Design method and device for hybrid mining electric shovel, and readable storage medium

Abstract

This application provides a design method and device for a hybrid mining electric shovel, as well as a readable storage medium. The method includes: based on the motion characteristics and degree-of-freedom requirements of the mining electric shovel, performing type synthesis on the mining electric shovel based on spinor theory to determine multiple candidate configurations; performing discrete element simulation on the multiple candidate configurations of the mining electric shovel to determine the dynamic digging resistance of each of the multiple candidate configurations; solving the dynamic models of the multiple candidate configurations of the mining electric shovel based on the dynamic digging resistance to determine the dynamic simulation results; based on the dynamic simulation results of the multiple candidate configurations of the mining electric shovel, determining the optimal configuration of the mining electric shovel based on the motion continuity, singularity, and magnitude of the dynamic digging resistance; and establishing a parametric model, boundary conditions, and multi-objective design function for the optimal configuration using a multi-objective scale synthesis method to perform multi-objective scale synthesis on the optimal configuration.

Description

Technical Field

[0001] This application relates to the field of machinery, and more specifically, to a design method and apparatus for a hybrid mining electric shovel, and a readable storage medium. Background Technology

[0002] Electric mining shovels are key equipment used in mining to excavate large pieces of ore and earth. Traditional electric mining shovels have a relatively simple configuration, usually a two-degree-of-freedom planar structure.

[0003] Current research on electric shovels mainly focuses on lightweight design, algorithm optimization, and dynamics, with relatively little direct structural innovation. Furthermore, kinematic analyses often treat electric shovels as a series mechanism. However, if we consider the shovel's rotating platform as a stationary platform, the boom as a series component, and the corresponding digging section as a parallel mechanism, then from a structural perspective, mining electric shovels are hybrid devices.

[0004] Compared to the aforementioned two-degree-of-freedom (DOF) electric shovel mechanisms, multi-DOF (e.g., three-DOF) hybrid electric shovels are more advantageous in reducing maximum digging resistance, especially in mining areas with steep slopes and complex working environments, significantly improving the shovel's operating efficiency and stability. In related technologies, the configuration design of multi-DOF electric shovels relies heavily on experience or traditional design methods, which have significant limitations. For example, in designing the configuration of an electric shovel, simply replacing some kinematic pairs of the moving platform or making local modifications based on existing solutions (e.g., adjusting link length, adjusting cylinder stroke, etc.) leads to a simplistic configuration design. Furthermore, the evaluation of new configurations typically relies only on isolated kinematic or dynamic parameters. These methods result in new configurations that only meet basic functions, offering limited improvement to overall performance. Simultaneously, the lack of reliable evaluation indicators and subsequent comprehensive studies of the mechanism dimensions for newly designed electric shovel configurations leads to low design efficiency and completeness. Summary of the Invention

[0005] This application mainly provides a design method and device for a hybrid mining electric shovel, as well as a readable storage medium. The technical solution of this application is implemented as follows:

[0006] Firstly, a design method for a hybrid electric mining shovel is provided. The method includes: based on the kinematic characteristics and degree-of-freedom requirements of the electric mining shovel, performing type synthesis on the shovel using spinor theory to determine multiple alternative configurations; performing discrete element simulation on the multiple alternative configurations to determine the dynamic digging resistance of each configuration; solving the dynamic models of the multiple alternative configurations based on the dynamic digging resistance to determine the dynamic simulation results; determining a superior configuration based on the dynamic simulation results of the multiple alternative configurations, considering the kinematic continuity, singularity, and magnitude of the dynamic digging resistance; and establishing a parametric model, boundary conditions, and multi-objective design functions for the superior configuration using a multi-objective scale synthesis method to perform multi-objective scale synthesis on the superior configuration.

[0007] The mining electric shovel design method provided in this application efficiently generates multiple candidate configurations based on spinor theory. The dynamic performance of each configuration is evaluated through a combination of discrete element simulation and dynamics analysis. The optimal configuration is determined based on the analysis of motion continuity, singularity, and dynamic digging resistance. Then, the configuration is parametrically modeled, boundary conditions are set, a multi-objective design function is established, and a genetic algorithm is used to search for parameter combinations. Finally, the optimal structural parameters and installation position angle parameters of the configuration are obtained, completing the high-performance dimensional synthesis of the hybrid mechanism. This method not only improves the scientific rigor and accuracy of configuration design but also effectively enhances the operating efficiency and stability of mining electric shovels under complex working conditions, realizing the integrated design of mining electric shovels from configuration synthesis to dimensional parameters.

[0008] In some embodiments, the step of performing discrete element simulation on the plurality of candidate configurations of electric shovels to determine the dynamic digging resistance of the plurality of candidate configurations of electric shovels includes: establishing discrete element simulation models of the plurality of candidate configurations of electric shovels; establishing ore particle models in discrete element simulation software; setting driving functions for the plurality of discrete element simulation models in the discrete element simulation software; and using the discrete element simulation software to solve for the dynamic digging resistance of each candidate configuration of electric shovel.

[0009] Based on the above technical means, by establishing an ore particle model, the mechanical response between electric shovels of different configurations and ore can be accurately predicted; at the same time, by establishing different types of particle models, the impact of different ore conditions on the performance of electric shovels can be evaluated, enhancing the adaptability of the design.

[0010] In some embodiments, the step of solving the dynamic models of the plurality of candidate electric shovel configurations based on the dynamic digging resistance and determining the dynamic simulation results includes: establishing a dynamic simulation model of each candidate electric shovel configuration in dynamic simulation software; setting a driving function for each dynamic simulation model in the dynamic simulation software; and applying a corresponding dynamic digging resistance to each dynamic model; solving each dynamic simulation model using the dynamic simulation software to obtain the dynamic simulation results for each candidate configuration; the dynamic simulation results include velocity curves, acceleration curves, and digging trajectories at multiple points on the bucket teeth.

[0011] Based on the aforementioned technical methods, a dynamic model of each candidate configuration of the electric shovel is established in dynamic simulation software, and reasonable drive functions and dynamic digging resistance are set to obtain the velocity curves, acceleration curves, and digging trajectory of each point on the bucket tip. This allows for accurate evaluation of the motion continuity and stability of each configuration in actual operation, enabling the selection of the optimal configuration and ultimately improving the overall performance and operational efficiency of the electric shovel.

[0012] In some embodiments, determining the preferred configuration of the electric shovel based on its motion continuity and singularity includes: determining the first candidate configuration as the preferred configuration if the dynamic simulation results of the first candidate configuration among the plurality of candidate configurations meet the following conditions: the velocity curve corresponding to the first candidate configuration changes smoothly and has no inflection point; the acceleration curve corresponding to the first candidate configuration changes smoothly and the acceleration curve has no infinite or infinitesimal points.

[0013] Based on the aforementioned technical methods, by comprehensively analyzing the variation characteristics of velocity and acceleration curves, the motion continuity and non-singular performance of a mining electric shovel under a specific configuration can be effectively evaluated. Only when both types of curves exhibit good smoothness and stability can the configuration be considered to have high engineering applicability and reliability, and in this case, the configuration is considered superior.

[0014] In some embodiments, the step of performing type synthesis on the electric shovel based on spinor theory, according to the motion characteristics and degree-of-freedom requirements of the electric shovel, to determine multiple alternative configurations of the electric shovel includes: determining the motion spinor system of the moving platform of the electric shovel based on spinor theory according to the degrees of freedom and motion characteristics of the electric shovel; determining the constraint spinor system of the moving platform according to spinor reciprocity theory; determining the constraint spinor system of each branch according to the constraint spinor system of the moving platform and the motion characteristics of multiple branches of the electric shovel; determining the motion spinor system of each branch according to the constraint spinor system of each branch through spinor reciprocity theory; determining multiple configurations of each branch according to the motion spinor system of each branch; and determining multiple alternative configurations of the electric shovel according to the multiple configurations of each branch.

[0015] In some embodiments, determining the constraint spinor system of each branch based on the motion characteristics of the moving platform constraint spinor system and the multiple branches of the mining electric shovel includes: determining the dimension of the constraint spinor system of the moving platform based on the dimension of the moving platform's motion spinor system; decomposing the constraint spinor system of the moving platform based on the number of multiple branches and the motion characteristics of each branch to determine the constraint situation of each branch; and determining the constraint spinor system of each branch based on the constraint situation of each branch; wherein the number of independent constraints among all constraints provided by each branch is consistent with the dimension of the constraint spinor system of the moving platform.

[0016] Based on the above technical means, by decomposing the constraint space of the moving platform into the constraint subspace of each branch, and obtaining the corresponding motion space of the branch through spinor reciprocity, the efficiency and accuracy of configuration design can be improved.

[0017] In some embodiments, determining multiple candidate configurations of the mining electric shovel based on multiple configurations of each branch includes: determining multiple configurations of each branch based on different arrangements of multiple kinematic pairs of each branch; combining the multiple configurations of each branch to obtain multiple combined configurations of the mining electric shovel; combining the constraint spinor systems of each branch to determine the constraint spinor system provided by each branch in each combined configuration to the moving platform, determining the dimension of the constraint spinor system corresponding to each combined configuration to determine the motion degrees of freedom of each combined configuration; and selecting the combined configuration whose degrees of freedom in the multiple combined configurations match the degree of freedom requirements of the mining electric shovel as the candidate configuration.

[0018] In some embodiments, the multi-objective scale synthesis of the preferred configuration includes: establishing constraints on the mining electric shovel during the excavation process based on the preferred configuration; establishing a parametric model of the optimal configuration by using the structural dimensions and kinematic pair installation parameters in the preferred configuration as design variables; introducing boundary conditions and design constraints to establish a multi-objective design solution domain; establishing a multi-objective design function for the preferred configuration based on the end-of-line trajectory requirements, workspace requirements, and energy consumption requirements of the mining electric shovel's moving platform; and using a genetic algorithm to search for the optimal combination of the structural dimensions and the installation parameters within the multi-objective design solution domain to complete the multi-objective scale synthesis design of the preferred configuration.

[0019] Secondly, a design device for a mining electric shovel is provided. The device includes: a first determining unit, used to perform type synthesis on the mining electric shovel based on spinor theory according to the motion characteristics and degree-of-freedom requirements of the mining electric shovel, and determine multiple candidate configurations of the mining electric shovel; a discrete element simulation unit, used to perform discrete element simulation on the multiple candidate configurations of the mining electric shovel, and determine the dynamic digging resistance of the multiple candidate configurations of the mining electric shovel respectively; a dynamic simulation unit, used to solve the dynamic model of the multiple candidate configurations of the mining electric shovel according to the dynamic digging resistance, and determine the dynamic simulation results; a second determining unit, used to determine the optimal configuration of the mining electric shovel based on the dynamic simulation results of the multiple candidate configurations of the mining electric shovel, and based on the motion continuity, singularity, and magnitude of the dynamic digging resistance of the mining electric shovel; and a scale synthesis unit, used to establish the parameterized model, boundary conditions, and multi-objective design function of the optimal configuration according to the multi-objective scale synthesis method, so as to perform multi-objective scale synthesis on the optimal configuration.

[0020] Thirdly, a computer-readable storage medium is provided for storing a computer program that, when run, executes the method described in the first aspect. Attached Figure Description

[0021] Figure 1 A schematic flowchart illustrating the design method for an electric shovel used in mining, as provided in an embodiment of this application;

[0022] Figure 2 An example diagram illustrating the structural motion of a three-degree-of-freedom mining electric shovel;

[0023] Figure 3 A schematic flowchart illustrating the method for determining the dynamic digging resistance of multiple alternative configurations of electric shovels in the design method of electric shovels provided in the embodiments of this application;

[0024] Figure 4 This is a schematic diagram of discrete element simulation of a mining electric shovel.

[0025] Figure 5 A schematic flowchart illustrating the method for solving the dynamic model of multiple alternative configurations of electric shovels in the design method of electric shovels provided in the embodiments of this application;

[0026] Figure 6 Example diagram of the dynamic simulation model of the mining electric shovel provided in the embodiments of this application;

[0027] Figure 7 A schematic flowchart illustrating the method for determining multiple alternative configurations of a mining electric shovel in the mining electric shovel design method provided in the embodiments of this application;

[0028] Figure 8 Example diagram of the geometric representation of the kinematic spinor system of a 1R2T three-degree-of-freedom mining electric shovel platform;

[0029] Figure 9 for Figure 8 Example diagram of the geometric representation of the constrained spinor system corresponding to the dynamic spinor system;

[0030] Figure 10 A schematic diagram of the kinematic pair of the support chain of a 1R2T three-degree-of-freedom mining electric shovel;

[0031] Figure 11 A schematic flowchart illustrating the determination of each branch constraint space in the mining electric shovel design method provided in this application embodiment;

[0032] Figure 12 A schematic flowchart illustrating the determination of the movement space of each branch in the design method for mining electric shovels provided in this application embodiment;

[0033] Figure 13 A schematic flowchart illustrating the multi-objective scale synthesis method for mining electric shovels provided in this application embodiment;

[0034] Figure 14 A schematic diagram illustrating several possible combinations of configurations of a three-degree-of-freedom mining electric shovel provided in the embodiments of this application;

[0035] Figure 15 A schematic flowchart illustrating a design method for an electric shovel used in mining, provided in another embodiment of this application;

[0036] Figure 16 A schematic structural diagram of the design device for a mining electric shovel provided in the embodiments of this application;

[0037] Figure 17 This is a schematic structural diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0038] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0039] It should be noted that the terms "comprising" and "having," and any variations thereof, in the embodiments and accompanying drawings of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the steps or units listed, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices.

[0040] The terms "first," "second," "third," and "fourth," etc., used in the specification and drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0041] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0042] Electric shovels are key equipment used in mining for excavating large blocks of ore and earth. The rapid development of open-pit mining has expanded the demand for electric shovels. However, with the increasing complexity of mining environments, the design of traditional electric shovels is gradually failing to meet the growing demands of modern mines for operational efficiency, safety, and adaptability, placing higher requirements on their mechanical design and structural innovation.

[0043] Traditional mining electric shovels have a relatively simple configuration. For example, the widely used planar two-degree-of-freedom electric shovel structure relies on a lifting wire rope for lifting motion. When the bucket starts or the bucket teeth are subjected to strong impact loads, the bucket lifted by the wire rope will sway in all directions. The wire rope will also elongate, deform, or even knot under the impact of operation, affecting the accuracy of lifting and lowering. With frequent use, it is more prone to strand breakage under impact, reducing the safety and reliability of the equipment. In addition, the friction between the wire rope and the drum is relatively high, resulting in significant power consumption of the lifting motor and greatly reducing the service life of both the wire rope and the drum.

[0044] Current research on electric shovels mainly focuses on lightweight design, algorithm optimization, and dynamics, with relatively little direct structural innovation. Furthermore, kinematic analyses often treat electric shovels as a series mechanism. However, if we consider the shovel's rotating platform as a stationary platform, the boom as a series component, and the corresponding digging section as a parallel mechanism, then from a structural perspective, mining electric shovels are hybrid devices.

[0045] Compared to the aforementioned two-degree-of-freedom (DOF) electric shovel mechanisms, multi-DOF (e.g., three-DOF) electric shovels are more advantageous in reducing maximum digging resistance, especially in mining areas with steep slopes and complex working environments, significantly improving the shovel's operating efficiency and stability. In related technologies, the design of multi-DOF electric shovel configurations relies heavily on experience or traditional design methods, which have significant limitations. For example, in designing electric shovel configurations, simply replacing some kinematic pairs on the moving platform or making local modifications based on existing solutions (e.g., adjusting link length, adjusting cylinder stroke, etc.) leads to simplistic configuration designs. Furthermore, evaluation of new configurations typically relies solely on isolated kinematic or dynamic parameters. These methods result in new configurations that only meet basic functions, offering limited improvement to overall performance. Moreover, reliable evaluation indicators are lacking for newly designed electric shovel configurations, and the dimensional integration of the new configuration is rarely considered, leading to low design efficiency and completeness.

[0046] Therefore, how to break through the limitations of traditional design methods, improve the efficiency and accuracy of mining electric shovel configuration design, and increase the completeness of the mining electric shovel design process has become an urgent problem to be solved.

[0047] In view of the above problems, embodiments of this application provide a design method and apparatus for a hybrid mining electric shovel, and a computer-readable storage medium.

[0048] Figure 1 This is a schematic flowchart of the design method for mining electric shovels provided in the embodiments of this application. Figure 1 The method includes steps S110-S150.

[0049] In step S110, based on the motion characteristics and degree-of-freedom requirements of the mining electric shovel, the mining electric shovel is subjected to type synthesis based on spinor theory to determine multiple alternative configurations of the mining electric shovel.

[0050] In the technical solution of this application embodiment, it is first necessary to clarify the working requirements of the mining electric shovel, that is, the specific movement forms that the end effector of the mining electric shovel mechanism can achieve in space.

[0051] Traditional electric shovels for mining typically only achieve 2T of movement within the working plane. To improve the working flexibility of electric shovels and reduce digging resistance, they can be configured with a three-degree-of-freedom mechanism, adding one rotational degree of freedom to the moving platform, thus achieving 1R2T within the working plane. Figure 2 This is a structural example diagram illustrating the motion of a three-degree-of-freedom mining electric shovel.

[0052] Screw theory is a unified mathematical method for describing the motion and forces of rigid bodies in space. It uses screws to couple the translation and rotation of a rigid body as a whole. Its core principle is that any motion of a rigid body can be represented by a set of motion screws. To describe; among them, For line vectors, corresponding rotations, As an even quantity, corresponding to translation, the two combine to form a six-dimensional spinor, which can describe the translation and rotation of a rigid body in space.

[0053] The spinor reciprocity theory is the core content of spinor theory, establishing the motion space. With constrained space The two spaces are orthogonal subspaces of each other, with a total dimension of six, thus realizing the mutual mapping between the degrees of freedom and constraints of motion.

[0054] More specifically, the motion screw system of the moving platform of the working device is established based on screw theory, and the constraint screw system of the moving platform is solved by reciprocity theory. Then, the constraint screw system of the moving platform is decomposed into the constraint screws of each branch. According to the number of branches and the motion characteristics of each branch, the corresponding constraint screws are assigned. Then, the motion screws of the branches are obtained by reciprocity theory, thereby determining the combination form of the kinematic pairs of each branch.

[0055] Because the combination of kinematic pairs in each branch can be diverse, the overall configuration formed by multiple branches will also vary, resulting in a variety of alternative configurations. For example, in one configuration, a branch may adopt a RUS (rotation-slip-rotation) or RSS (rotation-slip-slip) form, while in another configuration, the branch may adopt an RRR (three revolute joints) or RPR (rotation-slip-rotation) form. Different branch combinations lead to different kinematic pair arrangements, thus affecting the dynamic performance and structural stability of the entire mechanism.

[0056] The above-described configuration synthesis process can be completed using computer-aided design software. For example, a screw space can be established using platforms such as MATLAB and ADAMS, and algorithms can be used to automatically generate multiple possible configuration schemes. Several candidate configurations are then selected for subsequent simulation and evaluation.

[0057] The specific steps for the integrated design of mining electric shovels based on spinor theory will be described in more detail later, and will not be repeated here.

[0058] The configuration design scheme based on spinor theory provided in this application can quickly and accurately describe rigid body motion and constraints in a unified manner. Especially for complex hybrid mechanism designs, it can start from the essential dimension of the mechanism's motion space and realize the transformation from a simplified motion diagram to a mathematical description, making the configuration design process more systematic and scientific.

[0059] Step S120: Perform discrete element simulation on multiple candidate configurations of electric mining shovels to determine the dynamic digging resistance of each candidate configuration.

[0060] Dynamic excavation resistance refers to the instantaneous resistance generated by friction, compression, shearing, and other forces between ore particles and the bucket surface. It varies over time and is influenced by factors such as bucket speed, angle, and material properties. Discrete element method (DEM) simulation allows for a direct observation of particle flow at the bucket tooth tip and quantitative analysis of its stress state, providing input data and reference for subsequent dynamic simulations.

[0061] Discrete element method (DEM) simulation is a numerical calculation method based on a particle model. It treats ore as an aggregate of a large number of discrete particles and simulates their interaction by setting contact mechanical parameters between particles (such as elastic modulus, friction coefficient, and coefficient of restitution).

[0062] In discrete element method (DEM) simulations, each particle is treated as an independent rigid body, its motion following Newton's laws of motion. The position and velocity of each particle are updated using contact detection and force calculation algorithms. This method accurately reflects the dynamic changes of materials during the mining process, and is particularly suitable for simulating discontinuous media (such as loose ore).

[0063] In practical implementation, to improve the accuracy of the simulation, reasonable simulation parameters need to be set according to the actual working conditions, such as particle size distribution, bulk density, and bucket movement trajectory. Furthermore, the velocity curve, acceleration curve, and digging trajectory at the bucket tooth tip need to be recorded in detail for use as boundary conditions in subsequent dynamic simulations. By comparing the dynamic digging resistance of electric shovels with different configurations, their energy consumption and operational efficiency in actual operation can be preliminarily assessed.

[0064] Step S130: Based on the dynamic excavation resistance, solve the dynamic models of multiple alternative configurations of electric mining shovels and determine the dynamic simulation results.

[0065] The dynamic digging resistance obtained from the aforementioned discrete element simulation is used as an external load and input into the dynamic model to solve for the dynamic behavior of each alternative configuration during the digging process. The dynamic model typically includes inertia matrix, Coriolis force matrix, gravity term, control input, etc., and the system's equations of motion are solved using numerical integration methods. Through dynamic simulation, the velocity curve, acceleration curve, and digging trajectory of the bucket tooth tip can be obtained, and the motion continuity of each configuration can be evaluated accordingly.

[0066] Dynamic simulations are typically performed using multibody dynamics software such as ADAMS. This software supports dynamic modeling and simulation of complex mechanisms and can handle various factors such as nonlinear constraints, contact forces, and external loads. By jointly solving the discrete element simulation results with the dynamic model, the dynamic performance of each configuration can be evaluated more comprehensively, and reliable data support can be provided for subsequent configuration optimization.

[0067] Step S140: Based on the dynamic simulation results of multiple alternative configurations of electric mining shovels, and considering the motion continuity, singularity, and dynamic digging resistance of the electric mining shovels, determine the optimal configuration of the electric mining shovels.

[0068] The assessment of motion continuity mainly focuses on the changing trends of the velocity and acceleration curves at the tip of the bucket teeth. For example, whether the velocity change at the tip of the bucket teeth is gradual. If there are sudden velocity changes, the motion continuity is considered to be poor.

[0069] Singularity analysis focuses on whether a mechanism exhibits degree-of-freedom degradation at specific positions. For example, when a moving platform is in certain specific postures, it may lose one or more degrees of freedom, thereby causing uncontrollable motion behavior.

[0070] In practical applications, the motion characteristics of each configuration can be intuitively determined by plotting velocity curves, acceleration curves, and excavation trajectory diagrams. Alternatively, as a possible approach, quantitative analysis can be performed using mathematical tools such as the Lyapunov index and the rank of the Jacobian matrix to determine the presence of singular states. Configurations exhibiting singular states should be excluded or their structure optimized. Ultimately, the optimal configuration is selected based on good motion continuity, absence of singular states, and low dynamic excavation resistance.

[0071] Step S150: Based on the multi-objective scale synthesis method, establish a parameterized model and add boundary conditions, determine the multi-objective design function, and use a genetic algorithm to combine structural parameters to complete scale synthesis.

[0072] Based on the optimal configuration, a multi-objective scale synthesis method is adopted to establish a parametric model that includes variables such as the length, width, thickness, installation angle, and position of each component of the configuration. The required digging depth, unloading height, and rotation angle of the electric shovel during actual operation are considered as boundary conditions. Based on the end trajectory of the moving platform, the working space, and energy consumption, a multi-objective design function for the configuration is established. A genetic algorithm is used to combine the optimal structural parameters to obtain the optimal size parameters and installation angle of the configuration, thus completing the optimal scale synthesis of the hybrid mechanism of the mining electric shovel working device.

[0073] Parametric models refer to mathematically modeling a mechanism configuration using a set of controllable design variables. Different structural dimensions and assembly states can be automatically generated by adjusting these variables. These variables are used as inputs, acting as "genes" referenced by a genetic algorithm and substituted into the kinematic model to calculate the end effector pose, trajectory, and workspace.

[0074] Boundary conditions refer to the maximum range of values ​​for parameters during the design process, used to limit the search space of design variables. For example, the maximum digging depth and minimum unloading height that an electric shovel needs to meet, and the maximum rotation angle of a rotating mechanism.

[0075] A multi-objective design function is a mathematical expression that incorporates multiple design objectives into the design process simultaneously, ultimately finding a balanced solution. Specifically, in some embodiments, the objective functions include minimizing the end-point trajectory error (making the end-point trajectory fit the logarithmic spiral digging trajectory as closely as possible), maximizing the workspace (increasing the coverage of the mechanism so that the electric shovel can adapt to more digging postures), and minimizing energy consumption (solving system energy consumption based on joint motion power consumption), etc.

[0076] Genetic algorithms are a global search method based on natural selection and genetic mechanisms. They use parameter variables as genes, objective functions as evaluation criteria, set the number of generations, perform genetic operations, and obtain a set of optimal structural parameters and installation angle combinations that satisfy all constraints and have a good balance of multiple objectives, thus completing the scale synthesis of the optimal configuration.

[0077] In summary, the mining electric shovel design method provided in this application efficiently generates multiple candidate configurations based on spinor theory. The dynamic performance of each configuration is evaluated through a combination of discrete element simulation and dynamics analysis. Finally, the optimal configuration is determined based on motion continuity and singularity analysis. Then, parametric modeling of this configuration is performed, boundary conditions are set, a multi-objective design function is established, and a genetic algorithm is used to search for parameter combinations. Ultimately, the optimal structural parameters and installation position angle parameters of this configuration are obtained, completing the high-performance dimensional synthesis of the hybrid mechanism. This method not only improves the scientific rigor and accuracy of configuration design but also effectively enhances the operating efficiency and stability of the mining electric shovel under complex working conditions, realizing the integrated design of the mining electric shovel from configuration synthesis to dimensional parameters.

[0078] In some embodiments, such as Figure 3 As shown, the aforementioned step S120 involves performing discrete element simulation on multiple candidate configurations of electric mining shovels to determine the dynamic digging resistance of each candidate configuration, and further includes steps S121-S124.

[0079] In step S121, discrete element simulation models of multiple alternative configurations of mining electric shovels are established respectively.

[0080] Discrete element simulation models are used to reproduce the interaction process between an electric shovel and ore particles in a computer virtual environment. Since the aforementioned alternative configurations have different structural forms, they need to be modeled separately. More specifically, for each alternative configuration, a simplified 3D model can be created in 3D modeling software and imported into discrete element simulation software (such as EDEM) to form a discrete element simulation model.

[0081] In step S122, a model of ore particles is established in the discrete element simulation software.

[0082] The ore particle model is a granular mechanical model built in discrete element simulation software. Ore particles usually have irregular geometric shapes, different particle size distributions, and complex friction and collision characteristics, all of which will affect the simulation results.

[0083] To improve the accuracy of discrete element simulation results, the ore particle model can be set based on the characteristics of the ore in the actual application environment of the mining electric shovel. For example, parameters such as the density, elastic modulus, and friction coefficient of the material in the ore particle model can be determined by experimental testing, and the particle size distribution of the ore particles can be determined by stepwise sieving.

[0084] The contact forces acting on ore particles can be described using the soft sphere model in EDEM software, which can consider the interactions between particles or multiple particles in the calculation. The contact model between particles can be any of the following: Hertz-Mindlin (no slip), Hertz-Mindlin with Bonding, Hertz-Mindlin with JKR, Linear Cohesion, Linear Spring, Moving Plane, and Trio charging.

[0085] By establishing the above-mentioned ore particle model, the mechanical response between electric shovels of different configurations and ore can be accurately predicted. At the same time, by establishing different types of particle models, the impact of different ore conditions on the performance of electric shovels can be evaluated, enhancing the adaptability of the design.

[0086] Figure 4 The diagram shown illustrates a discrete element method (DEM) simulation of a mining electric shovel; in which, Figure 4 The ore particle model shown is a highly realistic particle model composed of spherical particles of different sizes.

[0087] In step S123, driving functions are set for multiple discrete element simulation models in the discrete element simulation software.

[0088] The driving function is an external input signal applied to the electric shovel simulation model during discrete element simulation to simulate its motion state in actual operation. This driving function can be one or more of the following: displacement function, velocity function, or acceleration function. These functions determine the motion trajectory of the boom, stick, and bucket mechanisms in the electric shovel.

[0089] In step S124, the dynamic digging resistance of the mining electric shovel for each candidate configuration is solved using discrete element simulation software.

[0090] As mentioned earlier, dynamic digging resistance is the instantaneous resistance generated between the bucket and the ore during the digging process of an electric shovel mechanism due to collisions, friction, and shearing. This resistance varies with time and is affected by the configuration of the electric shovel and the characteristics of the ore particles. By calculating the contact force and the sum of the forces between the bucket teeth and the ore particles, the change of dynamic digging resistance over time can be obtained.

[0091] Based on the above technical means, by establishing discrete element simulation models of multiple alternative configurations and constructing an ore particle model, and by setting precise driving functions to simulate the mining process, the dynamic mining resistance is obtained, and the performance evaluation of the three-degree-of-freedom mining electric shovel configuration is realized, thereby improving the scientificity and rationality of configuration selection.

[0092] In some embodiments, such as Figure 5 As shown, the aforementioned step S130 involves solving the dynamic models of multiple alternative configurations of electric mining shovels based on dynamic excavation resistance, determining the dynamic simulation results, and further includes steps S131-S133.

[0093] In step S131, a dynamic simulation model of each candidate configuration of the mining electric shovel is established in the dynamic simulation software.

[0094] The dynamic simulation software could be, for example, Adams, which is widely used in the design and analysis of mechanical systems. It can simulate the motion behavior of complex mechanical systems through modeling and simulation to accurately calculate parameters such as the interaction forces, velocities, and accelerations between components. Figure 6 An example of a dynamic simulation model provided for an embodiment of this application.

[0095] In the technical solution of this application embodiment, for each alternative configuration, a corresponding simulation model is established in the dynamic simulation software, and the connection relationship and constraint conditions between each component are set, thereby generating a complete dynamic simulation model.

[0096] In step S132, a driving function is set for each dynamic simulation model in the dynamic simulation software, and a corresponding dynamic excavation resistance is applied to each dynamic model.

[0097] The aforementioned driving function refers to the input signal set for the driving components in the model during the dynamic simulation process. For example, in a mining electric shovel, different driving functions can be set for the input ends of different branches so that the bucket at the end can move according to a preset law. Meanwhile, to more accurately simulate real working conditions, in this embodiment, during the dynamic simulation, the dynamic digging resistance obtained based on the discrete element simulation method is also applied as an external load to the tip of the bucket teeth.

[0098] More specifically, in the aforementioned steps, discrete element simulation is performed in discrete element simulation software to obtain the resistance changes at different positions of the bucket during the digging process. This resistance data is then imported into dynamic simulation software, and applied to the corresponding positions frame by frame after aligning the time steps, thereby achieving a high-fidelity simulation of the electric shovel mechanism during actual operation.

[0099] In step S133, each dynamic simulation model is solved using dynamic simulation software to obtain the dynamic simulation results for each candidate configuration.

[0100] The dynamic simulation results include velocity curves, acceleration curves, and digging trajectory for multiple points on the bucket teeth. The velocity curves represent the rate of change of distance traveled by each point on the bucket teeth per unit time, reflecting the smoothness of the bucket's movement during digging. The acceleration curves describe the rate of change of velocity at the bucket teeth per unit time. The digging trajectory is the movement path of the bucket teeth in three-dimensional space, reflecting the actual working range and coverage capacity of the bucket during digging. By analyzing the velocity, acceleration, and digging trajectory, the continuity and stability of the mining electric shovel's movement during digging can be intuitively assessed, providing a scientific basis for optimal configuration and ensuring the selected scheme has good engineering feasibility.

[0101] Based on the aforementioned technical methods, by establishing a dynamic model of each candidate configuration of the electric shovel in dynamic simulation software and setting reasonable drive functions and dynamic digging resistance, the velocity curves, acceleration curves, and digging trajectories of each point on the bucket tip can be obtained. This allows for accurate evaluation of the motion continuity and stability of each configuration in actual operation, enabling the selection of the optimal configuration and ultimately improving the overall performance and operational efficiency of the electric shovel.

[0102] In some embodiments, step S140, based on the dynamic simulation results of multiple alternative configurations of the electric shovel and considering the motion continuity and singularity of the electric shovel, determines a more optimal configuration of the electric shovel, further including:

[0103] The first candidate configuration is determined as the preferred configuration if its dynamic simulation results meet the following conditions: the velocity curve corresponding to the first candidate configuration changes smoothly and has no inflection point; the acceleration curve corresponding to the first candidate configuration changes smoothly and has no infinitesimal or infinitesimal points. Here, the first candidate configuration can be one or more of the multiple candidate configurations.

[0104] In the technical solution of this application, the speed curve describes the speed change of a certain point or component of the mining electric shovel over time during operation. A smooth speed curve indicates stable movement without sudden changes or drastic fluctuations, which is beneficial for improving operational efficiency and equipment stability. An inflection point is a point on the speed curve where the direction or slope changes significantly, usually indicating a discontinuity or unusual phenomenon in the mechanism at that location. The presence of an inflection point in the speed curve may mean that the mechanism experiences restricted movement or jamming in that area, affecting overall operational performance.

[0105] The acceleration curve reflects the magnitude and trend of the rate of change of velocity. If the acceleration curve changes smoothly, it indicates that the mechanism transitions naturally during acceleration or deceleration, without causing additional impact or vibration to the structure. The appearance of infinite or infinitesimal points on the acceleration curve indicates that the mechanism may be in a limit state or a state of uncontrolled motion at certain moments. This phenomenon is usually caused by unreasonable mechanism configuration or other improper actions, which may lead to equipment damage or decreased work efficiency.

[0106] By comprehensively analyzing the variation characteristics of velocity and acceleration curves, the motion continuity and non-singular performance of mining electric shovels under specific configurations can be effectively evaluated. Only when both types of curves exhibit good smoothness and stability can the configuration be considered to have high engineering applicability and reliability, and in this case, the configuration is considered superior.

[0107] like Figure 7 As shown, in some embodiments, the aforementioned step S110, based on the motion characteristics and degree-of-freedom requirements of the mining electric shovel, performs type synthesis on the mining electric shovel based on spinor theory to determine multiple alternative configurations of the mining electric shovel, and further includes steps S111-S116.

[0108] In step S111, based on the degrees of freedom and motion characteristics of the mining electric shovel, and using spinor theory, the motion spinor system of the moving platform of the mining electric shovel is determined.

[0109] Screw theory is a unified mathematical tool for describing the motion and mechanical behavior of rigid bodies in space. It represents the displacement and force systems of a rigid body as six-dimensional vector forms of motion screws and force screws, respectively, thereby achieving accurate modeling of the motion degrees of freedom and force constraints of a mechanism. In configuration design, screw theory constructs the target motion screw system at the end of the task, derives the constraint screw system required to achieve that motion, and further maps it to the combination scheme of kinematic pairs and branch structures, guiding the selection of kinematic pair types and branch configurations. It is an efficient design method that derives "structural composition" from "functional objectives." Compared with traditional configuration methods, screw theory is more suitable for spatial parallel mechanisms and hybrid systems, possessing greater accuracy and controllability.

[0110] For example, in a 1R2T three-degree-of-freedom mining electric shovel, the moving platform typically has one rotational degree of freedom and two translational degrees of freedom, and its corresponding kinematic spinor system is:

[0111]

[0112] In step S112, the constraint spinor system of the moving platform is determined according to the spinor reciprocity theory.

[0113] For example, in a 1R2T three-degree-of-freedom mining electric shovel, the corresponding constraint screw system is solved based on the motion screw system of the moving platform:

[0114]

[0115] The screw reciprocity theory is a fundamental theory used to establish a one-to-one correspondence between the motion space and constraint space of a mechanism. Specifically, if the dimension of the mechanism's motion screw system is n, then the dimension of its corresponding constraint screw system must be 6-n. By representing the six degrees of freedom of space in a screw manner, the mechanism space is decomposed into motion space and constraint space, enabling rapid and accurate conversion between motion degrees of freedom and constraints.

[0116] Still with Figure 8 Taking the spinor geometric representation shown as an example, based on the spinor reciprocity theory, we obtain... Figure 9 The constrained spinor system shown is represented by the diagram.

[0117] Figure 9 As shown , As a line vector, it represents a restriction on rotation along this axis. To constrain an even quantity, it means to restrict movement along the direction of that even quantity.

[0118] In step S113, the constraint spinor system of each branch is determined based on the motion characteristics of the dynamic platform constraint spinor system and the multiple branches of the mining electric shovel.

[0119] The branch constraint screw system is a subset obtained by decomposing the moving platform constraint screw system. Each branch is responsible for providing a portion of the constraints to act collectively on the moving platform. By properly allocating the moving platform constraint screw system, it can be ensured that the sum of the independent constraints provided by each branch is consistent with the overall mechanism.

[0120] For example, in the aforementioned 1R2T three-degree-of-freedom mining electric shovel, the constraint condition of the moving platform is a linear vector. , Even quantity .

[0121] Based on the number of branches or the specific motion requirements of a branch, the constraint space of the moving platform is decomposed. The number of independent constraints provided by each branch should be consistent with or equivalent to the total constraints of the moving platform. Considering redundant constraints, several cases may be included:

[0122] (1) Two 6-DOF branches and one 1R2T branch (providing constraints) , , );

[0123] (2) One 6-DOF branch and two 1R2T branches (providing constraints) , , );

[0124] (3) Three 1R2T 3-DOF branches (providing constraints) , , );

[0125] (4) One 6-DOF branch and one 2R2T 4-DOF branch (providing constraints) , or , ) and 1 1R2T 3-DOF branch ( , , );

[0126] (5) Two 2R2T 4-DOF branches (providing constraints) , or , ) and a 1R2T 3-DOF branch (providing constraints) , , );

[0127] (6) Three 2R2T 4-DOF branches (each providing constraints) , or , (At least one branch constraint is different).

[0128] (7) Two 2R3T 5-DOF branches (providing constraints) or ) and one 2R2T 4-DOF branch (providing constraints) , or , );

[0129] (8) Two 2R3T 5-DOF branches (providing constraints) or Two branches (providing different constraints) and one 3R2T 5-DOF branch (providing constraints) ).

[0130] In step S114, based on the constraint spinor system of each branch, the motion spinor system of each branch is determined by the spinor reciprocity theory.

[0131] After determining the constraint screw system of each branch, the motion screw system corresponding to each branch is calculated based on the screw reciprocity theory. By representing the motion screw with geometric characteristics, the role of the branch in the mechanism can be understood more intuitively, and a basis can be provided for the subsequent design of kinematic pair combinations.

[0132] Taking the aforementioned cases (1), (2), and (3) as examples, since all three are provided with the constraints of the moving platform by a single branch, the spinor system of this branch is the same as that of the moving platform, namely:

[0133]

[0134] In step S115, based on the kinematic spinor system of each branch, multiple configurations of each branch are determined.

[0135] Based on the kinematic spinor system of each branch, mathematical elements are converted into kinematic pairs, thereby realizing the combination of kinematic pairs of branches.

[0136] Where the linear vectors are revolute joints and the even quantities are prismatic joints, the arrangement of the kinematic joints is considered, and different arrangements correspond to different branch configurations. Structural variants are formed under different arrangements or connection methods.

[0137] For example, for an RPR branch, its kinematic pairs can be arranged in the order of RPR, or in the manner of PRR or RRP. Different arrangements will affect the overall stiffness, accuracy and range of motion of the branch.

[0138] The kinematic pairs of each branch in the aforementioned situations (1), (2), and (3) are as follows: Figure 10As shown.

[0139] In step S116, multiple alternative configurations of the mining electric shovel are determined based on the multiple configurations of each branch.

[0140] After completing the configuration analysis of each branch, different branches can be combined according to their number and type to form a complete configuration of the mining electric shovel working device. For example, a mechanism composed of 3 RPR branches can form a three-degree-of-freedom configuration; while a mechanism composed of 2 RSS branches and 1 UPU branch may achieve higher stiffness and stability.

[0141] Based on the multiple configurations of each branch determined by the technical solution above, multiple branches are combined to obtain multiple alternative configurations of the mining electric shovel.

[0142] In some embodiments, see Figure 11 The aforementioned step S113, which determines the constraint spinor system of each branch based on the motion characteristics of the dynamic platform constraint spinor system and the multiple branches of the mining electric shovel, further includes steps S1131-S1133.

[0143] In step S1131, the dimension of the constraint spinor system (constraint space) of the moving platform is determined based on the dimension of the motion spinor system (motion space) of the moving platform.

[0144] Screw theory provides a way to transform motion into an algebraic expression, facilitating computation and analysis. Through screw theory and dimension determination, the dimensions of the degree-of-freedom space and constraint space are precisely defined. This eliminates the influence of redundant constraints, thereby improving the accuracy of mechanism configuration design and optimizing the constraint allocation between branches.

[0145] In step S1132, the constraint space of the moving platform is decomposed according to the number of branches and the motion characteristics of each branch, and the constraint situation of each branch is determined. The number of independent constraints provided by each branch is consistent with the dimension of the rotating coefficient system of the moving platform constraint.

[0146] After determining the dimension of the constraint space of the moving platform, these constraints need to be rationally allocated to each branch. Each branch has different degrees of freedom, and therefore provides different independent constraints. For example, a branch with three degrees of freedom provides three independent constraints, while a branch with six degrees of freedom provides no constraints. By decomposing the overall constraint space into constraint subspaces for each branch and ensuring that the number of independent constraints provided by each branch matches the overall independent constraints, consistency between branch constraints and the overall system constraints can be achieved, avoiding contradictions or duplicate constraints between branches.

[0147] In step S1133, the constraint spinor system (constraint space) of each branch is determined according to the constraints of each branch.

[0148] After assigning the branch constraints, the constraint screw system of the branch can be obtained. The branch constraint space refers to the space formed by the opening of all the constraint screws provided by the branch. The space composed of these screws not only describes the constraint form of the branch (such as rotational constraints and translational constraints), but also clarifies its orientation and positional relationship in space, reflecting the constraint capability of the branch on the moving platform, and providing a basis for subsequent branch motion space solution and kinematic pair selection.

[0149] Based on the above technical means, by decomposing the constraint space of the moving platform into the constraint subspace of each branch, and obtaining the corresponding motion space of the branch through spinor reciprocity, the efficiency and accuracy of configuration design can be improved.

[0150] In some embodiments, see Figure 12 The aforementioned step S116, which determines the multiple configurations of each branch based on the multiple configurations of each branch, further includes steps S1161-S1164.

[0151] In step S1161, the various configurations of each branch are determined according to the different arrangement order of the various kinematic pairs of each branch.

[0152] Different types of kinematic pairs, combined in different orders, can generate branched structures with different kinematic properties. For example, a branch can form two different configurations by different arrangements of RPR and PRR.

[0153] Changes in the arrangement order affect the kinematic characteristics and spatial layout of the branches. By altering the arrangement order of the kinematic pairs, the functions of the branches can be diversified without adding extra components. For example, the digging arm branches of a mining shovel may employ an RPR or PRP arrangement, corresponding to different end effector postures and force transmission paths, respectively. Adjusting the arrangement order of the kinematic pairs can optimize the spatial layout of the branches.

[0154] In step S1162, multiple configurations of each branch in the multiple branches are combined to obtain multiple combined configurations of the mining electric shovel.

[0155] Since each branch can have multiple configurations, their combinations generate a large number of potential mechanism schemes. For example, in a three-degree-of-freedom mining electric shovel, if three branches are used, each with three configurations, then a total of [number missing] schemes can be generated. A combination configuration.

[0156] Figure 13 Schematic diagrams of several possible combinations of configurations for a three-degree-of-freedom mining electric shovel are presented.

[0157] In step S1163, the constraint spinor system of each branch is combined to determine the constraint spinor system provided by each branch to the moving platform in each combined configuration, and the dimension of the constraint spinor system corresponding to each combined configuration is determined to determine the motion degree of freedom of each combined configuration.

[0158] By combining the constraint spinor systems of all branches and analyzing the dimension of the spinor systems, the total number of constraints on the moving platform can be accurately calculated, and its degrees of freedom can be derived to determine whether it meets the target motion requirements.

[0159] In step S1164, the combination configuration that matches the degree of freedom requirement of the mining electric shovel among multiple combination configurations is selected as the alternative configuration.

[0160] Degrees of freedom requirement refers to the type and number of degrees of freedom required for a specific motion task to be performed by a mining electric shovel in actual operation. For example, a three-degree-of-freedom electric shovel needs to achieve one rotation and two translations (1R2T) within the working plane.

[0161] When determining alternative configurations, it is necessary to screen out those combinations that can provide a precise match to the degrees of freedom. Only when the branch combination can provide motion capabilities that are completely consistent with the degree of freedom requirements can it be considered a feasible candidate, that is, the alternative configurations mentioned above.

[0162] In some embodiments, see Figure 14 The aforementioned step S150, which involves multi-objective scale synthesis of the preferred configuration, further includes steps S151-S155.

[0163] In step S151, based on the optimal configuration, constraints are established for the electric shovel during actual excavation.

[0164] Based on the results of the configuration design phase, the mechanism type is confirmed, and the motion function indicators that the configuration needs to meet are extracted, such as maximum digging depth (5m), maximum unloading height (9m), and maximum bucket rotation angle (110°), to provide a basis for subsequent parameter modeling and objective function.

[0165] In step S152, the key structural dimensions and kinematic pair installation parameters in the configuration are used as design variables to establish a parametric model of the optimal configuration.

[0166] Based on the structural type, design variables are defined, such as boom length, installation angle, installation hinge point position, and maximum component stroke. These are uniformly defined as optimizable variables, and a parametric model of the optimal configuration is established to lay the foundation for subsequent parametric design.

[0167] In step S153, boundary conditions and design constraints are introduced to establish a multi-objective design solution domain.

[0168] Taking into account the motion performance conditions, structural reliability conditions, and geometric constraints in actual excavation, these are used as boundary conditions and design constraints to form the solution domain, thus defining the range for parameter design.

[0169] In step S154, a multi-objective design function for the optimal configuration is established based on the requirements of the moving platform end trajectory, workspace requirements, and energy consumption requirements.

[0170] Taking into account multiple performance objectives, such as the error between the end trajectory of the moving platform and the logarithmic spinor trajectory, the size of the workspace, and the energy consumption, a multi-objective design function for the optimal configuration is established, providing a basis for determining the optimal parameters.

[0171] In step S155, a genetic algorithm is used to search for the optimal combination of structural dimensions and installation parameters within the solution domain, thereby completing the multi-objective scale integrated design of the optimal configuration.

[0172] The genetic algorithm (GA) is used to search for the optimal combination of design parameters in the parameter space. The design variables are used as chromosomes, the population is initialized and the operation parameters are set. The termination criterion is that the number of iterations in a fixed interval does not change significantly. A global search is performed and the optimized combination of variables is extracted as the final structural size configuration to complete the scale synthesis of the optimal configuration.

[0173] The following is combined Figure 15 The design method of the mining electric shovel provided in the embodiments of this application will be further described.

[0174] This design methodology involves configuration synthesis and multi-objective scale synthesis based on screw theory. Screw theory is used to solve the motion space of the mechanism, and its digital representation enables efficient, rational, and standardized design of the mining electric shovel configuration. For optional configurations, a multi-objective scale synthesis method is employed to establish a parametric model including configuration parameter dimensions. Considering boundary conditions and motion requirements during the excavation process, constraints are added. A multi-objective design function is constructed based on the end-effector trajectory, workspace, and energy consumption. A genetic algorithm is used for global search to obtain the component size configuration that meets workspace requirements and minimizes energy consumption, thus achieving high-performance structural dimensional parameter design for the mining electric shovel working device.

[0175] Figure 15 The method includes steps S1601-S1621.

[0176] In step S1601, the degree-of-freedom characteristics are determined according to the motion requirements of the mining electric shovel.

[0177] Based on the desired motion requirements of the electric shovel mechanism, the nature of the mechanism's degrees of freedom is determined, and the working requirements of the mechanism are clarified, namely, the specific achievable motion forms of the mechanism's end effector in space. Traditional mining electric shovels can only achieve 2T within the working plane. To improve the working flexibility of mining electric shovels, in the solution of this application embodiment, a rotational degree of freedom is added to the moving platform, that is, achieving 1R2T three degrees of freedom within the working plane. The specific motion forms can be found in [reference needed]. Figure 2 .

[0178] In step S1602, the kinematic spinor system of the mining electric shovel platform is solved according to spinor theory.

[0179] Based on the degrees of freedom of the mechanism, the screw theory is used to solve for the kinematic screw system of the moving platform. The kinematic screw system constitutes the motion space of the moving platform, with rotational joints corresponding to linear vectors and translational joints corresponding to even quantities. For example, for a three-degree-of-freedom mining electric shovel with 1R²T degree of freedom, its kinematic screw system is:

[0180]

[0181] In step S1603, the constraint spinor system of the moving platform is determined according to the spinor reciprocity theory.

[0182] Using the screw reciprocity theory, the constraint screw system of the moving platform is solved. The constraint screw system constitutes the constraint space of the moving platform. The linear vector restricts rotation along the linear direction, and the even quantity restricts movement along the even quantity direction. For a three-degree-of-freedom mining electric shovel with 1R²T degree of freedom, its constraint screw system is:

[0183]

[0184] In step S1604, the independent constraint space of the moving platform is determined based on the dimension of the spinor system.

[0185] Based on the dimension of the constraint screw system of the moving platform, determine the actual number of constraints on the moving platform. Remove the interrelated screws in the constraint screw system, and the dimension of the simplified matrix is ​​the dimension of the constraint space.

[0186] In step S1605, the constraint space of the moving platform is decomposed.

[0187] Based on the number of branches or the motion requirements of a specific branch, the constraint space of the moving platform is decomposed. The number of independent constraints provided by each branch should be consistent with or equivalent to the constraints of the moving platform.

[0188] In step S1606, each branch constraint is assigned.

[0189] In the aforementioned 1R2T three-degree-of-freedom mining electric shovel, the constraints on the moving platform are constrained by a double constraint. Line vector , .

[0190] Based on the number of branches or the specific motion requirements of a branch, the constraint space of the moving platform is decomposed. The number of independent constraints provided by each branch should be consistent with or equivalent to the total constraints of the moving platform. Considering redundant constraints, several cases may be included:

[0191] (1) Two 6-DOF branches and one 1R2T branch (providing constraints) , , );

[0192] (2) One 6-DOF branch and two 1R2T branches (providing constraints) , , );

[0193] (3) Three 1R2T 3-DOF branches (providing constraints) , , );

[0194] (4) One 6-DOF branch and one 2R2T 4-DOF branch (providing constraints) , or , ) and 1 1R2T 3-DOF branch ( , , );

[0195] (5) Two 2R2T 4-DOF branches (providing constraints) , or , ) and a 1R2T 3-DOF branch (providing constraints) , , );

[0196] (6) Three 2R2T 4-DOF branches (each providing constraints) , or , (At least one branch constraint is different).

[0197] (7) Two 2R3T 5-DOF branches (providing constraints) or ) and one 2R2T 4-DOF branch (providing constraints) , or , );

[0198] (8) Two 2R3T 5-DOF branches (providing constraints) or Two branches (providing different constraints) and one 3R2T 5-DOF branch (providing constraints) ).

[0199] In step S1607, the constraint spinor system of each branch is solved according to spinor theory.

[0200] In step S1608, the kinematic spinor system of each branch is solved according to the spinor reciprocity theory.

[0201] Taking the aforementioned cases (1), (2), and (3) as examples, since all constraints of the moving platform are provided by a single branch, the constraint space of that branch is consistent with the constraint space of the moving platform, and is:

[0202]

[0203] In step S1609, branches are configured according to constraints and rationality, and the spin of each branch is converted into the corresponding kinematic pair.

[0204] Based on the spinor system of each branch, and considering design rationality, linear vectors or even quantities are converted into kinematic pairs to achieve the combination of kinematic pairs of the branches. Linear vectors represent revolute joints, and even quantities represent translating joints. The order of kinematic pairs is considered, as different arrangements correspond to different branch configurations.

[0205] In step S1610, the branches are combined into a kinematic chain and a hybrid structure. The selected branches are combined using a hybrid mechanism, and the branch arrangement is rationally selected based on mechanical principles.

[0206] In step S1611, the motion space of the hybrid mechanism is solved according to the spinor theory to verify the motion characteristics of the hybrid mechanism. If the degree of freedom requirement is met, step S1612 is executed; otherwise, step S1609 is returned.

[0207] As described above, by combining the constraint spinor systems of all branches and performing dimensional analysis, the total number of constraints on the moving platform can be accurately calculated, and its degrees of freedom can be derived. When the derived degrees of freedom are the same as the degree of freedom requirement in step S1601, it is determined that the hybrid configuration meets the degree of freedom requirement.

[0208] In step S1612, a discrete mechanics and dynamics joint simulation is performed on the hybrid structure. The continuity is verified based on the velocity curve. If the continuity requirement is met, step S1613 is executed; otherwise, step S1609 is returned.

[0209] In step S1613, the singularity is verified based on the acceleration curve of the hybrid structure. If the singularity meets the requirements, step S1614 is executed; otherwise, step S1609 is returned.

[0210] After completing the configuration synthesis of the three-degree-of-freedom mining electric shovel working device, dynamic verification of the new configuration is required. Due to the numerous configurations, solving the dynamics using numerical methods is labor-intensive. Furthermore, the shovel working device experiences varying digging resistance from the material surface during excavation. Therefore, considering granular mechanics, a ore particle model is established in Edem. A simplified three-dimensional model of the new configuration is then created and imported into Adams for configuration, with relevant driving functions set. By combining the dynamic model with the discrete element model, the dynamic digging resistance feedback from the discrete element model allows for accurate solution of the dynamic model. Based on the velocity curves, acceleration curves, and digging trajectory at each point on the bucket tip, the motion continuity of the new configuration mining electric shovel can be determined. If the velocity curve changes smoothly without inflection points, and the acceleration curve changes smoothly without infinity or infinitesimal values, it indicates that the new configuration has motion continuity within this motion range.

[0211] In step S1614, the configuration integration of the hybrid mining electric shovel is completed.

[0212] In step S1615, constraints are established for the electric shovel during actual excavation based on the optimal configuration.

[0213] In step S1616, the key structural dimensions, kinematic pair installation positions, and angle parameters in the configuration are used as design variables to establish a parametric model of the optimal configuration.

[0214] In step S1617, boundary conditions and design constraints are introduced to establish a multi-objective parameter design solution domain.

[0215] In step S1618, a multi-objective design function for the configuration is established based on the end trajectory of the moving platform, the workspace, and the energy consumption.

[0216] In step S1619, a genetic algorithm is used to search for the optimal combination of structural dimensions and installation parameters within the solution domain.

[0217] In step S1620, the multi-objective scale integrated design of the new hybrid mining electric shovel configuration is completed.

[0218] The above text combined Figures 1-15 The method embodiments of this application have been described in detail below, and will be combined with the following. Figure 16 The device embodiments described in this application are presented here. It should be understood that the description of the device embodiments corresponds to the method embodiments. Therefore, any parts not described in detail can be referred to the method embodiments above.

[0219] Figure 16This is a schematic structural diagram of the design device for the mining electric shovel provided in the embodiments of this application. Figure 16 The design device 1600 includes:

[0220] The first determining unit 1610 is used to perform type synthesis on the mining electric shovel based on the rotation theory according to the motion characteristics and degree of freedom requirements of the mining electric shovel, and to determine multiple alternative configurations of the mining electric shovel.

[0221] Discrete element simulation unit 1620 is used to perform discrete element simulation on the multiple candidate configurations of mining electric shovels, and to determine the dynamic digging resistance of the multiple candidate configurations of mining electric shovels respectively.

[0222] The dynamic simulation unit 1630 is used to solve the dynamic model of the multiple alternative configurations of the electric shovel for mining based on the dynamic digging resistance, and to determine the dynamic simulation results.

[0223] The second determining unit 1640 is used to determine the optimal configuration of the mining electric shovel based on the dynamic simulation results of the multiple alternative configurations of the mining electric shovel, and based on the motion continuity, singularity and dynamic digging resistance of the mining electric shovel.

[0224] The scale synthesis unit 1650 is used to establish the parameterized model, boundary conditions and multi-objective design functions of the better configuration according to the multi-objective scale synthesis method, so as to perform multi-objective scale synthesis on the better configuration.

[0225] In some embodiments, the discrete element simulation unit 1620 is further configured to: establish discrete element simulation models of the plurality of alternative configurations of mining electric shovels respectively; establish ore particle models in discrete element simulation software; set driving functions for the plurality of discrete element simulation models respectively in the discrete element simulation software; and use the discrete element simulation software to solve the dynamic digging resistance of each alternative configuration of mining electric shovel.

[0226] In some embodiments, the dynamics simulation unit 1630 is further configured to: establish a dynamics simulation model of each of the candidate configurations of the mining electric shovel in the dynamics simulation software; set a driving function for each of the dynamics simulation models in the dynamics simulation software; and apply a corresponding dynamic digging resistance to each of the dynamics models; solve each of the dynamics simulation models using the dynamics simulation software to obtain the dynamics simulation results for each of the candidate configurations; the dynamics simulation results include velocity curves, acceleration curves, and digging trajectories at multiple points on the tip of the bucket teeth.

[0227] In some embodiments, determining the preferred configuration of the electric shovel based on its motion continuity and singularity includes: determining the first candidate configuration as the preferred configuration if the dynamic simulation results of the first candidate configuration among the plurality of candidate configurations meet the following conditions: the velocity curve corresponding to the first candidate configuration changes smoothly and has no inflection point; the acceleration curve corresponding to the first candidate configuration changes smoothly and the acceleration curve has no infinite or infinitesimal points.

[0228] In some embodiments, the first determining unit is further configured to: determine the motion screw system of the moving platform of the mining electric shovel based on screw theory, according to the degrees of freedom and motion characteristics of the mining electric shovel; determine the constraint screw system of the moving platform based on screw reciprocity theory; determine the constraint screw system of each branch based on the constraint screw system of the moving platform and the motion characteristics of multiple branches of the mining electric shovel; determine the motion screw system of each branch based on the constraint screw system of each branch, using screw reciprocity theory; determine multiple configurations of each branch based on the motion screw system of each branch; and determine multiple alternative configurations of the mining electric shovel based on the multiple configurations of each branch.

[0229] In some embodiments, determining the constraint spinor system of each branch based on the motion characteristics of the moving platform constraint spinor system and the multiple branches of the mining electric shovel includes: determining the dimension of the constraint spinor system of the moving platform based on the dimension of the moving platform's motion spinor system; decomposing the constraint spinor system of the moving platform based on the number of multiple branches and the motion characteristics of each branch to determine the constraint situation of each branch; and determining the constraint spinor system of each branch based on the constraint situation of each branch; wherein the number of independent constraints among all constraints provided by each branch is consistent with the dimension of the constraint spinor system of the moving platform.

[0230] In some embodiments, determining multiple candidate configurations of the mining electric shovel based on multiple configurations of each branch includes: determining multiple configurations of each branch based on different arrangements of multiple kinematic pairs of each branch; combining the multiple configurations of each branch to obtain multiple combined configurations of the mining electric shovel; combining the constraint spinor systems of each branch to determine the constraint spinor system provided by each branch in each combined configuration to the moving platform, determining the dimension of the constraint spinor system corresponding to each combined configuration to determine the motion degrees of freedom of each combined configuration; and selecting the combined configuration whose degrees of freedom in the multiple combined configurations match the degree of freedom requirements of the mining electric shovel as the candidate configuration.

[0231] In some embodiments, the scale integration unit 1650 is further configured to: establish constraints on the mining electric shovel during the excavation process based on the preferred configuration; establish a parameterized model of the optimal configuration by using the structural dimensions and kinematic pair installation parameters in the preferred configuration as design variables; introduce boundary conditions and design constraints to establish a multi-objective design solution domain; establish a multi-objective design function for the preferred configuration based on the end-of-line trajectory requirements, workspace requirements, and energy consumption requirements of the mining electric shovel's moving platform; and use a genetic algorithm to search for the optimal combination of the structural dimensions and the installation parameters within the multi-objective design solution domain to complete the multi-objective scale integration design of the preferred configuration.

[0232] Figure 17 This is a schematic structural diagram of the electronic device provided in the embodiments of this application. Figure 17 The electronic device 1700 is used to implement the design method described in the above method embodiments.

[0233] Electronic device 1700 may include one or more processors 1710. The processor 1710 may support the electronic device 1700 in implementing the methods described in the preceding method embodiments. The processor 1710 may be a general-purpose processor or a special-purpose processor. For example, the processor may be a central processing unit (CPU). Alternatively, the processor 1710 may also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0234] The electronic device 1700 may also include one or more memories 1720. The memories 1720 store a program that can be executed by the processor 1710, causing the processor 1710 to perform the methods described in the preceding method embodiments. The memories 1720 may be independent of the processor 1710 or integrated into the processor 1710.

[0235] This application also provides a computer-readable storage medium storing executable code thereon, which, when executed, can implement the methods in various embodiments of this application.

[0236] This application also provides a computer program product. The computer program product includes a program that causes a computer to perform the methods described in various embodiments of this application.

[0237] This application also provides a computer program. This computer program causes a computer to perform the methods described in the various embodiments of this application.

[0238] It should be understood that in the embodiments of this application, "B corresponding to A" means that B is associated with A, and B can be determined based on A. However, it should also be understood that determining B based on A does not mean that B is determined solely based on A; B can also be determined based on A and / or other information.

[0239] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0240] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0241] In the embodiments provided in this application, it should be understood that the disclosed systems and devices can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0242] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0243] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0244] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can read or a data storage device such as a server or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., digital video discs (DVDs)), or semiconductor media (e.g., solid-state disks (SSDs)).

[0245] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A design method for a hybrid electric mining shovel, characterized in that, The electric shovel used in mining is an electric shovel with one rotational and two translational degrees of freedom. The method includes: Based on the motion characteristics and degree-of-freedom requirements of the mining electric shovel, the mining electric shovel is subjected to type synthesis based on spinor theory to determine multiple alternative configurations of the mining electric shovel. Discrete element simulation was performed on the multiple candidate configurations of the electric shovel to determine the dynamic digging resistance of each of the multiple candidate configurations. The dynamic excavation resistance is used as an external load and input into the dynamic model to solve the dynamic model of the multiple alternative configurations of the electric shovel for mining, and the dynamic simulation results are determined. Based on the dynamic simulation results of the multiple alternative configurations of the electric shovel, and considering the motion continuity and singularity of the electric shovel, the optimal configuration of the electric shovel is determined. Based on the multi-objective scale synthesis method, a parametric model, boundary conditions, and multi-objective design functions for the preferred configuration are established to perform multi-objective scale synthesis on the preferred configuration. Based on the motion characteristics and degree-of-freedom requirements of the mining electric shovel, and using spinor theory, a type synthesis is performed on the mining electric shovel to determine several alternative configurations, including: Based on the degrees of freedom and motion characteristics of the electric mining shovel, and using spinor theory, the motion spinor system of the moving platform of the electric mining shovel is determined. Based on the spinor reciprocity theory, the constraint spinor system of the moving platform is determined; Based on the motion characteristics of the constraint spinor system of the moving platform and the multiple branches of the mining electric shovel, the constraint spinor system of each branch is determined; Based on the constraint spinor system of each branch, the motion spinor system of each branch is determined by the spinor reciprocity theory; Based on the kinematic spinor system of each branch, multiple configurations of each branch are determined; Based on the multiple configurations of each branch, a number of alternative configurations for the mining electric shovel are determined; The step of determining multiple alternative configurations of the mining electric shovel based on multiple configurations of each branch includes: Based on the different arrangement order of the various kinematic pairs of each branch, multiple configurations of each branch are determined; Multiple configurations of the mining electric shovel are obtained by combining the various configurations of each of the multiple branches. Combine the constraint screw system of each branch to determine the constraint screw system provided by each branch in each combined configuration to the moving platform, and determine the dimension of the constraint screw system corresponding to each combined configuration to determine the motion degree of freedom of each combined configuration; The combination configuration in which the degrees of freedom in the multiple combined configurations match the degree of freedom requirement of the mining electric shovel is selected as the alternative configuration; The multi-objective scale synthesis of the preferred configuration includes: Based on the preferred configuration, constraints are established for the mining electric shovel during the excavation process; Using the structural dimensions and kinematic pair installation parameters in the preferred configuration as design variables, a parametric model of the optimal configuration is established. By introducing boundary conditions and design constraints, a multi-objective design solution domain is established. Based on the end-point trajectory requirements, workspace requirements, and energy consumption requirements of the electric shovel's moving platform, a multi-objective design function for the optimal configuration is established. Using a genetic algorithm, the optimal combination of the structural dimensions and the installation parameters is searched within the multi-objective design solution domain to complete the multi-objective scale integrated design of the superior configuration.

2. The method according to claim 1, characterized in that, The discrete element method (DEM) simulation of the multiple candidate configurations of electric mining shovels, to determine the dynamic digging resistance of each candidate configuration, includes: Discrete element simulation models of the multiple alternative configurations of mining electric shovels were established respectively; Establish an ore particle model in discrete element simulation software; In the discrete element simulation software, driving functions are set for each of the discrete element simulation models; The dynamic digging resistance of each of the candidate configurations of the electric shovel is solved using the discrete element simulation software.

3. The method according to claim 2, characterized in that, The process of solving the dynamic models of the multiple alternative configurations of electric mining shovels based on the dynamic digging resistance, and determining the dynamic simulation results, includes: A dynamic simulation model of the mining electric shovel for each of the candidate configurations is established in the dynamic simulation software; In the dynamic simulation software, a driving function is set for each dynamic simulation model, and a corresponding dynamic excavation resistance is applied to each dynamic model; The dynamic simulation software is used to solve each of the dynamic simulation models to obtain the dynamic simulation results of each of the candidate configurations; the dynamic simulation results include the velocity curves, acceleration curves and digging trajectory of multiple points on the tip of the bucket teeth.

4. The method according to claim 3, characterized in that, The process of determining a better configuration of the electric mining shovel based on its motion continuity and singularity includes: The preferred configuration is determined to be the first candidate configuration if the dynamic simulation results of the first candidate configuration among the plurality of candidate configurations meet the following conditions: The velocity curve corresponding to the first alternative configuration changes smoothly and has no inflection point; The acceleration curve corresponding to the first alternative configuration changes smoothly, and the acceleration curve does not have any infinite or infinitesimal points.

5. The method according to claim 1, characterized in that, The step of determining the constraint spinor system of each branch based on the motion characteristics of the constraint spinor system of the moving platform and the multiple branches of the mining electric shovel includes: The dimension of the constraint spinor system of the moving platform is determined based on the dimension of the motion spinor system of the moving platform. Based on the number of branches and the motion characteristics of each branch, the constraint spinor system of the moving platform is decomposed to determine the constraint situation of each branch. Determine the constraint spinor system for each branch based on the constraints of each branch; The number of independent constraints provided by each branch is consistent with the dimension of the constraint spinor system of the moving platform.

6. The method according to claim 1, characterized in that, The step of determining multiple alternative configurations of the mining electric shovel based on multiple configurations of each branch includes: Based on the different arrangement order of the various kinematic pairs of each branch, multiple configurations of each branch are determined; Multiple configurations of the mining electric shovel are obtained by combining the various configurations of each of the multiple branches. Combine the constraint screw system of each branch to determine the constraint screw system provided by each branch in each combined configuration to the moving platform, and determine the dimension of the constraint screw system corresponding to each combined configuration to determine the motion degree of freedom of each combined configuration; The alternative configuration is the one whose degree of freedom in the multiple combined configurations matches the degree of freedom requirement of the mining electric shovel.

7. A design device for a mining electric shovel, characterized in that, The device includes: The first determining unit is used to perform type synthesis on the mining electric shovel based on the rotation theory according to the motion characteristics and degree of freedom requirements of the mining electric shovel, and to determine multiple alternative configurations of the mining electric shovel. The discrete element simulation unit is used to perform discrete element simulation on the multiple candidate configurations of the electric shovel for mining, and to determine the dynamic digging resistance of the multiple candidate configurations of the electric shovel for mining. The dynamic simulation unit is used to input the dynamic digging resistance as an external load into the dynamic model, solve the dynamic model of the multiple alternative configurations of the electric shovel, and determine the dynamic simulation results. The second determining unit is used to determine the optimal configuration of the mining electric shovel based on the dynamic simulation results of the multiple candidate configurations of the mining electric shovel and the motion continuity and singularity of the mining electric shovel. The scale synthesis unit is used to establish the parameterized model, boundary conditions and multi-objective design functions of the better configuration according to the multi-objective scale synthesis method, so as to perform multi-objective scale synthesis on the better configuration; Based on the motion characteristics and degree-of-freedom requirements of the mining electric shovel, and using spinor theory, a type synthesis is performed on the mining electric shovel to determine several alternative configurations, including: Based on the degrees of freedom and motion characteristics of the electric mining shovel, and using spinor theory, the motion spinor system of the moving platform of the electric mining shovel is determined. Based on the spinor reciprocity theory, the constraint spinor system of the moving platform is determined; Based on the motion characteristics of the constraint spinor system of the moving platform and the multiple branches of the mining electric shovel, the constraint spinor system of each branch is determined; Based on the constraint spinor system of each branch, the motion spinor system of each branch is determined by the spinor reciprocity theory; Based on the kinematic spinor system of each branch, multiple configurations of each branch are determined; Based on the multiple configurations of each branch, a number of alternative configurations for the mining electric shovel are determined; The step of determining multiple alternative configurations of the mining electric shovel based on multiple configurations of each branch includes: Based on the different arrangement order of the various kinematic pairs of each branch, multiple configurations of each branch are determined; Multiple configurations of the mining electric shovel are obtained by combining the various configurations of each of the multiple branches. Combine the constraint screw system of each branch to determine the constraint screw system provided by each branch in each combined configuration to the moving platform, and determine the dimension of the constraint screw system corresponding to each combined configuration to determine the motion degree of freedom of each combined configuration; The combination configuration in which the degrees of freedom in the multiple combined configurations match the degree of freedom requirement of the mining electric shovel is selected as the alternative configuration; The multi-objective scale synthesis of the preferred configuration includes: Based on the preferred configuration, constraints are established for the mining electric shovel during the excavation process; Using the structural dimensions and kinematic pair installation parameters in the preferred configuration as design variables, a parametric model of the optimal configuration is established. By introducing boundary conditions and design constraints, a multi-objective design solution domain is established. Based on the end-point trajectory requirements, workspace requirements, and energy consumption requirements of the electric shovel's moving platform, a multi-objective design function for the optimal configuration is established. Using a genetic algorithm, the optimal combination of the structural dimensions and the installation parameters is searched within the multi-objective design solution domain to complete the multi-objective scale integrated design of the superior configuration.

8. A computer-readable storage medium, characterized in that, The computer storage medium is used to store a computer program, which, when run, performs the method as described in any one of claims 1-6.

Images