collected earlier in the two adjacent data. 02 The data type indicating missing data corresponds to the data value of the later data collected in the two adjacent data. 01i The data type representing missing data corresponds to the data value of the i-th valid data corresponding to the valid data collected earlier in the two adjacent data before and after, and the m consecutive data collected earlier in time; W 02i The data type representing missing data corresponds to the data value of the i-th valid data corresponding to the data collected at the later time in the two adjacent data before and after; Using all valid data in the environmental data corresponding to the data type of the missing data to compensate and adjust the first replacement data, to obtain second replacement data; The second replacement data corresponding to the missing data is obtained by the following formula:

[0045] Among them, W t02 W represents the second replacement data corresponding to the missing data; t01 represents the first replacement data corresponding to the missing data; W 01 The data type indicating missing data corresponds to the valid data value collected earlier in the two adjacent data. 02 The data type of the missing data corresponds to the data value of the later data collected in the two adjacent data; k represents the total number of all valid data corresponding to the data type of the missing data; W irepresents the data value of the i-th valid data among all valid data corresponding to the data type of the missing data; z Represents the data middle value of all valid data corresponding to the data type of the missing data; The missing data is replaced by second replacement data corresponding to the missing data.

[0046] The technical effect of the above technical solution is: the above technical solution not only considers the processing of invalid data, but also adds the monitoring and processing of missing data, thereby realizing comprehensive preprocessing of environmental data. This ensures the integrity and availability of the data set, and provides a more solid foundation for subsequent data analysis and decision-making. By extracting the nearest valid data before and after the data collection time corresponding to the missing data, and using these data to calculate the first replacement data through the above formula, the above technical solution can estimate the value of the missing data more accurately. In addition, by further using all valid data corresponding to the data type of the missing data to compensate and adjust the first replacement data, and obtaining the second replacement data, the accuracy of the replacement data can be further improved. This double replacement strategy significantly reduces the deviation caused by missing data. At the same time, the value range of the number of valid data collection m and k in the above scheme is very flexible and can be adjusted according to the data type and actual situation. This flexibility enables the replacement data to more accurately reflect the actual situation of the missing data points, and improves the adaptability and accuracy of data processing. Through reasonable replacement data calculation and adjustment strategies, the above technical solution can maintain the consistency and continuity of the data. This is particularly important for application scenarios that require continuous data support, such as time series analysis and trend prediction, and helps to reduce analysis errors caused by missing or abnormal data.

[0047] The entire data preprocessing process, including the monitoring of missing data, the extraction of valid data, the calculation of replacement data and the replacement of missing data, can be automated through programming. This not only improves processing efficiency, but also reduces the errors caused by human intervention, making the data preprocessing process more intelligent and standardized. Since the collection and analysis of environmental data are widely used in many fields, such as environmental monitoring, climate change research, agricultural production, urban planning, etc., this technical solution has a wide range of applicability. By improving data quality and continuity, more accurate and reliable data support can be provided for these fields, promoting the development and progress of related fields.

[0048] In summary, this technical solution effectively improves the quality and integrity of environmental data through a series of scientific and reasonable data preprocessing steps, providing strong data support for research and applications in related fields.

[0049] In order to solve the problem that the photovoltaic bracket installation process is not simulated in the existing technology, and the performance of the photovoltaic bracket installation under different conditions cannot be understood, resulting in inaccurate photovoltaic bracket steel quantity acquisition, please refer to Figure 1 and Figure 2 , this embodiment provides the following technical solutions: Finite element analysis is performed on the simulated structural model in S4, and the load data of the bracket in the simulated structural model is obtained. The steel usage is optimized based on the finite element analysis and load data, including: The simulated structural model is subjected to static analysis, modal analysis, buckling analysis and fatigue analysis using finite element software; Among them, the static analysis is to calculate the static balance data according to the connection and load data between the bracket and the floating body in the simulated structural model, and obtain the displacement, stress, strain, reaction force and deformation shape data of the simulated structural model after calculation; Modal analysis is to perform operation analysis based on the connection between the bracket and the floating body in the simulated structural model. After the operation analysis, the natural frequency, vibration mode, damping ratio and mass participation coefficient of the simulated structural model are obtained. Buckling analysis is to perform operation analysis based on the connection and load data between the bracket and the floating body in the simulated structural model, and after the operation analysis, the buckling load factor, buckling mode, critical stress and buckling load of the simulated structural model are obtained; Fatigue analysis is performed based on the static analysis results of the simulated structural model. After fatigue analysis, the stress range, stress amplitude, average stress, fatigue life, damage accumulation, fatigue safety factor and SN curve of the simulated structural model are obtained.

[0050] Specifically, through a variety of finite element analysis methods (static analysis, modal analysis, buckling analysis and fatigue analysis), the performance of offshore photovoltaic brackets under different working conditions can be comprehensively evaluated. These analyses not only consider the behavior of the bracket under static loads, but also consider the dynamic response (such as vibration characteristics), stability (buckling) and fatigue life under long-term use, thereby greatly improving the comprehensiveness and accuracy of the analysis. The detailed data obtained (such as displacement, stress, strain, reaction force, natural frequency, vibration mode, damping ratio, buckling load factor, critical stress, fatigue life, etc.) provide solid data support for the optimization of steel usage. These data can be directly used to evaluate the bearing capacity and safety of the bracket, and provide a scientific basis for reducing unnecessary steel use or strengthening weak areas. By accurately analyzing the performance of the bracket under different working conditions, the amount of steel can be determined more reasonably, avoiding cost waste caused by over-design, while ensuring the safety and stability of the bracket. This helps to improve the overall economy of the project. Through buckling analysis and fatigue analysis, the bearing capacity and fatigue life of the bracket under extreme conditions can be evaluated, thereby avoiding safety problems such as buckling instability or fatigue damage during the use of the bracket. This improves the overall safety and reliability of the photovoltaic bracket and extends its service life.

[0051] Determine whether the types of steel pipe columns and steel trusses meet the standards based on the load data and finite element analysis data. If they do not meet the standards, reselect the steel pipe columns and steel trusses. According to the finite element analysis data, the cross-sectional dimensions of the steel pipe columns and steel trusses are adjusted, and the structural stiffness is adjusted after the cross-sectional dimensions are adjusted; After the structural stiffness adjustment is completed, the support optimization and connection design are carried out according to the load data; After the support optimization and connection design are completed, the volume data of the steel pipe column and steel truss are confirmed, and the density of the steel pipe column and steel truss is multiplied by the volume data to obtain the optimized amount of steel; At the same time, the optimized dosage includes cutting loss and welding joint loss; The optimized usage of steel is marked as offshore photovoltaic support steel quantity data.

[0052] Specifically, by combining load data and finite element analysis data, it is possible to accurately determine whether the types of steel pipe columns and steel trusses meet the design standards, thereby ensuring the safety and stability of the structure. The adjustment of cross-sectional dimensions and structural stiffness is also based on detailed data analysis, avoiding blind design and waste of resources. It takes into account actual production losses such as cutting loss and welding joint loss, making the optimized use of steel closer to the actual situation and reducing waste. By optimizing the use of steel, resource consumption and waste generation are reduced, which is in line with the concept of sustainable development.

[0053] In S5, the demand is summarized and optimized based on the steel quantity data of offshore photovoltaic brackets, and then transmitted to the display terminal for display after summary and optimization, including: The steel quantity demand data, bearing capacity data and constructed model data in the offshore photovoltaic bracket steel quantity data are summarized respectively; After the aggregation, text data and image data are generated, and the generated text data and image data are converted into visual data; After visualization conversion, it is transmitted to the display terminal for display.

[0054] Specifically, multi-dimensional information such as steel demand data, bearing capacity data, and constructed model data are integrated and summarized to provide comprehensive and integrated information support for decision makers. By visually converting text data and image data and displaying them on the display terminal, the originally complex and abstract data becomes intuitive and easy to understand. The key data such as steel demand is publicly displayed in a visual form, which helps to enhance the transparency and credibility of the project.

[0055] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0056] While the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that many changes, modifications, substitutions and variations can be made to the embodiments without departing from the principles and spirit of the invention.

Claims

1. A method for calculating and optimizing the steel demand for offshore photovoltaic brackets, characterized in that: The steps include: S1: Photovoltaic support data confirmation: confirm the basic data and load data of the photovoltaic support, and obtain the support data after confirmation, wherein the basic data and load data of the photovoltaic support are retrieved from the database; S2: Confirmation of offshore environmental data: Confirm the offshore location where the photovoltaic bracket is installed, and confirm the offshore environmental data according to the offshore location, and obtain the environmental data after confirmation; S3: Construction of simulation structure model: The structure model of offshore photovoltaic support installation is constructed according to the support data and environmental data, and the simulation structure model is obtained after the construction; S4: Structural model analysis: Perform finite element analysis on the simulated structural model, obtain the load data of the bracket in the simulated structural model, optimize the steel usage based on the finite element analysis and load data, and obtain the steel quantity data of the offshore photovoltaic bracket after optimization; S5: Steel quantity data output: The demand is summarized and optimized based on the steel quantity data of the offshore photovoltaic bracket, and after summary and optimization, it is transmitted to the display terminal for display.

2. The method for calculating and optimizing the steel demand for offshore photovoltaic brackets according to claim 1 is characterized in that: Confirm the basic data and load data of the photovoltaic bracket in S1, including: The photovoltaic support is made of steel pipe columns and steel trusses; The steel pipe column adopts a variable diameter steel pipe column, with a diameter of 1m below the mud surface and a wall thickness of 10-20mm, and a diameter of 0.4m above the mud surface and a wall thickness of 10-20mm; The basic data of photovoltaic brackets include size data, material data, connection method and surface treatment data; Among them, the dimensional data are the structural dimensions and floating body dimensions of the bracket; the material data are the material type, specifications and mechanical properties of the bracket; the connection methods are bolt connection and welding connection; the surface treatment data are the anti-corrosion treatment and anti-corrosion layer thickness data of the bracket.

3. The method for calculating and optimizing the steel demand for offshore photovoltaic brackets according to claim 2 is characterized in that: Confirm the basic data and load data of the photovoltaic bracket in S1, including: The load data of photovoltaic bracket includes constant load, live load, special load and other loads; Dead loads include deadweight loads and static loads; live loads include wind loads, wave loads, flow loads and tidal loads; special loads include sea ice loads, earthquake loads and temperature loads; other loads include biological attachment loads and drifting objects loads; The acquired load data and basic data are marked as support data.

4. The method for calculating and optimizing the steel demand for offshore photovoltaic brackets according to claim 3 is characterized in that: Confirm the sea area where the photovoltaic bracket will be installed in S2, and confirm the marine environmental data according to the sea area location, including: Obtain the photovoltaic bracket installation position from the database, wherein the photovoltaic bracket installation position is located by GPS; Use sonar to conduct topographic mapping of the installation location and perform simulated installation verification, and confirm the installation location of the photovoltaic bracket based on the verification results.

5. The method for calculating and optimizing the steel demand for offshore photovoltaic brackets according to claim 4 is characterized in that: Confirm the sea area where the photovoltaic bracket will be installed in S2, and confirm the marine environmental data according to the sea area location, including: Confirm offshore environmental data according to the installation location of the photovoltaic bracket; Marine environmental data include meteorological data, oceanographic data, ecological data, engineering-related data, geological and topographic data; Among them, marine environmental data are obtained using satellite remote sensing technology; And mark the marine environmental data as environmental data.

6. The method for calculating and optimizing the steel demand for offshore photovoltaic brackets according to claim 5 is characterized in that: The structural model of offshore photovoltaic bracket installation is constructed according to bracket data and environmental data in S3, including: Confirm the bracket data and environmental data, and perform data preprocessing after confirmation; After data preprocessing, a geometric model is established according to the stent dimensions in the stent data; Set material properties in the geometric model according to material data; The connection conditions of the geometric model are defined based on geological, topographic data and connection methods.

7. The method for calculating and optimizing the steel demand for offshore photovoltaic brackets according to claim 6 is characterized in that: Data preprocessing of environmental data includes: Monitor the invalid values ​​of the collected environmental data and obtain the data collection time corresponding to the invalid data; Extracting the valid data that is closest to and adjacent to the data collection time corresponding to the invalid data and corresponds to the data type of the invalid data; Acquire replacement data corresponding to the invalid data by using the valid data corresponding to the data type of the invalid data that is closest to and adjacent to the data collection time; The replacement data corresponding to the invalid data is obtained by the following formula: Among them, X t Indicates the replacement data corresponding to the invalid data; n indicates the number of valid data collected before and after the data collection time corresponding to the data type of the invalid data, and the value range of the number of valid data collected is 3-5; X 01 The data type indicating invalid data corresponds to the valid data value collected earlier in the two adjacent data; X 02 The data type indicating invalid data corresponds to the data value of the later data collected in the two adjacent data; X 01i The data type representing invalid data corresponds to the data value of the ith valid data corresponding to the valid data collected earlier in the two adjacent data before and after, and the data value of the i-th valid data corresponding to the n consecutive collected data before; X 02i The data type representing invalid data corresponds to the data value of the ith valid data corresponding to the data collected at the later time in the two adjacent data before and after; The invalid data is replaced by replacement data corresponding to the invalid data.

8. The method for calculating and optimizing the steel demand for offshore photovoltaic brackets according to claim 7, characterized in that: Data preprocessing for environmental data also includes: Monitor the missing data of the collected environmental data and obtain the data collection time corresponding to the missing data; Extract the valid data closest to the data collection time corresponding to the missing data; Acquire first replacement data corresponding to the missing data using the nearest valid data before and after the data collection time corresponding to the missing data; The first replacement data corresponding to the missing data is obtained by the following formula: Among them, W t01 represents the first replacement data corresponding to the missing data; m represents the number of valid data collected before and after the data collection time corresponding to the two adjacent data before and after the data type of the missing data, and the value range of the number of valid data collected is 3-5; W 01 The data type indicating missing data corresponds to the valid data value collected earlier in the two adjacent data. 02 The data type indicating missing data corresponds to the data value of the later data collected in the two adjacent data. 01i The data type representing missing data corresponds to the data value of the i-th valid data corresponding to the valid data collected earlier in the two adjacent data before and after, and the m consecutive data collected earlier in time; W 02i The data type representing missing data corresponds to the data value of the i-th valid data corresponding to the data collected at the later time in the two adjacent data before and after; Using all valid data in the environmental data corresponding to the data type of the missing data to compensate and adjust the first replacement data, to obtain second replacement data; The second replacement data corresponding to the missing data is obtained by the following formula: Among them, W t02 W represents the second replacement data corresponding to the missing data; t01 represents the first replacement data corresponding to the missing data; W 01 The data type indicating missing data corresponds to the valid data value collected earlier in the two adjacent data. 02 The data type of the missing data corresponds to the data value of the later data collected in the two adjacent data; k represents the total number of all valid data corresponding to the data type of the missing data; W i represents the data value of the i-th valid data among all valid data corresponding to the data type of the missing data; z Represents the data middle value of all valid data corresponding to the data type of the missing data; The missing data is replaced by second replacement data corresponding to the missing data.

9. The method for calculating and optimizing the steel demand for offshore photovoltaic brackets according to claim 6, characterized in that: The construction of the structural model for offshore photovoltaic bracket installation based on bracket data and environmental data in S3 also includes: After the connection conditions of the geometric model are defined, loads are applied; Among them, the geometric model is meshed into hexahedral elements; After the model mesh is divided, the load is applied to the model mesh by the distributed load application method; After the load is applied, the simulated structural model of the offshore photovoltaic support installation is obtained.

10. The method for calculating and optimizing the steel demand for offshore photovoltaic brackets according to claim 9, characterized in that: Finite element analysis is performed on the simulated structural model in S4, and the load data of the bracket in the simulated structural model is obtained. The steel usage is optimized based on the finite element analysis and load data, including: The simulated structural model is subjected to static analysis, modal analysis, buckling analysis and fatigue analysis using finite element software; Among them, the static analysis is to calculate the static balance data according to the connection and load data between the bracket and the floating body in the simulated structural model, and obtain the displacement, stress, strain, reaction force and deformation shape data of the simulated structural model after calculation; Modal analysis is to perform operation analysis based on the connection between the bracket and the floating body in the simulated structural model. After the operation analysis, the natural frequency, vibration mode, damping ratio and mass participation coefficient of the simulated structural model are obtained. Buckling analysis is to perform operation analysis based on the connection and load data between the bracket and the floating body in the simulated structural model, and after the operation analysis, the buckling load factor, buckling mode, critical stress and buckling load of the simulated structural model are obtained; Fatigue analysis is performed based on the static analysis results of the simulated structural model. After fatigue analysis, the stress range, stress amplitude, average stress, fatigue life, damage accumulation, fatigue safety factor and SN curve of the simulated structural model are obtained.

11. The method for calculating and optimizing the steel demand for offshore photovoltaic brackets according to claim 10, characterized in that: In S4, the simulated structural model is subjected to finite element analysis, and the load data of the bracket in the simulated structural model is obtained. The steel usage is optimized according to the finite element analysis and load data, and also includes: Determine whether the types of steel pipe columns and steel trusses meet the standards based on the load data and finite element analysis data. If they do not meet the standards, reselect the steel pipe columns and steel trusses. According to the finite element analysis data, the cross-sectional dimensions of the steel pipe columns and steel trusses are adjusted, and the structural stiffness is adjusted after the cross-sectional dimensions are adjusted; After the structural stiffness adjustment is completed, the support optimization and connection design are carried out according to the load data; After the support optimization and connection design are completed, the volume data of the steel pipe column and steel truss are confirmed, and the density of the steel pipe column and steel truss is multiplied by the volume data to obtain the optimized amount of steel; At the same time, the optimized dosage includes cutting loss and welding joint loss; The optimized usage of steel is marked as offshore photovoltaic support steel quantity data.

12. The method for calculating and optimizing the steel demand for offshore photovoltaic brackets according to claim 11, characterized in that: In S5, the demand is summarized and optimized based on the steel quantity data of offshore photovoltaic brackets, and then transmitted to the display terminal for display after summary and optimization, including: The steel quantity demand data, bearing capacity data and constructed model data in the offshore photovoltaic bracket steel quantity data are summarized respectively; After the aggregation, text data and image data are generated, and the generated text data and image data are converted into visual data; After visualization conversion, it is transmitted to the display terminal for display.

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