Lattice structure optimization method, device and equipment with nonlinear stiffness damping and medium

Abstract

The application relates to a lattice structure optimization method, device, equipment and medium with nonlinear stiffness damping, and the method comprises the following steps: taking the relative density of all finite elements as a design variable, constructing a lattice unit cell topology optimization model under horizontal tensile deformation and horizontal compression deformation working conditions; based on the lattice unit cell topology optimization model, a lattice unit cell topology configuration sample is solved, a structure contour feature of the lattice unit cell topology configuration sample is extracted by using an encoder-decoder network, and the structure contour feature is input into a preset adversarial generation network until convergence, so that multiple groups of candidate lattice unit cell topology configurations meeting a stiffness design target are generated; a comprehensive evaluation index is constructed, multiple groups of candidate lattice unit cells are quantitatively scored, an optimal lattice unit cell topology configuration is determined, and the optimal lattice unit cell topology configuration is arranged in a space periodic array to construct the lattice structure. The application can greatly reduce the leakage rate and the reabsorption rate under a high-speed seeding working condition.

Description

Technical Field

[0001] This application relates to the field of vibration reduction in agricultural equipment, and in particular to a method for optimizing a lattice structure with nonlinear stiffness vibration reduction, a corresponding device, electronic equipment, and a computer-readable storage medium. Background Technology

[0002] Air-suction precision seed metering devices have been widely used in precision seeding operations due to their high seed suction accuracy, simple structure, and low seed damage rate. However, with increasing seeding speeds, the forced vibrations of the seed metering device caused by vibrations from undulating ground become increasingly significant, which is the core reason for missed or repeated seed suction under high-speed operating conditions. In precision seeding scenarios, particularly those involving small, pelleted seeds with a diameter of 2 to 3 millimeters, the requirements for seed suction consistency are especially stringent. The adverse effects of vibration on seed suction performance intensify with increasing operating speed, severely restricting the improvement of high-speed operating performance of precision seeding machinery.

[0003] To effectively control the vibration response of the seed metering device, the vibration damping structure must possess both high static load-bearing capacity and low dynamic stiffness, i.e., high static-low dynamic nonlinear stiffness characteristics. High static stiffness ensures that the structure does not undergo excessive static displacement under rated load, while low dynamic stiffness ensures a sufficiently low initial isolation frequency, thereby effectively suppressing the interference of low-frequency vibrations on the seed suction process. Furthermore, during field operations, the load on the seed metering device dynamically changes with the operating speed, requiring the vibration damping structure to be able to adjust its stiffness characteristics in real time to maintain stable low-frequency vibration damping performance under different operating conditions.

[0004] Existing vibration damping structures mainly achieve high static-low dynamic nonlinear stiffness characteristics by introducing negative stiffness elements, such as spring combinations, magnetic negative stiffness mechanisms, or buckling beam structures. However, such solutions generally suffer from the following technical drawbacks:

[0005] First, the introduction of negative stiffness components introduces inherent instability into the system, making it prone to jumping or instability when subjected to disturbances. Second, structural parameters are difficult to adjust online, making it unable to respond to dynamic changes in operating conditions. Third, the multi-component combined structure is large in size and complex to assemble, making it difficult to meet the engineering requirements of the seeding unit for lightweight and easy-to-assemble vibration damping devices.

[0006] In summary, the introduction of negative stiffness elements into existing vibration reduction structures leads to inherent instability, difficulty in online adjustment of structural parameters, and large volume and complex assembly of multi-element combined structures. The applicant has made corresponding explorations to address these issues. Summary of the Invention

[0007] The purpose of this application is to solve the above-mentioned problems by providing a method for optimizing lattice structures with nonlinear stiffness vibration reduction, a corresponding device, electronic equipment, and a computer-readable storage medium.

[0008] To achieve the various objectives of this application, the following technical solution is adopted:

[0009] A lattice structure optimization method with nonlinear stiffness reduction, proposed to meet one of the purposes of this application, includes:

[0010] The upper limit constraint of the initial vibration isolation frequency and the lower limit constraint of the static load stiffness of the lattice structure of the air-suction precision seed meter are determined, wherein the lattice structure includes multiple lattice unit cells.

[0011] Based on the upper bound constraint of the initial vibration isolation frequency and the lower bound constraint of the static load stiffness, the upper and lower control limit curves of the nonlinear stiffness of the lattice structure are constructed using B-spline curves, and these curves are determined as the boundary conditions of the lattice unit cell topology optimization model.

[0012] Based on the SIMP density interpolation method, the design domain of the lattice unit cell is discretized into multiple finite elements to determine the relative density of each finite element. Using the relative density of all finite elements as design variables, a topology optimization model of the lattice unit cell is constructed under horizontal tensile deformation and horizontal compressive deformation conditions. The equivalent stiffness of the lattice unit cell in the vertical direction synchronously approximates the upper and lower control limit curves of the nonlinear stiffness.

[0013] Based on the lattice unit cell topology optimization model, the relative density of different finite elements and the lattice unit cell topology configuration samples corresponding to various load conditions are obtained. The encoder-decoder network is used to extract the structural contour features of the lattice unit cell topology configuration samples, and the structural contour features are input into a preset adversarial generative network for training until convergence, so as to generate multiple sets of candidate lattice unit cell topology configurations that meet the stiffness design target.

[0014] A comprehensive evaluation index including stiffness limit deviation, static bearing capacity, structural quality, and additive manufacturing formability is constructed. The multiple groups of candidate lattice unit cells are quantitatively scored to determine the optimal lattice unit cell topology. The optimal lattice unit cell topology is then arranged in a spatial periodic array to construct the lattice structure, thereby completing the optimization of the lattice structure with nonlinear stiffness vibration reduction.

[0015] Optionally, the step of constructing upper and lower bound curves for the nonlinear stiffness of the lattice structure using B-spline curves based on the upper bound constraint of the initial vibration isolation frequency and the lower bound constraint of the static load stiffness, and determining these curves as boundary conditions for the lattice unit cell topology optimization model, includes:

[0016] Based on the upper bound constraint of the initial vibration isolation frequency and the lower bound constraint of the static load stiffness, the nonlinear stiffness characteristics of the lattice structure are explicitly expressed by B-spline curves. By determining the static equilibrium point, the load extreme point, and the initial vibration isolation point, nonlinear vibration reduction stiffness characteristic curves that meet the precise vibration absorption conditions are constructed under different operating speed conditions.

[0017] The upper and lower envelopes of the nonlinear vibration reduction stiffness characteristic curve are selected as the upper and lower control limit curves of the nonlinear stiffness characteristic, respectively, and the upper and lower control limit curves are determined as the boundary conditions of the lattice unit cell topology optimization model.

[0018] Optionally, the step of discretizing the lattice unit cell design domain into multiple finite elements based on the SIMP density interpolation method to determine the relative density of each finite element includes:

[0019] Based on the SIMP density interpolation method, the design domain of the lattice unit cell is discretized into multiple finite elements, and the relative density of each finite element is used as the design variable to characterize the distribution configuration of the matrix material in the lattice unit cell.

[0020] The first difference between the elastic modulus of the matrix material and the minimum elastic modulus is calculated, and the first product between the relative density of the finite element with the introduced penalty factor and the first difference is calculated, wherein the minimum elastic modulus is used to prevent the introduction of singularity in the stiffness matrix, and the penalty factor is used to cause the relative density of the element to tend towards the boundary value in order to form a material distribution topology.

[0021] The equivalent elastic modulus of each finite element is determined based on the first sum between the minimum elastic modulus and the first product.

[0022] Optionally, the step of constructing a lattice unit cell topology optimization model, using the relative density of all finite elements as design variables, under horizontal tensile and compressive deformation conditions, in which the equivalent stiffness of the lattice unit cell in the vertical direction synchronously approximates the upper and lower control limit curves of the nonlinear stiffness, includes:

[0023] The first equivalent stiffness of the lattice unit cell in the vertical direction under horizontal tensile deformation, the second equivalent stiffness of the lattice unit cell in the vertical direction under horizontal compressive deformation, the first target stiffness of the upper control limit curve of the nonlinear stiffness under the horizontal tensile deformation at the corresponding displacement, and the second target stiffness of the lower control limit curve of the nonlinear stiffness under the horizontal compressive deformation at the corresponding displacement are obtained.

[0024] Calculate and determine the first square value of the Euclidean norm between the first equivalent stiffness and the first target stiffness, calculate and determine the second square value of the Euclidean norm between the second equivalent stiffness and the second target stiffness, and minimize the weighted sum between the first square value and the second square value as the objective function of the lattice unit cell topology optimization model.

[0025] Using the structural stiffness equation of the lattice unit cell as the mechanical equilibrium constraint, and the upper limit of the material volume fraction of the lattice unit cell and the range of relative density values ​​of the finite elements as constraints, a topology optimization model of the lattice unit cell is constructed to simultaneously approximate the upper and lower control limit curves of the nonlinear stiffness with the equivalent stiffness of the lattice unit cell in the vertical direction.

[0026] Optionally, the step of calibrating the upper limit constraint of the initial vibration isolation frequency and the lower limit constraint of the static load stiffness of the lattice structure of the air-suction precision seed meter includes:

[0027] Time-domain signals of vibration acceleration of a pneumatic precision seed metering device at multiple operating speeds were collected.

[0028] The vibration acceleration time-domain signal is converted into a vibration acceleration frequency-domain signal by fast Fourier transform, and the vibration acceleration frequency-domain signal is integrated twice to obtain the vibration displacement frequency-domain signal. Then, the vibration displacement frequency-domain signal is restored to the vibration displacement time-domain signal by inverse Fourier transform.

[0029] Based on the spatial power spectral density analysis results of the road surface unevenness spectrum sequence, the acceleration distribution matrix corresponding to each vibration excitation frequency of the air-suction precision seed metering device under different operating speeds is determined, so as to calibrate the upper limit constraint of the initial vibration isolation frequency and the lower limit constraint of the static bearing stiffness of the lattice structure of the air-suction precision seed metering device.

[0030] Optionally, after the step of arranging the optimal lattice unit cell topology in a spatially periodic array to construct the lattice structure, the method includes:

[0031] Using the optimal lattice unit cell topology as the basic unit, a lattice structure is constructed by arranging multiple units in a spatial periodic array.

[0032] Multiple horizontal tensile and compressive deformations are applied, and the equivalent stiffness of the lattice structure in the vertical direction corresponding to each horizontal tensile and compressive deformation is calculated. A discrete correspondence between the horizontal tensile and compressive deformations and the equivalent stiffness in the vertical direction is established, and a nonlinear stiffness control model is established by curve fitting.

[0033] The target vertical equivalent stiffness is determined based on the real-time operating speed and real-time load information of the air-suction precision seed metering device. The target vertical equivalent stiffness is then input into the nonlinear stiffness control model to output the target horizontal tension and compression deformation command. The target horizontal tension and compression deformation command is executed to perform closed-loop active control of the vertical nonlinear stiffness.

[0034] Optionally, the lattice unit cell is the smallest basic unit that constitutes a periodic lattice structure. It can be assembled into an overall lattice structure by repeatedly arranging them in a spatial periodic array.

[0035] A lattice structure optimization device with nonlinear stiffness reduction, provided for another purpose of this application, includes:

[0036] The vibration excitation parameter calibration module is set to calibrate the upper limit constraint of the initial vibration isolation frequency and the lower limit constraint of the static load stiffness of the lattice structure of the air-suction precision seed meterer, wherein the lattice structure includes multiple lattice unit cells.

[0037] The stiffness control limit construction module is set to construct the upper and lower control limit curves of the nonlinear stiffness of the lattice structure based on the upper limit constraint of the initial vibration isolation frequency and the lower limit constraint of the static load stiffness using B-spline curves, and determine them as the boundary conditions of the lattice unit cell topology optimization model.

[0038] The topology optimization model construction module is configured to discretize the lattice unit cell design domain into multiple finite elements based on the SIMP density interpolation method to determine the relative density of each finite element. Using the relative density of all finite elements as design variables, under horizontal tensile deformation and horizontal compressive deformation conditions, a lattice unit cell topology optimization model is constructed in which the equivalent stiffness of the lattice unit cell in the vertical direction synchronously approximates the upper and lower control limit curves of the nonlinear stiffness.

[0039] The unit cell topology configuration generation module is configured to solve for the relative density of different finite elements and the lattice unit cell topology configuration samples corresponding to various load conditions based on the lattice unit cell topology optimization model. The encoder-decoder network is used to extract the structural contour features of the lattice unit cell topology configuration samples, and the structural contour features are input into a preset adversarial generative network for training until convergence, so as to generate multiple sets of candidate lattice unit cell topology configurations that meet the stiffness design target.

[0040] The lattice structure construction module is configured to construct a comprehensive evaluation index including stiffness limit deviation, static bearing capacity, structural quality, and additive manufacturing formability. It quantifies and scores the multiple candidate lattice unit cells, determines the optimal lattice unit cell topology, and arranges the optimal lattice unit cell topology in a spatial periodic array to construct the lattice structure, thereby completing the optimization of the lattice structure with nonlinear stiffness vibration reduction.

[0041] An electronic device provided for another purpose of this application includes a central processing unit and a memory, wherein the central processing unit is used to invoke and run a computer program stored in the memory to perform the steps of the lattice structure optimization method with nonlinear stiffness reduction described in this application.

[0042] A computer-readable storage medium is provided for another purpose of this application, which stores, in the form of computer-readable instructions, a computer program implemented according to the aforementioned lattice structure optimization method with nonlinear stiffness vibration reduction, which, when called by a computer, executes the steps included in the corresponding method.

[0043] Compared to existing technologies, this application addresses the problems of inherent instability caused by the introduction of negative stiffness elements in existing vibration reduction structures, difficulty in online adjustment of structural parameters, and large volume and complex assembly of multi-element combined structures. This application includes, but is not limited to, the following beneficial effects:

[0044] Firstly, this application abandons the traditional design approach of relying on negative stiffness elements such as spring combinations, magnetic mechanisms, and buckling beams for vibration reduction structures. Instead, it relies on lattice unit cell topology optimization and periodic array construction to achieve high static-low dynamic nonlinear stiffness characteristics, thereby eliminating the inherent instability of the system caused by negative stiffness elements from the root, avoiding structural jumping and instability under operating disturbances, and improving the operational reliability of the seed metering vibration reduction system.

[0045] Secondly, this application establishes a mapping and control model between horizontal deformation and the vertical equivalent stiffness of the lattice structure through controllable horizontal tensile and compressive deformation. It can dynamically adjust the nonlinear stiffness of the structure according to the real-time operating speed of the seed metering device and changes in field load, thus solving the defects of existing vibration reduction structures that cannot be adjusted online and cannot adapt to multi-condition vibration excitation. It maintains the stability of low-frequency vibration isolation and precision seed collection throughout the process.

[0046] Thirdly, this application uses lattice unit cells as basic units to arrange spatial periodic arrays, and combines topology optimization and volume fraction constraints to achieve lightweight structural design. Compared with traditional multi-element combined vibration reduction mechanisms, the overall configuration is compact, highly modular, and has a simple assembly process, which can meet the engineering application requirements of air-suction precision seeding units for vibration reduction devices with small volume, easy assembly, and low additional load.

[0047] Fourth, a dual-condition multi-objective topology optimization model is constructed based on the SIMP density interpolation method. The goal is to accurately approximate the upper and lower limits of nonlinear stiffness in vertical stiffness, while applying multiple mechanical and manufacturability constraints. Then, candidate unit cell configurations are generated in batches by combining encoder-decoder feature extraction with adversarial generative networks. This solves the problems of difficult analytical acquisition of sensitivity, single design scheme, and low optimization efficiency in traditional nonlinear topology optimization, and obtains more novel lattice topology configurations that meet the requirements of stiffness, load-bearing capacity, and manufacturing.

[0048] Fifth, construct a quantitative evaluation system that includes stiffness limit deviation, static bearing capacity, structural quality, and additive manufacturing formability. Select the optimal matrix unit cell from multiple dimensions such as vibration reduction accuracy, bearing strength, lightweight level, and additive manufacturing process adaptability to ensure that the designed structure not only meets the nonlinear stiffness vibration reduction design target, but also has good engineering machinability and service durability.

[0049] Furthermore, this application precisely calibrates the constraint boundary by using the road spectrum and vibration excitation characteristics of undulating farmland, and matches the sensitive frequency range of the seed metering device for precision seed suction vibration. This effectively suppresses the transmission of low-frequency vibration in the field, significantly reduces the missed suction rate and repeated suction rate under high-speed sowing conditions, solves the industry pain point of vibration interference restricting the speed-up operation of precision sowing machinery, and improves the seed suction consistency and sowing uniformity in harsh scenarios such as small-diameter pelleted seeds. Attached Figure Description

[0050] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0051] Figure 1 This is a flowchart illustrating the optimization method for a lattice structure with nonlinear stiffness vibration reduction in this application embodiment;

[0052] Figure 2 This is a schematic diagram of the process for collecting ground unevenness and extracting the vibration damping stiffness constraint of the seed metering device in an embodiment of this application;

[0053] Figure 3 This is a schematic diagram of the deep learning-assisted lattice unit cell topology optimization generation and selection process in an embodiment of this application;

[0054] Figure 4 This is a schematic diagram of the lattice structure optimization device with nonlinear stiffness reduction in the embodiments of this application;

[0055] Figure 5 This is a schematic diagram of the structure of the computer device in the embodiments of this application. Detailed Implementation

[0056] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application.

[0057] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this application means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when we say an element is “connected” or “coupled” to another element, it can be directly connected or coupled to the other element, or there may be intermediate elements. Furthermore, “connected” or “coupled” as used herein can include wireless connections or wireless coupling. The term “and / or” as used herein includes all or any units and all combinations of one or more associated listed items.

[0058] Those skilled in the art will understand that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the same meaning as in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined as herein.

[0059] Those skilled in the art will understand that the terms "client," "terminal," and "terminal device" as used herein include both devices that receive wireless signals, devices that only possess wireless signal receiver capabilities without transmission capabilities, and devices with receiving and transmitting hardware, devices that have receiving and transmitting hardware capable of bidirectional communication over a bidirectional communication link. Such devices may include: cellular or other communication devices such as personal computers or tablets, having single-line displays, multi-line displays, or cellular or other communication devices without multi-line displays; PCS (Personal Communications Service) that can combine voice, data processing, fax, and / or data communication capabilities; PDAs (Personal Digital Assistants) that may include radio frequency receivers, pagers, internet / intranet access, web browsers, notebooks, calendars, and / or GPS (Global Positioning System) receivers; and conventional laptops and / or handheld computers or other devices that have and / or include radio frequency receivers. As used herein, "client," "terminal," and "terminal device" can be portable, transportable, installed in a means of transportation (air, sea, and / or land), or suitable and / or configured to operate locally and / or in a distributed manner, operating in any other location on Earth and / or in space. "Client," "terminal," and "terminal device" as used herein can also be a communication terminal, an internet access terminal, or a music / video playback terminal, such as a PDA, a MID (Mobile Internet Device), and / or a mobile phone with music / video playback capabilities, or a smart TV, set-top box, etc.

[0060] The hardware referred to by the names "server," "client," and "service node" in this application is essentially an electronic device with the equivalent capabilities of a personal computer. It is a hardware device with the necessary components revealed by the von Neumann architecture, such as a central processing unit (including an arithmetic logic unit and a control unit), memory, input devices, and output devices. The computer program is stored in its memory, and the central processing unit loads the program stored in the secondary storage into the main memory to run it, execute the instructions in the program, and interact with the input and output devices to complete specific functions.

[0061] It should be noted that the concept of "server" used in this application can also be extended to the case of server clusters. Based on the network deployment principles understood by those skilled in the art, the servers should be logically divided. Physically, these servers can be independent of each other but accessible through interfaces, or they can be integrated into a single physical computer or a computer cluster. Those skilled in the art should understand this flexibility and should not use it to constrain the implementation of the network deployment method in this application.

[0062] One or more of the technical features of this application, unless explicitly specified herein, can be deployed on a server and accessed by a client remotely calling the online service interface provided by the server, or can be directly deployed and run on a client for access.

[0063] Unless otherwise specified, the neural network models referenced or potentially referenced in this application may be deployed on a remote server and invoked remotely on the client, or deployed on a client with the capability to invoke directly. In some embodiments, when running on the client, the corresponding intelligence may be acquired through transfer learning in order to reduce the requirements on the client's hardware resources and avoid excessive consumption of the client's hardware resources.

[0064] Unless otherwise specified, all data involved in this application may be stored remotely on a server or on a local terminal device, as long as it is suitable for use by the technical solution of this application.

[0065] Those skilled in the art will understand that although the various methods in this application are described based on the same concept and thus present commonality among them, they can be performed independently unless otherwise specified. Similarly, the various embodiments disclosed in this application are all based on the same inventive concept; therefore, concepts expressed in the same way, as well as concepts that are appropriately changed for convenience but are expressed differently, should be understood equivalently.

[0066] Unless otherwise expressly stated, the various embodiments disclosed in this application can be combined in a cross-cutting manner to flexibly construct new embodiments, as long as such combination does not depart from the inventive spirit of this application and can meet the needs of the prior art or solve a certain deficiency in the prior art. Those skilled in the art should be aware of such modifications.

[0067] Please see Figure 1 In one embodiment of the lattice structure optimization method with nonlinear stiffness reduction of this application, the method includes:

[0068] Step S10: Calibrate the upper limit constraint of the initial vibration isolation frequency and the lower limit constraint of the static load stiffness of the lattice structure of the air-suction precision seed meter, wherein the lattice structure includes multiple lattice unit cells.

[0069] The terminal equipment, equipped with a nonlinear stiffness vibration reduction lattice structure optimization system, can acquire the surface unevenness spectrum sequence of the air-suction precision seed metering device on undulating farmland. By processing the surface unevenness spectrum sequence through spatial power spectral density analysis, the acceleration distribution matrix corresponding to each vibration excitation frequency at different operating speeds is obtained. This matrix is ​​used to calibrate the upper bound constraint of the initial vibration isolation frequency and the lower bound constraint of the static load-bearing stiffness of the lattice structure of the air-suction precision seed metering device. The lattice structure comprises multiple lattice unit cells; each lattice unit cell is the smallest basic unit constituting a periodic lattice structure. These cells can be assembled into an overall lattice structure through repeated spatial periodic array arrangements.

[0070] Specifically, the inertial reference method was used to collect the surface unevenness spectrum sequence of farmland: using a rigid straight beam as the measurement reference, a displacement recorder was moved at a constant speed along the working direction to record the longitudinal profile of the measured ground; combined with the adjustment of the adjusting supports at both ends of the rigid straight beam using a level, the ground unevenness was accurately measured. After repeated measurements, the effective unevenness data were processed by spatial power spectral density (PSD) analysis to obtain the vibration frequency and acceleration distribution matrix of the air-suction precision seed metering device under different operating speeds (0 to 8 km / h).

[0071] Based on the multiphysics coupling simulation analysis results of the seed metering device's precision seed suction vibration conditions, the critical frequency range that leads to a significant decrease in the seed metering device's seed suction performance is determined. The lower limit of this range is used as the upper bound constraint of the starting vibration isolation frequency of the lattice structure. This refers to the upper limit of the low dynamic stiffness design target; simultaneously, based on the known load range of the lattice structure... To prevent excessive static displacement at the static equilibrium point. As a criterion, determine the minimum support stiffness that the structure must satisfy. Establish the lower bound constraint of the static load-bearing stiffness of the lattice structure.

[0072] In some embodiments, the step of calibrating the upper limit constraint of the initial vibration isolation frequency and the lower limit constraint of the static load-bearing stiffness of the lattice structure of the air-suction precision seed meter includes:

[0073] Step S101: Collect the time-domain signals of vibration acceleration of the air-suction precision seed metering device at multiple operating speeds;

[0074] Step S102: Convert the vibration acceleration time-domain signal into a vibration acceleration frequency-domain signal using a fast Fourier transform, perform a second integration on the vibration acceleration frequency-domain signal to obtain a vibration displacement frequency-domain signal, and then use an inverse Fourier transform to restore the vibration displacement frequency-domain signal to a vibration displacement time-domain signal.

[0075] Step S103: Based on the spatial power spectral density analysis results of the surface unevenness road spectrum sequence, determine the acceleration distribution matrix corresponding to each vibration excitation frequency of the air-suction precision seed metering device at different operating speeds, so as to calibrate the upper limit constraint of the initial vibration isolation frequency and the lower limit constraint of the static bearing stiffness of the lattice structure of the air-suction precision seed metering device.

[0076] Specifically, an electric vibration testing system is used for signal acquisition. The system includes an acceleration sensor, a signal acquisition module, and a data processing terminal. The acceleration sensor is installed vertically on the base of the seed metering device to acquire the vibration acceleration time-domain signal of the seed metering device at various operating speeds from 0 to 8 km / h.

[0077] The vibration acceleration time-domain signal is processed using a frequency domain integration method. A Fast Fourier Transform (FFT) is used to convert the vibration acceleration time-domain signal into a vibration acceleration frequency-domain signal. A second integration is performed on the vibration acceleration frequency-domain signal to obtain the vibration displacement frequency-domain signal. This is then restored to the vibration displacement time-domain signal using an Inverse Fourier Transform (IFFT). The steady-state vibration amplitude and frequency range of the air-suction precision seed metering device under typical operating conditions are extracted. Combined with the spatial power spectral density analysis results of the surface unevenness road spectrum sequence, the excitation vibration frequency and acceleration distribution matrix are jointly determined. In the frequency domain, there is an interrelationship between displacement and acceleration. The relationship (corresponding to the second-order differential in the time domain). For Inverting the expression yields the frequency domain representation of the displacement, enabling frequency domain integration from acceleration to displacement and avoiding the problems of accumulated errors and low-frequency drift in time domain integration. Cutoff frequency [ , It acts as a bandpass filter, preserving the effective frequency band of the vibration signal. Therefore, the calculation formula for converting the vibration acceleration time-domain signal into the vibration displacement frequency-domain signal using Fast Fourier Transform is expressed as:

[0078]

[0079] in, Represents the frequency domain signal of vibration displacement; The Fourier transform of the time-domain signal of vibration acceleration; Indicates the lower limit of the cutoff frequency; Indicates the upper limit of the cutoff frequency;

[0080] Furthermore, the formula for calculating the vibration displacement time-domain signal by inverse Fourier transform is as follows:

[0081]

[0082] in, Represents the time-domain signal of vibration displacement; This is the inverse Fourier transform operator.

[0083] As can be seen from the above calculation formula, transforming the displacement signal obtained by frequency domain integration back to the time domain yields a displacement time history that can be directly analyzed. This history is used to extract the steady-state vibration amplitude and frequency range of the air-suction precision seed metering device under typical operating conditions, providing a data basis for the construction of the acceleration distribution matrix.

[0084] Step S20: Based on the upper bound constraint of the initial vibration isolation frequency and the lower bound constraint of the static load stiffness, the upper and lower control limit curves of the nonlinear stiffness of the lattice structure are constructed using B-spline curves, and these curves are determined as the boundary conditions of the lattice unit cell topology optimization model.

[0085] A surface unevenness spectrum sequence of the air-suction precision seed metering device on undulating farmland is obtained. The surface unevenness spectrum sequence is processed by spatial power spectral density analysis to obtain the acceleration distribution matrix corresponding to each vibration excitation frequency at different operating speeds. After calibrating the upper bound constraint of the initial vibration isolation frequency and the lower bound constraint of the static load-bearing stiffness of the lattice structure of the air-suction precision seed metering device, based on the upper bound constraint of the initial vibration isolation frequency and the lower bound constraint of the static load-bearing stiffness, the upper and lower control limit curves of the nonlinear stiffness of the lattice structure are constructed using B-spline curves, and these are determined as the boundary conditions of the lattice unit cell topology optimization model.

[0086] In some embodiments, the step of constructing upper and lower bound curves for the nonlinear stiffness of the lattice structure using B-spline curves based on the upper bound constraint of the initial vibration isolation frequency and the lower bound constraint of the static load stiffness, and determining these curves as boundary conditions for the lattice unit cell topology optimization model, includes:

[0087] Step S201: Based on the upper bound constraint of the initial vibration isolation frequency and the lower bound constraint of the static load stiffness, the nonlinear stiffness characteristics of the lattice structure are explicitly expressed by B-spline curves. By determining the static equilibrium point, the load extreme point, and the initial vibration isolation point, a nonlinear vibration reduction stiffness characteristic curve that satisfies the precise vibration absorption condition is constructed under different operating speed conditions.

[0088] Specifically, the static equilibrium point corresponds to the lattice structure under rated load. working displacement below The stiffness at this point satisfies The extreme point of the load corresponds to the maximum load. With minimum load Displacement limit below , The initial vibration isolation point corresponds to the initial vibration isolation frequency constraint. The corresponding upper limit of dynamic stiffness ,in, The equivalent quality of the seed metering device.

[0089] Under different operating speeds from 0 to 8 km / h, the above characteristic point determination process was repeated to construct a set of nonlinear vibration reduction stiffness characteristic curves that meet the conditions for precision seed absorption vibration.

[0090] Step S202: Select the upper and lower envelopes of the nonlinear vibration reduction stiffness characteristic curve as the upper and lower control limit curves of the nonlinear stiffness characteristic, respectively, and determine the upper and lower control limit curves as the boundary conditions of the lattice unit cell topology optimization model.

[0091] The upper and lower envelopes of the nonlinear vibration reduction stiffness characteristic curve are selected as the upper control limit curves of the nonlinear stiffness characteristic. With lower control limit curve The upper and lower control limit curves are determined as the boundary conditions of the lattice unit cell topology optimization model.

[0092] Step S30: Discretize the lattice unit cell design domain into multiple finite elements based on the SIMP density interpolation method to determine the relative density of each finite element. Using the relative density of all finite elements as design variables, construct a lattice unit cell topology optimization model under horizontal tensile deformation and horizontal compressive deformation conditions, in which the equivalent stiffness of the lattice unit cell in the vertical direction synchronously approximates the upper and lower control limit curves of the nonlinear stiffness.

[0093] Based on the upper bound constraint of the initial vibration isolation frequency and the lower bound constraint of the static load stiffness, the upper and lower control limit curves of the nonlinear stiffness of the lattice structure are constructed using B-spline curves. After determining these curves as the boundary conditions of the lattice unit cell topology optimization model, the lattice unit cell design domain is discretized into multiple finite elements based on the SIMP density interpolation method to determine the relative density of each finite element. Using the relative density of all finite elements as design variables, under horizontal tensile deformation and horizontal compressive deformation conditions, a lattice unit cell topology optimization model is constructed in which the equivalent stiffness of the lattice unit cell in the vertical direction synchronously approximates the upper and lower control limit curves of the nonlinear stiffness.

[0094] In some embodiments, the step of discretizing the lattice unit cell design domain into multiple finite elements based on the SIMP density interpolation method to determine the relative density of each finite element includes:

[0095] Step S301: Based on the SIMP density interpolation method, the lattice unit cell design domain is discretized into multiple finite elements, and the relative density of each finite element is used as the design variable to characterize the distribution configuration of the matrix material in the lattice unit cell.

[0096] Based on the SIMP density interpolation method (SIMP method), the lattice unit cell design domain is... Discretized A finite number of elements, with the relative density of each element. As a design variable, it describes the distribution configuration of the matrix material in the unit cell.

[0097] Step S302: Calculate and determine the first difference between the elastic modulus of the matrix material and the minimum elastic modulus, and calculate and determine the first product between the relative density of the finite element with the introduced penalty factor and the first difference, wherein the minimum elastic modulus is used to prevent the introduction of singularity in the stiffness matrix, and the penalty factor is used to cause the relative density of the element to tend towards the boundary value in order to form a material distribution topology.

[0098] Step S303: Determine the equivalent elastic modulus of each finite element based on the first sum value between the minimum elastic modulus and the first product.

[0099] The expression for the equivalent elastic modulus of each finite element is as follows:

[0100]

[0101] in, For the first The relative density of a finite element, with values ​​ranging from [0, 1], where 0 represents empty material and 1 represents solid material; For the first The equivalent elastic modulus of a finite element; The elastic modulus of the matrix material; To prevent the introduction of a minimum elastic modulus due to the singularity of the stiffness matrix, we take... ; The penalty factor (can be taken as follows) , used for The penalty factor (tending towards a clear topology of 0 or 1) The value is not limited to 3 and can be adjusted within the range of 2 to 5 according to the characteristics of the matrix material and the optimization convergence requirements; upper limit of material volume fraction. The value can be set in the range of 0.3 to 0.6 according to the lightweight requirements of the vibration reduction structure.

[0102] As can be seen from the above expression, the core objective of topology optimization is to determine whether the material is present or not within the design domain. The SIMP method relaxes the discrete material states into continuous density variables in the interval [0,1] and introduces a power penalty term to suppress the intermediate density, thereby driving the density variables to converge toward the boundary value during the optimization process, and finally forming a clear topological configuration close to 0 or 1.

[0103] In a further embodiment, the step of constructing a lattice unit cell topology optimization model, using the relative density of all finite elements as design variables, under horizontal tensile and compressive deformation conditions, in which the equivalent stiffness of the lattice unit cell in the vertical direction synchronously approximates the upper and lower control limit curves of the nonlinear stiffness, includes:

[0104] Step S3001: Obtain the first equivalent stiffness of the lattice unit cell in the vertical direction under horizontal tensile deformation, the second equivalent stiffness of the lattice unit cell in the vertical direction under horizontal compressive deformation, the first target stiffness of the upper control limit curve of the nonlinear stiffness under the horizontal tensile deformation at the corresponding displacement, and the second target stiffness of the lower control limit curve of the nonlinear stiffness under the horizontal compressive deformation at the corresponding displacement.

[0105] Horizontal tensile deformation Horizontal compression deformation Under two loading conditions, the first equivalent stiffness of the lattice unit cell in the vertical direction under horizontal tensile deformation is obtained. The second equivalent stiffness of the lattice unit cell in the vertical direction under horizontal compressive deformation conditions. The first target stiffness at the corresponding displacement is the upper control limit curve of the nonlinear stiffness under the horizontal tensile deformation condition. And the second target stiffness at the corresponding displacement of the lower control limit curve of the nonlinear stiffness under the horizontal compression deformation condition. .

[0106] Step S3002: Calculate and determine the first square value of the Euclidean norm between the first equivalent stiffness and the first target stiffness, and calculate and determine the second square value of the Euclidean norm between the second equivalent stiffness and the second target stiffness, so as to minimize the weighted sum between the first square value and the second square value as the objective function of the lattice unit cell topology optimization model.

[0107] Calculate and determine the first square value of the Euclidean norm between the first equivalent stiffness and the first target stiffness. Calculate and determine the second square value of the Euclidean norm between the second equivalent stiffness and the second target stiffness. The objective function of the lattice unit cell topology optimization model is to minimize the weighted sum between the first squared value and the second squared value, wherein the expression of the objective function of the lattice unit cell topology optimization model is:

[0108]

[0109] in, The design variable vector consists of the relative densities of all finite elements; The objective function for the lattice unit cell topology optimization model is the total error that needs to be minimized. , Let be the weight coefficients of the two objectives, satisfying... This reflects the relative importance attached to approximating the upper and lower control limit curves of nonlinear stiffness. It is the square of the Euclidean norm, used to measure the magnitude of the deviation between the actual stiffness and the target stiffness.

[0110] As can be seen from the expression of the objective function of the above lattice unit cell topology optimization model, it embodies the dual-objective design concept of "one unit cell configuration simultaneously satisfying two stiffness limits." (Horizontal tensile deformation) Driven vertical stiffness approaches the upper limit, horizontal compressive deformation By driving the vertical stiffness to approach the lower limit, and minimizing the weighted sum of the two, the unit cell configuration corresponding to the two boundaries of the stiffness control range can be obtained simultaneously in one optimization.

[0111] Step S3003: Using the structural stiffness equation of the lattice unit cell as the mechanical equilibrium constraint, and the upper limit of the material volume fraction of the lattice unit cell and the relative density range of the finite element as the constraint conditions, construct a lattice unit cell topology optimization model in which the equivalent stiffness of the lattice unit cell in the vertical direction synchronously approximates the upper and lower control limit curves of the nonlinear stiffness.

[0112] The structural stiffness equation of the lattice unit cell As a mechanical equilibrium constraint, the upper limit of the material volume fraction of the lattice unit cell is used. and the range of relative density values ​​for finite elements. As constraints, a lattice unit cell topology optimization model is constructed to simultaneously approximate the upper and lower control limit curves of the nonlinear stiffness with the equivalent stiffness of the lattice unit cell in the vertical direction. .

[0113] in, Represents the overall stiffness matrix of the structure; Represents the nodal displacement vector; Represents the external load vector;

[0114] This indicates an upper limit constraint on the volume fraction of the material. This represents the lower limit of relative density to prevent the stiffness matrix from becoming singular.

[0115] Structural stiffness equation These are the fundamental equilibrium equations of finite element analysis, serving as the mechanical equilibrium constraints for the optimization problem. In each iteration, for a given set of design variables... The displacement field must first be obtained by solving the stiffness equation of the structure. Only then can the equivalent stiffness in the vertical direction be calculated. This allows for the evaluation of the objective function value. It guarantees that each candidate design physically satisfies mechanical equilibrium.

[0116] Step S40: Based on the lattice unit cell topology optimization model, solve for the relative density of different finite elements and the lattice unit cell topology configuration samples corresponding to various load conditions. Use an encoder-decoder network to extract the structural contour features of the lattice unit cell topology configuration samples, and input the structural contour features into a preset adversarial generative network for training until convergence, so as to generate multiple sets of candidate lattice unit cell topology configurations that meet the stiffness design target.

[0117] Based on the SIMP density interpolation method, the lattice unit cell design domain is discretized into multiple finite elements to determine the relative density of each finite element. Using the relative density of all finite elements as design variables, a lattice unit cell topology optimization model is constructed under horizontal tensile and compressive deformation conditions. This model synchronously approximates the upper and lower control limit curves of the nonlinear stiffness with the equivalent stiffness of the lattice unit cell in the vertical direction. Based on the lattice unit cell topology optimization model, lattice unit cell topology configuration samples with different relative densities of finite elements and various load conditions are obtained. An encoder-decoder network is used to extract the structural contour features of the lattice unit cell topology configuration samples. The structural contour features are then input into a preset adversarial generative network and trained until convergence to generate multiple sets of candidate lattice unit cell topology configurations that meet the stiffness design objectives.

[0118] In some embodiments, please refer to Figure 3 The steps for generating candidate lattice unit cell topology configurations by optimizing the solution using a deep learning model based on the aforementioned lattice unit cell topology optimization model include:

[0119] Step S4001: Based on the lattice unit cell topology optimization model, solve for the relative density thresholds of different finite elements (taking multiple thresholds between 0.3 and 0.7) and various load conditions (covering horizontal tensile deformation). With horizontal compression deformation The topological configuration samples of the lattice unit cells corresponding to the multiple deformation gradients are obtained; the data augmentation processing such as rotation, flipping, and scaling is performed on the obtained lattice unit cell topological configuration samples to expand the number of samples and construct a training dataset with sufficient diversity.

[0120] Step S4002: An encoder-decoder neural network model with structural boundary feature extraction capability is used to learn the training dataset and extract the structural contour features of the lattice unit cell topology configuration samples with high precision; an adversarial generation mechanism is introduced, and through adversarial training between the generation network and the discriminant network, the novel unit cell scheme generated by the generation network is made to approximate the real topology in terms of distribution.

[0121] Step S4003: Input the structural contour features into a preset adversarial generative network, train the network until it converges, and generate multiple sets of candidate lattice unit cell topological configurations that satisfy the design objectives of the upper and lower nonlinear stiffness control limit curves.

[0122] Step S50: Construct a comprehensive evaluation index that includes stiffness limit deviation, static bearing capacity, structural quality, and additive manufacturing formability; quantify and score the multiple groups of candidate lattice unit cells; determine the optimal lattice unit cell topology; and arrange the optimal lattice unit cell topology in a spatial periodic array to construct the lattice structure, thereby completing the optimization of the lattice structure with nonlinear stiffness vibration reduction.

[0123] Based on the aforementioned lattice unit cell topology optimization model, lattice unit cell topology configuration samples with different relative densities of finite elements and various load conditions are obtained. An encoder-decoder network is used to extract the structural contour features of these lattice unit cell topology configuration samples. These structural contour features are then input into a pre-defined adversarial generative network and trained until convergence. This generates multiple sets of candidate lattice unit cell topology configurations that meet stiffness design objectives. A comprehensive evaluation index is then constructed, including stiffness limit deviation, static bearing capacity, structural mass, and additive manufacturing formability. These multiple sets of candidate lattice unit cells are quantitatively scored to determine the optimal lattice unit cell topology configuration. Finally, the optimal lattice unit cell topology configuration is arranged in a spatially periodic array to construct the lattice structure, thus completing the optimization of the lattice structure with nonlinear stiffness reduction.

[0124] Specifically, a comprehensive evaluation index is constructed, including stiffness limit deviation, static bearing capacity, structural mass, and additive manufacturing formability, to perform mechanical performance analysis and comprehensive evaluation on the candidate lattice unit cell configuration generated in step S40; wherein, the stiffness limit deviation is the deviation of the vertical stiffness characteristics from the upper and lower control limit curves, quantified by root mean square error; the static bearing capacity is the value under maximum load... The maximum stress under the condition does not exceed the allowable stress of the matrix material; the mass of the structure is a volume fraction that does not exceed the constraint. The additive manufacturing formability is defined as a minimum feature size not lower than the resolution threshold of the selected process; each candidate lattice unit cell topology is weighted and comprehensively scored according to the above evaluation indicators to determine the optimal lattice unit cell topology; the optimal lattice unit cell topology is arranged in a spatial periodic array to construct the lattice structure, thereby completing the optimization of the lattice structure with nonlinear stiffness vibration reduction.

[0125] In some embodiments, after the step of arranging the optimal lattice unit cell topology in a spatially periodic array to construct the lattice structure, the method includes:

[0126] Step S501: Using the optimal lattice unit cell topology as the basic unit, construct a lattice structure by arranging multiple units in a spatial periodic array.

[0127] Step S502: Apply multiple horizontal tensile and compressive deformations, calculate the equivalent vertical stiffness of the lattice structure corresponding to each horizontal tensile and compressive deformation, establish a discrete correspondence between the horizontal tensile and compressive deformations and the equivalent vertical stiffness, and establish a nonlinear stiffness control model through curve fitting.

[0128] Step S503: Determine the target vertical equivalent stiffness based on the real-time operating speed and real-time load information of the air-suction precision seed meterer, input the target vertical equivalent stiffness into the nonlinear stiffness control model to output the target horizontal tension and compression deformation command, and execute the target horizontal tension and compression deformation command to perform closed-loop active control of the vertical nonlinear stiffness.

[0129] Specifically, using the optimal lattice unit cell topology as the basic unit, a complete lattice structure is constructed by periodically arranging multiple lattice unit cells in two-dimensional or three-dimensional space. A series of horizontal tensile and compressive deformations are applied to the system. The equivalent stiffness of the lattice structure in the vertical direction corresponding to each deformation was calculated using the finite element simulation method. A discrete correspondence between horizontal tensile and compressive deformation and vertical stiffness characteristics was established, and a nonlinear stiffness control model was established through curve fitting. .

[0130] A horizontal pre-stretching or pre-compression deformation is applied to the lattice structure by an electric or pneumatic drive device. The target vertical equivalent stiffness is determined based on the real-time operating speed and real-time load information of the air-suction precision seed metering device. The target vertical equivalent stiffness is input into the nonlinear stiffness control model to output the target horizontal tension / compression deformation command. The target horizontal tension / compression deformation command is executed to perform closed-loop active control of the nonlinear stiffness in the vertical direction.

[0131] In some embodiments, horizontal deformation The application method is not limited to overall pre-deformation; it can also be equivalently achieved in simulation by applying displacement boundary conditions to the boundary nodes of the lattice structure. (Nonlinear stiffness control model) The fitting function can take forms including, but not limited to, polynomial fitting, spline interpolation, or neural network regression.

[0132] In some embodiments, the lattice structure sample optimized in the above steps is prepared using additive manufacturing technology (including but not limited to selective laser sintering, fused deposition modeling, or photopolymerization processes), and the stiffness characteristics and installation seed absorption performance of the lattice structure sample are tested, including:

[0133] (1) Stiffness characteristic test: A universal testing machine was used to apply a vertical load to the sample, and the load-displacement curve was recorded to extract different horizontal deformations. The vertical equivalent stiffness value is compared with the upper and lower control limit curves of the nonlinear stiffness determined in the above embodiment to verify whether the structural performance meets the design requirements. If the deviation exceeds the allowable range, the weight coefficients of the objective function of the lattice unit cell topology optimization model are corrected, and the topology optimization process is re-executed with the corrected weight coefficients.

[0134] (2) Verification of seed suction performance: The lattice vibration damping structure with qualified stiffness characteristics was integrated with the drive device and assembled into the seed metering prototype to build a seed suction performance test platform under vibration conditions. Within the operating speed range of 0 to 8 km / h, different load conditions were set, and the leakage rate and re-suction rate under each condition were tested. The results were compared with the baseline state without the vibration damping structure to verify the improvement effect of the vibration damping structure on the precision seed suction performance of the seed metering device. The optimization model was then modified as necessary based on the test results.

[0135] As can be seen from the above embodiments, compared with the prior art, this application addresses the problems of inherent instability caused by the introduction of negative stiffness elements in existing vibration reduction structures, difficulty in online adjustment of structural parameters, and large volume and complex assembly of multi-component combined structures. This application has, but is not limited to, the following beneficial effects:

[0136] Firstly, this application abandons the traditional design approach of relying on negative stiffness elements such as spring combinations, magnetic mechanisms, and buckling beams for vibration reduction structures. Instead, it relies on lattice unit cell topology optimization and periodic array construction to achieve high static-low dynamic nonlinear stiffness characteristics, thereby eliminating the inherent instability of the system caused by negative stiffness elements from the root, avoiding structural jumping and instability under operating disturbances, and improving the operational reliability of the seed metering vibration reduction system.

[0137] Secondly, this application establishes a mapping and control model between horizontal deformation and the vertical equivalent stiffness of the lattice structure through controllable horizontal tensile and compressive deformation. It can dynamically adjust the nonlinear stiffness of the structure according to the real-time operating speed of the seed metering device and changes in field load, thus solving the defects of existing vibration reduction structures that cannot be adjusted online and cannot adapt to multi-condition vibration excitation. It maintains the stability of low-frequency vibration isolation and precision seed collection throughout the process.

[0138] Thirdly, this application uses lattice unit cells as basic units to arrange spatial periodic arrays, and combines topology optimization and volume fraction constraints to achieve lightweight structural design. Compared with traditional multi-element combined vibration reduction mechanisms, the overall configuration is compact, highly modular, and has a simple assembly process, which can meet the engineering application requirements of air-suction precision seeding units for vibration reduction devices with small volume, easy assembly, and low additional load.

[0139] Fourth, a dual-condition multi-objective topology optimization model is constructed based on the SIMP density interpolation method. The goal is to accurately approximate the upper and lower limits of nonlinear stiffness in vertical stiffness, while applying multiple mechanical and manufacturability constraints. Then, candidate unit cell configurations are generated in batches by combining encoder-decoder feature extraction with adversarial generative networks. This solves the problems of difficult analytical acquisition of sensitivity, single design scheme, and low optimization efficiency in traditional nonlinear topology optimization, and obtains more novel lattice topology configurations that meet the requirements of stiffness, load-bearing capacity, and manufacturing.

[0140] Fifth, construct a quantitative evaluation system that includes stiffness limit deviation, static bearing capacity, structural quality, and additive manufacturing formability. Select the optimal matrix unit cell from multiple dimensions such as vibration reduction accuracy, bearing strength, lightweight level, and additive manufacturing process adaptability to ensure that the designed structure not only meets the nonlinear stiffness vibration reduction design target, but also has good engineering machinability and service durability.

[0141] Furthermore, this application precisely calibrates the constraint boundary by using the road spectrum and vibration excitation characteristics of undulating farmland, and matches the sensitive frequency range of the seed metering device for precision seed suction vibration. This effectively suppresses the transmission of low-frequency vibration in the field, significantly reduces the missed suction rate and repeated suction rate under high-speed sowing conditions, solves the industry pain point of vibration interference restricting the speed-up operation of precision sowing machinery, and improves the seed suction consistency and sowing uniformity in harsh scenarios such as small-diameter pelleted seeds.

[0142] Please see Figure 4A lattice structure optimization device with nonlinear stiffness vibration reduction, provided to meet one of the purposes of this application, includes a vibration excitation parameter calibration module 1100, a stiffness control limit construction module 1200, a topology optimization model construction module 1300, a unit cell topology configuration generation module 1400, and a lattice structure construction module 1500. Among them, The vibration excitation parameter calibration module 1100 is configured to calibrate the upper bound constraint of the initial vibration isolation frequency and the lower bound constraint of the static load stiffness of the lattice structure of the air-suction precision seed metering device, wherein the lattice structure includes multiple lattice unit cells; the stiffness control boundary construction module 1200 is configured to construct the upper and lower control boundary curves of the nonlinear stiffness of the lattice structure using B-spline curves based on the upper bound constraint of the initial vibration isolation frequency and the lower bound constraint of the static load stiffness, and determine them as the boundary conditions of the lattice unit cell topology optimization model; the topology optimization model construction module 1300 is configured to discretize the lattice unit cell design domain into multiple finite elements based on the SIMP density interpolation method to determine the relative density of each finite element, and use the relative density of all finite elements as design variables to construct the upper and lower control boundaries of the equivalent stiffness of the lattice unit cell in the vertical direction to synchronously approximate the nonlinear stiffness under horizontal tensile deformation and horizontal compressive deformation conditions. A lattice unit cell topology optimization model with finite curves is provided. A unit cell topology generation module 1400 is configured to, based on the lattice unit cell topology optimization model, solve for the relative density of different finite elements and lattice unit cell topology samples corresponding to various load conditions. An encoder-decoder network is used to extract the structural contour features of the lattice unit cell topology samples, and the structural contour features are input into a preset adversarial generative network for training until convergence, thereby generating multiple sets of candidate lattice unit cell topology configurations that meet stiffness design objectives. A lattice structure construction module 1500 is configured to construct a comprehensive evaluation index including stiffness limit deviation, static bearing capacity, structural mass, and additive manufacturing formability. The module quantifies and scores the multiple sets of candidate lattice unit cells, determines the optimal lattice unit cell topology configuration, and arranges the optimal lattice unit cell topology configuration in a spatial periodic array to construct the lattice structure, thereby completing the optimization of the lattice structure with nonlinear stiffness reduction.

[0143] Based on any embodiment of this application, please refer to Figure 5 Another embodiment of this application also provides an electronic device, which can be implemented by a computer device, such as... Figure 5The diagram shows the internal structure of a computer device. The computer device includes a processor, a computer-readable storage medium, a memory, and a network interface connected via a system bus. The computer-readable storage medium stores an operating system, a database, and computer-readable instructions. The database may store a sequence of control information. When executed by the processor, the computer-readable instructions enable the processor to implement a lattice structure optimization method with nonlinear stiffness vibration reduction. The processor provides computational and control capabilities, supporting the operation of the entire computer device. The memory stores computer-readable instructions, which, when executed by the processor, enable the processor to execute the lattice structure optimization method with nonlinear stiffness vibration reduction described in this application. The network interface of the computer device is used for communication with a terminal. Those skilled in the art will understand that… Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0144] In this embodiment, the processor is used to execute... Figure 4 The specific functions of each module are defined within the device, and the memory stores the program code and various data required to execute these modules. A network interface is used for data transmission between the user terminal and the server. In this embodiment, the memory stores the program code and data required to execute all modules in the nonlinear stiffness damping lattice structure optimization device of this application. The server can call the server's program code and data to execute the functions of all modules.

[0145] This application also provides a storage medium storing computer-readable instructions, which, when executed by one or more processors, cause the one or more processors to perform the steps of the lattice structure optimization method with nonlinear stiffness reduction described in any embodiment of this application.

[0146] This application also provides a computer program product, including a computer program / instructions that, when executed by one or more processors, implement the steps of the lattice structure optimization method with nonlinear stiffness reduction described in any embodiment of this application.

[0147] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. This computer program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The aforementioned storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0148] The above description is only a partial embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for optimizing a lattice structure with nonlinear stiffness vibration reduction, applied to the vibration-damping load-bearing structure of a pneumatic precision seed metering device, characterized in that... include: The upper limit constraint of the initial vibration isolation frequency and the lower limit constraint of the static load stiffness of the lattice structure of the air-suction precision seed meter are determined, wherein the lattice structure includes multiple lattice unit cells. Based on the upper bound constraint of the initial vibration isolation frequency and the lower bound constraint of the static load stiffness, the upper and lower control limit curves of the nonlinear stiffness of the lattice structure are constructed using B-spline curves, and these curves are determined as the boundary conditions of the lattice unit cell topology optimization model. Based on the SIMP density interpolation method, the design domain of the lattice unit cell is discretized into multiple finite elements to determine the relative density of each finite element. Using the relative density of all finite elements as design variables, a topology optimization model of the lattice unit cell is constructed under horizontal tensile deformation and horizontal compressive deformation conditions. The equivalent stiffness of the lattice unit cell in the vertical direction synchronously approximates the upper and lower control limit curves of the nonlinear stiffness. Based on the lattice unit cell topology optimization model, the relative density of different finite elements and the lattice unit cell topology configuration samples corresponding to various load conditions are obtained. The encoder-decoder network is used to extract the structural contour features of the lattice unit cell topology configuration samples, and the structural contour features are input into a preset adversarial generative network for training until convergence, so as to generate multiple sets of candidate lattice unit cell topology configurations that meet the stiffness design target. A comprehensive evaluation index including stiffness limit deviation, static bearing capacity, structural quality, and additive manufacturing formability is constructed. The multiple groups of candidate lattice unit cells are quantitatively scored to determine the optimal lattice unit cell topology. The optimal lattice unit cell topology is then arranged in a spatial periodic array to construct the lattice structure, thereby completing the optimization of the lattice structure with nonlinear stiffness vibration reduction.

2. The method for optimizing a lattice structure with nonlinear stiffness vibration reduction according to claim 1, characterized in that, Based on the upper bound constraint of the initial vibration isolation frequency and the lower bound constraint of the static load stiffness, the steps of constructing the upper and lower control limit curves of the nonlinear stiffness of the lattice structure using B-spline curves and determining them as the boundary conditions of the lattice unit cell topology optimization model include: Based on the upper bound constraint of the initial vibration isolation frequency and the lower bound constraint of the static load stiffness, the nonlinear stiffness characteristics of the lattice structure are explicitly expressed by B-spline curves. By determining the static equilibrium point, the load extreme point, and the initial vibration isolation point, nonlinear vibration reduction stiffness characteristic curves that meet the precise vibration absorption conditions are constructed under different operating speed conditions. The upper and lower envelopes of the nonlinear vibration reduction stiffness characteristic curve are selected as the upper and lower control limit curves of the nonlinear stiffness characteristic, respectively, and the upper and lower control limit curves are determined as the boundary conditions of the lattice unit cell topology optimization model.

3. The method for optimizing a lattice structure with nonlinear stiffness reduction according to claim 1, characterized in that, The steps for discretizing the lattice unit cell design domain into multiple finite elements based on the SIMP density interpolation method to determine the relative density of each finite element include: Based on the SIMP density interpolation method, the design domain of the lattice unit cell is discretized into multiple finite elements, and the relative density of each finite element is used as the design variable to characterize the distribution configuration of the matrix material in the lattice unit cell. The first difference between the elastic modulus of the matrix material and the minimum elastic modulus is calculated, and the first product between the relative density of the finite element with the introduced penalty factor and the first difference is calculated, wherein the minimum elastic modulus is used to prevent the introduction of singularity in the stiffness matrix, and the penalty factor is used to cause the relative density of the element to tend towards the boundary value in order to form a material distribution topology. The equivalent elastic modulus of each finite element is determined based on the first sum between the minimum elastic modulus and the first product.

4. The method for optimizing a lattice structure with nonlinear stiffness reduction according to claim 1, characterized in that, The steps of constructing a lattice unit cell topology optimization model, using the relative density of all finite elements as design variables, under horizontal tensile and compressive deformation conditions, to simultaneously approximate the upper and lower control limit curves of the nonlinear stiffness with the equivalent stiffness of the lattice unit cell in the vertical direction, include: The first equivalent stiffness of the lattice unit cell in the vertical direction under horizontal tensile deformation, the second equivalent stiffness of the lattice unit cell in the vertical direction under horizontal compressive deformation, the first target stiffness of the upper control limit curve of the nonlinear stiffness under the horizontal tensile deformation at the corresponding displacement, and the second target stiffness of the lower control limit curve of the nonlinear stiffness under the horizontal compressive deformation at the corresponding displacement are obtained. Calculate and determine the first square value of the Euclidean norm between the first equivalent stiffness and the first target stiffness, calculate and determine the second square value of the Euclidean norm between the second equivalent stiffness and the second target stiffness, and minimize the weighted sum between the first square value and the second square value as the objective function of the lattice unit cell topology optimization model. Using the structural stiffness equation of the lattice unit cell as the mechanical equilibrium constraint, and the upper limit of the material volume fraction of the lattice unit cell and the range of relative density values ​​of the finite elements as constraints, a topology optimization model of the lattice unit cell is constructed to simultaneously approximate the upper and lower control limit curves of the nonlinear stiffness with the equivalent stiffness of the lattice unit cell in the vertical direction.

5. The method for optimizing a lattice structure with nonlinear stiffness reduction according to claim 1, characterized in that, The steps for calibrating the upper limit constraint of the initial vibration isolation frequency and the lower limit constraint of the static load-bearing stiffness of the lattice structure of the air-suction precision seed meter include: Time-domain signals of vibration acceleration of a pneumatic precision seed metering device at multiple operating speeds were collected. The vibration acceleration time-domain signal is converted into a vibration acceleration frequency-domain signal by fast Fourier transform, and the vibration acceleration frequency-domain signal is integrated twice to obtain the vibration displacement frequency-domain signal. Then, the vibration displacement frequency-domain signal is restored to the vibration displacement time-domain signal by inverse Fourier transform. Based on the spatial power spectral density analysis results of the road surface unevenness spectrum sequence, the acceleration distribution matrix corresponding to each vibration excitation frequency of the air-suction precision seed metering device under different operating speeds is determined, so as to calibrate the upper limit constraint of the initial vibration isolation frequency and the lower limit constraint of the static bearing stiffness of the lattice structure of the air-suction precision seed metering device.

6. The method for optimizing a lattice structure with nonlinear stiffness reduction according to claim 1, characterized in that, After the step of arranging the optimal lattice unit cell topology into a spatially periodic array to construct the lattice structure, the following steps are included: Using the optimal lattice unit cell topology as the basic unit, a lattice structure is constructed by arranging multiple units in a spatial periodic array. Multiple horizontal tensile and compressive deformations are applied, and the equivalent stiffness of the lattice structure in the vertical direction corresponding to each horizontal tensile and compressive deformation is calculated. A discrete correspondence between the horizontal tensile and compressive deformations and the equivalent stiffness in the vertical direction is established, and a nonlinear stiffness control model is established by curve fitting. The target vertical equivalent stiffness is determined based on the real-time operating speed and real-time load information of the air-suction precision seed metering device. The target vertical equivalent stiffness is then input into the nonlinear stiffness control model to output the target horizontal tension and compression deformation command. The target horizontal tension and compression deformation command is executed to perform closed-loop active control of the vertical nonlinear stiffness.

7. The method for optimizing a lattice structure with nonlinear stiffness reduction according to any one of claims 1 to 6, characterized in that, The lattice unit cell is the smallest basic unit that constitutes a periodic lattice structure. It can be assembled into an overall lattice structure by repeating the spatial periodic array.

8. A lattice structure optimization device with nonlinear stiffness vibration reduction, characterized in that, include: The vibration excitation parameter calibration module is set to calibrate the upper limit constraint of the initial vibration isolation frequency and the lower limit constraint of the static load stiffness of the lattice structure of the air-suction precision seed meterer, wherein the lattice structure includes multiple lattice unit cells. The stiffness control limit construction module is set to construct the upper and lower control limit curves of the nonlinear stiffness of the lattice structure based on the upper limit constraint of the initial vibration isolation frequency and the lower limit constraint of the static load stiffness using B-spline curves, and determine them as the boundary conditions of the lattice unit cell topology optimization model. The topology optimization model construction module is configured to discretize the lattice unit cell design domain into multiple finite elements based on the SIMP density interpolation method to determine the relative density of each finite element. Using the relative density of all finite elements as design variables, under horizontal tensile deformation and horizontal compressive deformation conditions, a lattice unit cell topology optimization model is constructed in which the equivalent stiffness of the lattice unit cell in the vertical direction synchronously approximates the upper and lower control limit curves of the nonlinear stiffness. The unit cell topology configuration generation module is configured to solve for the relative density of different finite elements and the lattice unit cell topology configuration samples corresponding to various load conditions based on the lattice unit cell topology optimization model. The encoder-decoder network is used to extract the structural contour features of the lattice unit cell topology configuration samples, and the structural contour features are input into a preset adversarial generative network for training until convergence, so as to generate multiple sets of candidate lattice unit cell topology configurations that meet the stiffness design target. The lattice structure construction module is configured to construct a comprehensive evaluation index including stiffness limit deviation, static bearing capacity, structural quality, and additive manufacturing formability. It quantifies and scores the multiple candidate lattice unit cells, determines the optimal lattice unit cell topology, and arranges the optimal lattice unit cell topology in a spatial periodic array to construct the lattice structure, thereby completing the optimization of the lattice structure with nonlinear stiffness vibration reduction.

9. An electronic device comprising a central processing unit and a memory, characterized in that, The central processing unit is used to invoke and run a computer program stored in the memory to perform the steps of the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, It stores, in the form of computer-readable instructions, a computer program implemented according to any one of claims 1 to 7, which, when invoked by a computer, executes the steps included in the corresponding method.

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