Crankshaft Quality Assessment Method, Device and Server

Abstract

The present invention provides a crankshaft quality assessment method, device and server, relating to the technical field of quality assessment, including: obtaining a crankshaft model and receiving interaction information of the user terminal for the crankshaft model; identifying various internal components of the crankshaft from the crankshaft model according to the interaction information, and determining the physical characteristic information of each internal component of the crankshaft by identifying the surface feature IDs of each internal component of the crankshaft; performing numerical analysis and processing on the internal component types and corresponding physical characteristic information of the internal components of the crankshaft to determine the constraint equations corresponding to each internal component of the crankshaft; through a preset finite element solver, based on the physical characteristic information and constraint equations corresponding to each internal component of the crankshaft, performing finite element numerical calculation on the crankshaft model to determine the crankshaft quality assessment result. The present invention can significantly improve the accuracy of crankshaft quality assessment, reduce the usage threshold, and improve the assessment efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of quality assessment, and in particular, to a method, device, and server for crankshaft quality assessment. Background Art

[0002] As a core internal component of power equipment such as engines and diesel engines, the quality and reliability of the crankshaft are key factors to ensure the normal operation of mechanical equipment. At present, related technologies propose that the structural strength of the crankshaft can be detected by traditional physical experimental methods such as appearance inspection, strength test, and fatigue test. However, the appearance inspection method is mainly used to check defects such as cracks and wear on the surface of the crankshaft, and it cannot judge the internal structural strength of the crankshaft. The strength test must rely on physical products, and the experimental cycle of the fatigue test is long and the cost is high. Summary of the Invention

[0003] In view of this, an object of the present invention is to provide a method, device, and server for crankshaft quality assessment, which can significantly improve the accuracy of crankshaft quality assessment and improve the assessment efficiency.

[0004] In a first aspect, an embodiment of the present invention provides a method for crankshaft quality assessment, the method including: obtaining a crankshaft model and receiving interaction information of a user terminal for the crankshaft model; identifying various internal components of the crankshaft from the crankshaft model according to the interaction information, and determining physical feature information of each internal component of the crankshaft by identifying the surface feature ID of each internal component of the crankshaft; performing numerical analysis processing on the internal component type and corresponding physical feature information of the internal components of the crankshaft to determine a constraint equation corresponding to each internal component of the crankshaft, where the constraint equation is used to simulate the boundary constraints and load application conditions of each internal component of the crankshaft; and performing finite element numerical calculation on the crankshaft model based on the physical feature information and constraint equation corresponding to each internal component of the crankshaft through a preset finite element solver to determine the crankshaft quality assessment result.

[0005] In an implementation manner, the step of identifying various internal components of the crankshaft from the crankshaft model according to the interaction information includes: obtaining surface feature data of the crankshaft model by traversing each surface of the crankshaft model; and determining surface feature data associated with the target operation surface and geometric features corresponding to the surface feature data by parsing the target operation surface determined according to the interaction information to identify various internal components of the crankshaft.

[0006] In one embodiment, the step of determining the physical characteristic information of each internal crankshaft component by identifying the surface feature IDs of each internal crankshaft component includes: configuring the corresponding physical characteristic information from the material data in a preset material library based on the surface feature IDs of each internal crankshaft component, where the physical characteristic information includes: density, elastic modulus, Poisson's ratio, yield strength, ultimate strength, and S-N curve data.

[0007] In one embodiment, the step of performing finite element numerical calculation on the crankshaft model by a preset finite element solver based on the corresponding physical characteristic information and constraint equations of each internal crankshaft component to determine the crankshaft mass evaluation result further includes: obtaining the external load vector of the crankshaft model, where the external load vector includes: the moment on the front end face of the crankshaft, the cylindrical support force on the thrust face of the crankshaft, the cylindrical support force on the support face of the crankshaft, and the non-uniform load on the journal face of the crankshaft; discretizing the continuous structure of the crankshaft model into multiple finite elements, and constructing the basic equation for finite element solution corresponding to the crankshaft model based on the external load vector and the finite elements; solving the basic equation for finite element solution corresponding to the crankshaft model by a preset finite element solver based on the corresponding physical characteristic information and constraint equations of each internal crankshaft component to determine the nodal displacement vector, stress vector, and strain vector of the crankshaft under different loadings, and determining the nodal displacement vector, stress vector, and strain vector as the crankshaft mass evaluation result.

[0008] In one embodiment, the basic equation for finite element solution corresponding to the crankshaft model is:

[0009]

[0010] Wherein, is the global stiffness matrix, which is composed of the element stiffness matrices, is the nodal displacement vector, representing the displacements of each mesh node, is the external load vector.

[0011] In one embodiment, the step of determining the nodal displacement vector, stress vector, and strain vector of the crankshaft under different loadings includes: determining the strain vector based on the nodal displacement vector, and obtaining the constitutive matrix of the material from a preset material library; determining the stress vector using the linear proportional relationship between the strain vector and the stress vector and the constitutive matrix.

[0012] In one embodiment, after the steps of determining the nodal displacement vector, stress vector, and strain vector of the crankshaft under different loads, the method includes: generating a feature distribution contour map corresponding to each evaluation feature by using a preset image rendering model with the nodal displacement vector, stress vector, and strain vector, and generating a digital verification report by using the crankshaft mass evaluation result; and sending the feature distribution contour map and the digital verification report to the client for displaying the evaluation result.

[0013] In a second aspect, an embodiment of the present invention further provides a crankshaft mass evaluation device, which includes: an information acquisition module for acquiring a crankshaft model and receiving interaction information of the client for the crankshaft model; a model interaction module for identifying each internal component of the crankshaft from the crankshaft model according to the interaction information, and determining the physical feature information of each internal component of the crankshaft by identifying the surface feature ID of each internal component of the crankshaft; a numerical analysis module for performing numerical analysis processing on the internal component type and corresponding physical feature information of the internal components of the crankshaft to determine a constraint equation corresponding to each internal component of the crankshaft, where the constraint equation is used to simulate the boundary constraints and load application conditions of each internal component of the crankshaft; and a mass evaluation module for performing finite element numerical calculation on the crankshaft model by using a preset finite element solver based on the physical feature information and constraint equation corresponding to each internal component of the crankshaft to determine the crankshaft mass evaluation result.

[0014] In a third aspect, an embodiment of the present invention further provides a server, which includes a processor and a memory. The memory stores computer executable instructions that can be executed by the processor, and the processor executes the computer executable instructions to implement the method according to any one of the first aspect.

[0015] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, which stores computer executable instructions. When the computer executable instructions are called and executed by the processor, the computer executable instructions cause the processor to implement the method according to any one of the first aspect.

[0016] The embodiments of the present invention bring the following beneficial effects:

[0017] A crankshaft quality assessment method, device, and server provided by an embodiment of the present invention. After obtaining a crankshaft model and receiving interaction information from a user terminal for the crankshaft model, this method identifies various internal components of the crankshaft from the crankshaft model, determines the physical characteristic information of each internal component of the crankshaft by identifying the surface feature IDs of each internal component of the crankshaft, then performs numerical analysis processing on the internal component types and corresponding physical characteristic information of the internal components of the crankshaft to determine the constraint equations corresponding to each internal component of the crankshaft. Finally, through a preset finite element solver, based on the physical characteristic information and constraint equations corresponding to each internal component of the crankshaft, finite element numerical calculation is performed on the crankshaft model to determine the crankshaft quality assessment result. The embodiment of the present invention can quickly and efficiently perform accurate assessment and prediction of the crankshaft quality and service life through a lightweight digital R & D process, with the help of the crankshaft three-dimensional model and interaction data, providing a new solution for the design, optimization, and quality control of the crankshaft.

[0018] Other features and advantages of the present invention will be described in the following specification, and, in part, will be obvious from the specification, or will be understood by implementing the present invention. The objectives and other advantages of the present invention are achieved and obtained by the structures specifically pointed out in the specification, claims, and drawings.

[0019] To make the above objectives, features, and advantages of the present invention more obvious and understandable, the following specifically enumerates preferred embodiments and, in conjunction with the accompanying drawings, details are described as follows. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for use in the description of the specific embodiments or the prior art. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0021] Figure 1 It is a schematic flowchart of a crankshaft quality assessment method provided by an embodiment of the present invention;

[0022] Figure 2 It is a schematic structural diagram of a crankshaft theoretical analysis model provided by an embodiment of the present invention;

[0023] Figure 3 It is a schematic structural diagram of a crankshaft model provided by an embodiment of the present invention;

[0024] Figure 4 It is a specific schematic flowchart of a crankshaft quality assessment method provided by an embodiment of the present invention;

[0025] Figure 5A schematic diagram of load parameters provided by an embodiment of the present invention;

[0026] Figure 6 A schematic diagram of a digital verification result provided by an embodiment of the present invention;

[0027] Figure 7 A schematic structural diagram of a crankshaft quality assessment device provided by an embodiment of the present invention;

[0028] Figure 8 A schematic structural diagram of a server provided by an embodiment of the present invention. Detailed implementation manners

[0029] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Apparently, the described embodiments are some, rather than all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0030] Currently, in the field of modern mechanical engineering, power equipment such as engines and diesel engines is widely used in multiple key links such as transportation, industrial production, and energy conversion. As the core internal component of these mechanical equipment, the importance of the crankshaft is self-evident. During the complex power transmission process, the crankshaft bears huge mechanical stresses and alternating loads, and its performance directly determines the output efficiency and service life of the engine. However, due to the diversity of working environments, from high-speed automotive engines to heavy-duty low-speed marine diesel engines, different application scenarios pose extremely high requirements for the adaptability of the crankshaft. The quality and reliability of the crankshaft are the key factors to ensure the normal operation of mechanical equipment. However, traditional evaluation methods often rely on experience or cumbersome experimental tests and are difficult to quickly and accurately identify the weak points of the crankshaft.

[0031] In the field of crankshaft structural strength and quality assessment, traditional physical test methods mainly include appearance inspection, strength test, and fatigue test. However, these methods all have certain limitations: First, the appearance inspection method is mainly used to check defects such as cracks and wear on the surface of the crankshaft, but it cannot judge its internal structural strength. For example, the commonly used magnetic particle flaw detection technology in factories can detect the existence and length of cracks, but it cannot accurately evaluate the crack depth. Especially for the closed cracks at the fillet of the crankshaft journal, conventional detection methods have problems such as high detection difficulty and difficulty in quantification.

[0032] Second, the strength test is an important means to evaluate the structural strength of the crankshaft, but its drawback is that it must rely on physical products, which means that during the product development stage, a complete physical crankshaft needs to be manufactured to conduct the test. This not only increases the R & D cost but also prolongs the development cycle.

[0033] Finally, the fatigue test is a key method for evaluating the service life of the crankshaft, but it has a long cycle and high cost. For example, the fatigue test of the crankshaft of an automotive engine usually requires thousands of hours of bench strengthening tests, which not only takes a long time, but also requires a large amount of experimental equipment and human input. In addition, although the traditional fatigue test method can provide relatively accurate results, it is difficult to monitor the fatigue state of the crankshaft under actual working conditions in real time.

[0034] In summary, the traditional physical test methods have obvious limitations in the evaluation of the structural strength and quality of the crankshaft and cannot meet the requirements of modern industry for efficient, low-cost and high-precision evaluation. Based on this, the crankshaft quality evaluation method, device and server provided by the embodiments of the present invention can significantly improve the accuracy rate of crankshaft quality evaluation and improve the evaluation efficiency.

[0035] See Figure 1 The schematic flow chart of a crankshaft quality evaluation method shown in the figure, this method mainly includes the following steps S102 to step S108:

[0036] Step S102, obtain a crankshaft model and receive the interaction information of the user terminal for the crankshaft model. In one implementation, the crankshaft model is constructed based on a preset crankshaft theoretical analysis model. By simulating the actual usage of the internal components of the crankshaft in the crankshaft - connecting rod - piston mechanism and theoretically analyzing and defining the crankshaft structure, the crankshaft theoretical analysis model can be determined. See Figure 2 The schematic structural diagram of a crankshaft theoretical analysis model shown in the figure, the crankshaft is divided into several key internal components: the AB section is defined as the thrust part of the crankshaft, the BC and EF sections are defined as the crank arm parts of the crankshaft, the CE section is defined as the journal part of the crankshaft, the FG section is defined as the support part of the crankshaft, and the GH section is defined as the front end part of the crankshaft.

[0037] Under normal working conditions, the thrust part (AB section) of the crankshaft and the internal components connected to it jointly bear the supporting effect on the bearing. For the sake of simplified analysis, this effect is here transformed into the supporting forces of the AB section in the x-axis and y-axis directions and , so that the force condition of the thrust part can be accurately described in numerical calculations.

[0038] The crank arm parts (BC and EF sections) are important components of the crankshaft. Their main function is to convert the linear motion of the piston into rotational motion. The crank arms themselves have no boundary degree of freedom restrictions, but the strength check of them is the focus of crankshaft quality evaluation and life prediction.

[0039] The crankshaft journal part (CE section) is connected to the connecting rod, and the driving force of the piston is transmitted to the journal through the connecting rod. For the convenience of numerical calculation, this process is converted into the tangential force on the CE section here. and the radial force , so as to accurately describe the stress state of the journal part.

[0040] The crankshaft support part (FG section) bears the support function for the bearing. Similar to the thrust part, this function is converted into the support forces of the FG section in the x-axis and y-axis directions here, so as to accurately describe the stress condition of the support part in numerical calculation.

[0041] Finally, the front end part (GH section) of the crankshaft will be subjected to an external torque. For the sake of simplified analysis, this effect is converted into the torque on the GH section here , so as to accurately describe the stress state of the front end part, and then establish a crankshaft model according to the crankshaft theoretical analysis model to perform numerical analysis transformation on each part of the crankshaft model. For the specific structure diagram of a crankshaft model, please refer to Figure 3 the structure schematic diagram of a crankshaft model shown.

[0042] Step S104, identify each internal crankshaft component from the crankshaft model according to the interaction information, and determine the physical characteristic information of each internal crankshaft component by identifying the surface feature ID of each internal crankshaft component. The surface feature ID is the key data for subsequent finite element numerical calculation. The surface feature ID defines the acting position and mode of the load and boundary. In one implementation, the surface feature data of the crankshaft model can be obtained by traversing each surface of the crankshaft model, and the surface feature data associated with the target operation surface can be determined by parsing and processing the target operation surface determined according to the interaction information, as well as the geometric features corresponding to the surface feature data, so as to identify each internal crankshaft component.

[0043] Specifically, when evaluating the numerical calculation of the crankshaft journal part, it is necessary to consider the complex alternating loads generated by the piston movement. In order to better transform and apply these loads, they can be calculated based on actual engineering data. Since the piston movement will generate alternating loads, an extreme case evaluation will be adopted here. The corresponding engineering data includes the maximum explosion pressure during actual piston movement and the cylinder liner diameter D. The specific calculation formula is as follows:

[0044]

[0045] This formula calculates the impact force generated by the piston on the crankshaft journal at the highest explosion pressure. Among them, Pi is the highest explosion pressure during actual piston movement, and D is the cylinder liner diameter. This impact force is a key parameter for evaluating the stress state of the crankshaft journal, which directly affects the prediction of crankshaft deformation, stress distribution, and fatigue life. In finite element analysis, the impact force F_impact will be used as one of the boundary loads to simulate the stress condition of the crankshaft under actual working conditions. In this way, the performance of the crankshaft under extreme working conditions can be predicted more accurately.

[0046] During the application of the sinusoidal distribution non-uniform load, the characteristic ID of the crankshaft journal surface can be obtained through an interactive method. This can be achieved by selecting the journal surface of the crankshaft. After selecting the journal surface, the system can identify and obtain the corresponding surface characteristic ID, thus providing the necessary information for the accurate application of the load. This step is crucial in the load transfer process because it ensures that the load can be correctly applied to a specific area of the crankshaft.

[0047] Taking the STEP file in the 3D CAD model storage format as an example, it can store geometric, topological, and feature information. To identify and obtain the surface characteristic ID of the selected surface, it is first necessary to parse the STEP file and extract its geometric and topological data. Each face in the STEP file is usually represented by a unique identifier (ID), and these IDs are associated with geometric entities (such as planes, cylindrical surfaces, spherical surfaces, etc.). Open source tools such as OpenCASCADE or PythonOCC can be used to parse the STEP file. These tools can convert the geometric data in the STEP file into a programmable data structure, such as a boundary representation (BRep) model. The BRep model represents a three-dimensional object as a set of vertices, edges, and faces, and each face has a unique ID.

[0048] After obtaining the surface feature data of the model, the next step is to select a specific surface through an interactive method. Specifically, the algorithm will traverse all the faces of the model and select the determined face. It is necessary to identify its geometric features and obtain the corresponding feature ID. The faces in the STEP file are usually associated with geometric features (such as planes, cylindrical surfaces, etc.), and these features are defined by specific names (such as PLANE, CYLINDRICAL_SURFACE, etc.) in the file. By parsing the topological and geometric entity relationships in the STEP file, the selected face can be associated with its corresponding feature ID. For example, in the selection of this part of the crankshaft, if the selected face is a cylindrical surface, the geometric feature ID corresponding to the selected face can be found by traversing the CYLINDRICAL_SURFACE entities in the STEP file.

[0049] In another embodiment, corresponding physical characteristic information can be configured from the material data in the preset material library based on the surface feature IDs of each internal component of the crankshaft. The physical characteristic information includes: density, elastic modulus, Poisson's ratio, yield strength, ultimate strength, and S-N curve data. Specifically, the material library is set based on the configurable characteristics of the low-code platform. By importing predefined material data, corresponding physical properties are assigned to the geometric model. These parameters directly determine the response behavior of the model to external loads during the simulation process. In addition, the material library supports custom extensions. For example, the S-N curve data will be extended here to accurately describe the material behavior under more complex working conditions.

[0050] Step S106: Perform numerical analysis processing on the internal component types and corresponding physical characteristic information of the internal components of the crankshaft to determine the constraint equations corresponding to each internal component of the crankshaft. The constraint equations are used to simulate the boundary constraints and load application conditions of each internal component of the crankshaft. In one embodiment, a reference direction needs to be determined according to the principle of non-uniform load. This reference direction is arbitrary. However, to ensure the accuracy and consistency of the analysis, it is usually set with reference to the absolute coordinate system of the crankshaft model. After determining the reference direction, a sine waveform can be used to simulate the load distribution. This distribution method can better simulate the non-uniformity of the load under actual working conditions.

[0051] In numerical analysis, in order to accurately simulate the support forces in the x-axis and y-axis directions of the AB section, a cylindrical support method can be used for transformation to apply constraints on the cylindrical surface in the three dimensions of radial, axial, and tangential directions to accurately simulate the action of the actual support force. The cylindrical support is mainly based on the thrust surface of the crankshaft and uses its geometric characteristics to apply corresponding constraint conditions. For the support forces in the x-axis and y-axis directions, the radial and tangential degrees of freedom of the thrust surface can be restricted. Among them, the restriction of the radial degree of freedom ensures that the displacement of the crankshaft in the radial direction is controlled, thereby effectively simulating the support action in the x-axis and y-axis directions. The constraint of the tangential degree of freedom can prevent the thrust surface from slipping along the cylindrical surface, further enhancing the stability of the model.

[0052] In addition, considering the force-bearing characteristics of the thrust surface, the movement in the z-axis direction may be restricted under certain working conditions. Therefore, its axial degree of freedom can be further restricted to simulate the state where the z-axis is restricted under some working conditions, so as to effectively reproduce the support action of the crankshaft on the thrust surface in the actual working condition, ensure the rationality of the force during the numerical calculation process, and establish corresponding constraint equations.

[0053] In the finite element model of the cylindrical support, the constraint equations are used to simulate the force-bearing situation of the thrust surface of the crankshaft, ensure the reasonable support forces in the x-axis and y-axis directions, and restrict the z-axis degree of freedom under specific working conditions:

[0054] 1. The radial constraint equation is used to restrict the displacement of the thrust surface in the radial direction, keeping the node always on the cylindrical surface:

[0055]

[0056] where, is the initial radius, ensuring that the thrust surface is restricted in the x and y directions.

[0057] 2. The tangential constraint equation is used to prevent the thrust surface from slipping tangentially:

[0058]

[0059] Ensuring that the thrust surface does not rotate around the axis or slip laterally.

[0060] 3. The axial constraint equation is used to further restrict the movement in the z direction under specific working conditions:

[0061]

[0062] Preventing the thrust surface from moving freely along the axis and simulating the restricted state of the z-axis.

[0063] In addition, by reasonably selecting the thrust surface of the crankshaft, appropriate boundary conditions can be applied in the finite element model to make it conform to the force conditions in actual engineering applications: for the supporting forces of the FG section in the x-axis and y-axis directions, the same method of cylindrical support is also used for transformation to ensure the accuracy of numerical analysis and the stability of calculation. This method simulates the supporting forces in the x-axis and y-axis directions by restricting the radial degrees of freedom of the crankshaft thrust surface, so that the thrust surface does not displace radially. By reasonably selecting the supporting surface of the crankshaft, finite element constraints can be effectively applied to correctly simulate the supporting effect in numerical analysis, thereby improving the overall calculation accuracy and the force rationality of the model.

[0064] At the front end of the crankshaft (GH section), the torque is a key action quantity, and its calculation and analysis directly affect the accuracy of numerical evaluation. In actual engineering, in order to more accurately transform and apply this torque, it is necessary to combine the actual engine working conditions and obtain the numerical value of the torque through engineering data to meet the numerical calculation requirements. These engineering data mainly include the output power P (unit: kilowatt, kW) and rotational speed n (unit: revolutions per minute, RPM) of the engine, and the two can reflect the working characteristics of the engine under actual operating conditions. The calculation formula of the torque is:

[0065]

[0066] where, The torque at the front end of the crankshaft, with the unit of Newton-meter (N·m); P is the output power of the engine, with the unit of kilowatt (kW); n is the engine speed, with the unit of revolutions per minute (RPM); 9549 is the constant for power and speed conversion torque, which comes from unit conversion (1kW = 1000W, 1RPM = rad / s).

[0067] In step S108, through a preset finite element solver, based on the physical characteristic information and constraint equations corresponding to each internal component of the crankshaft, perform finite element numerical calculation on the crankshaft model to determine the crankshaft mass evaluation result.

[0068] The above-mentioned crankshaft mass evaluation method provided by the embodiments of the present invention can significantly improve the accuracy of crankshaft mass evaluation and improve the evaluation efficiency.

[0069] See Figure 4 The specific process schematic diagram of a crankshaft mass evaluation method shown. Starting from model import, combined with the corresponding mesh settings and material library settings, perform general preprocessing on the geometric model, and then introduce various boundary and load conditions for the solutions in the specific scenario of the crankshaft, including the torque on the front end face of the crankshaft, the cylindrical support force on the thrust face of the crankshaft, the cylindrical support force on the support face of the crankshaft, and the non-uniform load on the journal face of the crankshaft. After completing the material library settings and applying the boundary conditions, the system calls the finite element solver for calculation. The finite element divides the continuous structure into multiple finite elements through discretization and establishes the corresponding solution equations, so as to calculate the key results such as stress and deformation of the crankshaft under different loads. The embodiments of the present invention also provide an implementation method for performing finite element numerical calculation on the crankshaft model to determine the crankshaft mass evaluation result. Specifically, see the following (1) to (3):

[0070] (1) Obtain the external load vector of the crankshaft model, where the external load vector includes: the torque on the front end face of the crankshaft, the cylindrical support force on the thrust face of the crankshaft, the cylindrical support force on the support face of the crankshaft, and the non-uniform load on the journal face of the crankshaft.

[0071] (2) Discretize the continuous structure of the crankshaft model into multiple finite elements, and based on the external load vector and the finite elements, construct the basic equation for finite element solution corresponding to the crankshaft model. Among them, the basic equation for finite element solution corresponding to the crankshaft model is:

[0072]

[0073] Among them, is the global stiffness matrix, which is composed of the element stiffness matrices, is the node displacement vector, representing the displacement of each mesh node, is an external load vector, including: the moment on the front end face of the crankshaft, the cylindrical supporting force on the thrust face of the crankshaft, the cylindrical supporting force on the supporting face of the crankshaft, and the non-uniform load on the journal face of the crankshaft.

[0074] (3) By presetting a finite element solver, based on the physical characteristic information and constraint equations corresponding to each internal component of the crankshaft, solve the basic equations of the finite element solution corresponding to the crankshaft model to determine the nodal displacement vector, stress vector, and strain vector of the crankshaft under different loads, and determine the nodal displacement vector, stress vector, and strain vector as the crankshaft mass evaluation result. In one implementation, determine the strain vector according to the nodal displacement vector, obtain the constitutive matrix of the material from the preset material library, and then use the linear proportional relationship between the strain vector and the stress vector and the constitutive matrix to determine the stress vector. In another implementation, through a preset image rendering model, use the nodal displacement vector, stress vector, and strain vector to generate a characteristic distribution cloud map corresponding to each evaluation feature, and generate a digital verification report using the crankshaft mass evaluation result. Finally, send the characteristic distribution cloud map and the digital verification report to the user terminal for displaying the evaluation result.

[0075] Specifically, under the action of the boundary conditions, the finite element solver solves the above basic equations of the finite element solution through matrix operations to obtain the displacement field of the crankshaft, and further calculates the stress and strain:

[0076]

[0077] Among them, is the stress vector, including the normal stress and shear stress in each direction; is the constitutive matrix of the material, which depends on the elastic properties of the material (provided by the material library parameters); is the strain vector, which is calculated from the nodal displacement.

[0078] The evaluation results are displayed in the form of a rendered cloud map, and the data results of various factors affecting its structural strength and service life can be directly displayed, so that engineers can intuitively analyze the stress distribution, deformation mode, and force conditions of key parts of the crankshaft. For example, the high stress concentration area: indicates the part where the crankshaft may undergo fatigue failure; the maximum deformation area: used to evaluate whether the stiffness and deformation of the crankshaft exceed the allowable range; the contact pressure distribution: used to analyze the interaction between the journal face and the bearing. Here, a complete report form will be used for automatic generation and display, thus forming a complete method for evaluating and predicting the quality of the crankshaft.

[0079] In practical applications, for the crankshaft model, each part is selected interactively, including the crankshaft thrust surface, crankshaft journal surface, crankshaft support surface, and crankshaft front end surface. This process can be achieved through a graphical user interface. By selecting different parts of the crankshaft, the system can automatically identify and obtain the corresponding surface feature IDs.

[0080] After obtaining the surface feature data, finite element numerical calculations can be performed, and the results will be displayed in the form of nephograms after the calculation is completed. For example, the total deformation distribution nephogram, equivalent stress distribution nephogram, etc. The color scale shown in the nephogram uses a gradient mode of red - green - blue - gray, and a gray scale more similar to the original color of the model is used to display the characteristics of the model with less deformation or less stress, so as to avoid the interference of strong saturation colors on the distribution of weak points of the model. This visualization method helps engineers intuitively identify potential problem areas of the crankshaft, so as to carry out targeted design optimization.

[0081] To achieve the post - processing rendering display of the model file, the finite element result file can be converted into a VTK visualization format file and transmitted to the Web side. VTK (Visualization Toolkit) is an open - source software system for 3D computer graphics, image processing, and visualization. In this way, users can perform interactive model analysis and result viewing on the Web side.

[0082] See Figure 5 A schematic diagram of a load parameter shown below. Subsequent reports and numerical feedback are generated automatically. In addition to the fixed project background and corresponding reference test standards in this scenario, the input power, rotational speed, maximum explosion pressure, and cylinder liner diameter parameters can also be combined here to generate a corresponding table and issue the results of digital diagnosis. See Figure 6 A schematic diagram of a digital verification result shown below. Among them, according to the input of material properties, the basis for digital diagnosis is as follows:

[0083] The maximum stress value < the material yield strength, it is considered that plastic deformation will not occur, and the reference suggestion is qualified; the material yield strength ≤ the maximum stress value ≤ the material ultimate strength, it is considered that plastic deformation will occur but will not break, and the reference suggestion is a warning; the maximum stress value > the material ultimate strength, it is considered that breakage will occur, and the reference suggestion is unqualified.

[0084] The allowable number of times of the crankshaft can also be judged with reference to its actual use standard, so as to put forward reference opinions: the maximum allowable number of times < the actual use standard, the reference suggestion is unqualified; the maximum allowable number of times ≥ the actual use standard, the reference suggestion is qualified.

[0085] In summary, the present invention can quickly and efficiently conduct accurate assessment and prediction of the quality and service life of a crankshaft through a lightweight digital R & D process, with the aid of a three-dimensional model of the crankshaft and interactive data, providing a new solution for the design, optimization, and quality control of the crankshaft.

[0086] For the crankshaft quality assessment method provided in the foregoing embodiment, the present invention provides a crankshaft quality assessment device. Refer to Figure 7 the structural schematic diagram of a crankshaft quality assessment device shown in

[0087] An information acquisition module 702, which acquires a crankshaft model and receives interactive information of the user terminal for the crankshaft model;

[0088] A model interaction module 704, which identifies various internal components of the crankshaft from the crankshaft model according to the interactive information, and determines the physical characteristic information of each internal component of the crankshaft by identifying the surface feature IDs of each internal component of the crankshaft;

[0089] A numerical analysis module 706, which conducts numerical analysis processing on the internal component types and corresponding physical characteristic information of the internal components of the crankshaft to determine the constraint equations corresponding to each internal component of the crankshaft, wherein the constraint equations are used to simulate the boundary constraints and load application conditions of each internal component of the crankshaft;

[0090] A quality assessment module 708, which conducts finite element numerical calculation on the crankshaft model through a preset finite element solver based on the physical characteristic information and constraint equations corresponding to each internal component of the crankshaft to determine the crankshaft quality assessment result.

[0091] The above-mentioned crankshaft quality assessment device provided by the embodiments of the present application can significantly improve the accuracy of crankshaft quality assessment and improve the assessment efficiency.

[0092] In one implementation manner, when performing the step of identifying various internal components of the crankshaft from the crankshaft model according to the interactive information, the above-mentioned model interaction module 704 is further configured to: obtain the surface feature data of the crankshaft model by traversing each surface of the crankshaft model; determine the surface feature data associated with the target operation surface and the geometric features corresponding to the surface feature data by parsing the target operation surface determined according to the interactive information, so as to identify various internal components of the crankshaft.

[0093] In one implementation manner, when performing the step of determining the physical characteristic information of each internal component of the crankshaft by identifying the surface feature IDs of each internal component of the crankshaft, the above-mentioned model interaction module 704 is further configured to: configure the corresponding physical characteristic information from the material data of the preset material library based on the surface feature IDs of each internal component of the crankshaft, wherein the physical characteristic information includes: density, elastic modulus, Poisson's ratio, yield strength, and ultimate strength.

[0094] In one implementation, when performing the step of performing finite element numerical calculation on the crankshaft model through a preset finite element solver based on the physical characteristic information and constraint equations corresponding to each internal component of the crankshaft to determine the crankshaft mass evaluation result, the above-mentioned mass evaluation module 708 is further configured to: obtain the external load vector of the crankshaft model, where the external load vector includes: the moment on the front end face of the crankshaft, the cylindrical support force on the thrust face of the crankshaft, the cylindrical support force on the support face of the crankshaft, and the non-uniform load on the journal face of the crankshaft; discretize the continuous structure of the crankshaft model into multiple finite elements, and construct the basic equation for finite element solution corresponding to the crankshaft model based on the external load vector and the finite elements; solve the basic equation for finite element solution corresponding to the crankshaft model through a preset finite element solver based on the physical characteristic information and constraint equations corresponding to each internal component of the crankshaft to determine the node displacement vector, stress vector, and strain vector of the crankshaft under different loads, and determine the node displacement vector, stress vector, and strain vector as the crankshaft mass evaluation result.

[0095] In one implementation, the above-mentioned mass evaluation module 708 further includes: The basic equation for finite element solution corresponding to the crankshaft model is:

[0096]

[0097] Where is the global stiffness matrix, which is composed of the element stiffness matrices, is the node displacement vector, representing the displacement of each grid node, is the external load vector.

[0098] In one implementation, when performing the step of determining the node displacement vector, stress vector, and strain vector of the crankshaft under different loads, the above-mentioned mass evaluation module 708 is further configured to: determine the strain vector according to the node displacement vector, and obtain the constitutive matrix of the material from a preset material library; use the linear proportional relationship between the strain vector and the stress vector and the constitutive matrix to determine the stress vector.

[0099] In one implementation, after performing the step of determining the node displacement vector, stress vector, and strain vector of the crankshaft under different loads, the above-mentioned mass evaluation module 708 is further configured to: generate a feature distribution cloud map corresponding to each evaluation feature by using a preset image rendering model with the node displacement vector, stress vector, and strain vector, and generate a digital verification report by using the crankshaft mass evaluation result; send the feature distribution cloud map and the digital verification report to the user terminal for displaying the evaluation result.

[0100] The device provided by the embodiment of the present invention has the same implementation principle and technical effects as those of the foregoing method embodiment. For the sake of brief description, for the parts not mentioned in the device embodiment, reference may be made to the corresponding content in the foregoing method embodiment.

[0101] The embodiment of the present invention provides a server. Specifically, the server includes a processor and a storage device; a computer program is stored on the storage device, and when the computer program is run by the processor, it executes the method described in any one of the foregoing embodiments.

[0102] Figure 8 FIG. is a schematic structural diagram of a server provided by an embodiment of the present invention. The server 100 includes: a processor 80, a memory 81, a bus 82, and a communication interface 83. The processor 80, the communication interface 83, and the memory 81 are connected through the bus 82; the processor 80 is used to execute an executable module stored in the memory 81, such as a computer program.

[0103] Among them, the memory 81 may include a high-speed random access memory (RAM, Random Access Memory), and may also include a non-volatile memory, such as at least one disk memory. Through at least one communication interface 83 (which may be wired or wireless), a communication connection is established between this system network element and at least one other network element, and the Internet, wide area network, local area network, metropolitan area network, etc. can be used.

[0104] The bus 82 may be an ISA bus, a PCI bus, an EISA bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of convenience of representation, Figure 8 only a bidirectional arrow is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0105] Among them, the memory 81 is used to store a program. After receiving an execution instruction, the processor 80 executes the program. The method executed by the device defined by the flow process disclosed in any one of the foregoing embodiments of the present invention can be applied to the processor 80 or implemented by the processor 80.

[0106] The processor 80 may be an integrated circuit chip with the ability to process signals. In the implementation process, each step of the above method can be completed by the integrated logic circuit of the hardware in the processor 80 or the instructions in the form of software. The above-mentioned processor 80 may be a general-purpose processor, including a central processing unit (CPU for short), a network processor (NP for short), etc.; it may also be a digital signal processor (DSP for short), an application specific integrated circuit (ASIC for short), a field-programmable gate array (FPGA for short), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. It can implement or execute the various methods, steps and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in combination with the embodiments of the present invention can be directly embodied as being executed and completed by the hardware decoding processor, or executed and completed by the combination of the hardware and software modules in the decoding processor. The software module may be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. This storage medium is located in the memory 81, and the processor 80 reads the information in the memory 81 and combines its hardware to complete the steps of the above method.

[0107] The computer program product of the readable storage medium provided by the embodiments of the present invention includes a computer-readable storage medium storing program code, and the instructions included in the program code can be used to execute the method described in the foregoing method embodiments. For the specific implementation, reference can be made to the foregoing method embodiments, which will not be elaborated here.

[0108] When the above-mentioned function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or a part of this technical solution can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs.

[0109] Finally, it should be noted that the above-mentioned embodiments are only specific implementation manners of the present invention, used to illustrate the technical solutions of the present invention, rather than limiting it. The protection scope of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: any person skilled in the art within the technical scope disclosed by the present invention can still modify the technical solutions recorded in the foregoing embodiments or easily conceive of changes, or make equivalent replacements for some of the technical features; and these modifications, changes, or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A method for evaluating the quality of a crankshaft, characterized in that, The method includes: Obtaining a crankshaft model and receiving interaction information of the user terminal for the crankshaft model; Identifying various internal components of the crankshaft from the crankshaft model according to the interaction information, and determining physical characteristic information of the various internal components of the crankshaft by identifying the surface feature IDs of the various internal components of the crankshaft; Performing numerical analysis processing on the internal component types of the internal components of the crankshaft and the corresponding physical characteristic information to determine constraint equations corresponding to the various internal components of the crankshaft, where the constraint equations are used to simulate the boundary constraints and load application conditions of the various internal components of the crankshaft; Performing finite element numerical calculation on the crankshaft model through a preset finite element solver based on the physical characteristic information and the constraint equations corresponding to the various internal components of the crankshaft to determine a crankshaft mass evaluation result; Among them, the step of identifying various internal components of the crankshaft from the crankshaft model according to the interaction information includes: obtaining surface feature data of the crankshaft model by traversing each surface of the crankshaft model; determining surface feature data associated with the target operation surface and geometric features corresponding to the surface feature data by parsing the target operation surface determined according to the interaction information, so as to identify various internal components of the crankshaft; Among them, the step of determining physical characteristic information of the various internal components of the crankshaft by identifying the surface feature IDs of the various internal components of the crankshaft includes: configuring corresponding physical characteristic information from material data in a preset material library based on the surface feature IDs of the various internal components of the crankshaft, where the physical characteristic information includes: density, elastic modulus, Poisson's ratio, yield strength, ultimate strength, and S-N curve data, and the surface feature ID is the key data for performing finite element numerical calculation, and the surface feature ID is used to define the action position and action mode of the load and boundary; 2. The crankshaft mass evaluation method according to claim 1, characterized in that, The step of performing finite element numerical calculation on the crankshaft model through a preset finite element solver based on the physical characteristic information and the constraint equations corresponding to the various internal components of the crankshaft to determine a crankshaft mass evaluation result further includes: Obtaining an external load vector of the crankshaft model, where the external load vector includes: the torque on the front end surface of the crankshaft, the cylindrical support force on the thrust surface of the crankshaft, the cylindrical support force on the support surface of the crankshaft, and the non-uniform load on the journal surface of the crankshaft; Discretizing the continuous structure of the crankshaft model into multiple finite elements, and constructing a basic equation for finite element solution corresponding to the crankshaft model based on the external load vector and the finite elements; Solving the basic equation for finite element solution corresponding to the crankshaft model through a preset finite element solver based on the physical characteristic information and the constraint equations corresponding to the various internal components of the crankshaft to determine the node displacement vector, stress vector, and strain vector of the crankshaft under different load actions, and determining the node displacement vector, stress vector, and strain vector as the crankshaft mass evaluation result; 3. The crankshaft mass evaluation method according to claim 2, characterized in that The basic equation for finite element solution corresponding to the crankshaft model is: Among them, is the global stiffness matrix, which is composed of element stiffness matrices, is the node displacement vector of the said, representing the displacements of each grid node, is the external load vector.

4. The crankshaft mass evaluation method according to claim 2, characterized in that, The steps of determining the nodal displacement vector, as well as the stress vector and strain vector of the crankshaft under different loads include: Determine the strain vector according to the nodal displacement vector, and obtain the constitutive matrix of the material from a preset material library; Determine the stress vector by using the linear proportional relationship between the strain vector and the stress vector and the constitutive matrix.

5. The crankshaft mass evaluation method according to claim 2, characterized in that, After the steps of determining the nodal displacement vector, as well as the stress vector and strain vector of the crankshaft under different loads, it includes: Through a preset image rendering model, use the nodal displacement vector, the stress vector and the strain vector to generate a feature distribution cloud map corresponding to each evaluation feature, and generate a digital verification report by using the crankshaft quality evaluation result; Send the feature distribution cloud map and the digital verification report to the client for displaying the evaluation result.

6. A crankshaft mass evaluation device, characterized in that, The device includes: An information acquisition module, which acquires a crankshaft model and receives interaction information from the client regarding the crankshaft model; A model interaction module, which identifies each internal component of the crankshaft from the crankshaft model according to the interaction information, and determines the physical feature information of each internal component of the crankshaft by identifying the surface feature ID of each internal component of the crankshaft; A numerical analysis module, which performs numerical analysis processing on the internal component type of the internal components of the crankshaft and the corresponding physical feature information to determine the constraint equations corresponding to each internal component of the crankshaft, where the constraint equations are used to simulate the boundary constraints and load application conditions of each internal component of the crankshaft; A quality evaluation module, which performs finite element numerical calculation on the crankshaft model through a preset finite element solver based on the physical feature information and the constraint equations corresponding to each internal component of the crankshaft to determine the crankshaft quality evaluation result; Among them, the step of identifying each internal component of the crankshaft from the crankshaft model according to the interaction information includes: obtaining the surface feature data of the crankshaft model by traversing each surface of the crankshaft model; determining the surface feature data associated with the target operation surface and the geometric features corresponding to the surface feature data by parsing the target operation surface determined according to the interaction information, so as to identify each internal component of the crankshaft; Among them, the step of determining the physical feature information of each internal component of the crankshaft by identifying the surface feature ID of each internal component of the crankshaft includes: configuring the corresponding physical feature information from the material data of the preset material library based on the surface feature ID of each internal component of the crankshaft, where the physical feature information includes: density, elastic modulus, Poisson's ratio, yield strength, ultimate strength and S-N curve data, and the surface feature ID is the key data for performing finite element numerical calculation, and the surface feature ID is used to define the action position and action mode of the load and boundary.

7. A server, characterized in that, It includes a processor and a memory, the memory stores computer executable instructions that can be executed by the processor, and the processor executes the computer executable instructions to implement the method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when called and executed by a processor, cause the processor to implement the method according to any one of claims 1 to 5.

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