Chassis sinking simulation method and system, terminal and storage medium

Abstract

The application relates to the technical field of servers, and specifically provides a case sinking simulation method and system, a terminal and a storage medium, which comprise the following steps: acquiring test data, wherein the test data comprises vertical deflection data of a plurality of test points of a sample case in an empty state; fitting the test data through a probability distribution curve to obtain error data; constructing a case model of the sample case, and correcting nodes corresponding to the test points of the sample case in the case model by using the error data; and applying a gravity field to the corrected case model to perform sinking simulation and obtain sinking data. The application quickly and accurately obtains a case sinking amount by simulating and analyzing test results, guides a case factory to make a pre-arch, improves the process level of the case, and improves product quality.

Description

Technical Field

[0001] This invention belongs to the field of server technology, specifically relating to a chassis sinking simulation method, system, terminal, and storage medium. Background Technology

[0002] Servers in data center server rooms are not placed directly on the ground. To save land and resources, the room contains numerous server racks, with servers stacked layer upon layer on rails. The distance between each rack is only about 1mm. The servers are supported on the left and right sides of the rails, with the middle section suspended in the air. Due to gravity, they will inevitably sag. If this sag exceeds the gap between each server layer, it will lead to two disadvantages: 1. It hinders ventilation and heat dissipation between layers; 2. It hinders server installation and subsequent maintenance. To solve this problem, the server chassis needs to be pre-cambered upwards based on the sag value during design to counteract it. However, the pre-camber should not be too large, otherwise it can easily cause excessive stress during board installation, damaging electronic components. Therefore, obtaining the sag amount and a sufficiently accurate sag measurement is crucial.

[0003] Currently, chassis recess measurement is obtained through finite element method (FEM) simulation analysis. For example, simulation engineers import the complete 3D model of the chassis into the simulation preprocessing software Hypermesh for geometric cleanup and simplification, construct the chassis model, and obtain the recess model through gravity loading simulation.

[0004] However, this simulation method often results in calculated values ​​that are much lower than the test values. Because the model differs from the actual chassis base shape, this leads to severe distortion of the simulation data. Summary of the Invention

[0005] In view of the above-mentioned shortcomings of the prior art, the present invention provides a chassis sinking simulation method, system, terminal and storage medium to solve the above-mentioned technical problems.

[0006] In a first aspect, the present invention provides a method for simulating chassis sinking, comprising: Acquire test data, which includes vertical deflection data of multiple test points of the sample chassis under no-load conditions; Error data is obtained by fitting the test data to a probability distribution curve; Construct a chassis model of the sample chassis, and use the error data to correct the nodes in the chassis model that correspond to the test points of the sample chassis; A gravity field was applied to the modified chassis model to simulate sinking and obtain sinking data.

[0007] In one optional implementation, test data is acquired, the test data including vertical deflection data of multiple test points of the sample chassis under no-load conditions, including: Set the coordinates of the test points, save the coordinates of the test points to the test task, and send the test task to the test production line; Save the vertical deflection data of the same test point of multiple sample chassis as a test array; After marking the coordinates of the test points belonging to multiple test arrays, save them to the test result record file.

[0008] In an optional implementation, the test data is fitted using a probability distribution curve to obtain error data, including: The test array is extracted sequentially from the test result record file, and the test array is fitted with a normal distribution function. The value of the specified confidence interval is calculated based on the normal distribution function of the test array, and the value is set as the error value of the corresponding test point; Summarize the error values ​​of all test points to obtain the error data.

[0009] In one optional implementation, a chassis model of the sample chassis is constructed, and the error data is used to correct the nodes in the chassis model corresponding to the test points of the sample chassis, including: Establish a finite element model of the server; Based on the coordinates of the test points, positioning points are generated at the corresponding positions of the chassis base in the finite element model; The error data is written into the configuration file, and an error value is matched for each positioning point based on the coordinate correspondence between the test point and the positioning point. The matching error value of the positioning point is read by an automatic execution script, and the positioning point coordinates and matching error value are imported into the corresponding configuration item in the adjustment interface of the model processing software to adjust the position of the positioning point. Iterate through all the points to correct their positions. The chassis base of the finite element model was smoothed using model processing software based on the corrected positioning points to obtain the corrected chassis model.

[0010] In an optional implementation, positioning points are generated at corresponding positions on the chassis base of the finite element model based on the coordinates of the test points, including: Enter the shape adjustment interface of the model processing software, and then call the conversion option in the shape adjustment interface; Input the coordinates of the test point into the conversion option to obtain the positioning point corresponding to the test point; The positioning points are set as movable points, and a mesh is built based on the positioning points.

[0011] In an optional implementation, a gravity field is applied to the modified chassis model to simulate sinking, obtaining sinking data, including: Import the corrected chassis model into the finite element analysis tool to perform gravity loading calculations and obtain the deformation. Export the model of the deformed chassis base as a file in a format recognizable by 3D software, and save the file as sinking data.

[0012] In an optional implementation, after acquiring the test data, the method further includes: Select some target test points from multiple test points, obtain the vertical deflection of the target test points of the sample chassis during the actual sinking test, and obtain the actual sinking data; Obtain theoretical sinking data from sinking simulation of the chassis model; The difference between the actual sinking data and the corresponding theoretical sinking data is saved as the actual error data of the target test point; Select all vertical deflection data corresponding to the target test point from the test data as input data, and filter all data corresponding to the target test point from the actual error data as output data; The input and output data are classified into negative maximum, negative large, negative medium, negative small, zero, positive small, positive medium, positive large, and positive maximum according to the linguistic description of random variables in the fuzzy control algorithm. Among them, zero represents the average value of the data set, negative indicates a downward deviation from the average value, and positive indicates an upward deviation from the average value. Using the input and output data as the basic universe of discourse, create corresponding fuzzy subset universes of discourse, and establish the transformation relationship between the basic universe of discourse and the fuzzy subset universes of discourse; Fuzzy control rules are established based on the correspondence between the vertical deflection of test points under no-load conditions and the corresponding actual error. Calculate fuzzy relations and calculate fuzzy decisions based on fuzzy relations; Using the fuzzy decision method, error data for other test points besides the target test point is obtained. The theoretical sinking data corresponding to the test points in the chassis model are adjusted using the error data to obtain the corrected chassis model base. The corrected chassis model base is then saved as a sinking model file.

[0013] Secondly, the present invention provides a chassis sinking simulation system, comprising: The no-load test module is used to acquire test data, which includes vertical deflection data of multiple test points of the sample chassis under no-load conditions. The curve fitting module is used to fit the test data using a probability distribution curve to obtain error data; The model correction module is used to construct a chassis model of the sample chassis and use the error data to correct the nodes in the chassis model that correspond to the test points of the sample chassis. The sinking simulation module is used to apply a gravity field to the corrected chassis model to simulate sinking and obtain sinking data.

[0014] In one optional implementation, the no-load test module includes: The task generation unit is used to set the coordinates of the test points, save the coordinates of the test points to the test task, and send the test task to the test production line. The data processing unit is used to save the vertical deflection data of the same test point of multiple sample chassis into a test array; The data recording unit is used to mark the coordinates of the test points belonging to multiple test arrays and save them to the test result recording file.

[0015] In one optional implementation, the curve fitting module includes: The curve fitting unit is used to extract the test array from the test result record file in sequence and fit the test array with a normal distribution function. An error calculation unit is used to calculate a value in a specified confidence interval based on the normal distribution function of the test array, and set the value as the error value of the corresponding test point; The error summarization unit is used to summarize the error values ​​of all test points to obtain error data.

[0016] In one optional implementation, the model correction module includes: Model building unit, used to build the finite element model of the server; Node positioning unit, used to generate positioning points at the corresponding positions of the chassis base of the finite element model based on the coordinates of the test points; An error matching unit is used to write the error data into a configuration file and match an error value for each positioning point based on the coordinate correspondence between the test point and the positioning point. The position adjustment unit is used to read the matching error value of the positioning point using an automatically executed script, and import the positioning point coordinates and matching error value into the corresponding configuration item in the adjustment interface of the model processing software to adjust the position of the positioning point. The node traversal unit is used to traverse all positioning points to correct their positions. The model correction unit is used to smooth the chassis base of the finite element model based on the corrected positioning points using model processing software, thereby obtaining the corrected chassis model.

[0017] In one optional implementation, the node positioning unit includes: The option call subunit is used to enter the shape adjustment interface of the model processing software and call the conversion options under the shape adjustment interface; The coordinate input subunit is used to input the coordinates of the test point into the conversion option to obtain the positioning point corresponding to the test point; The attribute adjustment sub-unit is used to set the positioning point as a movable point and to build a mesh based on the positioning point.

[0018] In one optional implementation, the sinking simulation module includes: Gravity loading element is used to import the modified chassis model into the finite element calculation tool to perform gravity loading calculations and obtain the deformation. The file export unit is used to export the model of the deformed chassis base into a file in a format recognizable by 3D software, and save the file as sinking data.

[0019] In an optional implementation, the system further includes: The first acquisition module is used to select some target test points from multiple test points, acquire the vertical deflection of the target test points of the sample chassis during the actual sinking test, and obtain the actual sinking data. The second acquisition module is used to acquire theoretical sinking data obtained by sinking simulation of the chassis model; The data calculation module is used to save the difference between the actual sinking data and the corresponding theoretical sinking data as the actual error data of the target test point; The data selection module is used to select all vertical deflection data corresponding to the target test point from the test data as input data, and to filter all data corresponding to the target test point from the actual error data as output data. The data partitioning module is used to divide the input and output data into negative maximum, negative large, negative medium, negative small, zero, positive small, positive medium, positive large, and positive maximum according to the linguistic description of random variables in the fuzzy control algorithm. Here, zero represents the average value of the data set, negative indicates a downward deviation from the average value, and positive indicates an upward deviation from the average value. The first calculation module is used to take the input data and output data as the basic universe of discourse, create the corresponding fuzzy subset universe of discourse, and establish the transformation relationship between the basic universe of discourse and the fuzzy subset universe of discourse. The second calculation module is used to establish fuzzy control rules based on the correspondence between the vertical deflection of the test point under no-load conditions and the corresponding actual error. The third calculation module is used to calculate fuzzy relations and to calculate fuzzy decisions based on fuzzy relations; The fourth calculation module is used to calculate the error data of other test points besides the target test point using the fuzzy decision. The fifth calculation module is used to adjust the theoretical sinking data corresponding to the test points in the chassis model using error data, so as to obtain the corrected chassis model base and save the corrected chassis model base as a sinking model file.

[0020] Thirdly, a terminal is provided, including: Processor, memory, among which, This memory is used to store computer programs. The processor is used to retrieve and run the computer program from memory, causing the terminal to perform the terminal method described above.

[0021] Fourthly, a computer storage medium is provided, wherein instructions are stored therein, which, when executed on a computer, cause the computer to perform the methods described in the above aspects.

[0022] The beneficial effects of the present invention are that the chassis sinking simulation method, system, terminal and storage medium provided by the present invention obtain the no-load deformation of the chassis, obtain the error of multiple test points by curve fitting of the no-load deformation, and then adjust the position of the corresponding points of the chassis model to obtain the corrected chassis model. Using the corrected chassis model to perform sinking simulation, more realistic simulation results can be obtained.

[0023] The chassis sinking simulation method, system, terminal, and storage medium provided by this invention obtain more realistic error values ​​by using a normal distribution function to fit the unloaded deformation of the test points, thereby improving the simulation accuracy.

[0024] The chassis sinking simulation method, system, terminal, and storage medium provided by this invention utilize fuzzy control algorithms to compensate for errors. Compared with error data obtained by curve fitting methods, this reduces the amount of data computation and improves the accuracy of error data.

[0025] Furthermore, the design principle of this invention is reliable, the structure is simple, and it has a very wide range of application prospects. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a schematic flowchart of a method according to an embodiment of the present invention.

[0028] Figure 2 This is a surface plot of measured data of the chassis base of a method according to an embodiment of the present invention.

[0029] Figure 3 This is a discrete line diagram of the chassis base of a method according to an embodiment of the present invention.

[0030] Figure 4 This is a curve fitting the probability distribution function of the server front window position measurement value according to an embodiment of the present invention.

[0031] Figure 5 This is a curve fitting the probability distribution function of the server back window position measurement value according to an embodiment of the present invention.

[0032] Figure 6 This is a schematic flowchart illustrating the model simulation of a method according to an embodiment of the present invention.

[0033] Figure 7 This is a chassis deformation simulation cloud diagram of a method according to an embodiment of the present invention.

[0034] Figure 8 This is a schematic block diagram of a system according to an embodiment of the present invention.

[0035] Figure 9 This is a schematic diagram of the structure of a terminal provided in an embodiment of the present invention. Detailed Implementation

[0036] To enable those skilled in the art to better understand the technical solutions of this invention, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this invention.

[0037] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.

[0038] The key terms used in this invention will be explained below.

[0039] Hypermesh is a CAE application software package and an innovative, open enterprise-level CAE platform that integrates various tools needed for design and analysis. It boasts powerful finite element mesh generation and preprocessing capabilities.

[0040] The chassis sinking simulation method provided in this embodiment of the invention is executed by a computer device, and correspondingly, the chassis sinking simulation system runs in the computer device.

[0041] Figure 1 This is a schematic flowchart illustrating a method according to an embodiment of the present invention. Wherein, Figure 1 The implementing entity can be a chassis sinking simulation system. Depending on different requirements, the order of the steps in this flowchart can be changed, and some can be omitted.

[0042] like Figure 1 As shown, the method includes: Step 110: Obtain test data, which includes vertical deflection data of multiple test points of the sample chassis under no-load conditions; Step 120: Fit the test data using a probability distribution curve to obtain error data; Step 130: Construct a chassis model of the sample chassis, and use the error data to correct the nodes in the chassis model that correspond to the test points of the sample chassis. Step 140: Apply a gravity field to the corrected chassis model to simulate sinking and obtain sinking data.

[0043] The problem this invention aims to solve is to improve the accuracy of server chassis recess measurement and comparison, and to guide chassis manufacturers in pre-cambering of chassis. The basic idea is to obtain the probability distribution function of the manufacturing error of a batch of chassis through sampling experiments, and then, after dividing the error-free 3D model of the chassis base into a finite element mesh, call the program to move the corresponding mesh nodes according to the probability distribution function of each measurement point.

[0044] To facilitate understanding of the present invention, the following description further illustrates the chassis sinking simulation method provided by the present invention, based on the principle of the chassis sinking simulation method and in conjunction with the process of simulating chassis sinking in the embodiments.

[0045] Specifically, the chassis sinking simulation method includes: S1. Obtain test data, which includes vertical deflection data of multiple test points of the sample chassis under no-load conditions.

[0046] Set the coordinates of the test points and save them to the test task. Then, send the test task to the test production line. Save the vertical deflection data of the same test point of multiple sample chassis as a test array. After marking the coordinates of the test points to which the multiple test arrays belong, save them to the test result record file.

[0047] For example, before mass production, 50 chassis (unloaded state) are sampled; 200 measuring points are set at equal intervals on the chassis base according to the principle of 10 width × 20 length. The SAG value of each unloaded chassis base is measured sequentially using an SAG tester; the test data of the 50 chassis can be written as [Xmn,Yn], where m is 1 to 200, representing points 1 to 200 of each chassis, and n is 1 to 50, representing the chassis number.

[0048] Specifically, consider the chassis base as a rectangle, dividing it evenly into m-1 parts along its length and n-1 parts along its width, forming an m×n point matrix. Using a SAG tester, the vertical deflection at each of these m×n points yields the measured value of the chassis base's sinking. After data measurement, a 3D modeling tool can be used to generate a 3D surface from the measured data to examine the specific deformation, such as... Figure 2 As shown.

[0049] from Figure 3 As can be seen, the actual chassis base is uneven due to manufacturing tolerances, while the model used in the simulation is level. Therefore, the calculated sinking amount is submerged in the tolerances, resulting in very poor simulation accuracy. Clearly, using this simulation data cannot guide chassis manufacturers in performing pre-camber operations.

[0050] S2. Fit the test data using the probability distribution curve to obtain error data.

[0051] The test array is extracted sequentially from the test result record file, and a normal distribution function is fitted to the test array. The value of the specified confidence interval is calculated based on the normal distribution function of the test array, and the value is set as the error value of the corresponding test point. The error values ​​of all test points are summarized to obtain the error data.

[0052] Specifically, a program is written to fit a common probability distribution function to the 200 measured points. The most commonly used probability distribution in engineering is the normal distribution function, which is... The curve is bell-shaped, in which The standard deviation determines the width of the curve. The average value determines the center offset of the curve.

[0053] Obtain 200 probability distribution curves with different standard deviations and different mathematical expectations, such as Figure 4 and Figure 5 The figures show the fitted curves for the front and rear window positions of a server, respectively, with a fitting residual of less than 5%.

[0054] The shape of the curve shows that the sample measurements are relatively consistent with a normal distribution.

[0055] By fitting the probability distribution curves, we calculated the values ​​of the random variables corresponding to a 95% probability confidence interval, for a total of 200 variables.

[0056] In another optional embodiment of the present invention, the sampling fuzzy control algorithm processes the error, including: Select some target test points from multiple test points, obtain the vertical deflection of the target test points of the sample chassis during the actual sinking test, and obtain the actual sinking data; Obtain theoretical sinking data from sinking simulation of the chassis model; save the difference between the actual sinking data and the corresponding theoretical sinking data as the actual error data of the target test point; Select all vertical deflection data corresponding to the target test point from the test data as input data, and filter all data corresponding to the target test point from the actual error data as output data; The input and output data are classified into negative maximum, negative large, negative medium, negative small, zero, positive small, positive medium, positive large, and positive maximum according to the linguistic description of random variables in the fuzzy control algorithm. Among them, zero represents the average value of the data set, negative indicates a downward deviation from the average value, and positive indicates an upward deviation from the average value. Using the input and output data as the basic universe of discourse, corresponding fuzzy subset universes of discourse are created, and a transformation relationship between the basic universe of discourse and the fuzzy subset universes of discourse is established. For example, let the fuzzy sets of input and output be {NB, NS, O, PS, PB} and {NB, NS, O, PS, PB}, respectively. Here, NB represents negative large, NS represents negative small, 0 represents zero, PS represents positive small, and PB represents positive large. Furthermore, let the fuzzy subset universes of discourse for input and output be ({-4, -3, -2,-1,0,1,2,3, 4} and {3,-2,-1,0,1,2,3}. A general formula can be derived for the transformation relationship from the basic universe of discourse to the (a, b) fuzzy subset universe of discourse [-n, n]: y = (x - (a + b) / 2) × 2n / (ba) Fuzzy control rules are established based on the correspondence between the vertical deflection of test points under no-load conditions and the corresponding actual error.

[0057] The process involves calculating fuzzy relations and then calculating fuzzy decisions based on these relations. A fuzzy control rule is a set of multiple statements that can be represented as a fuzzy subset of EXU, i.e., a fuzzy relation R. The fuzzy decision is the union of the fuzzy relations and the error vector.

[0058] Using the fuzzy decision, the error data of other test points besides the target test point is calculated; the drooping deflection of other test points under no-load conditions is input into the fuzzy decision to obtain the error data.

[0059] S3. Construct a chassis model of the sample chassis, and use the error data to correct the nodes in the chassis model that correspond to the test points of the sample chassis.

[0060] A finite element model of the server is established; positioning points are generated at the corresponding positions of the chassis base of the finite element model based on the coordinates of the test points; the error data is written into a configuration file, and an error value is matched for each positioning point based on the coordinate correspondence between the test points and the positioning points; the matching error value of the positioning point is read using an automatic execution script, and the positioning point coordinates and matching error value are imported into the corresponding configuration items in the adjustment interface of the model processing software to adjust the position of the positioning point; all positioning points are traversed to correct the position of all positioning points; the chassis base of the finite element model is smoothed using the model processing software based on the corrected positioning points to obtain the corrected chassis model.

[0061] The method for establishing the finite element model of the server is as follows: Figure 6 As shown, the specific steps include: 1. Model Input: After generating the detailed 3D design of the server, the structural design engineer exports the STP format to the simulation engineer.

[0062] 2. Model Simplification: Simulation engineers import the complete 3D model into the simulation preprocessing software Hypermesh for geometric cleaning and simplification, removing small holes and rounded corners with radii less than 0.5mm to avoid generating poor-quality meshes. Components that do not affect the overall calculation are simplified. The simplification principle is to not affect the overall stiffness, moment of inertia, center of mass and other key parameters of the component. Other small features can be removed.

[0063] 3. Mesh Generation: For thin-walled sheet metal parts such as chassis base, chassis top cover, hard drive frame, fan frame, power supply frame, PCIe frame, and support beams, the mid-surface is extracted and meshed using S4R reduced integral shell units. After extensive simplification of blocks such as fans, hard drives, power supplies, and heat sinks, meshing is performed using C3D8R reduced integral hexahedral units. For board-type components, meshing is performed using C3D8I non-conforming hexahedral units.

[0064] 4. Finite element connection: Finite element analysis is performed on the bolted connections, welding and other connection methods between components. Bolted connections are simulated using rigid elements and beam elements. The motherboard is connected to the chassis base with screws. Connectors, memory and other components are connected to the motherboard using a common node method.

[0065] 5. Define material models and properties: Sheet metal parts and circuit board components such as chassis base, chassis top cover, hard drive frame, etc. use elastoplastic constitutive models; hard drives, power supplies, fans, and heat sinks use linear elastic material models. Since the geometry has been simplified, the material density needs to use equivalent density to ensure that the mass center of mass and rotational inertia of the simplified finite element model are consistent with the original 3D model.

[0066] 6. Define Contact: First, create contact properties. Here, you need to define the normal and tangential forces of the contact. The tangential force includes the relative motion between the contact surfaces and any possible frictional shear stress. The normal force defines the relationship between the contact force and the contact gap. When calculating SAG, the hard contact algorithm is used for the normal force, and the friction model is used for the tangential force. The tangential friction coefficient is defined as 0.2.

[0067] 7. Define boundary conditions: Apply a gravity field to the entire model, setting the Gravity to 9810 in the -Z direction. Only constrain the Z-direction movement degree of freedom on the left and right sides of the chassis base. After setting, export the model as an .inp file.

[0068] 8. Open Abaqus, import the inp file generated in the previous step, and submit the calculation directly.

[0069] The model is revised, specifically including the following steps: Before meshing the chassis base in the model, point points need to be placed at 200 points according to their coordinate positions so that mesh nodes can be generated at these points during meshing, and these nodes should be forcibly numbered 1-200.

[0070] Open Hypermesh, then click Tool--HyperMorph--freehand to enter the manual shape adjustment interface. In the move nodes interface, select the translate button. Enter the vector values ​​of the nodes to be moved (x, y, z) in the three blank boxes below, which are the error values ​​of the 200 points calculated in step S3. In moving nodes, select the nodes to be moved (the corresponding mesh nodes of the 200 measurement points). In fixed nodes, select the mesh nodes of the left and right side edges of the chassis. In affected elements, select all elements of the chassis base.

[0071] The Hyperworks program automatically records the previous operation and writes it to the script. After adding an if-else loop to the script and executing it, the program will automatically move nodes numbered 1-200 sequentially until all 200 nodes have been adjusted. At this point, the deformation caused by machining errors is superimposed on the ideal chassis base simulation model (flat plate state).

[0072] S4. Apply a gravity field to the corrected chassis model to simulate sinking and obtain sinking data.

[0073] Import the corrected chassis model into a finite element analysis tool to perform gravity loading calculations and obtain the deformation amount; export the deformed chassis base model into a file in a format recognizable by 3D software, and save the file as sinking data.

[0074] Specifically, it includes the following processes: (1) Import the finite element calculation program to perform loading calculations and obtain the combined value of the SAG value generated by gravity and the deformation caused by processing error.

[0075] (2) Next, the calculated model of the deformed chassis base needs to be exported to a format that can be recognized by 3D software, such as igs, stp, parasolid, etc., and sent to the chassis manufacturer so as to guide the chassis manufacturer in pre-arching design. The specific method is as follows: First, import the result file of the calculation completed in step (1) into the Abaqus software. Select File—import—part in sequence and a dialog box will pop up. In File Filter, select Output Database (*.odb*). In File name, select the result file of the calculation completed. In the pop-up dialog box, in Deformed Configuration, select the name of the last working condition in step and select the last incremental step in Frame. Import the chassis after superimposed gravity deformation and processing error deformation into the pre-processing module of the Abaqus software.

[0076] (3) Enter the Abaqus job manager module, click the write input button, and export the deformed chassis mesh model as .inp format.

[0077] (4) Re-enter the Hypermesh software and import the inp file generated in step (3). At this time, the deformed chassis mesh is imported into the Hypermesh preprocessing software. Then, use Hypermesh-Geometry-Surfaces-From FE to enter the interface for generating surfaces from the mesh. Select the chassis base in elems, drag the progress bar of Surface Complexity to select the maximum value of 10, and click Create to generate the geometric surfaces of the chassis base from the deformed mesh, such as Figure 7 As shown.

[0078] (5) Export the generated surface as an IGS format file and give it to the chassis manufacturer to guide them in the pre-arching work of the chassis before production.

[0079] In some embodiments, the chassis sinking simulation system may include multiple functional modules composed of computer program segments. The computer programs for each program segment in the chassis sinking simulation system may be stored in the memory of a computer device and executed by at least one processor to perform (see details). Figure 1 (Description) Functionality of chassis sinking simulation.

[0080] In this embodiment, the chassis sinking simulation system can be divided into multiple functional modules according to its functions, such as... Figure 8 As shown. The functional modules of system 800 may include: an idle test module 810, a curve fitting module 820, a model correction module 830, and a sinking simulation module 840. The module referred to in this invention is a series of computer program segments that can be executed by at least one processor and perform a fixed function, and are stored in memory. In this embodiment, the functions of each module will be described in detail in subsequent embodiments.

[0081] The no-load test module is used to acquire test data, which includes vertical deflection data of multiple test points of the sample chassis under no-load conditions. The curve fitting module is used to fit the test data using a probability distribution curve to obtain error data; The model correction module is used to construct a chassis model of the sample chassis and use the error data to correct the nodes in the chassis model that correspond to the test points of the sample chassis. The sinking simulation module is used to apply a gravity field to the corrected chassis model to simulate sinking and obtain sinking data.

[0082] Optionally, as an embodiment of the present invention, the no-load test module includes: The task generation unit is used to set the coordinates of the test points, save the coordinates of the test points to the test task, and send the test task to the test production line. The data processing unit is used to save the vertical deflection data of the same test point of multiple sample chassis into a test array; The data recording unit is used to mark the coordinates of the test points belonging to multiple test arrays and save them to the test result recording file.

[0083] Optionally, as an embodiment of the present invention, the curve fitting module includes: The curve fitting unit is used to extract the test array from the test result record file in sequence and fit the test array with a normal distribution function. An error calculation unit is used to calculate a value in a specified confidence interval based on the normal distribution function of the test array, and set the value as the error value of the corresponding test point; The error summarization unit is used to summarize the error values ​​of all test points to obtain error data.

[0084] Optionally, as an embodiment of the present invention, the model correction module includes: Model building unit, used to build the finite element model of the server; Node positioning unit, used to generate positioning points at the corresponding positions of the chassis base of the finite element model based on the coordinates of the test points; An error matching unit is used to write the error data into a configuration file and match an error value for each positioning point based on the coordinate correspondence between the test point and the positioning point. The position adjustment unit is used to read the matching error value of the positioning point using an automatically executed script, and import the positioning point coordinates and matching error value into the corresponding configuration item in the adjustment interface of the model processing software to adjust the position of the positioning point. The node traversal unit is used to traverse all positioning points to correct their positions. The model correction unit is used to smooth the chassis base of the finite element model based on the corrected positioning points using model processing software, thereby obtaining the corrected chassis model.

[0085] Optionally, as an embodiment of the present invention, the node positioning unit includes: The option call subunit is used to enter the shape adjustment interface of the model processing software and call the conversion options under the shape adjustment interface; The coordinate input subunit is used to input the coordinates of the test point into the conversion option to obtain the positioning point corresponding to the test point; The attribute adjustment sub-unit is used to set the positioning point as a movable point and to build a mesh based on the positioning point.

[0086] Optionally, as an embodiment of the present invention, the sinking simulation module includes: Gravity loading element is used to import the modified chassis model into the finite element calculation tool to perform gravity loading calculations and obtain the deformation. The file export unit is used to export the model of the deformed chassis base into a file in a format recognizable by 3D software, and save the file as sinking data.

[0087] Optionally, as an embodiment of the present invention, the system further includes: The first acquisition module is used to select some target test points from multiple test points, acquire the vertical deflection of the target test points of the sample chassis during the actual sinking test, and obtain the actual sinking data. The second acquisition module is used to acquire theoretical sinking data obtained by sinking simulation of the chassis model; The data calculation module is used to save the difference between the actual sinking data and the corresponding theoretical sinking data as the actual error data of the target test point; The data selection module is used to select all vertical deflection data corresponding to the target test point from the test data as input data, and to filter all data corresponding to the target test point from the actual error data as output data. The data partitioning module is used to divide the input and output data into negative maximum, negative large, negative medium, negative small, zero, positive small, positive medium, positive large, and positive maximum according to the linguistic description of random variables in the fuzzy control algorithm. Here, zero represents the average value of the data set, negative indicates a downward deviation from the average value, and positive indicates an upward deviation from the average value. The first computation module is used to take the input data and output data as the basic universe of discourse, create the corresponding fuzzy subset universe of discourse, and establish the transformation relationship between the basic universe of discourse and the fuzzy subset universe of discourse. The second calculation module is used to establish fuzzy control rules based on the correspondence between the vertical deflection of the test point under no-load conditions and the corresponding actual error. The third calculation module is used to calculate fuzzy relations and calculate fuzzy decisions based on fuzzy relations; The fourth calculation module is used to calculate the error data of other test points besides the target test point using the fuzzy decision; The fifth calculation module is used to adjust the theoretical sinking data corresponding to the test points in the chassis model using error data, so as to obtain the corrected chassis model base and save the corrected chassis model base as a sinking model file.

[0088] Figure 9 This is a schematic diagram of the structure of a terminal 900 provided in an embodiment of the present invention. The terminal 900 can be used to execute the chassis sinking simulation method provided in the embodiment of the present invention.

[0089] The terminal 900 may include a processor 910, a memory 920, and a communication module 930. These components communicate via one or more buses. Those skilled in the art will understand that the server structure shown in the figure does not constitute a limitation of the present invention. It may be a bus topology or a star topology, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0090] The memory 920 can be used to store the execution instructions of the processor 910. The memory 920 can be implemented by any type of volatile or non-volatile memory terminal or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. When the execution instructions in the memory 920 are executed by the processor 910, the terminal 900 is able to perform some or all of the steps in the above method embodiments.

[0091] The processor 910 serves as the control center of the storage terminal, connecting various parts of the electronic terminal via various interfaces and lines. It executes software programs and / or modules stored in the memory 920, and calls data stored in the memory to perform various functions of the electronic terminal and / or process data. The processor can be composed of integrated circuits (ICs), such as a single packaged IC or multiple packaged ICs with the same or different functions connected together. For example, the processor 910 may consist only of a central processing unit (CPU). In this embodiment of the invention, the CPU may have a single processing core or include multiple processing cores.

[0092] The communication module 930 is used to establish a communication channel, enabling the storage terminal to communicate with other terminals. It receives user data sent by other terminals or sends user data to other terminals.

[0093] The present invention also provides a computer storage medium, wherein the computer storage medium may store a program, which, when executed, may include some or all of the steps provided in the embodiments of the present invention. The storage medium may be a magnetic disk, an optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0094] Therefore, this invention obtains the unloaded deformation of the chassis, performs curve fitting on the unloaded deformation to obtain the error of multiple test points, and then adjusts the positions of the corresponding points of the chassis model to obtain a corrected chassis model. By using the corrected chassis model to perform sinking simulation, a more realistic simulation result can be obtained. The technical effects that this embodiment can achieve can be seen in the description above, and will not be repeated here.

[0095] Those skilled in the art will clearly understand that the techniques in the embodiments of the present invention can be implemented using software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solutions in the embodiments of the present invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium such as a USB flash drive, mobile hard drive, read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk, or other media capable of storing program code. It includes several instructions to cause a computer terminal (which may be a personal computer, server, or a second terminal, network terminal, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention.

[0096] The same or similar parts between the various embodiments in this specification can be referred to mutually. In particular, the terminal embodiments are basically similar to the method embodiments, so the description is relatively simple, and the relevant parts can be referred to the description in the method embodiments.

[0097] In the embodiments provided by this invention, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules 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 systems or modules may be electrical, mechanical, or other forms.

[0098] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0099] In addition, the functional modules in the various embodiments of the present invention can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0100] Although the present invention has been described in detail with reference to the accompanying drawings and preferred embodiments, the invention is not limited thereto. Various equivalent modifications or substitutions can be made to the embodiments of the invention by those skilled in the art without departing from the spirit and essence of the invention, and such modifications or substitutions should all be within the scope of the invention. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the invention should also be covered within the protection scope of the invention. Therefore, the protection scope of the invention should be determined by the scope of the claims.

Claims

1. A method for simulating chassis sinking, characterized in that, include: Acquire test data, which includes vertical deflection data of multiple test points of the sample chassis under no-load conditions; Error data is obtained by fitting the test data to a probability distribution curve; Construct a chassis model of the sample chassis, and use the error data to correct the nodes in the chassis model that correspond to the test points of the sample chassis; A gravity field was applied to the modified chassis model to simulate sinking and obtain sinking data.

2. The method according to claim 1, characterized in that, Acquire test data, which includes vertical deflection data of multiple test points of the sample chassis under no-load conditions, including: Set the coordinates of the test points, save the coordinates of the test points to the test task, and send the test task to the test production line; Save the vertical deflection data of the same test point of multiple sample chassis as a test array; After marking the coordinates of the test points belonging to multiple test arrays, save them to the test result record file.

3. The method according to claim 2, characterized in that, Error data is obtained by fitting the test data to a probability distribution curve, including: The test array is extracted sequentially from the test result record file, and the test array is fitted with a normal distribution function. The value of the specified confidence interval is calculated based on the normal distribution function of the test array, and the value is set as the error value of the corresponding test point; Summarize the error values ​​of all test points to obtain the error data.

4. The method according to claim 3, characterized in that, Construct a chassis model of the sample chassis, and use the error data to correct the nodes in the chassis model corresponding to the test points of the sample chassis, including: Establish a finite element model of the server; Based on the coordinates of the test points, positioning points are generated at the corresponding positions of the chassis base in the finite element model; The error data is written into the configuration file, and an error value is matched for each positioning point based on the coordinate correspondence between the test point and the positioning point. The matching error value of the positioning point is read by an automatic execution script, and the positioning point coordinates and matching error value are imported into the corresponding configuration item in the adjustment interface of the model processing software to adjust the position of the positioning point. Iterate through all the points to correct their positions. The chassis base of the finite element model was smoothed using model processing software based on the corrected positioning points to obtain the corrected chassis model.

5. The method according to claim 4, characterized in that, Based on the coordinates of the test points, positioning points are generated at the corresponding positions of the chassis base in the finite element model, including: Enter the shape adjustment interface of the model processing software, and then call the conversion option in the shape adjustment interface; Input the coordinates of the test point into the conversion option to obtain the positioning point corresponding to the test point; The positioning points are set as movable points, and a mesh is built based on the positioning points.

6. The method according to claim 1, characterized in that, A gravity field was applied to the modified chassis model to simulate sinking, and sinking data was obtained, including: Import the corrected chassis model into the finite element analysis tool to perform gravity loading calculations and obtain the deformation. Export the model of the deformed chassis base as a file in a format recognizable by 3D software, and save the file as sinking data.

7. The method according to claim 1, characterized in that, After acquiring the test data, the method further includes: Select some target test points from multiple test points, obtain the vertical deflection of the target test points of the sample chassis during the actual sinking test, and obtain the actual sinking data; Obtain theoretical sinking data from sinking simulation of the chassis model; The difference between the actual sinking data and the corresponding theoretical sinking data is saved as the actual error data of the target test point; Select all vertical deflection data corresponding to the target test point from the test data as input data, and filter all data corresponding to the target test point from the actual error data as output data; According to the linguistic description of random variables in the fuzzy control algorithm, the input data and output data are converted into corresponding fuzzy sets. The fuzzy sets include negative maximum, negative large, negative medium, negative small, zero, positive small, positive medium, positive large, and positive maximum. Among them, zero represents the average value of the data in the fuzzy set, negative indicates downward deviation from the average value, and positive indicates upward deviation from the average value. Using the input and output data as the basic universe of discourse, create corresponding fuzzy subset universes of discourse, and establish the transformation relationship between the basic universe of discourse and the fuzzy subset universes of discourse; Fuzzy control rules are established based on the correspondence between the vertical deflection of test points under no-load conditions and the corresponding actual error. Calculate fuzzy relations and calculate fuzzy decisions based on fuzzy relations; Using the fuzzy decision method, error data for other test points besides the target test point is obtained. The theoretical sinking data corresponding to the test points in the chassis model are adjusted using the error data to obtain the corrected chassis model base. The corrected chassis model base is then saved as a sinking model file.

8. A chassis sinking simulation system, characterized in that, include: The no-load test module is used to acquire test data, which includes vertical deflection data of multiple test points of the sample chassis under no-load conditions. The curve fitting module is used to fit the test data using a probability distribution curve to obtain error data; The model correction module is used to construct a chassis model of the sample chassis and use the error data to correct the nodes in the chassis model that correspond to the test points of the sample chassis. The sinking simulation module is used to apply a gravity field to the corrected chassis model to simulate sinking and obtain sinking data.

9. A terminal, characterized in that, include: The memory is used to store the chassis sinking simulation program; A processor, configured to implement the steps of the chassis sinking simulation method as described in any one of claims 1-7 when executing the chassis sinking simulation program.

10. A computer-readable storage medium storing a computer program, characterized in that, The readable storage medium stores a chassis sinking simulation program, which, when executed by a processor, implements the steps of the chassis sinking simulation method as described in any one of claims 1-7.

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