Design method based on three-dimensional simulation of ski equipment structure

Abstract

The present invention relates to the field of three-dimensional simulation technology, and in particular to a three-dimensional simulation design method based on a ski device structure. The method comprises the following steps: obtaining ski device design data, and performing three-dimensional topological structure modeling to obtain a ski device structure model; performing ski load simulation according to the ski device design data to obtain ski load simulation data; performing load stress risk assessment on the ski device structure model according to the ski load simulation data to obtain load stress risk data; performing ski device load stress balance optimization on the ski device structure model to obtain a ski device load stress balance structure model set; obtaining customer ski device demand data, and performing customer demand load balance structure matching on the ski device load stress balance structure model set according to the customer ski device demand data, thereby obtaining a customer ski device balance structure model. The present invention can improve the load balance of ski devices.

Description

Technical Field

[0001] The invention relates to the technical field of three-dimensional simulation, and in particular to a three-dimensional simulation design method based on a ski device structure. Background Art

[0002] With the rise of global skiing and the development of technology, skiing equipment, as one of the key equipment, has gradually received attention for its design and performance requirements. Traditional skiing equipment design mainly relies on experience and laboratory testing. Although this method can ensure basic safety and performance, its limitation is that it cannot effectively predict the structural response under complex load conditions. In addition, traditional design methods are often time-consuming, costly, and difficult to quickly compare and optimize multiple design schemes. In recent years, with the application of 3D printing technology, new materials, and the innovation of sports equipment design concepts, the design of skiing equipment has become more personalized and refined. Consumers' demand for skiing equipment is not only limited to basic functional performance, but also includes lightweight, environmental protection, durability, comfort and other requirements. How to meet these diverse consumer needs while ensuring structural strength and safety has become a new challenge for traditional design methods. Summary of the invention

[0003] Based on this, it is necessary for the present invention to provide a three-dimensional simulation design method based on the structure of a ski device to solve at least one of the above technical problems.

[0004] To achieve the above object, a three-dimensional simulation design method based on the structure of a ski device includes the following steps:

[0005] Step S1: obtaining ski device design data, and extracting ski device structural features from the ski device design data, thereby obtaining ski board structural data; performing three-dimensional topological structure modeling based on the ski board structural data, thereby obtaining a ski device structural model;

[0006] Step S2: integrating the working conditions of the ski device according to the ski device design data, thereby obtaining the ski device design working condition data, and performing ski load simulation on the ski device design working condition data through the ski device structure model, thereby obtaining ski load simulation data;

[0007] Step S3: performing structural stress distribution analysis on the ski device structure model according to the ski load simulation data, thereby obtaining ski device stress distribution data, and performing load stress risk assessment according to the ski device stress distribution data, thereby obtaining load stress risk data;

[0008] Step S4: performing ski device stress risk structure division on the ski device structure model based on the load stress risk data, thereby obtaining ski device stress risk structure data; performing ski device load stress balance optimization on the ski device structure model according to the ski device stress risk structure data and the ski load simulation data, thereby obtaining a ski device load stress balance structure model set;

[0009] Step S5: Obtain customer ski equipment demand data, and perform customer demand load-balanced structure matching on the ski equipment load stress-balanced structure model set according to the customer ski equipment demand data, thereby obtaining the customer ski equipment balanced structure model.

[0010] The present invention extracts key structural features from existing ski design data. By analyzing and extracting data, designers can have a deeper understanding of the current design status and problems. This data-driven approach helps to establish a benchmark and lay the foundation for subsequent optimization and improvement. After integrating various working conditions, load simulation can accurately simulate real usage conditions. By applying actual loads to the structural model, designers can evaluate the performance of the ski under different environments and stresses. This helps to discover the weak links and potential risks of the design, thereby guiding subsequent structural optimization and improvement. Analyzing stress distribution can help understand the mechanical response of the ski under load, determine potential structural problems and local stress concentration areas. Through risk assessment, potential structural failure risks can be identified, providing designers with a basis and direction for improving the design. In the structural division stage, designers can optimize the structure based on previous analysis results to achieve load stress balance. This means that while ensuring structural strength, unnecessary material use is reduced as much as possible to achieve lightweight and efficient design. Matching the structural model according to customer needs can ensure that the ski not only meets basic functional performance, but also takes into account the personalized needs of customers. This customer-driven design method improves the market adaptability and user satisfaction of the product. In summary, this design process not only focuses on traditional safety and performance requirements, but also pays attention to consumer needs in various aspects such as personalization, lightweight, environmental protection and comfort. By combining advanced design tools and technologies such as 3D printing and simulation analysis, designers can respond to market needs more quickly and effectively and provide innovative ski equipment designs that meet expectations.

[0011] Optionally, step S1 specifically includes:

[0012] Step S11: obtaining ski device design data, and extracting ski device structural features according to the ski device design data, thereby obtaining ski device structural data;

[0013] Step S12: classifying the ski device structure data into device structure data, thereby obtaining the snowboard structure data and the fixing device structure data;

[0014] Step S13: performing a fixture topology structure analysis according to the fixture structure data, thereby obtaining a fixture topology structure model;

[0015] Step S14: performing a snowboard strength structure analysis according to the snowboard structure data, thereby obtaining a snowboard strength structure model;

[0016] Step S15: Combining the fixing device topology structure model and the ski board strength structure model into a ski device structure model, thereby obtaining a ski device structure model.

[0017] The present invention obtains accurate design data to help ensure the accuracy and reliability of subsequent analysis and design processes. Design data serves as the basis of the entire design process and provides necessary information support for subsequent structural analysis and optimization. Through classification analysis, the advantages and disadvantages of different structures can be better understood, providing a basis for optimal design. The classification results help engineers select the type of ski device structure that best suits specific needs. Analyzing the topological structure of the fixing device can ensure the stability and safety of the ski device during use. The most suitable fixing scheme can be determined to ensure that the device can be effectively installed and operated. Through structural analysis, the strength and durability of the device can be optimized to ensure its reliability under various conditions of use. The analysis helps to determine the safety margins of the device under normal and abnormal workloads and prevent structural failure. The various components are integrated together to ensure the integrity and efficiency of the device in operation and use. Through the combined structural model, the integrity and reliability of the design scheme can be verified.

[0018] Optionally, step S13 is specifically:

[0019] Step S131: extracting structural material characteristics from the fixture structure data to obtain fixture structure material data, and performing material property analysis based on the fixture structure material data to obtain fixture structure material property data;

[0020] Step S132: classifying the fixture structure data into structural components, thereby obtaining independent connection structure data and component structure data;

[0021] Step S133: dividing the component connection structure according to the component structure data, thereby obtaining component connection structure data;

[0022] Step S134: Calculating the structural similarity of the component connection structure data and the independent connection structure data, thereby obtaining connection structure similarity data;

[0023] Step S135: integrating the connection relationship of the device connection structure data and the component structure data according to the connection structure similarity data, thereby obtaining the fixed device structure connection data;

[0024] Step S136: performing topological structure analysis according to the fixture structure connection data to obtain the fixture topological structure, and performing structural material property mapping on the fixture topological structure based on the fixture structure material property data to obtain a fixture topological structure model.

[0025] The present invention can obtain specific structural material data by extracting material features from the fixture structure data. This is crucial for material selection, performance evaluation and subsequent analysis. For example, physical properties such as material strength and corrosion resistance, as well as its performance under specific environmental conditions, can be determined. Classifying the structural data of the fixture can help clarify the relationship and dependency between components, so as to better understand the overall structure. This classification helps to accurately locate and process each component in subsequent analysis, improving the efficiency of system design and maintenance. The connection structure division based on the component structure data can identify the connection mode and association rules between each component. This helps to understand the functional distribution and data transmission path inside the device, and lays the foundation for subsequent connection structure analysis. By calculating the similarity of the component connection structure, the structural characteristics and similarities between different components can be quantified. This is very critical for identifying reused design patterns, optimizing connection methods or discovering potential design defects. The device connection structure and component structure are integrated according to the connection structure similarity data, and the structure and relationship network of the entire fixture can be clearly described. This integration helps system engineers or designers to fully understand the functions and performance characteristics of the device. Through topological structure analysis, the overall layout, data flow path and key nodes of the fixture can be deeply understood. This kind of analysis is of great significance for optimizing structural design, improving performance and reducing the probability of failure.

[0026] Optionally, step S14 is specifically:

[0027] Step S141: extracting ski board material features from the ski board structure data to obtain ski board material data, and performing material strength characteristic analysis based on the ski board material data to obtain ski board material strength data;

[0028] Step S142: classifying the snowboard structure data into snowboard hierarchical categories, thereby obtaining snowboard hierarchical structure data;

[0029] Step S143: classifying the material strength according to the snowboard material strength data, thereby obtaining high-strength material data and low-strength material data;

[0030] Step S144: dividing the snowboard hierarchical structure data into high-strength material hierarchical structure data according to the high-strength material data, thereby obtaining high-strength material hierarchical structure data; dividing the snowboard hierarchical structure data into low-strength material hierarchical structure data according to the low-strength material data, thereby obtaining low-strength material hierarchical structure data;

[0031] Step S145: constructing a three-dimensional high-strength material hierarchy structure model based on the high-strength material hierarchy structure data; constructing a three-dimensional low-strength material hierarchy structure model based on the low-strength material hierarchy structure data;

[0032] Step S146: Performing ski board hierarchical integration on the three-dimensional high-strength material hierarchical structure model and the three-dimensional low-strength material hierarchical structure model, thereby obtaining a ski board strength structure model.

[0033] The present invention can obtain key characteristics of various materials, such as density, strength, elastic modulus, etc., by extracting material characteristics from the structural data of the ski device. These data are crucial for subsequent design and analysis because the performance of different materials directly affects the overall performance and durability of the ski device. Hierarchical classification of the structural data of the ski device helps to understand the complexity of the device and the relationship between different parts. This hierarchical data can provide guidance for subsequent design optimization to ensure the structural rationality and optimized performance of the device. Classification of materials (high strength and low strength) based on the extracted material strength data helps to select appropriate materials during the design process. High-strength materials are usually used to withstand greater pressure and stress, while low-strength materials may be used for lightweight and flexible parts, thereby balancing performance and cost in the overall design. Combining structural data with material strength data can make more refined hierarchical divisions. This classification helps to optimize the structure of the device, ensuring that high-strength materials are in positions that withstand the greatest stress, while using low-strength materials to optimize overall weight and flexibility. Based on the hierarchical data of high-strength and low-strength materials, three-dimensional models are constructed and integrated. These models not only reflect the physical form of the device, but also take into account the mechanical properties of the material. Through this integration, designers can predict the intensity distribution and overall performance of the device in actual use.

[0034] Optionally, step S2 specifically includes:

[0035] Step S21: integrating the working conditions of the ski device according to the ski device design data, thereby obtaining the ski device design working condition data;

[0036] Step S22: performing mechanical load simulation on the design working condition data of the ski device through the ski device structure model, thereby obtaining mechanical load simulation data of the ski device;

[0037] Step S23: performing a Monte Carlo random environmental condition simulation according to the design working condition data of the ski device, thereby obtaining environmental condition simulation data;

[0038] Step S24: performing environmental device performance simulation on the ski device structure model according to the environmental condition simulation data, thereby obtaining ski device environmental performance simulation data;

[0039] Step S25: performing load simulation coupling on the ski device environmental performance simulation data and the ski device mechanical load simulation data, so as to obtain ski load simulation data.

[0040] The present invention integrates the working conditions of the ski device according to the design data, including usage scenarios, operating conditions, load expectations, etc., so as to clarify the design working condition data. These data are the basis for subsequent simulation and analysis, ensuring that the diversity and complexity of actual usage conditions are taken into account during the design process. The structural model of the ski device is used to perform mechanical load simulation on the design working condition data. This includes analyzing the mechanical properties of the device such as stress, strain, and deformation under various load conditions. Through simulation, the structural stability and safety of the device under different load conditions can be evaluated to help optimize the design and material selection. Monte Carlo random simulation is performed based on the design working condition data to simulate the changes and uncertainties under different environmental conditions. This method can capture the potential impact of environmental factors (such as temperature changes, wind, humidity, etc.) on the performance of the device and improve the robustness and reliability of the design. Using environmental condition simulation data, the structural model of the ski device is simulated for performance. This includes analyzing the durability, protection performance and long-term use effect of the device under different environmental conditions. By simulating the impact of the environment on the device, the material selection and design scheme can be optimized to ensure that the device can operate stably and maintain performance in various environments. The environmental performance simulation data and the mechanical load simulation data are coupled for analysis. This coupled simulation can comprehensively consider the complete load conditions of the device under real working conditions, including the combined effects of environmental influences and external mechanical loads on the device. Through comprehensive analysis, designers can evaluate the overall performance and stability of the device and make necessary optimizations and improvements.

[0041] Optionally, step S22 is specifically:

[0042] Step S221: extracting load condition characteristics of the ski device design condition data, thereby obtaining the ski device design load data;

[0043] Step S222: performing high load level division according to the ski device design load data, thereby obtaining design high load data;

[0044] Step S223: calculating the excess load coefficient for the designed high load data to obtain excess load data, and selecting an excess load working condition for the designed working condition data of the ski device based on the excess load data to obtain excess load working condition data;

[0045] Step S224: performing mechanical load simulation on the ski device design working condition data through the ski device structure model, thereby obtaining ski device design mechanical load simulation data;

[0046] Step S225: performing mechanical load simulation on the excess load working condition data through the ski device structure model, thereby obtaining excess mechanical load simulation data of the ski device;

[0047] Step S226: merging the ski device design mechanical load simulation data and the ski device excess mechanical load simulation data to obtain the ski device mechanical load simulation data.

[0048] The present invention can extract key load condition characteristics by analyzing the design working condition data of the ski device. These characteristics include information such as force, pressure, torque, etc. that the device bears under different operating conditions. The purpose of this step is to ensure that the design can cover all possible working conditions, so as to ensure the safety and stability of the ski device in actual use. According to the design load data, the load levels are divided into different levels or categories. This classification can help engineers understand more accurately under what circumstances the ski device will face higher loads, and help to focus on solving possible strength and durability problems in the design stage. The excess load factor is calculated to consider safety factors and life prediction in the design. The excess load data specifies the load conditions outside the normal operating range to ensure that the design is strong enough to cope with unexpected or extreme situations. The excess load condition data is selected to establish appropriate design boundary conditions to ensure the reliability of the device under various adverse conditions. The design working condition data and the excess load condition data are subjected to mechanical load simulation through the structural model. This simulation helps to predict the various mechanical loads that the device bears in actual use, such as stress, deformation, fatigue, etc. Through simulation, engineers can evaluate the strength and durability of the design and make necessary optimizations and adjustments. The design mechanical load simulation data and excess mechanical load simulation data are combined to obtain complete mechanical load simulation data. These data are the key output of the entire design process and provide the basis for subsequent structural analysis, optimization and verification. By comprehensively analyzing the combined data, the engineering team can ensure that the ski device can operate safely and reliably under various designed working conditions.

[0049] Optionally, step S3 specifically includes:

[0050] Step S31: meshing the ski device structure model to obtain a device structure meshing model;

[0051] Step S32: performing device load stress calculation on the device structure mesh division model according to the ski load simulation data, thereby obtaining ski device load stress data;

[0052] Step S33: performing stress distribution analysis of ski device parts on the ski device load stress data, thereby obtaining ski device stress distribution data;

[0053] Step S34: extracting the ski device structure strength characteristics from the ski device structure model, thereby obtaining the ski device structure strength data;

[0054] Step S35: Performing a load stress risk assessment on a part according to the stress distribution data of the ski device and the structural strength data of the ski device, thereby obtaining load stress risk data.

[0055] In the present invention, meshing is the process of decomposing the ski device structure model into multiple small areas or units. These small areas are called mesh units and are used for subsequent numerical calculations and analysis. The mesh model after division can capture the geometry and complexity of the device structure more accurately, providing a basis for subsequent load stress calculations. Based on the device structure meshing model, the device load stress calculation is performed using the ski load simulation data. This step determines the load stress to which each mesh unit is subjected, including force, pressure, torque, etc. These data are key indicators for evaluating the stress conditions of the device in actual use, helping engineers understand the stress distribution of the device under various working conditions. The load stress data is analyzed to obtain the stress distribution of each part of the ski device. This analysis helps to identify which parts are subjected to higher stress, which may lead to fatigue or damage. Engineers can optimize the design based on these data to ensure that the strength and durability of each part can meet the design requirements. The structural strength characteristic data of the device are extracted from the structural model. These data describe the physical properties of the material strength, fracture toughness, etc. of each part of the device. Combined with the stress distribution data, engineers can evaluate the safety margin of the device under the design load and perform structural optimization. Based on stress distribution data and structural strength data, a load stress risk assessment is performed on the parts. This assessment aims to identify which parts are at risk under load conditions and may need to be strengthened or adjusted in design. Accurate risk assessment can reduce uncertainty and failure risks in the design and ensure the reliability and safety of the device during use.

[0056] Optionally, step S35 is specifically:

[0057] According to the ski device structure strength data, the device structure strength is divided to obtain high-strength device structure data and low-strength device structure data;

[0058] According to the stress distribution data of the ski device, the stress concentration structure is divided, so as to obtain the stress concentration device structure data and the stress uniform device structure data;

[0059] Perform structural intersection operations on high-strength device structure data and stress-uniform device structure data to obtain low-load stress risk structure data;

[0060] Perform structural intersection operations on low-strength device structure data and stress concentration device structure data to obtain high-load stress risk structure data;

[0061] The low load stress risk structure data and the high load stress risk structure data are merged in structural space to obtain the load stress risk data.

[0062] The present invention can clarify which parts have high strength and can withstand large loads and stresses, and which parts have low strength and need to be designed more carefully to avoid failure or damage by dividing them according to the structural strength data of the ski device. This division helps designers to choose appropriate materials and design parameters when building ski devices to ensure that the device has sufficient strength in actual use, thereby improving its durability and safety. According to the stress distribution data of the ski device, it is identified which parts or areas have stress concentration, that is, areas with large local stress, and which parts have uniform stress distribution and relatively small stress. This analysis can help designers avoid or reduce the existence of stress concentration areas, thereby reducing the risk of fatigue damage of the device, and optimize the structural design to distribute stress more evenly and extend the service life of the device. By performing intersection operations on the device structure data with high strength and suitable stress distribution, the areas with both high strength and high stress distribution are determined, which helps to identify areas that may be subject to dual challenges, that is, those device structures that require not only high strength but also reasonable stress distribution, so as to focus on and optimize the design of these areas. The low load stress risk structure data and the high load stress risk structure data are combined to obtain the overall load stress risk data. Bringing together all key structural risk areas provides designers with a comprehensive perspective, ensuring they fully consider the safety and performance of the installation during the design process.

[0063] Optionally, step S4 is specifically:

[0064] Step S41: dividing the ski device stress risk structure of the ski device structure model based on the load stress risk data, thereby obtaining the ski device stress risk structure data;

[0065] Step S42: performing stress concentration area load calculation according to the ski device stress risk structure data and the ski load simulation data, thereby obtaining stress concentration area load data;

[0066] Step S43: performing stress distribution equilibrium optimization on the ski device structure model according to the ski device stress risk structure data, thereby obtaining a stress distribution equilibrium optimized structure model group;

[0067] Step S44: performing stress concentration area load minimization adjustment on the ski device structure model according to the stress concentration area load data, thereby obtaining a stress concentration optimized structure model group;

[0068] Step S45: merging the data of the stress distribution equilibrium optimization structure model group and the stress concentration optimization structure model group to obtain a ski device load stress equilibrium structure model set.

[0069] The present invention can identify which parts or areas have a high stress risk by dividing the ski device structure model based on the load stress risk data. This enables the designer to carry out subsequent analysis and optimization in a targeted manner, focusing on the key areas that may cause the device to fail or be damaged. According to the stress risk structure data obtained in the previous step and the ski load simulation data, the load calculation of the stress concentration area is carried out. This helps to quantify the force conditions of each stress concentration area and confirm which areas bear a large load, thereby providing data support for subsequent structural optimization. Based on the stress risk structure data of the ski device, the structural model is optimized for stress distribution balance. This step aims to adjust the design to make the stress distribution more uniform and avoid or reduce stress concentration. The optimized structural model group can improve the safety and durability of the device under the same load conditions. According to the load data of the stress concentration area, the ski device structure model is minimized to reduce the degree of stress concentration. This can reduce the potential risk of fatigue damage, extend the service life of the device, and improve its reliability. The structural model group that has undergone stress distribution balance optimization and stress concentration optimization is merged. In this way, an overall load stress balance structural model set can be obtained, which integrates all optimization measures and ensures the safety and performance stability of the device under different load conditions.

[0070] Optionally, step S5 specifically includes:

[0071] Step S51: obtaining customer ski equipment demand data, and extracting customer body shape features from the customer ski equipment demand data, thereby obtaining customer body shape data;

[0072] Step S52: performing skiing device material matching on the skiing device load stress balance structure model set according to the customer skiing device demand data, thereby obtaining a skiing device material matching model set;

[0073] Step S53: performing ski device maximum load matching on the ski device load stress balance structure model set according to the customer's body shape data, thereby obtaining a ski device load matching model set;

[0074] Step S54: performing a model intersection operation on the ski device material matching model set and the ski device load matching model set, thereby obtaining a balanced structural model of the customer's ski device.

[0075] The present invention obtains the customer's ski device demand data, and then matches the previously optimized ski device load stress balance structure model set according to the data. This process ensures that the ski device can meet the customer's specific needs when skiing, such as safety, comfort and performance requirements. Through matching, the structural model can be adjusted to meet the customer's personalized needs, such as specific load distribution, functional requirements or experience. By obtaining the customer's ski device demand data, the customer's body feature data is extracted from it. These data may include information such as height, weight, and foot size. These features are crucial for customizing ski devices because the comfort and compliance of the device largely depends on the degree of matching with the customer's body features. According to the customer's specific demand data, this step involves material matching of the ski device load stress balance structure model set. Different materials have a significant impact on the performance, weight and durability of the ski device. By selecting appropriate materials, it can be ensured that the ski device can achieve the best performance and safety during use, while meeting the customer's requirements for lightweight, strength and durability of the device. Based on the customer's body data, the ski device load stress balance structure model set is matched for maximum load. Considering the maximum load that the customer may bear, such as various forces and pressures during the sliding process, the structure can be adjusted through matching to ensure that the device can maintain stability and safety in various situations. The model intersection operation is performed on the ski device material matching model set and the ski device load matching model set. This ensures that the customer-customized ski device balanced structure model can comprehensively consider the material characteristics and load requirements, so as to achieve the best design effect. Through this process, customized ski devices that meet the personalized needs of customers can be provided, improving the user experience and the overall performance of the device. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments thereof made with reference to the following drawings:

[0077] Figure 1 A schematic diagram of the steps of the method for designing a ski device structure based on three-dimensional simulation of the present invention;

[0078] Figure 2 Detailed step flow diagram of step S1 in the present invention;

[0079] Figure 3 Detailed step flow diagram of step S2 in the present invention;

[0080] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0081] The technical method of the present invention is described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are 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 technicians in this field without creative work are within the scope of protection of the present invention.

[0082] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0083] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0084] To achieve this, please refer to Figures 1 to 3 The present invention provides a three-dimensional simulation design method based on the structure of a ski device, the method comprising the following steps:

[0085] Step S1: obtaining ski device design data, and extracting ski device structural features from the ski device design data, thereby obtaining ski board structural data; performing three-dimensional topological structure modeling based on the ski board structural data, thereby obtaining a ski device structural model;

[0086] In this embodiment, the ski design data including the length, width, material strength parameters, etc. of the skis are obtained from the ski manufacturer. With these data, computer-aided design (CAD) software can be used to extract the structural features of the skis, such as the geometric shape, curvature, and edge processing of the skis. For example, a parametric modeling tool in the CAD software is used to draw a specific ski structure diagram based on the design data to ensure that the design requirements are met and the structure is optimized to improve performance.

[0087] Step S2: integrating the working conditions of the ski device according to the ski device design data, thereby obtaining the ski device design working condition data, and performing ski load simulation on the ski device design working condition data through the ski device structure model, thereby obtaining ski load simulation data;

[0088] In this embodiment, according to the obtained ski design data, the working conditions of the ski, such as snow conditions, speed requirements, and sliding posture, are integrated to obtain detailed design working conditions data. The ski load simulation is performed using the previously established ski structure model. For example, the stress condition of the ski board is simulated by finite element analysis (FEA) software to verify the stability and reliability of the design under various working conditions.

[0089] Step S3: performing structural stress distribution analysis on the ski device structure model according to the ski load simulation data, thereby obtaining ski device stress distribution data, and performing load stress risk assessment according to the ski device stress distribution data, thereby obtaining load stress risk data;

[0090] In this embodiment, based on the ski load simulation data, the finite element analysis tool is used to perform stress distribution analysis on the ski device structure model. This includes analyzing the stress distribution of the ski board in various key areas and determining possible high stress areas. Based on the analysis results, a load stress risk assessment is performed, such as assessing which parts may have the risk of material fatigue or structural damage, thereby obtaining load stress risk data.

[0091] Step S4: performing ski device stress risk structure division on the ski device structure model based on the load stress risk data, thereby obtaining ski device stress risk structure data; performing ski device load stress balance optimization on the ski device structure model according to the ski device stress risk structure data and the ski load simulation data, thereby obtaining a ski device load stress balance structure model set;

[0092] In this embodiment, the ski device structure model is divided into stress risk structures according to the load stress risk data, for example, marking the areas that need additional reinforcement or optimization. Combined with the ski load simulation data, the ski device load stress balance optimization is performed, for example, adjusting the material distribution or strengthening the structure of a specific part to balance the stress distribution, thereby obtaining an optimized ski device load stress balance structure model set.

[0093] Step S5: Obtain customer ski equipment demand data, and perform customer demand load-balanced structure matching on the ski equipment load stress-balanced structure model set according to the customer ski equipment demand data, thereby obtaining the customer ski equipment balanced structure model.

[0094] In this embodiment, the customer's skiing device demand data is obtained from the skiing device manufacturer, and the optimized structure model set is matched with the customer's load-balanced structure according to the customer's skiing device demand data, including the customer's weight, skill level, and preference (such as speed or flexibility requirements). For example, the length, hardness, and edge design of the ski board are adjusted according to the customer's physical indicators and preferences to ensure that the final skiing device balanced structure model can maximize the satisfaction of the customer's expectations and needs.

[0095] Optionally, step S1 specifically includes:

[0096] Step S11: obtaining ski device design data, and extracting ski device structural features according to the ski device design data, thereby obtaining ski device structural data;

[0097] In this embodiment, the ski design data obtained from the ski manufacturer includes the geometric parameters (such as length, width, curvature), material properties (such as elastic modulus, density), design purpose and expected sliding conditions (such as snow quality, slope) of the ski. A three-dimensional model of the ski is created based on these design data using CAD software and parametric modeling technology. For example, a CAD tool is used to draw the geometric shape of the ski based on the design data, ensuring that the size and curvature meet the design requirements, and taking into account the material properties and the designer's aesthetic intentions.

[0098] Step S12: classifying the ski device structure data into device structure data, thereby obtaining the snowboard structure data and the fixing device structure data;

[0099] In this embodiment, the ski device structure data is classified into device structure, thereby obtaining the snowboard structure data and the fixing device structure data. At this stage, computer vision technology and machine learning algorithms can be used to automatically identify and classify the different components and structures of the ski device. For example, the shape, surface texture and edge features of the snowboard are analyzed by image processing technology, so as to classify them into different types, such as freestyle snowboards, alpine snowboards or downhill snowboards. At the same time, the fixing device structure data includes the straps, buckles or adjustment devices fixed to the snowboard, which can be modeled and classified in detail by CAD software.

[0100] Step S13: performing a fixture topology structure analysis according to the fixture structure data, thereby obtaining a fixture topology structure model;

[0101] In this embodiment, the fixture topology structure analysis is performed according to the fixture structure data to obtain the fixture topology structure model. In this step, the installation method and position of the fixture on the snowboard can be evaluated by CAD and simulation software. For example, by simulating different device layout schemes, the optimal fixture topology structure can be determined to ensure that it can provide stable support and optimal mechanical properties during use. This analysis usually includes considering the stability of the device under various load conditions and the dynamic effects during sliding. Finite element analysis (FEA) software and graph theory methods can also be used to analyze the connection, strength, stiffness and durability of the fixture in detail. For example, by applying different mechanical loads and constraints, the performance of the straps or adjustment devices under different working conditions is evaluated. These analysis results help to optimize the design of the device and ensure that it has good stability and safety in actual use.

[0102] Step S14: performing a snowboard strength structure analysis according to the snowboard structure data, thereby obtaining a snowboard strength structure model;

[0103] In this embodiment, the strength structure analysis of the snowboard is performed based on the snowboard structure data to obtain the strength structure model of the snowboard. In this stage, FEA software is used to analyze the stress distribution and deformation of the snowboard when subjected to different loads. For example, the bending strength and deflection of the snowboard are evaluated when descending at high speed or turning sharply. Through these analyses, the material selection and structural design of the board can be optimized to ensure that it can still provide good performance and controllability under various extreme use conditions.

[0104] Step S15: Combining the fixing device topology structure model and the ski board strength structure model into a ski device structure model, thereby obtaining a ski device structure model.

[0105] In this embodiment, the topological structure model of the fixture and the strength structure model of the ski board are combined to obtain the ski device structure model. Finally, the optimized fixture and ski board structure model are combined together through CAD software, and the overall assembly and design verification are performed. For example, it is ensured that the connection between the ski board and the fixture is firm and the device can maintain stability under various weather and terrain conditions. In this process, virtual simulation tests can also be performed to simulate the actual use of skiing to verify the reliability and safety of the design.

[0106] Optionally, step S13 is specifically:

[0107] Step S131: extracting structural material characteristics from the fixture structure data to obtain fixture structure material data, and performing material property analysis based on the fixture structure material data to obtain fixture structure material property data;

[0108] In this embodiment, structural material feature extraction is performed. This includes extracting material property data, such as strength, density, thermal conductivity, etc., from CAD files or actual physical structures. For example, for a reinforced concrete bridge, we can extract the specific specifications and material strength grades of concrete and steel bars from the design drawings, such as C30 concrete and Q235 steel. Then, through material property analysis, the various mechanical properties of these materials, such as compressive strength, elastic modulus, etc., can be calculated to obtain the structural material property data of the fixture.

[0109] Step S132: classifying the fixture structure data into structural components, thereby obtaining independent connection structure data and component structure data;

[0110] In this embodiment, the fixture structure data needs to be classified into structural components for further analysis and processing. For example, in a large mechanical equipment, the structural components can be divided into support structures, shell structures, power transmission components, etc. By classifying the function and position of each component, independent connection structure data (such as bolts, welding connections, etc.) and component structure data (such as the shape and size of each component, etc.) can be obtained.

[0111] Step S133: dividing the component connection structure according to the component structure data, thereby obtaining component connection structure data;

[0112] In this embodiment, the component connection structure can be divided according to the component structure data. For example, in a complex mechanical device, the connection methods between components may include bolt connection, welding, mortise and tenon connection, etc. By analyzing the connection method and structural characteristics of each component in detail, the component connection structure data, such as the connection method, connection material, etc., can be obtained.

[0113] Step S134: Calculating the structural similarity of the component connection structure data and the independent connection structure data, thereby obtaining connection structure similarity data;

[0114] In this embodiment, the structural similarity calculation is an important step for the component connection structure data. For example, in a multi-layered device structure, different component connection methods may affect the stability and strength of the overall structure. By calculating the similarity between different connection structures, their structural similarity can be quantified, providing a basis for subsequent structural integration.

[0115] Step S135: integrating the connection relationship of the device connection structure data and the component structure data according to the connection structure similarity data, thereby obtaining the fixed device structure connection data;

[0116] In this embodiment, the connection structure similarity data is crucial for the integration of device connection relationships. For example, when designing a complex mechanical system, the connection method between different components will directly affect the performance and stability of the overall system. By analyzing and integrating the connection structure similarity data, the optimal connection scheme and structural integration strategy can be determined to ensure the overall performance and reliability of the device.

[0117] Step S136: performing topological structure analysis according to the fixture structure connection data to obtain the fixture topological structure, and performing structural material property mapping on the fixture topological structure based on the fixture structure material property data to obtain a fixture topological structure model.

[0118] In this embodiment, it is an effective method to perform topological analysis on the connection of the fixture structure by graph theory. Graph theory is a branch of mathematics that specializes in the structure and properties of graphs, and is suitable for describing the structural relationship of various complex systems, including device structures in the engineering field. According to the obtained device connection data and component structure data, it is represented in the form of a graph. The nodes in the graph can represent the various components or connection structures of the device, and the edges represent the connection relationship between these components or structures. The connection mode and its influence between different components in the fixture are analyzed by using graph theory analysis methods, such as shortest path algorithm, connectivity analysis, etc. By identifying key nodes (such as highly connected components) and key paths (such as the main force transmission path), the overall stability and structural rationality of the device are evaluated. Based on the extracted fixture structure material property data, these data are mapped to the topological structure model obtained in the graph theory analysis. For example, the material type, strength characteristics and other information of each node (component) are associated with its position and connection relationship in the topological structure.

[0119] Optionally, step S14 is specifically:

[0120] Step S141: extracting ski board material features from the ski board structure data to obtain ski board material data, and performing material strength characteristic analysis based on the ski board material data to obtain ski board material strength data;

[0121] In this embodiment, it is key to extract material characteristics from the structural data of the skis. This includes identifying the type of material used in the skis, such as composite materials, glass fiber reinforced plastics, or wood. This can be extracted from the structural data of the skis provided by the manufacturer, or obtained experimentally. For example, by using X-ray diffraction analysis to determine the composition of the material, or using a scanning electron microscope (SEM) to observe the microstructure of the material. Based on these data, it is necessary to perform material strength property analysis to determine key properties such as tensile strength, flexural strength, and impact toughness of the material. For example, a tensile test is performed to measure the maximum stress and ductility of the material, or an impact test is used to evaluate its durability and damage tolerance.

[0122] Step S142: classifying the snowboard structure data into snowboard hierarchical categories, thereby obtaining snowboard hierarchical structure data;

[0123] In this embodiment, the snowboard structure data is hierarchically classified into surface layer, core layer and bottom layer, etc. Each layer is classified according to its function in the overall structure and material properties. For example, the surface layer is usually made of polyethylene or polyester resin with strong wear resistance, the core layer may be made of lightweight foam or wood, and the bottom layer needs to be made of wear-resistant and scratch-resistant materials.

[0124] Step S143: classifying the material strength according to the snowboard material strength data, thereby obtaining high-strength material data and low-strength material data;

[0125] In this embodiment, based on the material strength data extracted previously, the materials can be divided into high-strength and low-strength categories. For example, high-strength materials include carbon fiber composite materials or high-strength plastics, while low-strength materials are certain plastics or lightweight alloys. High-strength materials can be used for components that require higher performance, while low-strength materials can be used for economical products or beginners' snowboards.

[0126] Step S144: dividing the snowboard hierarchical structure data into high-strength material hierarchical structure data according to the high-strength material data, thereby obtaining high-strength material hierarchical structure data; dividing the snowboard hierarchical structure data into low-strength material hierarchical structure data according to the low-strength material data, thereby obtaining low-strength material hierarchical structure data;

[0127] In this embodiment, the hierarchical structure of the snowboard is divided based on the high-strength material data and the low-strength material data. The hierarchical structure where materials of different strengths appear is distinguished, for example, high-strength materials are generally used in the surface layer and the core layer to enhance the durability and performance of the snowboard, while low-strength materials are generally used in the bottom layer to reduce manufacturing costs and weight.

[0128] Step S145: constructing a three-dimensional high-strength material hierarchy structure model based on the high-strength material hierarchy structure data; constructing a three-dimensional low-strength material hierarchy structure model based on the low-strength material hierarchy structure data;

[0129] In this embodiment, the divided high-strength material hierarchy data is used to construct a three-dimensional high-strength material hierarchy model. This can be done through computer-aided design (CAD) software to ensure that the materials and structures of each layer meet the design requirements and performance standards. Similarly, the low-strength material hierarchy data is used to construct a three-dimensional low-strength material hierarchy model.

[0130] Step S146: Performing ski board hierarchical integration on the three-dimensional high-strength material hierarchical structure model and the three-dimensional low-strength material hierarchical structure model, thereby obtaining a ski board strength structure model.

[0131] In this embodiment, the three-dimensional high-strength material hierarchy model and the three-dimensional low-strength material hierarchy model are integrated to form a complete snowboard strength structure model. This includes considering the connection method and material transition between the layers to ensure that the overall structure has good stability and performance during use. For example, the strength and durability of the integrated structure under various conditions can be verified by finite element analysis (FEA).

[0132] Optionally, step S2 specifically includes:

[0133] Step S21: integrating the working conditions of the ski device according to the ski device design data, thereby obtaining the ski device design working condition data;

[0134] In this embodiment, the ski device operating condition integration is performed based on the ski device design data to obtain the ski device design operating condition data. This step involves integrating various design parameters such as ski board length, bending degree, material strength, etc. to ensure that the ski device performs well under various usage conditions. For example, design inputs from different departments, such as strength data from material science, aerodynamic properties of fluid mechanics, etc., can be integrated through engineering design software to generate comprehensive design operating condition data for the ski device.

[0135] Step S22: performing mechanical load simulation on the design working condition data of the ski device through the ski device structure model, thereby obtaining mechanical load simulation data of the ski device;

[0136] In this embodiment, mechanical load simulation is performed on the design working condition data of the ski device through the ski device structure model, thereby obtaining the mechanical load simulation data of the ski device. This step requires the use of computer-aided design (CAD) software and finite element analysis (FEA) tools to convert the design working condition data into specific mechanical load data. For example, the anisotropic loads borne by the ski board in various skiing scenes can be simulated, including stress and deformation caused by factors such as terrain changes, speed changes, and user actions.

[0137] Step S23: performing a Monte Carlo random environmental condition simulation according to the design working condition data of the ski device, thereby obtaining environmental condition simulation data;

[0138] In this embodiment, a Monte Carlo random environmental condition simulation is performed based on the design operating condition data of the ski device to obtain environmental condition simulation data. In this step, the performance of the ski device under different environmental conditions is simulated using the Monte Carlo method. For example, various weather conditions, terrain features, and user behaviors can be randomly generated to evaluate the performance of the ski device under various possible environmental conditions, thereby generating comprehensive environmental condition simulation data.

[0139] Step S24: performing environmental device performance simulation on the ski device structure model according to the environmental condition simulation data, thereby obtaining ski device environmental performance simulation data;

[0140] In this embodiment, the ski device structural model is simulated for environmental device performance according to the environmental condition simulation data, thereby obtaining the ski device environmental performance simulation data. In this step, the ski device is comprehensively simulated for environmental performance using multi-physics simulation software in combination with the environmental condition data obtained by the previous simulation. For example, key performance parameters such as the surface friction coefficient, material strength, and structural stability of the ski board under different temperature, humidity, and wind speed conditions can be simulated.

[0141] Step S25: performing load simulation coupling on the ski device environmental performance simulation data and the ski device mechanical load simulation data, so as to obtain ski load simulation data.

[0142] In this embodiment, load simulation coupling is performed on the environmental performance simulation data of the ski device and the mechanical load simulation data of the ski device, thereby obtaining ski load simulation data. The last step is to integrate and analyze the aforementioned environmental performance simulation data and mechanical load simulation data through an integrated tool to evaluate the comprehensive performance of the ski device under actual use. For example, the actual load response of the ski board under various environmental conditions can be predicted by combining the skier's operation mode and mechanical load data under different terrains to optimize the design or adjust the usage recommendations.

[0143] Optionally, step S22 is specifically:

[0144] Step S221: extracting load condition characteristics from the ski device design condition data, thereby obtaining the ski device design load data;

[0145] In this embodiment, it is necessary to extract load condition characteristics from the design condition data of the ski device. This usually involves analyzing and identifying various load conditions that may be encountered in skiing scenarios. First, various experimental data and simulation results are collected. These data include the mechanical properties of the skis under different snow qualities, temperatures and speeds, such as changes in torsion, bending and compression. By analyzing these data, key load condition characteristics can be identified, such as the maximum force and stress distribution during high-speed descents. Technically, sensors, numerical simulation software (such as numerical calculation libraries in MATLAB or Python), and finite element analysis tools are used to process and analyze the data to ensure that the extracted load characteristics accurately reflect the actual usage conditions.

[0146] Step S222: performing high load level division according to the ski device design load data, thereby obtaining design high load data;

[0147] In this embodiment, based on the extracted ski design load data, the engineering team divides the load levels into different high-load levels. This includes determining the priority and impact of load conditions so that they can be considered and processed in a targeted manner in the subsequent design stage. For example, the load data under high-speed downhill and different terrains are divided into major high-load categories so that the focus in the design is on improving the structural strength and stability.

[0148] Step S223: calculating the excess load coefficient for the designed high load data to obtain excess load data, and selecting an excess load working condition for the designed working condition data of the ski device based on the excess load data to obtain excess load working condition data;

[0149] In this embodiment, when calculating the excess load factor for the design high load data, the engineering team will consider safety factors and risk management. Empirical formulas or methods based on statistical analysis, such as probability statistics in reliability engineering, will be applied to determine the appropriate excess load factor. For example, an additional load of 20% is added to the design load to ensure that the ski device can still operate safely under abnormal load conditions. When selecting excess load conditions, the design condition data will be optimized based on these calculation results to ensure that the design can work stably under extreme conditions. Based on the collected excess load data and design requirements, critical conditions are defined. These conditions are the most challenging conditions that the device may encounter, such as maximum load, extreme temperature, maximum speed, etc. For example, if in the design of a ski board, for stress conditions under high-speed impact or extreme climate, an excess load factor of 1.2 to 1.5 times will be selected to ensure the reliability and safety of the design.

[0150] Step S224: performing mechanical load simulation on the ski device design working condition data through the ski device structure model, thereby obtaining ski device design mechanical load simulation data;

[0151] In this embodiment, when the mechanical load simulation of the design working condition data is performed through the ski device structure model, the geometric shape of the ski board is created using CAD software, and the load data of the ski device design working condition data is applied to the ski device structure model. For example, the load characteristic data in the ski device design working condition data is input into the model, and then the stress and deformation of the ski board under various working conditions are simulated by finite element analysis (FEA). This simulation not only considers static loads, but also can simulate dynamic loads, such as vibration and impact effects at different speeds, so as to evaluate the strength and stability of the structure.

[0152] Step S225: performing mechanical load simulation on the excess load working condition data through the ski device structure model, thereby obtaining excess mechanical load simulation data of the ski device;

[0153] In this embodiment, when performing mechanical load simulation on excess load condition data, the ski device structural model is also used for detailed analysis based on the calculated excess load data. Additional load conditions are applied to the model, and finite element analysis is performed to evaluate the response of the ski under these extreme load conditions. For example, the material strength and structural stability of the ski under extreme climate or collision conditions are simulated to ensure that the design can safely withstand the additional loads.

[0154] Step S226: merging the ski device design mechanical load simulation data and the ski device excess mechanical load simulation data to obtain the ski device mechanical load simulation data.

[0155] In this embodiment, the design mechanical load simulation data and the excess mechanical load simulation data are combined. The simulation results under different working conditions are comprehensively considered to obtain the overall mechanical load simulation data. This includes comparing the maximum stress, deformation and other key performance indicators under different working conditions to determine the effectiveness and optimization space of the design. For example, the stress distribution diagram under different load conditions is analyzed, and the performance of different design schemes is compared to guide the structural adjustment and optimization of the final product.

[0156] Optionally, step S3 specifically includes:

[0157] Step S31: meshing the ski device structure model to obtain a device structure meshing model;

[0158] In this embodiment, the ski device structural model is meshed to obtain the device structural mesh model. First, the three-dimensional structural model of the ski device needs to be converted into a computer-processable mesh model. This mesh is usually composed of many small units or elements, each unit having a specific geometric shape and size. For example, finite element analysis software such as ABAQUS or ANSYS can be used for meshing. For the example of the ski board, the meshing may be adjusted according to the overall shape and structural details of the ski board to ensure that the mechanical response and stress distribution of the device can be accurately simulated in subsequent steps.

[0159] Step S32: performing device load stress calculation on the device structure mesh division model according to the ski load simulation data, thereby obtaining ski device load stress data;

[0160] In this embodiment, the device load stress calculation is performed on the device structure mesh division model according to the ski load simulation data, so as to obtain the ski device load stress data. This involves numerical simulation and calculation of the stress conditions of the ski board under actual use conditions. For example, the load data of the ski board in various simulation scenarios can be used, such as wind resistance at different speeds, stress distribution when carrying different weights, etc. Through finite element analysis software, these load simulation data can be applied to the previously established mesh model to calculate the stress conditions of various parts of the ski board structure for further analysis and evaluation.

[0161] Step S33: performing stress distribution analysis of ski device parts on the ski device load stress data, thereby obtaining ski device stress distribution data;

[0162] In this embodiment, the ski device load stress data is subjected to stress distribution analysis of the ski device parts, thereby obtaining the ski device stress distribution data. In this step, the stress conditions of different parts of the ski device need to be analyzed and evaluated in detail. For example, the stress distribution conditions of the edges, central areas, and joints of the ski board can be checked to identify the high stress concentration areas or potential structural weaknesses. Through these analyses, designers can optimize the structural design of the device and improve its performance and durability.

[0163] Step S34: extracting the ski device structure strength characteristics from the ski device structure model, thereby obtaining the ski device structure strength data;

[0164] In this embodiment, the ski device structural strength feature extraction is performed on the ski device structural model to obtain the ski device structural strength data. In this step, it is necessary to extract key structural characteristic parameters from the mesh model of the ski board, such as the maximum stress point, the main stress direction, the strain distribution, etc. These characteristic data can help engineers evaluate the structural strength of the device in actual use and determine its safety performance when subjected to external loads. For example, stress cloud maps and main stress direction maps can be automatically generated by finite element analysis software to intuitively display the strength characteristics of the device.

[0165] Step S35: Performing a load stress risk assessment on a part according to the stress distribution data of the ski device and the structural strength data of the ski device, thereby obtaining load stress risk data.

[0166] In this embodiment, the load stress risk assessment of each part is performed based on the stress distribution data of the ski device and the structural strength data of the ski device, thereby obtaining the load stress risk data. In the last step, the risk assessment of different parts of the device will be performed in combination with the previous stress analysis and structural strength assessment. This includes determining whether the stress level of each key part is within the safe range and whether there is a risk of exceeding the material strength or design limit. For example, statistical methods or deterministic analysis can be used to calculate the load stress risk index of different parts, and provide engineers with suggestions for optimizing the design or correcting the structure to ensure the safety and reliability of the device under various conditions of use.

[0167] Optionally, step S35 is specifically:

[0168] According to the ski device structure strength data, the device structure strength is divided to obtain high-strength device structure data and low-strength device structure data;

[0169] In this embodiment, the device structure can be divided into two categories: high strength and low strength according to the structural strength data of the ski device. The structural strength data here may include information such as the tensile strength, bending strength, and torsional strength of the material. For example, suppose that the material strength data of a certain ski device at key parts are determined through material testing and engineering analysis. High-strength device structure data refers to those structural components with higher strength in key parts and higher load-bearing capacity; low-strength device structure data refers to components with lower strength than the former and more emphasis on lightweight and flexibility in design. For example, if the design standard is to withstand the maximum weight, then the high-strength structure can be defined as a device component that can withstand a force of more than 500 kilograms, and the low-strength structure is correspondingly lower than this value.

[0170] According to the stress distribution data of the ski device, the stress concentration structure is divided, so as to obtain the stress concentration device structure data and the stress uniform device structure data;

[0171] In this embodiment, according to the stress distribution data of the ski device, the device structure can be divided into two categories: stress concentration and uniform stress distribution. Stress concentration refers to the situation where the stress value in certain specific areas or points is significantly higher than that in the surrounding areas; uniform stress distribution means that the stress distribution of each part is relatively even. For example, stress distribution data obtained by means of finite element analysis can help determine the stress concentration area and uniform distribution area of ​​the device.

[0172] Perform structural intersection operations on high-strength device structure data and stress-uniform device structure data to obtain low-load stress risk structure data;

[0173] In this embodiment, the high-strength device structure data and the stress uniform device structure data are subjected to a structural intersection operation to identify and obtain the structure data with low load stress risk. This means selecting those components that have high key strength requirements (such as key connection points and load-bearing areas) but relatively uniform stress distribution. For example, high-strength device data refers to those components that are more structurally important and need to withstand high loads, while stress uniformity refers to the situation where these components are less affected by stress during use.

[0174] Perform structural intersection operations on low-strength device structure data and stress concentration device structure data to obtain high-load stress risk structure data;

[0175] In this embodiment, the low-strength device structure data and the stress concentration device structure data are subjected to a structural intersection operation to obtain the structure data with high load stress risk. This means selecting those components that have low strength requirements but have more concentrated stress distribution during use. For example, low-strength device data refers to those components that are designed to be lightweight or use softer materials, while stress concentration means that these components are prone to concentrated force or high stress during use.

[0176] The low load stress risk structure data and the high load stress risk structure data are merged in structural space to obtain the load stress risk data.

[0177] In this embodiment, the low load stress risk structural data and the high load stress risk structural data are spatially merged to comprehensively analyze and evaluate the load stress risk of the overall device. This can be done through 3D modeling software or CAD tools, matching and merging the spatial positions of the two types of risk data with the positions of the actual components. For example, a comprehensive structural risk analysis model can be created so that engineers can accurately assess the stress risk level of the device under different use conditions, and make further design optimization or improvements based on this.

[0178] Optionally, step S4 is specifically:

[0179] Step S41: dividing the ski device stress risk structure of the ski device structure model based on the load stress risk data, thereby obtaining the ski device stress risk structure data;

[0180] In this embodiment, based on the obtained load stress risk data, the structural model of the ski device is divided to identify structural components with potential risks. These components have higher structural risks due to stress concentration or other factors. Components in the ski device structural model that are associated with high stress or stress concentration are marked as risk structures.

[0181] Step S42: performing stress concentration area load calculation according to the ski device stress risk structure data and the ski load simulation data, thereby obtaining stress concentration area load data;

[0182] In this embodiment, the stress risk structure data of the ski device and the actual ski load simulation data are used to perform detailed stress concentration area load calculations. The specific load conditions of those marked as stress concentration areas are quantified for further optimization and adjustment. For structural components identified as stress concentration areas, such as a key support column, the specific load conditions such as pressure and bending force in actual use are calculated through numerical simulation and experimental data.

[0183] Step S43: performing stress distribution equilibrium optimization on the ski device structure model according to the ski device stress risk structure data, thereby obtaining a stress distribution equilibrium optimized structure model group;

[0184] In this embodiment, based on the stress risk structure data of the ski device, the overall structural model is optimized for stress distribution balance. The purpose is to adjust the design of the structure or material selection to ensure that the stress is more evenly distributed inside the structure and reduce possible stress concentration areas. Consider using different materials or design adjustments, such as increasing the cross-section of the structure or changing the connection method, to improve the strength distribution balance of the overall structure and reduce the occurrence of stress concentration.

[0185] Step S44: performing stress concentration area load minimization adjustment on the ski device structure model according to the stress concentration area load data, thereby obtaining a stress concentration optimized structure model group;

[0186] In this embodiment, the structural model is adjusted according to the load data of the stress concentration area to minimize the load conditions in these areas. This step involves local reinforcement of the structure, redesign of key connection points, or use of specific support structures. For the stress concentration areas found by calculation, it can be considered to add additional support or enhance the material strength of the area to reduce the load concentration effect on these components.

[0187] Step S45: merging the data of the stress distribution equilibrium optimization structure model group and the stress concentration optimization structure model group to obtain a ski device load stress equilibrium structure model set.

[0188] In this embodiment, the data of the structural model group that has undergone stress distribution balance optimization and stress concentration optimization is merged to form a set of structural models with load stress balance of the ski device. This set comprehensively considers the strength of the structure, the balance of stress distribution, and the minimization of the load concentration area to improve the overall safety and performance stability. The optimized structural models are combined to ensure that the design requirements are met in each key component and the overall structure, while maintaining the overall balance and load balance of the structure to cope with different usage conditions and load conditions.

[0189] Optionally, step S5 specifically includes:

[0190] Step S51: obtaining customer ski equipment demand data, and extracting customer body shape features from the customer ski equipment demand data, thereby obtaining customer body shape data;

[0191] In this embodiment, the customer's ski equipment demand data is obtained through the manufacturer or dealer, and the customer's body shape features are extracted to obtain the customer's body shape data. First, it is necessary to collect the customer's height, weight, leg length, arm length and other relevant data, which are crucial for designing customized ski equipment. For example, the customer's body shape data is obtained through 3D scanning technology, or sensors are used to measure the dimensions of key parts, such as knee bending angle and leg length. Accurate acquisition of these data can help ensure the load balance and comfort of the ski equipment in subsequent steps.

[0192] Step S52: performing skiing device material matching on the skiing device load stress balance structure model set according to the customer skiing device demand data, thereby obtaining a skiing device material matching model set;

[0193] In this embodiment, the ski device material is matched to the ski device load stress balance structure model set according to the customer's ski device demand data. The key to this step is to select suitable materials to ensure that the device can withstand the customer's weight and the stress caused by the skiing environment when in use. For example, using the principles of material science and engineering, combined with the customer's body data and skiing needs, a structural model of a material with good strength, durability and lightweight characteristics is selected from the ski device load stress balance structure model set. Finite element analysis (FEA) can be used to simulate the stress response of different materials to optimize material selection.

[0194] Step S53: performing ski device maximum load matching on the ski device load stress balance structure model set according to the customer's body shape data, thereby obtaining a ski device load matching model set;

[0195] In this embodiment, the ski device load stress balance structural model set is matched to the maximum load of the ski device according to the customer's body shape data. According to the customer's body load distribution and skiing habits, the optimal and most suitable load distribution model for the customer is selected from the ski device load stress balance structural model set to minimize the uncomfortable pressure and load of the device on the body. For example, according to the customer's body center of gravity and skiing action characteristics, a structural model with the most suitable center of gravity position and support point layout is selected from the ski device load stress balance structural model set to minimize the pressure and discomfort of the device on the body and improve the comfort and stability of sliding. CAD software can be used for virtual simulation and simulation to verify the designed load distribution and structural stability.

[0196] Step S54: performing a model intersection operation on the ski device material matching model set and the ski device load matching model set, thereby obtaining a balanced structural model of the customer's ski device.

[0197] In this embodiment, the model intersection operation is performed on the material matching model set and the load matching model set of the ski device, with the purpose of obtaining a balanced structural model of the customer's ski device. This step uses computer-aided design and optimization methods to comprehensively consider factors such as material properties, load distribution, and structural stability to generate the final device design. For example, the model set is merged through CAD software, and the design is iterated and adjusted using a multidisciplinary optimization algorithm to ensure that the device achieves the best performance and user experience in all aspects.

[0198] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0199] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A three-dimensional simulation design method based on the structure of a ski device, characterized in that: The following steps are involved: Step S1: obtaining ski device design data, and extracting ski device structural features from the ski device design data, thereby obtaining ski board structural data; Performing three-dimensional topological structure modeling according to the ski structure data, thereby obtaining a ski device structure model; Step S2: integrating the working conditions of the ski device according to the ski device design data, thereby obtaining the ski device design working condition data, and performing ski load simulation on the ski device design working condition data through the ski device structure model, thereby obtaining ski load simulation data; Step S3: performing structural stress distribution analysis on the ski device structure model according to the ski load simulation data, thereby obtaining ski device stress distribution data, and performing load stress risk assessment according to the ski device stress distribution data, thereby obtaining load stress risk data; Step S4: dividing the ski device stress risk structure of the ski device structure model based on the load stress risk data, thereby obtaining the ski device stress risk structure data; According to the ski device stress risk structure data and the ski load simulation data, the ski device load stress balance optimization is performed on the ski device structure model, so as to obtain the ski device load stress balance structure model set; Step S5: Obtain customer ski equipment demand data, and perform customer demand load-balanced structure matching on the ski equipment load stress-balanced structure model set according to the customer ski equipment demand data, thereby obtaining the customer ski equipment balanced structure model.

2. The method for designing a ski device structure based on three-dimensional simulation according to claim 1, characterized in that: Step S1 is specifically as follows: Step S11: obtaining ski device design data, and extracting ski device structural features according to the ski device design data, thereby obtaining ski device structural data; Step S12: classifying the ski device structure data into device structure data, thereby obtaining the snowboard structure data and the fixing device structure data; Step S13: performing a topological structure analysis of the fixture according to the fixture structure data, thereby obtaining a topological structure model of the fixture; Step S14: performing a snowboard strength structure analysis according to the snowboard structure data, thereby obtaining a snowboard strength structure model; Step S15: Combining the fixing device topology structure model and the ski board strength structure model into a ski device structure model, thereby obtaining a ski device structure model.

3. The method for designing a ski device structure based on three-dimensional simulation according to claim 2, characterized in that: Step S13 is specifically as follows: Step S131: extracting structural material characteristics from the fixture structure data to obtain fixture structure material data, and performing material property analysis based on the fixture structure material data to obtain fixture structure material property data; Step S132: classifying the fixture structure data into structural components, thereby obtaining independent connection structure data and component structure data; Step S133: dividing the component connection structure according to the component structure data, thereby obtaining component connection structure data; Step S134: Calculating the structural similarity of the component connection structure data and the independent connection structure data, thereby obtaining connection structure similarity data; Step S135: integrating the connection relationship of the device connection structure data and the component structure data according to the connection structure similarity data, thereby obtaining the fixed device structure connection data; Step S136: performing topological structure analysis according to the fixture structure connection data to obtain the fixture topological structure, and performing structural material property mapping on the fixture topological structure based on the fixture structure material property data to obtain a fixture topological structure model.

4. The method for designing a ski device structure based on three-dimensional simulation according to claim 2, characterized in that: Step S14 is specifically as follows: Step S141: extracting ski board material features from the ski board structure data to obtain ski board material data, and performing material strength characteristic analysis based on the ski board material data to obtain ski board material strength data; Step S142: classifying the snowboard structure data into snowboard hierarchical categories, thereby obtaining snowboard hierarchical structure data; Step S143: classifying the material strength according to the snowboard material strength data, thereby obtaining high-strength material data and low-strength material data; Step S144: dividing the snowboard hierarchy data into high-strength material hierarchy data according to the high-strength material data, thereby obtaining high-strength material hierarchy data; Dividing the snowboard hierarchy data into low-strength material hierarchical structures according to the low-strength material data, thereby obtaining low-strength material hierarchy data; Step S145: constructing a three-dimensional high-strength material hierarchy structure model based on the high-strength material hierarchy structure data; constructing a three-dimensional low-strength material hierarchy structure model based on the low-strength material hierarchy structure data; Step S146: Performing ski board hierarchical integration on the three-dimensional high-strength material hierarchical structure model and the three-dimensional low-strength material hierarchical structure model, thereby obtaining a ski board strength structure model.

5. The method for designing a ski device structure based on three-dimensional simulation according to claim 1, characterized in that: Step S2 is specifically as follows: Step S21: integrating the working conditions of the ski device according to the ski device design data, thereby obtaining the ski device design working condition data; Step S22: performing mechanical load simulation on the design working condition data of the ski device through the ski device structure model, thereby obtaining mechanical load simulation data of the ski device; Step S23: performing a Monte Carlo random environmental condition simulation according to the design working condition data of the ski device, thereby obtaining environmental condition simulation data; Step S24: performing environmental device performance simulation on the ski device structure model according to the environmental condition simulation data, thereby obtaining ski device environmental performance simulation data; Step S25: performing load simulation coupling on the ski device environmental performance simulation data and the ski device mechanical load simulation data, so as to obtain ski load simulation data.

6. The method for designing a ski device structure based on three-dimensional simulation according to claim 5, characterized in that: Step S22 is specifically as follows: Step S221: extracting load condition characteristics from the ski device design condition data, thereby obtaining the ski device design load data; Step S222: performing high load level division according to the ski device design load data, thereby obtaining design high load data; Step S223: calculating the excess load coefficient for the designed high load data to obtain excess load data, and selecting an excess load working condition for the designed working condition data of the ski device based on the excess load data to obtain excess load working condition data; Step S224: performing mechanical load simulation on the ski device design working condition data through the ski device structure model, thereby obtaining ski device design mechanical load simulation data; Step S225: performing mechanical load simulation on the excess load working condition data through the ski device structure model, thereby obtaining excess mechanical load simulation data of the ski device; Step S226: merging the ski device design mechanical load simulation data and the ski device excess mechanical load simulation data to obtain the ski device mechanical load simulation data.

7. The method for designing a ski device structure based on three-dimensional simulation according to claim 1, characterized in that: Step S3 is specifically as follows: Step S31: meshing the ski device structure model to obtain a device structure meshing model; Step S32: performing device load stress calculation on the device structure mesh division model according to the ski load simulation data, thereby obtaining ski device load stress data; Step S33: performing stress distribution analysis of ski device parts on the ski device load stress data, thereby obtaining ski device stress distribution data; Step S34: extracting the ski device structure strength characteristics from the ski device structure model, thereby obtaining the ski device structure strength data; Step S35: Performing a load stress risk assessment on a part according to the stress distribution data of the ski device and the structural strength data of the ski device, thereby obtaining load stress risk data.

8. The ski device structure three-dimensional simulation design method according to claim 7, characterized in that: Step S35 is specifically as follows: According to the ski device structure strength data, the device structure strength is divided to obtain high-strength device structure data and low-strength device structure data; According to the stress distribution data of the ski device, the stress concentration structure is divided, so as to obtain the stress concentration device structure data and the stress uniform device structure data; Perform structural intersection operations on high-strength device structure data and stress-uniform device structure data to obtain low-load stress risk structure data; Perform structural intersection operations on low-strength device structure data and stress concentration device structure data to obtain high-load stress risk structure data; The low load stress risk structure data and the high load stress risk structure data are merged in structural space to obtain the load stress risk data.

9. The ski device structure three-dimensional simulation design method according to claim 1, characterized in that: Step S4 is specifically as follows: Step S41: dividing the ski device stress risk structure of the ski device structure model based on the load stress risk data, thereby obtaining the ski device stress risk structure data; Step S42: performing stress concentration area load calculation according to the ski device stress risk structure data and the ski load simulation data, thereby obtaining stress concentration area load data; Step S43: performing stress distribution equilibrium optimization on the ski device structure model according to the ski device stress risk structure data, thereby obtaining a stress distribution equilibrium optimized structure model group; Step S44: performing stress concentration area load minimization adjustment on the ski device structure model according to the stress concentration area load data, thereby obtaining a stress concentration optimized structure model group; Step S45: merging the data of the stress distribution equilibrium optimization structure model group and the stress concentration optimization structure model group to obtain a ski device load stress equilibrium structure model set.

10. The ski device structure three-dimensional simulation design method according to claim 1, characterized in that: Step S5 is specifically as follows: Step S51: obtaining customer ski equipment demand data, and extracting customer body shape features from the customer ski equipment demand data, thereby obtaining customer body shape data; Step S52: performing skiing device material matching on the skiing device load stress balance structure model set according to the customer skiing device demand data, thereby obtaining a skiing device material matching model set; Step S53: performing ski device maximum load matching on the ski device load stress balance structure model set according to the customer's body shape data, thereby obtaining a ski device load matching model set; Step S54: performing a model intersection operation on the ski device material matching model set and the ski device load matching model set, thereby obtaining a balanced structural model of the customer's ski device.

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