GIS-based wind power blade transportation path three-dimensional simulation and dynamic optimization method

Abstract

The invention relates to the technical field of blade transportation, and discloses a GIS-based three-dimensional simulation and dynamic optimization method for a wind power blade transportation path, and the method comprises the steps: obtaining the geographic data of an undetermined transportation path based on the GIS, and carrying out the three-dimensional modeling, and obtaining a plurality of path three-dimensional models; acquiring real-time environment information, constructing a plurality of simulated transportation path environments by combining the plurality of path three-dimensional models, performing dynamic simulation of blade transportation on the simulated transportation path environments, and generating a transportation evaluation value according to a simulation result; screening out a plurality of optimal transportation paths and an optimizable area according to the transportation evaluation value, and performing simulation optimization on the optimizable area to obtain a plurality of optimal transportation paths after simulation optimization and an optimized path three-dimensional model; and carrying out optimization evaluation on the optimized path three-dimensional model, screening out an optimal transportation path according to an evaluation result, generating an optimal transportation strategy, ensuring the transportation stability of the wind power blade, and improving the transportation efficiency.

Description

Technical Field

[0001] The present application relates to the field of blade transportation technology, and in particular to a GIS-based three-dimensional simulation and dynamic optimization method for wind turbine blade transportation paths. Background Art

[0002] Wind turbine equipment mainly includes wind turbine blades, nacelle, hub and tower. The blades are extremely long, which is the main feature that distinguishes them from other wind turbine equipment. The longer the blades, the more difficult and costly it is to transport. Therefore, the transportation of wind turbine blades is a big problem.

[0003] In the existing technology, the transportation path of wind turbine blades is mostly fixed. If a place is encountered where the wind turbine blades cannot pass, real-time cleaning is required and the safe passage of the wind turbine cannot be guaranteed. This leads to a high risk of blade damage, poor transportation efficiency and high transportation costs. Therefore, a GIS-based three-dimensional simulation and dynamic optimization method for wind turbine blade transportation paths is urgently needed to improve the stability and efficiency of blade transportation and enhance the overall economic efficiency of mountain wind power projects. Summary of the Invention

[0004] To solve the above technical problems, the present application provides a GIS-based three-dimensional simulation and dynamic optimization method for wind turbine blade transportation paths. By determining the three-dimensional path models of multiple pending transportation paths and performing dynamic simulation of blade transportation, a transportation evaluation value for each pending transportation path is generated based on the simulation results. The preferred transportation path and the corresponding optimizable area are determined and optimized based on the transportation evaluation value. The optimized preferred transportation path is evaluated, and the optimal transportation path and the optimal transportation strategy are determined based on the evaluation results to ensure the transportation stability of wind turbine blades and improve transportation efficiency.

[0005] In some embodiments of the present application, a GIS-based three-dimensional simulation and dynamic optimization method for wind turbine blade transportation paths is provided, including: Pre-set multiple pending transport routes, obtain geographic data of the pending transport routes based on GIS and perform three-dimensional modeling to obtain three-dimensional path models of the multiple pending transport routes; Acquire real-time environmental information, and construct multiple simulated transport path environments by combining the three-dimensional path models of multiple pending transport paths. Perform dynamic simulation of blade transport in each simulated transport path environment, and generate a transport evaluation value for each pending transport path based on the simulation results. According to the transportation evaluation value, several preferred transportation routes and corresponding optimizable areas are screened out, and the optimizable areas are simulated and optimized to obtain several preferred transportation routes and corresponding optimized path three-dimensional models after simulation optimization; The optimized path three-dimensional model is optimized and evaluated, and the optimal transportation path is screened out and the optimal transportation strategy is generated based on the evaluation results.

[0006] In some embodiments of the present application, obtaining a plurality of three-dimensional path models of pending transport paths includes: Obtaining geographic data of each pending transport route based on GIS, wherein the geographic data includes road data, terrain data, and obstacle data; Preprocessing the geographic data, performing transport path contour extraction, path topology repair, and vector transformation analysis on the preprocessed geographic data corresponding to the undetermined transport path, and generating an initial path three-dimensional model corresponding to the undetermined transport path; The initial path 3D model is divided into multiple analysis areas, each analysis area is scanned by movement, and the focus features and feature information of the corresponding analysis area are determined based on the scanning results; According to the characteristic information of the characteristic of interest, a number of analysis points corresponding to the characteristic of interest are set, a risk coefficient of each analysis point is calculated, and an analysis point with a risk coefficient greater than a preset risk coefficient threshold is set as a characteristic point; Determine the risk area in the corresponding analysis area based on the difference between the risk coefficient of the feature points in the same analysis area and the risk coefficient of the preset risk coefficient threshold, the number of feature points, and the positional relationship between different feature points; Adjustments are performed on several risk areas of the same initial path 3D model, and other areas are smoothed. Based on the processing results, a path 3D model corresponding to the undetermined transport path is generated.

[0007] In some embodiments of the present application, calculating the risk factor of each analysis point includes: Set the center position of each feature of interest as the center point, and calculate the first distance between each analysis point and the center point of the corresponding feature of interest; Setting a weight coefficient of the corresponding analysis point according to the first distance and setting a scanning radius of the corresponding analysis point, and determining an analysis range of the corresponding analysis point according to the scanning radius; Sequentially set several standard points that meet the wind turbine blade transportation requirements at the focus features of each analysis area; Calculate the second distance between each analysis point and each standard point in the corresponding analysis range, and perform truncated mean processing on the second distances to obtain the third distance; generating a distance difference at a corresponding analysis point according to the third distance and a preset distance threshold, and generating a first risk coefficient for the corresponding analysis point according to the distance difference; Obtain basic information of the wind turbine blades, generate basic evaluation values ​​corresponding to the wind turbine blades, and generate point evaluation values ​​corresponding to the analysis points based on the point information of the analysis points; The historical transport logs are screened based on the point evaluation value and the basic evaluation value to obtain historical similar transport information. Based on the historical similar transport information, the historical similar transport cost, historical similar transport time, historical similar transport failure frequency and historical environmental impact coefficient of the corresponding analysis point are determined; Generate a second risk coefficient for the corresponding analysis point based on historically similar transportation costs and historically similar transportation times; Generate the third risk coefficient of the corresponding analysis point based on the historical similar transportation failure frequency; Generate the fourth risk coefficient of the corresponding analysis point based on the historical environmental impact coefficient; A risk coefficient of a corresponding analysis point is generated according to the first risk coefficient, the second risk coefficient, the third risk coefficient, and the fourth risk coefficient of the same analysis point.

[0008] In some embodiments of the present application, real-time environmental information is acquired, and multiple simulated transport path environments are constructed in combination with multiple three-dimensional path models of the to-be-determined transport paths, including: Acquiring real-time environmental information, including real-time weather data, real-time road condition data, real-time dynamic obstacle data, and real-time terrain change data; The three-dimensional model of each undetermined transport path is used as the basis, and a real-time data layer is superimposed. Real-time road condition data, real-time dynamic obstacle data, and real-time terrain change data are imported into the real-time data layer. The three-dimensional model of the path is updated according to the real-time data layer to obtain the initial simulated transport path environment corresponding to the undetermined transport path; Screening out feature points whose historical environmental impact coefficients are greater than a preset environmental impact coefficient threshold, obtaining several environmental impact factors of the screened feature points, and comparing the several environmental impact factors of the screened feature points with real-time environmental information to determine the real-time environmental impact factors; Determine the impact characteristics of real-time environmental influencing factors on corresponding feature points, dynamically update the corresponding feature points of the initial simulated transport path environment of the corresponding undetermined transport path based on the impact characteristics, and obtain the simulated transport path environment of the corresponding undetermined transport path.

[0009] In some embodiments of the present application, a dynamic simulation of blade transportation is performed on each simulated transportation path environment, and a transportation evaluation value of each undetermined transportation path is generated according to the simulation results, including: Construct a blade model of the wind turbine blade, add the blade model to the simulated transportation path environment of each undetermined transportation path, perform dynamic simulation of blade transportation, and obtain the simulated transportation parameters of the wind turbine blade passing through each risk area during the simulation process; Generate transportation sub-evaluation values ​​corresponding to risk areas based on simulated transportation parameters; Establish a transport sub-evaluation value sequence P, P (p1, ..., pn) for each risk area in the pending transport route, where pi is the transport sub-evaluation value of the i-th risk area in the pending transport route, and n is the number of risk areas in the pending transport route; generating a transport evaluation value corresponding to the undetermined transport path according to the transport sub-evaluation values ​​of multiple risk areas in the simulated transport path environment of the same undetermined transport path; The calculation formula of the transportation evaluation value is: ; Wherein, Y is the transport evaluation value, y1 is the first preset weight coefficient, y2 is the second preset weight coefficient, q1 is the first transport conversion coefficient, q2 is the second transport conversion coefficient, is the transport sub-evaluation value of the i-th risk area, ci is the weight coefficient of the i-th risk area, n0 is the total number of risk areas in the corresponding undetermined transport path whose transport sub-evaluation value is less than the transport sub-evaluation value threshold, is the transport sub-evaluation value threshold, pr is the transport sub-evaluation value of the r-th risk area whose transport sub-evaluation value is less than the transport sub-evaluation value threshold, and cr is the weight coefficient of the r-th risk area whose transport sub-evaluation value is less than the transport sub-evaluation value threshold.

[0010] In some embodiments of the present application, generating a transportation sub-evaluation value corresponding to a risk area based on simulated transportation parameters includes: Pre-set multiple transportation evaluation indicators; According to the correlation degree between the simulated transport parameter and each transport evaluation index, determining the correlated simulated transport parameter of each transport evaluation index; Comparing the associated simulated transport parameter of each transport evaluation index with the corresponding standard transport parameter, and generating a first evaluation value of the corresponding transport evaluation index according to the comparison result; generating a transportation sub-evaluation value corresponding to the risk area according to the first evaluation values ​​of the plurality of transportation evaluation indicators; The calculation formula of the transport sub-evaluation value is: ; Among them, p is the transportation sub-evaluation value of the corresponding risk area, Jm is the first evaluation value of the mth transportation evaluation index, and am is the weight coefficient of the mth transportation evaluation index.

[0011] In some embodiments of the present application, simulation optimization is performed on the optimizable area to obtain several optimized transportation paths and corresponding optimized path three-dimensional models after simulation optimization, including: Presetting a transport evaluation value threshold and a transport sub-evaluation value threshold; The undetermined transport path with a transport evaluation value greater than the transport evaluation value threshold is set as the preferred transport path; The risk area in the preferred transport path where the transport sub-evaluation value is less than the transport sub-evaluation value threshold is set as an optimizable area, and the optimizable features of the optimizable area are determined; Constructing an optimization reference library for each risk area, wherein the optimization reference library includes a number of preset optimizable features corresponding to the risk area, and each preset optimizable feature is associated with a corresponding preset optimization strategy; Based on the similarity analysis between the optimizable features of the current optimizable region and the preset optimizable features of the corresponding optimization reference library, the preset optimization strategy corresponding to the preset optimizable feature with the greatest similarity is set as the optimization strategy for the optimizable features of the current optimizable region; The optimizable area is simulated and optimized according to the optimization strategy, and the corresponding preferred transportation path and the corresponding path three-dimensional model are updated according to the optimizable area after simulation optimization to obtain the preferred transportation path after simulation optimization and the corresponding optimized path three-dimensional model.

[0012] In some embodiments of the present application, an optimization evaluation is performed on the optimized path three-dimensional model, and an optimal transportation path is screened out based on the evaluation results and an optimal transportation strategy is generated, including: Perform dynamic simulation of blade transportation based on the optimized path three-dimensional model, and generate an optimized transportation evaluation value corresponding to the optimal transportation path after simulation optimization according to the simulation results; The optimized transport evaluation value is subtracted from the transport evaluation value of the corresponding preferred transport path to obtain an optimized transport evaluation value difference, and the optimized evaluation value of the corresponding preferred transport path after simulation optimization is generated according to the optimized transport evaluation value difference; The optimal transport path after simulation optimization with the largest optimization evaluation value is set as the optimal transport path, and the optimal transport strategy is generated based on the optimal transport path, the optimal transport tooling equipment mapped by the optimal transport path, and the optimal blade transport posture.

[0013] Compared with the prior art, the GIS-based three-dimensional simulation and dynamic optimization method for wind turbine blade transportation paths in the embodiment of the present application has the following advantages: By determining the three-dimensional path models of multiple pending transport paths and conducting dynamic simulation of blade transportation, a transportation evaluation value for each pending transport path is generated based on the simulation results. The preferred transport path and the corresponding optimizable area are determined and optimized based on the transportation evaluation value. The optimized preferred transport path is evaluated, and the optimal transport path and optimal transportation strategy are determined based on the evaluation results to ensure the transportation stability of wind turbine blades and improve transportation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1It is a flow chart of the GIS-based three-dimensional simulation and dynamic optimization method of wind turbine blade transportation path in the embodiment of the present application. DETAILED DESCRIPTION

[0015] The following embodiments are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0016] In the description of this application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on this application.

[0017] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature specified as "first" or "second" may explicitly or implicitly include one or more of such features. Throughout this application, unless otherwise specified, "plurality" means two or more.

[0018] In the description of this application, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they can refer to fixed, detachable, or integral connections; mechanical or electrical connections; direct or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in this application based on the specific circumstances.

[0019] like Figure 1 As shown, the GIS-based three-dimensional simulation and dynamic optimization method for wind turbine blade transportation paths in an embodiment of the present application includes: Step S101: presetting a plurality of pending transport routes, obtaining geographic data of the pending transport routes based on GIS and performing three-dimensional modeling to obtain three-dimensional path models of the plurality of pending transport routes; Step S102: Acquire real-time environmental information, and construct multiple simulated transport path environments based on the three-dimensional path models of multiple pending transport paths. Perform a dynamic simulation of blade transport in each simulated transport path environment, and generate a transport evaluation value for each pending transport path based on the simulation results. Step S103: Filtering out several preferred transport routes and corresponding optimizable areas based on the transport evaluation values, performing simulation optimization on the optimizable areas, and obtaining several preferred transport routes and corresponding optimized path three-dimensional models after simulation optimization; Step S104: Optimize and evaluate the optimized path three-dimensional model, select the optimal transportation path based on the evaluation results, and generate the optimal transportation strategy.

[0020] In this embodiment, the optimal transportation strategy includes the optimal transportation path, the optimal transportation tooling equipment for the current blade mapped by the optimal transportation path, and the optimal transportation posture of the blade.

[0021] In this embodiment, multiple blade transportation postures of the current wind turbine blades, multiple transportation tooling equipment and the corresponding simulated transportation path environment are dynamically simulated to obtain multiple simulation results. Multiple transportation evaluation values ​​are generated based on the multiple simulation results, and the maximum transportation evaluation value is used as the transportation evaluation value of the undetermined transportation path in the present invention.

[0022] In some embodiments of the present application, obtaining a plurality of three-dimensional path models of pending transport paths includes: Obtaining geographic data of each pending transport route based on GIS, wherein the geographic data includes road data, terrain data, and obstacle data; Preprocessing the geographic data, performing transport path contour extraction, path topology repair, and vector transformation analysis on the preprocessed geographic data corresponding to the undetermined transport path, and generating an initial path three-dimensional model corresponding to the undetermined transport path; The initial path 3D model is divided into multiple analysis areas, each analysis area is scanned by movement, and the focus features and feature information of the corresponding analysis area are determined based on the scanning results; According to the characteristic information of the characteristic of interest, a number of analysis points corresponding to the characteristic of interest are set, a risk coefficient of each analysis point is calculated, and an analysis point with a risk coefficient greater than a preset risk coefficient threshold is set as a characteristic point; Determine the risk area in the corresponding analysis area based on the difference between the risk coefficient of the feature points in the same analysis area and the risk coefficient of the preset risk coefficient threshold, the number of feature points, and the positional relationship between different feature points; Adjustments are performed on several risk areas of the same initial path 3D model, and other areas are smoothed. Based on the processing results, a path 3D model corresponding to the undetermined transport path is generated.

[0023] In this embodiment, the focus features include protruding positions, steep slopes, sharp bends, and obstacles on the transport road surface in the corresponding analysis area. The feature information includes the position, volume, and feature attributes of the focus feature. The larger the volume of the focus feature, the greater the influence of the position, and the greater the influence of the feature attributes, the more analysis points there are. The risk coefficient of each analysis point is calculated to determine the risk area, and the risk area is adjusted with high precision to ensure the accuracy of the wind turbine blade transportation path simulation and improve the safety and feasibility of wind turbine blade transportation.

[0024] In this embodiment, the greater the risk coefficient difference and the greater the number of feature points, the larger the risk area in the corresponding analysis area, and the specific risk area is set according to the position information and position relationship of the feature points.

[0025] In this embodiment, the risk area is adjusted, and the adjustment processing includes but is not limited to precise coordinate matching, fine-grained reconstruction of local models, fine-tuning of dynamic simulation constraints, high-precision collision detection, etc. The other areas are smoothed, and the smoothing processing includes but is not limited to corresponding area model simplification, path following simplification, data smoothing, rendering optimization, etc. By making corresponding adjustments to the risk area and other areas, the calculation complexity is reduced while ensuring the model accuracy of the transportation path.

[0026] In some embodiments of the present application, calculating the risk factor of each analysis point includes: Set the center position of each feature of interest as the center point, and calculate the first distance between each analysis point and the center point of the corresponding feature of interest; Setting a weight coefficient of the corresponding analysis point according to the first distance and setting a scanning radius of the corresponding analysis point, and determining an analysis range of the corresponding analysis point according to the scanning radius; Sequentially set several standard points that meet the wind turbine blade transportation requirements at the focus features of each analysis area; Calculate the second distance between each analysis point and each standard point in the corresponding analysis range, and perform truncated mean processing on the second distances to obtain the third distance; generating a distance difference at a corresponding analysis point according to the third distance and a preset distance threshold, and generating a first risk coefficient for the corresponding analysis point according to the distance difference; Obtain basic information of the wind turbine blades, generate basic evaluation values ​​corresponding to the wind turbine blades, and generate point evaluation values ​​corresponding to the analysis points based on the point information of the analysis points; The historical transport logs are screened based on the point evaluation value and the basic evaluation value to obtain historical similar transport information. Based on the historical similar transport information, the historical similar transport cost, historical similar transport time, historical similar transport failure frequency and historical environmental impact coefficient of the corresponding analysis point are determined; Generate a second risk coefficient for the corresponding analysis point based on historically similar transportation costs and historically similar transportation times; Generate the third risk coefficient of the corresponding analysis point based on the historical similar transportation failure frequency; Generate the fourth risk coefficient of the corresponding analysis point based on the historical environmental impact coefficient; A risk coefficient of a corresponding analysis point is generated according to the first risk coefficient, the second risk coefficient, the third risk coefficient, and the fourth risk coefficient of the same analysis point.

[0027] In this embodiment, the basic information includes the blade body length, weight, material, torsion angle, resistance to extreme conditions, structure, etc. of the wind turbine blade, and the point information of the analysis point includes the shape, structure, type of interest feature, position in the interest feature, etc. of the analysis point.

[0028] In this embodiment, historical similar transportation information is extracted from historical transportation logs that are highly similar to the current wind turbine blades and corresponding analysis points. Based on the historical similar transportation information, several historical transportation times, several historical transportation costs, whether a fault occurs, and whether it is affected by the environment in several historical transportation logs that are highly similar to the current wind turbine blades and corresponding analysis points can be obtained. The several historical transportation times and several historical transportation costs are averaged to obtain historical similar transportation costs and historical similar transportation times. The historical similar transportation failure frequency is calculated based on the number of failures and the number of non-faults, and the historical environmental impact coefficient is calculated based on the transportation conditions under different environments.

[0029] In this embodiment, the distance difference = the third distance - the preset distance threshold. When the distance difference is smaller, the corresponding first risk coefficient is smaller, and vice versa. When the historically similar transportation cost is lower and the historically similar transportation time is shorter, the corresponding second risk coefficient is smaller, and vice versa. When the historically similar transportation failure frequency is smaller, the corresponding third risk coefficient is smaller, and vice versa. When the historical environmental impact coefficient is smaller, the corresponding fourth risk coefficient is smaller, and vice versa.

[0030] In this embodiment, by analyzing the feasibility, transportation cost, transportation time, failure probability and degree of environmental impact of wind turbine blades at each analysis point, the risk coefficient of the corresponding analysis point is obtained, thereby obtaining the risk area and performing corresponding processing on the initial path three-dimensional model, thereby improving the accuracy of the path three-dimensional model of each pending transportation path, laying the foundation for subsequent simulation, and improving the feasibility of the transportation path and the transportation stability of wind turbine blades.

[0031] In some embodiments of the present application, real-time environmental information is acquired, and multiple simulated transport path environments are constructed in combination with multiple three-dimensional path models of the to-be-determined transport paths, including: Acquiring real-time environmental information, including real-time weather data, real-time road condition data, real-time dynamic obstacle data, and real-time terrain change data; The three-dimensional model of each undetermined transport path is used as the basis, and a real-time data layer is superimposed. Real-time road condition data, real-time dynamic obstacle data, and real-time terrain change data are imported into the real-time data layer. The three-dimensional model of the path is updated according to the real-time data layer to obtain the initial simulated transport path environment corresponding to the undetermined transport path; Screening out feature points whose historical environmental impact coefficients are greater than a preset environmental impact coefficient threshold, obtaining several environmental impact factors of the screened feature points, and comparing the several environmental impact factors of the screened feature points with real-time environmental information to determine the real-time environmental impact factors; Determine the impact characteristics of real-time environmental influencing factors on corresponding feature points, dynamically update the corresponding feature points of the initial simulated transport path environment of the corresponding undetermined transport path based on the impact characteristics, and obtain the simulated transport path environment of the corresponding undetermined transport path.

[0032] In this embodiment, the selected characteristic points refer to points that are greatly affected by the environment, and the environmental influencing factors refer to environmental factors in historical transportation logs that have an impact on the corresponding characteristic points.

[0033] In this embodiment, the real-time environmental impact factor refers to the part where the real-time environmental information overlaps with the environmental impact factor of the corresponding feature point. The impact feature is determined based on the historical change characteristics of the feature point caused by the environmental impact factor, thereby dynamically updating the corresponding feature point and improving the simulation accuracy of the undetermined transportation path.

[0034] In some embodiments of the present application, a dynamic simulation of blade transportation is performed on each simulated transportation path environment, and a transportation evaluation value of each undetermined transportation path is generated according to the simulation results, including: Construct a blade model of the wind turbine blade, add the blade model to the simulated transportation path environment of each undetermined transportation path, perform dynamic simulation of blade transportation, and obtain the simulated transportation parameters of the wind turbine blade passing through each risk area during the simulation process; Generate transportation sub-evaluation values ​​corresponding to risk areas based on simulated transportation parameters; Establish a transport sub-evaluation value sequence P, P (p1, ..., pn) for each risk area in the pending transport route, where pi is the transport sub-evaluation value of the i-th risk area in the pending transport route, and n is the number of risk areas in the pending transport route; generating a transport evaluation value corresponding to the undetermined transport path according to the transport sub-evaluation values ​​of multiple risk areas in the simulated transport path environment of the same undetermined transport path; The calculation formula of the transportation evaluation value is: ; Wherein, Y is the transport evaluation value, y1 is the first preset weight coefficient, y2 is the second preset weight coefficient, q1 is the first transport conversion coefficient, q2 is the second transport conversion coefficient, is the transport sub-evaluation value of the i-th risk area, ci is the weight coefficient of the i-th risk area, n0 is the total number of risk areas in the corresponding undetermined transport path whose transport sub-evaluation value is less than the transport sub-evaluation value threshold, is the transport sub-evaluation value threshold, pr is the transport sub-evaluation value of the r-th risk area whose transport sub-evaluation value is less than the transport sub-evaluation value threshold, and cr is the weight coefficient of the r-th risk area whose transport sub-evaluation value is less than the transport sub-evaluation value threshold.

[0035] In this embodiment, y1 refers to the weight coefficient of the sum of the transport sub-evaluation values ​​of all risk areas in the pending transport path, and y2 is the weight coefficient of the sum of the transport sub-evaluation values ​​of the risk areas in the pending transport path whose transport sub-evaluation values ​​are less than the transport sub-evaluation value threshold. y1 is 0.6 and y2 is 0.4.

[0036] In this embodiment, the first transport conversion coefficient refers to converting the sum of the transport sub-evaluation values ​​of all risk areas into a numerical value of the same dimension as the transport evaluation value. The larger the sum of the transport sub-evaluation values ​​of all risk areas, the larger the corresponding transport evaluation value, and vice versa. The second transport conversion coefficient refers to converting the difference in transport sub-evaluation values ​​of risk areas whose transport sub-evaluation values ​​are less than the transport sub-evaluation value threshold into a numerical value of the same dimension as the transport evaluation value. The larger the difference in transport sub-evaluation values, the smaller the corresponding transport evaluation value, and vice versa.

[0037] In some embodiments of the present application, generating a transportation sub-evaluation value corresponding to a risk area based on simulated transportation parameters includes: Pre-set multiple transportation evaluation indicators; According to the correlation degree between the simulated transport parameter and each transport evaluation index, determining the correlated simulated transport parameter of each transport evaluation index; Comparing the associated simulated transport parameter of each transport evaluation index with the corresponding standard transport parameter, and generating a first evaluation value of the corresponding transport evaluation index according to the comparison result; generating a transportation sub-evaluation value corresponding to the risk area according to the first evaluation values ​​of the plurality of transportation evaluation indicators; The calculation formula of the transport sub-evaluation value is: ; Among them, p is the transportation sub-evaluation value of the corresponding risk area, Jm is the first evaluation value of the mth transportation evaluation index, and am is the weight coefficient of the mth transportation evaluation index.

[0038] In this embodiment, the transportation evaluation indicators include evaluation indicators such as transportation stability, transportation safety, transportation economy, and transportation efficiency. For example, the associated simulation transportation parameters of the transportation safety evaluation indicators include simulated blade tip swing amplitude, simulated blade stress points, simulated vibration times, etc.

[0039] In this embodiment, the smaller the parameter difference between the associated simulation transport parameter and the corresponding standard transport parameter, the larger the corresponding first evaluation value, and vice versa. When the first evaluation value is larger, the larger the transport sub-evaluation value of the corresponding risk area, and vice versa.

[0040] In some embodiments of the present application, simulation optimization is performed on the optimizable area to obtain several optimized transportation paths and corresponding optimized path three-dimensional models after simulation optimization, including: Presetting a transport evaluation value threshold and a transport sub-evaluation value threshold; The undetermined transport path with a transport evaluation value greater than the transport evaluation value threshold is set as the preferred transport path; The risk area in the preferred transport path where the transport sub-evaluation value is less than the transport sub-evaluation value threshold is set as an optimizable area, and the optimizable features of the optimizable area are determined; Constructing an optimization reference library for each risk area, wherein the optimization reference library includes a number of preset optimizable features corresponding to the risk area, and each preset optimizable feature is associated with a corresponding preset optimization strategy; Based on the similarity analysis between the optimizable features of the current optimizable region and the preset optimizable features of the corresponding optimization reference library, the preset optimization strategy corresponding to the preset optimizable feature with the greatest similarity is set as the optimization strategy for the optimizable features of the current optimizable region; The optimizable area is simulated and optimized according to the optimization strategy, and the corresponding preferred transportation path and the corresponding path three-dimensional model are updated according to the optimizable area after simulation optimization to obtain the preferred transportation path after simulation optimization and the corresponding optimized path three-dimensional model.

[0041] In this embodiment, the optimizable feature is set based on a transportation evaluation index whose first evaluation value is less than a preset first evaluation value threshold. For example, the transportation evaluation index whose first evaluation value is less than the preset first evaluation value threshold is a transportation safety evaluation index, and the associated simulation transportation parameter in the transportation safety evaluation index is determined to be less than the associated simulation transportation parameter of the standard transportation parameter and set as an optimizable feature.

[0042] In this embodiment, the optimization strategy includes but is not limited to area widening, reinforcement, laying of steel plates, new construction of detours, etc.

[0043] In this embodiment, by determining a preferred transportation path and a corresponding optimization strategy, the preferred transportation path is simulated and optimized to improve the transportation safety and feasibility of wind turbine blades.

[0044] In some embodiments of the present application, an optimization evaluation is performed on the optimized path three-dimensional model, and an optimal transportation path is screened out based on the evaluation results and an optimal transportation strategy is generated, including: Perform dynamic simulation of blade transportation based on the optimized path three-dimensional model, and generate an optimized transportation evaluation value corresponding to the optimal transportation path after simulation optimization according to the simulation results; The optimized transport evaluation value is subtracted from the transport evaluation value of the corresponding preferred transport path to obtain an optimized transport evaluation value difference, and the optimized evaluation value of the corresponding preferred transport path after simulation optimization is generated according to the optimized transport evaluation value difference; The optimal transport path after simulation optimization with the largest optimization evaluation value is set as the optimal transport path, and the optimal transport strategy is generated based on the optimal transport path, the optimal transport tooling equipment mapped by the optimal transport path, and the optimal blade transport posture.

[0045] The above is only a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and replacements can be made without departing from the technical principles of the present application. These improvements and replacements should also be regarded as the scope of protection of the present application.

Claims

1. A GIS-based three-dimensional simulation and dynamic optimization method for wind turbine blade transportation paths, characterized by: include: Pre-set multiple pending transport routes, obtain geographic data of the pending transport routes based on GIS and perform three-dimensional modeling to obtain three-dimensional path models of the multiple pending transport routes; Acquire real-time environmental information, and construct multiple simulated transport path environments by combining the three-dimensional path models of multiple pending transport paths. Perform dynamic simulation of blade transport in each simulated transport path environment, and generate a transport evaluation value for each pending transport path based on the simulation results. According to the transportation evaluation value, several preferred transportation routes and corresponding optimizable areas are screened out, and the optimizable areas are simulated and optimized to obtain several preferred transportation routes and corresponding optimized path three-dimensional models after simulation optimization; The optimized path three-dimensional model is optimized and evaluated, and the optimal transportation path is screened out and the optimal transportation strategy is generated based on the evaluation results.

2. The GIS-based three-dimensional simulation and dynamic optimization method for wind turbine blade transportation paths according to claim 1, characterized in that: Obtain a plurality of three-dimensional path models of undetermined transportation paths, including: Obtaining geographic data of each pending transport route based on GIS, wherein the geographic data includes road data, terrain data, and obstacle data; Preprocessing the geographic data, performing transport path contour extraction, path topology repair, and vector transformation analysis on the preprocessed geographic data corresponding to the undetermined transport path, and generating an initial path three-dimensional model corresponding to the undetermined transport path; The initial path 3D model is divided into multiple analysis areas, each analysis area is scanned by movement, and the focus features and feature information of the corresponding analysis area are determined based on the scanning results; According to the characteristic information of the characteristic of interest, a number of analysis points corresponding to the characteristic of interest are set, a risk coefficient of each analysis point is calculated, and an analysis point with a risk coefficient greater than a preset risk coefficient threshold is set as a characteristic point; Determine the risk area in the corresponding analysis area based on the difference between the risk coefficient of the feature points in the same analysis area and the risk coefficient of the preset risk coefficient threshold, the number of feature points, and the positional relationship between different feature points; Adjustments are performed on several risk areas of the same initial path 3D model, and other areas are smoothed. Based on the processing results, a path 3D model corresponding to the undetermined transport path is generated.

3. The GIS-based three-dimensional simulation and dynamic optimization method for wind turbine blade transportation paths according to claim 2, characterized in that: Calculate the risk factor for each analysis point, including: Set the center position of each feature of interest as the center point, and calculate the first distance between each analysis point and the center point of the corresponding feature of interest; Setting a weight coefficient of the corresponding analysis point according to the first distance and setting a scanning radius of the corresponding analysis point, and determining an analysis range of the corresponding analysis point according to the scanning radius; Sequentially set several standard points that meet the wind turbine blade transportation requirements at the focus features of each analysis area; Calculate the second distance between each analysis point and each standard point in the corresponding analysis range, and perform truncated mean processing on the second distances to obtain the third distance; generating a distance difference at a corresponding analysis point according to the third distance and a preset distance threshold, and generating a first risk coefficient for the corresponding analysis point according to the distance difference; Obtain basic information of the wind turbine blades, generate basic evaluation values ​​corresponding to the wind turbine blades, and generate point evaluation values ​​corresponding to the analysis points based on the point information of the analysis points; The historical transport logs are screened based on the point evaluation value and the basic evaluation value to obtain historical similar transport information. Based on the historical similar transport information, the historical similar transport cost, historical similar transport time, historical similar transport failure frequency and historical environmental impact coefficient of the corresponding analysis point are determined; Generate a second risk coefficient for the corresponding analysis point based on historically similar transportation costs and historically similar transportation times; Generate the third risk coefficient of the corresponding analysis point based on the historical similar transportation failure frequency; Generate the fourth risk coefficient of the corresponding analysis point based on the historical environmental impact coefficient; A risk coefficient of a corresponding analysis point is generated according to the first risk coefficient, the second risk coefficient, the third risk coefficient, and the fourth risk coefficient of the same analysis point.

4. The GIS-based three-dimensional simulation and dynamic optimization method for wind turbine blade transportation paths according to claim 3, characterized in that: Acquire real-time environmental information and build multiple simulated transport path environments by combining multiple 3D models of pending transport paths, including: Acquiring real-time environmental information, including real-time weather data, real-time road condition data, real-time dynamic obstacle data, and real-time terrain change data; The three-dimensional model of each undetermined transport path is used as the basis, and a real-time data layer is superimposed. Real-time road condition data, real-time dynamic obstacle data, and real-time terrain change data are imported into the real-time data layer. The three-dimensional model of the path is updated according to the real-time data layer to obtain the initial simulated transport path environment corresponding to the undetermined transport path; Screening out feature points whose historical environmental impact coefficients are greater than a preset environmental impact coefficient threshold, obtaining several environmental impact factors of the screened feature points, and comparing the several environmental impact factors of the screened feature points with real-time environmental information to determine the real-time environmental impact factors; Determine the impact characteristics of real-time environmental influencing factors on corresponding feature points, dynamically update the corresponding feature points of the initial simulated transport path environment of the corresponding undetermined transport path based on the impact characteristics, and obtain the simulated transport path environment of the corresponding undetermined transport path.

5. The GIS-based three-dimensional simulation and dynamic optimization method for wind turbine blade transportation paths according to claim 4, characterized in that: Perform dynamic simulation of blade transportation for each simulated transportation path environment, and generate a transportation evaluation value for each undetermined transportation path based on the simulation results, including: Construct a blade model of the wind turbine blade, add the blade model to the simulated transportation path environment of each undetermined transportation path, perform dynamic simulation of blade transportation, and obtain the simulated transportation parameters of the wind turbine blade passing through each risk area during the simulation process; Generate transportation sub-evaluation values ​​corresponding to risk areas based on simulated transportation parameters; Establish a transport sub-evaluation value sequence P, P (p1, ..., pn) for each risk area in the pending transport route, where pi is the transport sub-evaluation value of the i-th risk area in the pending transport route, and n is the number of risk areas in the pending transport route; generating a transport evaluation value corresponding to the undetermined transport path according to the transport sub-evaluation values ​​of multiple risk areas in the simulated transport path environment of the same undetermined transport path; The calculation formula of the transportation evaluation value is: ； Wherein, Y is the transport evaluation value, y1 is the first preset weight coefficient, y2 is the second preset weight coefficient, q1 is the first transport conversion coefficient, q2 is the second transport conversion coefficient, is the transport sub-evaluation value of the i-th risk area, ci is the weight coefficient of the i-th risk area, n0 is the total number of risk areas in the corresponding undetermined transport path whose transport sub-evaluation value is less than the transport sub-evaluation value threshold, is the transport sub-evaluation value threshold, pr is the transport sub-evaluation value of the r-th risk area whose transport sub-evaluation value is less than the transport sub-evaluation value threshold, and cr is the weight coefficient of the r-th risk area whose transport sub-evaluation value is less than the transport sub-evaluation value threshold.

6. The GIS-based three-dimensional simulation and dynamic optimization method for wind turbine blade transportation paths according to claim 5, characterized in that: Generate transportation sub-evaluation values ​​for corresponding risk areas based on simulated transportation parameters, including: Pre-set multiple transportation evaluation indicators; According to the correlation degree between the simulated transport parameter and each transport evaluation index, determining the correlated simulated transport parameter of each transport evaluation index; Comparing the associated simulated transport parameter of each transport evaluation index with the corresponding standard transport parameter, and generating a first evaluation value of the corresponding transport evaluation index according to the comparison result; generating a transportation sub-evaluation value corresponding to the risk area according to the first evaluation values ​​of the plurality of transportation evaluation indicators; The calculation formula of the transport sub-evaluation value is: ； Among them, p is the transportation sub-evaluation value of the corresponding risk area, Jm is the first evaluation value of the mth transportation evaluation index, and am is the weight coefficient of the mth transportation evaluation index.

7. The GIS-based three-dimensional simulation and dynamic optimization method for wind turbine blade transportation paths according to claim 6, characterized in that: Perform simulation optimization on the optimizable area to obtain several optimal transportation routes after simulation optimization and the corresponding optimized path three-dimensional models, including: Presetting a transport evaluation value threshold and a transport sub-evaluation value threshold; The undetermined transport path with a transport evaluation value greater than the transport evaluation value threshold is set as the preferred transport path; The risk area in the preferred transport path where the transport sub-evaluation value is less than the transport sub-evaluation value threshold is set as an optimizable area, and the optimizable features of the optimizable area are determined; Constructing an optimization reference library for each risk area, wherein the optimization reference library includes a number of preset optimizable features corresponding to the risk area, and each preset optimizable feature is associated with a corresponding preset optimization strategy; Based on the similarity analysis between the optimizable features of the current optimizable region and the preset optimizable features of the corresponding optimization reference library, the preset optimization strategy corresponding to the preset optimizable feature with the greatest similarity is set as the optimization strategy for the optimizable features of the current optimizable region; The optimizable area is simulated and optimized according to the optimization strategy, and the corresponding preferred transportation path and the corresponding path three-dimensional model are updated according to the optimizable area after simulation optimization to obtain the preferred transportation path after simulation optimization and the corresponding optimized path three-dimensional model.

8. The GIS-based three-dimensional simulation and dynamic optimization method for wind turbine blade transportation paths according to claim 7, characterized in that: Optimize and evaluate the optimized path 3D model, select the optimal transportation path based on the evaluation results, and generate the optimal transportation strategy, including: Perform dynamic simulation of blade transportation based on the optimized path three-dimensional model, and generate an optimized transportation evaluation value corresponding to the optimal transportation path after simulation optimization according to the simulation results; The optimized transport evaluation value is subtracted from the transport evaluation value of the corresponding preferred transport path to obtain an optimized transport evaluation value difference, and the optimized evaluation value of the corresponding preferred transport path after simulation optimization is generated according to the optimized transport evaluation value difference; The optimal transport path after simulation optimization with the largest optimization evaluation value is set as the optimal transport path, and the optimal transport strategy is generated based on the optimal transport path, the optimal transport tooling equipment mapped by the optimal transport path, and the optimal blade transport posture.

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