Automatic simulation platform and simulation method for crane control performance prediction
By using an automated simulation platform to achieve high-fidelity simulation modeling of the slewing system of a wheeled crane, the problems of high cost and long cycle in existing technologies have been solved, thereby improving simulation efficiency and product innovation speed.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-27
- Publication Date
- 2026-04-07
AI Technical Summary
Existing technologies for evaluating the control performance of wheeled crane slewing systems suffer from high testing costs, long development cycles, and high R&D barriers, especially in the simulation modeling of complex electromechanical-hydraulic systems where high-precision prediction is difficult to achieve.
An automated simulation platform for predicting crane control performance is provided, including a UI interaction system, a database management system, and a simulation modeling drive system. Through automated modeling and simulation, the technical threshold of simulation modeling is reduced, and high-fidelity simulation of electromechanical-hydraulic systems is achieved.
It achieves high-precision simulation calculations, reduces the knowledge requirements and software operation skills of R&D personnel, and significantly improves simulation efficiency and new product testing and verification efficiency.
Smart Images
Figure CN121808960A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The application belongs to the technical field of engineering machinery, and particularly relates to an automatic simulation platform and simulation method for crane control performance prediction. BACKGROUND
[0002] The wheeled crane has excellent mobility and powerful hoisting operation capacity, is widely used in various hoisting and carrying scenes such as infrastructure construction, port logistics and engineering construction, and its sales and possession have long been in the forefront of the industry, playing an important role in the national economic construction. The hoisting action of the wheeled crane is mainly completed by the slewing motion, the amplitude motion driven by the oil cylinder, the boom extension motion and the steel wire rope hoisting motion. Among them, the slewing system has the highest action frequency, and its characteristics of large inertia and flexible load result in that the slewing motion dynamic characteristics have a particularly prominent influence on the overall machine control performance. With the development of the wheeled crane hoisting operation towards large tonnage, multiple scenes and collaborative operation, the control performance of the slewing motion has become a core index affecting the hoisting efficiency, operation safety and operation comfort of the wheeled crane, and represents the market competitiveness of the wheeled crane product.
[0003] At present, the product research and development of the wheeled crane is developing towards specialization and customization to meet the differentiated needs of different application scenes, and this development trend puts forward higher requirements on the development efficiency of new products. At present, the evaluation method of the slewing system control performance mainly relies on the real vehicle test in the product verification stage, and this method has limitations such as high test cost and long development cycle. In recent years, the design method based on computer simulation has been widely used in the field of mechanical engineering. This method predicts the dynamic performance of the crane slewing system by establishing a virtual prototype model, and provides an effective verification means for the control performance evaluation in the product design stage. Compared with the traditional real vehicle test, the simulation technology can significantly shorten the development cycle and greatly reduce the development cost, and has become an important technical approach to improve the product innovation ability and market competitiveness.
[0004] Currently, engineering machinery system simulation widely adopts centralized parameter simulation modeling methods such as Simulink / AMESim, which provides an effective solution for model building of complex mechatronic hydraulic systems. However, there are still technical challenges in applying commercial simulation software to the control simulation of the crane slewing system: on the one hand, the slewing system involves many types of components with complex models, and its control performance is affected by the coupling of the electric control system, hydraulic transmission and mechanical structure, making it difficult to accurately predict the dynamic response characteristics of slewing motion; on the other hand, building a high-precision simulation model of the slewing system requires researchers to not only have a deep understanding of the functional architecture of the crane product, but also have cross-disciplinary simulation modeling capabilities, including simulation software operation, complex system parameterized modeling and special interface development. The increasing system complexity has significantly increased the threshold for the development of wheeled cranes, which has become a key technical bottleneck restricting the improvement of the design capability of the crane slewing system. SUMMARY
[0005] The purpose of the present application is to provide an automated simulation platform and simulation method for crane control performance prediction to significantly reduce the technical threshold for researchers to carry out high-fidelity simulation modeling of complex systems and improve the speed of innovation and iteration of crane products.
[0006] According to a first aspect of the embodiments of the present application, an automated simulation platform for crane control performance prediction is provided, comprising: a UI interaction system, a database management system and a simulation modeling driving system; The UI interaction system is used by researchers to set simulation parameters, start simulation tasks and view simulation results. The database management system is used to add, delete, modify and view data according to front-end input instructions, and returns the operation results. The simulation modeling driving system is used for automatic modeling and simulation. The database management system includes: a crane product configuration database, a three-dimensional model library, a component parameter database, a simulation model template database, a simulation task database, a simulation model database and a simulation result database. Among them, the crane product configuration database, the component parameter database and the simulation task database are relational databases based on MySQL database; the three-dimensional model library, the simulation model template database, the simulation model database and the simulation result database are used to store binary files and are based on MongoDB database.
[0007] In some optional embodiments of the present application, the crane product configuration database is used to store various product configurations of typical crane models, each model corresponds to a unique model ID, and calling this database can realize the mapping of the model ID to the key assembly or component model of the model. The element parameter database is used for storing parameters of hydraulic elements and mechanical parts required for simulation, including geometric dimensions, performance and efficiency, and the parameter list is stored in the form of a json string. Each type of part corresponds to a unique part ID. Calling the database can realize the mapping of part ID to part parameters. The simulation task database is used for storing setting information of each simulation task. The simulation platform sets a unique task ID for each simulation task and stores the vehicle model, product configuration and simulation working condition setting information corresponding to the task.
[0008] In some optional embodiments of the application, the three-dimensional model library is used for storing three-dimensional models of parts required for dynamic simulation, rigid body parts or assemblies, which are stored in the form of.stp or.igs format; flexible body parts are stored in the form of.op2 format. Calling the three-dimensional model library can realize the mapping of part ID to three-dimensional model of the part. The simulation model template database is used for storing code templates for generating simulation models. The code templates are stored in the form of text files. The database directly stores template files. Calling the database can realize the mapping of vehicle model ID to its modeling template file. The simulation model database is used for storing generated model files. Each simulation task generates a unique hydraulic system model, an electronic control system model and a dynamic simulation model. Calling the database can realize the mapping of task ID to its simulation model. The simulation result database is used for storing result files automatically generated by simulation software and result files generated by the simulation platform. Calling the database can realize the mapping of task ID to its simulation result data.
[0009] According to a second aspect of the embodiments of the application, an automatic simulation modeling method for a slewing system of a wheel crane is provided, comprising: Step one: input the wheel crane model through the simulation platform. The simulation platform queries the corresponding crane vehicle information in the material management system database according to the product model, analyzes the product BOM, and calls the hydraulic elements, mechanical parts and assembly models related to the slewing system. Step two: the simulation platform analyzes the hydraulic elements, mechanical parts and assembly models related to the slewing system called in step one one by one. The parts that need to be mathematically modeled request to call related key parameters from the element parameter database. In addition to querying the key parameters of the parts, the parts that need to be dynamically simulated also need to send a request to the three-dimensional model library according to the part ID to call the three-dimensional model. Step 3: Based on the wheeled crane model entered in Step 1, the simulation platform sends a request to the simulation model template database to call the simulation model template suitable for the current simulation task; and assigns values to the corresponding variables in the template according to the model parameters obtained in Step 2. In dynamic simulation, the 3D model retrieved in Step 2 is also imported into the simulation model, and assembly, constraint, and contact settings are executed to complete the simulation modeling, and the model is stored in the simulation model database. Step four: The simulation platform calls the simulation model established in step three, starts the simulation task according to the wheeled crane model entered in step one, and monitors the simulation progress until the simulation task is completed. Step 5: The simulation task is completed. The simulation platform reads the simulation calculation results of key physical quantities according to the settings, stores the simulation result files and simulation data in the simulation result database, queries the corresponding simulation results according to the simulation result category requested by the front-end UI, and displays them visually on the front-end interface.
[0010] In some optional embodiments of this application, the crane model information includes the crane's maximum lifting capacity, counterweight scheme, rigging and hook configuration parameters.
[0011] In some optional embodiments of this application, the hydraulic components related to the slewing system include a slewing main pump, a reversing buffer valve, a slewing hydraulic motor, a pilot valve assembly, and an oil tank. The mechanical components include slewing bearing, turntable, slewing gearbox, slewing gear, boom, hook and rope; The assembly models include the engine, transmission, power take-off, controller, and torque limiter.
[0012] Simulation modeling is accomplished through a combination of mathematical analytical modeling and dynamic modeling. In some optional embodiments of this application, mathematical analytical modeling is based on the analysis of the working principle of the components, and the input-output relationship of the components is calculated by direct analytical methods (e.g., the calculation of the output speed of the power take-off unit of a crane chassis). In some optional embodiments of this application, the lumped parameter method is used for mathematical modeling (e.g., modeling of a crane hydraulic system), with the component parameter variables that can be assigned values in the lumped parameter method modeling as the key parameters; Dynamic modeling involves analyzing the motion state and interaction relationships of a moving system to establish mathematical equations that describe the dynamic behavior of the physical system (e.g., modeling the slewing mechanism of a crane).
[0013] In some optional embodiments of this application, the key parameters of the three-dimensional model include the component geometry, assembly position, coefficient of friction, and mechanical properties; The geometric dimensions are used to generate the parametric model, the assembly position is used to drive the automatic assembly of parts in the dynamic simulation model, and the friction coefficient and mechanical performance parameters are used to set the constraints and material boundary conditions in the dynamic simulation model.
[0014] In some optional embodiments of this application, the model template is built based on the physical structure of the crane slewing system, which is divided into three parts: a decision control system, a hydraulic transmission system, and a mechanical actuator. The decision control system includes a signal input module, a control decision module, a control signal generation module, and a pilot control module; The hydraulic transmission system includes a rotary main pump module, a reversing buffer valve module, and a rotary hydraulic motor module; The mechanical actuator includes a rotary reducer module, a rotary gear module, a turntable module, a boom module, and a rope and lifting module.
[0015] In some optional embodiments of this application, the simulation model template includes the following information: the electromechanical-hydraulic modules involved in the simulation model, the simulation software to be called, and the simplified equivalent scheme of the model; The specific simulation model template called by the simulation task is determined by the crane configuration and the pre-set simulation parameters.
[0016] The above-mentioned technical solution of this application has the following beneficial technical effects: The simulation platform of this application realizes high-fidelity simulation modeling of electromechanical-hydraulic systems, solidifies the simulation process, ensures the accuracy of simulation calculations, and can automate simulation modeling, which greatly reduces the amount of knowledge required and the technical threshold for software operation required to carry out simulation research. In addition, the simulation platform can realize batch simulation calculations, which significantly improves simulation efficiency and enhances the efficiency of new product testing and verification. Attached Figure Description
[0017] Figure 1 is a schematic diagram of the structure of an automated simulation platform for predicting crane control performance in an exemplary embodiment of this application; Figure 2 is a flowchart of the automated simulation modeling method for a wheeled crane slewing system in an exemplary embodiment of this application. Figure 3 is a schematic diagram of modular modeling and data flow of a crane slewing system in an exemplary embodiment of this application; Figure 4 is an example of an AMESim simulation model of a hydraulic system automatically generated based on the present invention in an exemplary embodiment of this application; Figure 5 is an example of an AMESim simulation model of a buffer valve automatically generated based on the present invention in an exemplary embodiment of this application; Figure 6 is a rotational motion response curve of a certain type of crane obtained by the simulation platform automatically performing modeling analysis in an exemplary embodiment of this application. Detailed Implementation
[0018] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to specific embodiments and accompanying drawings. It should be understood that these descriptions are merely exemplary and not intended to limit the scope of this application. Furthermore, descriptions of well-known structures and technologies are omitted in the following description to avoid unnecessarily obscuring the concepts of this application.
[0019] The accompanying drawings illustrate a layer structure according to an embodiment of this application. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The various regions, layers, shapes, and their relative sizes and positional relationships shown in the drawings are merely exemplary.
[0020] Obviously, the described embodiments are only a part of the embodiments of this application, not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.
[0021] In the description of this application, it should be noted that the terms "first", "second", and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.
[0022] Furthermore, the technical features involved in the different embodiments of this application described below can be combined with each other as long as they do not conflict with each other.
[0023] The automated simulation platform and simulation method for predicting crane control performance provided in this application will be described in detail below with reference to the accompanying drawings, through specific embodiments and application scenarios.
[0024] like Figure 1 As shown in the attached figure, in a first aspect of the embodiments of this application, an architecture for an automated simulation platform (hereinafter referred to as the "simulation platform") for predicting the control performance of cranes is provided. Figure 1 As shown.
[0025] The simulation platform implements automatic modeling and simulation functions through a user interface system, a database management system, and a simulation modeling-driven system. The user interface system is used by developers to set simulation parameters, start simulation tasks, and view simulation results; the database management system performs CRUD operations on data based on input commands from the front end and returns the results; the simulation modeling-driven system is used to implement functions such as… Figure 2 The automated modeling and simulation process is shown.
[0026] The database system of this invention comprises seven databases: a crane product configuration database, a 3D model library, a component parameter database, a simulation model template database, a simulation task database, a simulation model database, and a simulation result database. Among them, the crane product configuration database, the component parameter database, and the simulation task database are traditional relational databases built on MySQL; the other databases are used to store binary files and are built on MongoDB.
[0027] The product configuration database is used to store the various product configurations of typical crane models. Each model corresponds to a unique model ID. Calling this database can realize the mapping from the model ID to the model of key assembly or component of that model.
[0028] The component parameter database is used to store the parameters of hydraulic components and mechanical parts required for simulation, including geometric dimensions, performance, efficiency, etc. The parameter list is stored in JSON string format. Each model of part corresponds to a unique part ID. Calling this database can realize the mapping from part ID to part parameters.
[0029] The 3D model library is used to store the 3D models of components required for dynamic simulation. Rigid parts or assemblies are stored in formats such as .stp / .igs, while flexible parts are stored in .op2 format. Calling this database can realize the mapping from part ID to component 3D model.
[0030] The simulation model template database is used to store code templates for generating simulation models. The code templates are stored in the form of text files. The database directly stores the template files. Calling this database can realize the mapping from vehicle ID to its modeling template file.
[0031] The simulation task database is used to store the settings information for each simulation task. The simulation platform assigns a unique task ID to each simulation task and stores the corresponding vehicle model, product configuration, and simulation condition settings.
[0032] The simulation model database is used to store the generated model files (such as .ame files generated by AMESim, .slx files generated by Simulink, and .sim files generated by Simcenter3D). Each simulation task generates a unique hydraulic system model, electronic control system model, and dynamic simulation model. Calling this database can realize the mapping from task ID to its simulation model.
[0033] The simulation results database is used to store the result files automatically generated by the simulation software and the result files generated by this simulation platform. Calling this database can realize the mapping from task ID to its simulation result data.
[0034] The simulation modeling driven system of this invention executes automated modeling and simulation tasks based on front-end input parameters, and its operation flow is as follows: Figure 2 As shown.
[0035] Step 1: R&D personnel input the model of the wheeled crane into the simulation platform. The simulation platform queries the corresponding crane model information in the material management system database based on the product model, automatically analyzes the product BOM, and retrieves the models of hydraulic components, mechanical parts and assemblies related to the slewing system.
[0036] Step two: The simulation platform analyzes each component retrieved in step one by one. Components that require mathematical modeling request relevant key parameters from the component parameter database. Components that require dynamic simulation modeling, in addition to querying key parameters, also need to send a request to the 3D model library based on the component ID to retrieve its 3D model.
[0037] Step 3: Based on the product model and simulation parameters input in Step 1, the simulation platform sends a request to the simulation model template database to call the simulation model template suitable for the current simulation task; and assigns values to the corresponding variables in the template according to the model parameters obtained in Step 2. In dynamic simulation, the 3D model retrieved in Step 2 is also imported into the simulation model, and assembly, constraint, contact and other settings are executed to complete the simulation modeling, and the model is stored in the simulation model database.
[0038] Step four: The simulation platform calls the simulation model established in step three, starts the simulation task according to the simulation parameters input in step one, and monitors the simulation progress until the simulation task is completed.
[0039] Step 5: The simulation task is completed. The simulation platform automatically reads the simulation calculation results of key physical quantities according to the settings, stores the simulation result files and simulation data in the simulation result database, queries the corresponding simulation results according to the simulation result category requested by the front-end UI, and displays them visually on the front-end interface.
[0040] The crane model information in step one includes the crane's maximum lifting capacity, counterweight scheme, rigging and hook configuration, etc.
[0041] The hydraulic components related to the slewing system in step one include the slewing main pump, directional buffer valve, slewing hydraulic motor, pilot valve group, oil tank, and other hydraulic components.
[0042] The mechanical components related to the slewing system in step one include slewing bearings, turntables, slewing gearboxes, slewing gears, booms, hooks, ropes, and other components.
[0043] The assemblies related to the slewing system in step one include the engine, gearbox, power take-off, controller, torque limiter, and other assembly models.
[0044] In step two, mathematical modeling refers to a modeling method that calculates the input and output of components based on the analysis of their working principles using mathematical analytical methods. This can be done by directly calculating the output results through mathematical formulas by analyzing the characteristics of the components, or by using lumped parameter simulation software such as AMESim / Simulink for mathematical modeling of components.
[0045] In step two, the key parameters of the components refer to the component parameter variables that can be assigned values in the lumped parameter method modeling. Taking the rotary main pump as an example, when using the gear pump model as its modeling template, the parameters such as the number of gear pump teeth, module, and tooth width stored in the component parameter database can be read and directly used for AMESim model parameter assignment. When using the fixed displacement pump as its modeling template, the above parameters can be used to calculate the pump displacement and then used for AMESim model parameter assignment.
[0046] Step two, dynamic modeling, refers to establishing mathematical equations describing the dynamic behavior of a physical system by analyzing the motion state and interaction relationships of the system. Models can be built using dynamic simulation software such as Adams or Simcenter3D Motion.
[0047] In step two, the key parameters of the three-dimensional component include the component's geometric dimensions, assembly position, friction coefficient, and mechanical properties. Among them, the geometric dimensions are used to generate the parametric model, the assembly position is used to drive the automatic assembly of parts in the dynamic simulation model, and the friction coefficient and mechanical property parameters are used to set the boundary conditions such as constraints and materials in the dynamic simulation model.
[0048] In step two, the parametric model refers to the 3D model of the part generated by driving geometric dimension parameters. Taking the pinion of a rotary gear pair as an example, a unique 3D part can be generated by using a series of parameters such as the number of teeth, module, tooth width, pitch circle diameter, hole diameter, and key width. Parametric modeling can significantly reduce the storage pressure of 3D models for serialized parts.
[0049] The three-dimensional model in step two refers to a three-dimensional model file in the format of .igs / .stp or a flexible body model file in the format of .op2, which can be imported into the dynamic simulation software. The specific model format to be called is determined by the simulation template determined in step three.
[0050] In step three, the model template is built based on the physical structure of the crane's slewing system. Figure 3 The system architecture shown is a modular architecture established after analyzing the motion transmission chain of the slewing system of a wheeled crane. The slewing system can be divided into three parts: decision control system, hydraulic transmission system and mechanical actuator.
[0051] The decision control system involved in step three includes a signal input module (including control handle, throttle, pilot switch, free slide switch, etc.), a control decision module (control algorithm and control logic), a control signal generation module (input to the left and right rotary valves, buffer valve, brake valve, free slide valve and other electronic control signals), and a pilot control module (including oil pump, pilot enable valve, left and right rotary solenoid valve and other components).
[0052] The hydraulic transmission system involved in step three includes a rotary main pump module, a reversing buffer valve module (including components such as reversing valves, buffer valves, and free-slide valves), and a rotary hydraulic motor module.
[0053] The mechanical actuators involved in step three include a slewing reducer module (including planetary gear train and brake discs), a slewing gear module (including slewing gear pairs and slewing bearings), a turntable module, a boom module (including the main boom, each extension boom section, luffing cylinder, etc.), and a rope and load-bearing module.
[0054] The power chain system of the crane chassis used for power supply in step three is not dynamically modeled, but the output speed of the power take-off is directly calculated using the following formula:
[0055] In the formula, n PTO and n E These represent the output speed of the power take-off unit and the input speed of the engine, respectively. i G and i PTO These represent the reduction ratios of the gearbox and the power take-off, respectively. The slewing reducer module involved in step three, due to its highly deterministic dynamic response characteristics and relatively small impact on slewing control performance, is only mathematically modeled, not dynamically simulated.
[0056] In step three, the stage of generating the simulation model, it is necessary to determine the simulation modeling framework (such as whether to enable the flexible model or whether to consider wind load) based on the working condition information and simulation settings of the simulation platform, and design a corresponding simulation model template for each simulation model framework.
[0057] The simulation model template includes the following information: the electromechanical and hydraulic modules involved in the simulation model, the simulation software to be called, and the simplified equivalent scheme of the model. The specific simulation model template called for the simulation task is determined by the crane configuration and the simulation parameters set by the R&D personnel. For example, when the simulation task is set as boom state 001112, boom tilt angle 60°, and lifting load of 15 tons, the influence of the flexible deformation of the motion mechanism on the slewing system cannot be ignored, and a flexible mechanical system template needs to be called for system modeling. When the simulation task is set as boom state 000000, boom tilt angle 70°, and no-load condition, the flexible deformation of the mechanical actuator decreases significantly, and the dynamic simulation model can be simplified to a rigid body model, or even simplified to a constant moment of inertia load. Therefore, in this invention, the choice between multidisciplinary joint simulation or single-platform simulation will be determined based on the specific simulation task.
[0058] Each type of simulation model template corresponds to a template code file. Running this code will generate the corresponding simulation model. Taking the AMESim model as an example, the corresponding hydraulic system structural framework (such as conventional architecture, dual reducer architecture, etc.) is determined based on the crane product configuration. AMESim models of various frameworks are built, and the simulation model is converted into the corresponding Python code script using a model script generation tool, which serves as the template code file for that framework.
[0059] Step 3, assigning simulation parameters, refers to generating a simulation model using the model parameters called in Step 2. Specifically, this is achieved by modifying the corresponding variables in the parameter setting instructions within the template code, synchronizing the parameters of the generated simulation model with those of the actual simulation object. Executing the modified code will then generate the corresponding simulation model (e.g., ...). Figures 4-5 (As shown).
[0060] It should be noted that in this patent, "modifying template code" and "adjusting template code" refer to the simulation platform automatically modifying the code based on the front-end input, rather than manual operation by human intervention.
[0061] Step 3, dynamic simulation modeling, requires not only calling model parameters to update the constraint, material, contact and other attribute parameters in the template code, but also using a 3D model called from the 3D model library or generated by dimension driving to replace the component model in the template code, so as to synchronize the generated simulation model with the 3D model of the actual simulation object.
[0062] In step three, the dynamic simulation modeling, the wire rope is discretized into a series of rigid body elements using the discrete rigid body method to achieve flexible modeling. Based on the Simcenter 3D developer tools, the rigid body elements and the bushing constraint properties between adjacent elements are defined in batches. The key parameters of the bushing properties are calculated according to Table 1. Table 1 Calculation Method of Key Bushing Parameters
[0063] In the formula K 1. K 2. K 3. K 4 represents the shear stiffness, tensile stiffness, bending stiffness, and torsional stiffness of the bushing constraint, respectively. A The cross-sectional area of the wire rope is... l The length of a single rigid body element. d The diameter of the wire rope, I The moment of inertia of the wire rope section, G r The Young's modulus of the steel wire rope. E r This refers to the bending modulus of the wire rope. Step four involves simulation parameters, including the working condition information, pose status information, operation command information, and simulation software configuration information specified at the front end. Based on this information, the simulation platform updates the corresponding parameters in the model configuration code or model generation code, thereby synchronizing the generated simulation model with the actual simulation working conditions.
[0064] Step four involves obtaining operational information, specifically including wind load conditions (wind speed and direction), and the inclination angle of the working ground (inclination angle and tilt direction). The wind load is calculated using the following formula:
[0065] In the formula F air Wind load (in N). p air density, C d This is the wind force coefficient. A The windward area is perpendicular to the wind direction. v The relative velocity of wind speed to a moving object can be calculated based on wind speed and direction information. The corresponding wind load values and directions are then updated in the dynamic simulation modeling script.
[0066] Ground tilt angle: Based on the tilt direction and angle set on the front-end simulation platform, the corresponding variable for the gravity direction is modified in the dynamic simulation modeling script to simulate the tilted ground condition. Step four: Pose state information includes boom tilt angle, boom length, fixed positions of boom pins for each boom segment, wire rope length, wire rope ratio, initial rotation angle, etc. Boom tilt angle, boom length, and fixed positions of boom pins for each boom segment are achieved by calculating the assembly position coordinates of each boom segment and modifying the assembly parameters generated in the dynamic simulation model; wire rope length and ratio are achieved by adjusting the position and number of rigid body elements generated in the dynamic simulation modeling.
[0067] Step four involves inputting command information, which refers to the input information simulating the driver's operation in the rotary motion simulation. This includes the handle tilt angle signal, accelerator pedal travel signal, free rotation signal, and pilot enable signal. The handle tilt angle and accelerator pedal travel are continuously changing proportional signals, while the free rotation and pilot enable signals are switching signals.
[0068] The handle tilt angle signal is the main signal for controlling the rotation of the turntable. Its parameters, such as the direction of motion and operating speed, are set by modifying the preset "handle tilt angle-time" curve.
[0069] Step four involves configuring the simulation software, which refers to the configuration parameters for performing the simulation calculation, including simulation duration, maximum simulation step size, and simulation result recording step size. Modify the corresponding variables in the simulation parameter settings in the template code.
[0070] Step four involves starting the simulation calculation using the start simulation command in the template code and predicting the current simulation progress by monitoring the size of the generated calculation result file.
[0071] Step 5 results files include results files automatically generated by the simulation software (such as .ame format files generated by AMESim software, .mres format files generated by Simcenter3D software, etc.), as well as simulation result curve data used for front-end UI display and operability analysis of the simulation platform.
[0072] Step 5: The simulation result curve data is read through the software API interface. The simulation platform requests the corresponding data according to the data category to be read, and the data is stored in .csv file format.
[0073] Step 5: The simulation result data categories are pre-defined according to the analysis requirements, covering, but not limited to, the following data: 1. Control current of left and right rotary valves, buffer valves, etc.; 2. Rotary main pump speed; 3. Displacement of directional valve spool; 4. Output flow rate and pressure of each oil port of directional valve, buffer valve, and pilot valve; 5. Output speed and torque of hydraulic motor; 6. Rotational angular displacement, angular velocity, and angular acceleration of turntable; 7. Three-dimensional spatial position of boom head, hook, and center of gravity of the load; 8. Stress at key measuring points in the frame, outriggers, turntable, and boom.
[0074] Step 5, result storage, refers to storing the simulation result file in binary file format to the simulation result database.
[0075] Step 5, result visualization, includes: 1. Displaying the simulation curves in the form of a line graph (e.g., Figure 6 ); 2. Display key evaluation indicators such as directional valve response time, acceleration time, and closing slip amount in numerical form; 3. Display the crane rotation process in 3D animation form; 4. Display the stress and strain distribution cloud map of flexible components in the form of stress cloud map.
[0076] The 3D animation of crane rotation can include stress-strain simulation cloud maps of flexible modeled components. The 3D modeling and cloud map coloring are achieved through Unity, and the motion state of the components is set. The web page is deployed through WebGL, thereby realizing the front-end display of the dynamic behavior and stress-strain cloud map of the crane rotation system.
[0077] The simulation modeling module can achieve batch simulation by setting a series of parameters and cyclically executing steps 1 to 5.
[0078] Compared with existing methods that analyze crane slewing control performance based on simulation calculations, this method has the following advantages: 1. The simulation platform enables high-fidelity simulation modeling of electromechanical-hydraulic systems, solidifies the simulation process, and ensures the accuracy of simulation calculations.
[0079] 2. The simulation platform can automate simulation modeling, which greatly reduces the amount of knowledge required and the technical threshold for software operation needed to conduct simulation research.
[0080] 3. The simulation platform can perform batch simulation calculations, which significantly improves simulation efficiency and enhances the efficiency of new product testing and verification.
[0081] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.
[0082] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.
[0083] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.
Claims
1. An automated simulation platform for predicting the control performance of cranes, characterized in that, include: UI interaction system, database management system and simulation modeling driven system; The UI interaction system is used by R&D personnel to set simulation parameters, start simulation tasks, and view simulation results. The database management system is used to perform data addition, deletion, modification, and viewing operations based on input commands from the front end, and returns the operation results; The simulation modeling driving system is used for automated modeling and simulation. The database management system includes: a crane product configuration database, a 3D model library, a component parameter database, a simulation model template database, a simulation task database, a simulation model database, and a simulation result database; The crane product configuration database, the component parameter database, and the simulation task database are relational databases built on MySQL; the 3D model library, simulation model template database, simulation model database, and simulation result database are used to store binary files and are built on MongoDB.
2. The automated simulation platform for predicting crane control performance according to claim 1, characterized in that, The crane product configuration database is used to store the product configurations of typical crane models. Each model corresponds to a unique model ID. Calling this database can realize the mapping from the model ID to the model of key assembly or component of that model. The component parameter database is used to store the parameters of hydraulic components and mechanical parts required for simulation, including geometric dimensions, performance, and efficiency. The parameter list is stored in JSON string format. Each model of part corresponds to a unique part ID. Calling this database can realize the mapping from part ID to part parameters. The simulation task database is used to store the settings information for each simulation task. The simulation platform assigns a unique task ID to each simulation task and stores the corresponding vehicle model, product configuration, and simulation condition settings.
3. The automated simulation platform for predicting crane control performance according to claim 1, characterized in that, The 3D model library is used to store the 3D models of components required for dynamic simulation. Rigid parts or assemblies are stored in .stp or .igs format; flexible parts are stored in .op2 format. Calling the 3D model library can realize the mapping from part ID to component 3D model. The simulation model template database is used to store code templates for generating simulation models. The code templates are stored in the form of text files. The database directly stores the template files. Calling this database can realize the mapping from vehicle ID to its modeling template file. The simulation model database is used to store the generated model files. Each simulation task generates a unique hydraulic system model, electronic control system model, and dynamic simulation model. Calling this database can realize the mapping from task ID to its simulation model. The simulation results database is used to store the result files automatically generated by the simulation software and the result files generated by this simulation platform. Calling this database can realize the mapping from task ID to its simulation result data.
4. An automated simulation modeling method for a wheeled crane slewing system, characterized in that, include: Step 1: Input the model of the wheeled crane into the simulation platform. The simulation platform will query the corresponding crane model information in the material management system database based on the product model, analyze the product BOM, and retrieve the models of hydraulic components, mechanical parts and assemblies related to the slewing system. Step 2: The simulation platform analyzes the hydraulic components, mechanical parts and assembly models related to the slewing system retrieved in Step 1 one by one. For parts that need mathematical modeling, the platform requests the relevant key parameters from the component parameter database. For parts that need dynamic simulation modeling, in addition to querying the key parameters of the parts, the platform also needs to send a request to the 3D model library based on the part ID to call its 3D model. Step 3: Based on the wheeled crane model entered in Step 1, the simulation platform sends a request to the simulation model template database to call the simulation model template suitable for the current simulation task; and assigns values to the corresponding variables in the template according to the model parameters obtained in Step 2. In dynamic simulation, the 3D model retrieved in Step 2 is also imported into the simulation model, and assembly, constraint, and contact settings are executed to complete the simulation modeling, and the model is stored in the simulation model database. Step four: The simulation platform calls the simulation model established in step three, starts the simulation task according to the wheeled crane model entered in step one, and monitors the simulation progress until the simulation task is completed. Step 5: The simulation task is completed. The simulation platform reads the simulation calculation results of key physical quantities according to the settings, stores the simulation result files and simulation data in the simulation result database, queries the corresponding simulation results according to the simulation result category requested by the front-end UI, and displays them visually on the front-end interface.
5. The automated simulation modeling method for the slewing system of a wheeled crane according to claim 4, characterized in that, The crane model information includes the crane's maximum lifting capacity, counterweight scheme, rigging and hook configuration.
6. The automated simulation modeling method for a wheeled crane slewing system according to claim 4, characterized in that, The hydraulic components related to the slewing system include the slewing main pump, directional buffer valve, slewing hydraulic motor, pilot valve assembly, and oil tank; The mechanical components include slewing bearing, turntable, slewing gearbox, slewing gear, boom, hook and ropes; The assembly models include the engine, transmission, power take-off, controller, and torque limiter.
7. The automated simulation modeling method for a wheeled crane slewing system according to claim 4, characterized in that, Simulation models of each module of the crane were established using both mathematical analytical modeling and dynamic modeling methods. Mathematical analytical modeling refers to the method of directly calculating the input-output relationship of components based on key parameters or using the lumped parameter method for modeling. Key parameters refer to component parameter variables that can be assigned values in the modeling process. Dynamic modeling involves analyzing the motion state and interaction relationships of a moving system to establish mathematical equations that describe the dynamic behavior of the physical system.
8. The automated simulation modeling method for the slewing system of a wheeled crane according to claim 4, characterized in that, Key parameters of a 3D model include component geometry, assembly location, coefficient of friction, and mechanical properties. The geometric dimensions are used to generate the parametric model, the assembly position is used to drive the automatic assembly of parts in the dynamic simulation model, and the friction coefficient and mechanical performance parameters are used to set the constraints and material boundary conditions in the dynamic simulation model. In dynamic simulation modeling, the wire rope is discretized into a series of rigid body elements using the discrete rigid body method to achieve flexible modeling.
9. The automated simulation modeling method for the slewing system of a wheeled crane according to claim 4, characterized in that, The model template is built based on the physical structure of the crane's slewing system, which is divided into three parts: a decision control system, a hydraulic transmission system, and a mechanical actuator. The decision control system includes a signal input module, a control decision module, a control signal generation module, and a pilot control module; The hydraulic transmission system includes a rotary main pump module, a reversing buffer valve module, and a rotary hydraulic motor module; The mechanical actuator includes a rotary reducer module, a rotary gear module, a turntable module, a boom module, and a rope and lifting module.
10. The automated simulation modeling method for the slewing system of a wheeled crane according to claim 4, characterized in that, The simulation model template includes the following information: the electromechanical and hydraulic modules involved in the simulation model, the simulation software to be called, and the simplified equivalent scheme of the model; The specific simulation model template called by the simulation task is determined by the crane configuration and the pre-set simulation parameters.