Flow mark prediction method and related device

Abstract

The invention discloses a flow mark prediction method and a related device, and relates to the technical field of flow mark detection, and the method comprises the steps: obtaining a three-dimensional model and a configuration file of a to-be-detected part; dividing the three-dimensional model into a plurality of voxel grids according to the grid size in the configuration file; performing analogue simulation on the process of filling a plurality of voxel grids in the molten state based on parameters in the configuration file, and determining the speed of filling a target voxel grid in the molten state at each moment of analogue simulation as the filling speed corresponding to each moment; and according to the filling speed corresponding to each moment, determining whether flow marks are generated when the target voxel grid is filled in the molten state at each moment. Whether the flow mark is generated at each moment in the analogue simulation process is predicted based on the related data in the analogue simulation process, and a complex numerical simulation method in commercial software does not need to be used, so that a large amount of calculation time and calculation resources are saved, and the flow mark prediction cost is reduced.

Description

Technical Field

[0001] The present application relates to the technical field of flow mark detection, and in particular to a flow mark prediction method and related devices. Background Art

[0002] In the plastic injection molding process, the plastic raw material is heated to a molten state, and then the molten state is pushed by the screw to be injected into a specific mold for filling and cooling to form the final part product. Due to the actual structure of the part and the problems of injection molding process design, flow mark defects may occur during the final part molding. It is necessary to avoid the occurrence of flow mark defects in the part structure design and process design stage to ensure the quality of the part.

[0003] The traditional method for predicting flow mark defects is based on commercial software. Specifically, the commercial software uses numerical simulation methods to solve the relevant data involved in the process of molten state filling the mold, and then manually analyzes the solved relevant data to analyze whether the process of molten state filling the mold will produce flow mark defects. However, commercial software is expensive, and numerical simulation methods require a lot of computing resources and computing time, which is difficult to meet the needs of rapid iterative design of plastic parts. Summary of the invention

[0004] In view of the above problems, the present application provides a flow mark prediction method and related devices to solve the problems of high cost and large amount of computing resources and computing time in existing flow mark defect prediction methods. The specific scheme is as follows:

[0005] The first aspect of the present application provides a flow mark prediction method, comprising:

[0006] Obtain the 3D model and configuration file of the part to be inspected;

[0007] Dividing the three-dimensional model into a plurality of voxel grids according to a grid size in the configuration file;

[0008] Simulating the process of the molten state filling the plurality of voxel grids based on the parameters in the configuration file, determining the speed of the molten state filling a target voxel grid at each moment of the simulation as the filling speed corresponding to each moment, wherein the target voxel grid refers to a voxel grid adjacent to at least one voxel grid filled by the molten state and not filled by the molten state;

[0009] According to the filling speed corresponding to each moment, it is determined whether flow marks will be generated when the molten state fills the target voxel grid at each moment.

[0010] In a possible implementation, the simulating the process of filling the plurality of voxel grids in a molten state based on the parameters in the configuration file includes:

[0011] Determine the voxel grid where the injection gate is located according to the injection gate position information in the configuration file;

[0012] The voxel grid where the injection gate is located is taken as the first voxel grid filled with the molten state, and a process of the molten state filling the target voxel grid is simulated.

[0013] In a possible implementation, determining the speed at which the molten state fills the target voxel grid at each moment of the simulation as the filling speed corresponding to each moment includes:

[0014] determining the speed at which the screw pushes the molten state at each moment according to the screw speed curve in the configuration file;

[0015] According to the speed at which the screw pushes the molten state at each moment, the filling speed corresponding to each moment is obtained.

[0016] In a possible implementation, obtaining the filling speed corresponding to each moment according to the speed at which the screw pushes the molten state at each moment includes:

[0017] Determining the total amount of the target voxel grid filled by the molten state at each time instant;

[0018] Calculating the surface area of ​​the target voxel grid filled by the molten state at each moment according to the total number and the grid size;

[0019] The filling speed corresponding to each moment is calculated based on the surface area and the speed at which the screw pushes the molten state at each moment.

[0020] In a possible implementation, determining whether flow marks will be generated when the molten state fills the target voxel grid at each moment according to the filling speed corresponding to each moment includes:

[0021] Obtaining a critical flow mark speed, wherein the critical flow mark speed is obtained based on the material of the part to be inspected and the mold temperature;

[0022] For each moment, determine whether the filling speed corresponding to the moment is greater than the flow mark critical speed. If so, determine that the molten state will not produce flow marks when filling the target voxel grid at this moment. If not, determine that the molten state will produce flow marks when filling the target voxel grid at this moment.

[0023] In a possible implementation, the flow mark prediction method further includes:

[0024] For each of the moments, if flow marks will be generated when the molten state fills the target voxel grid at the moment, the position of the target voxel grid at the moment is determined.

[0025] A second aspect of the present application provides a flow mark prediction device, comprising:

[0026] An information acquisition module is used to obtain a three-dimensional model and configuration file of the part to be inspected;

[0027] A grid division module, used for dividing the three-dimensional model into a plurality of voxel grids according to the grid size in the configuration file;

[0028] a simulation calculation module, configured to simulate the process of the molten state filling the plurality of voxel grids based on the parameters in the configuration file, and determine the speed at which the molten state fills a target voxel grid at each moment of the simulation as the filling speed corresponding to each moment, wherein the target voxel grid refers to a voxel grid adjacent to at least one voxel grid filled by the molten state and not filled by the molten state;

[0029] The flow mark prediction module is used to determine whether flow marks will be generated when the molten state fills the target voxel grid at each moment according to the filling speed corresponding to each moment.

[0030] A third aspect of the present application provides a computer program product, comprising computer-readable instructions. When the computer-readable instructions are executed on an electronic device, the electronic device implements the flow mark prediction method of the first aspect or any implementation of the first aspect.

[0031] A fourth aspect of the present application provides an electronic device, comprising at least one processor and a memory connected to the processor, wherein:

[0032] The memory is used to store computer programs;

[0033] The processor is used to execute the computer program so that the electronic device can implement the flow mark prediction method of the first aspect or any implementation manner of the first aspect.

[0034] A fifth aspect of the present application provides a computer storage medium, which carries one or more computer programs. When the one or more computer programs are executed by an electronic device, the electronic device can implement the flow mark prediction method of the above-mentioned first aspect or any implementation of the first aspect.

[0035] By means of the above technical solution, the flow mark prediction method provided by the present application can divide the three-dimensional model of the part to be detected into several voxel grids according to the grid size in the configuration file, simulate the process of the molten state filling several voxel grids based on the parameters in the configuration file, and can determine the speed of the molten state filling the target voxel grid at each moment of the simulation. According to the calculated speed, it can be determined whether flow marks will be generated when the molten state fills the target voxel grid at each moment. It can be seen that the present application can simulate the injection molding process based on the three-dimensional model of the part to be detected, and can determine the speed of the molten state filling the target voxel grid at each moment of the simulation during the simulation process, and then predict whether flow marks will be generated at each moment of the simulation process. Since there is no need to use complex numerical simulation methods in commercial software, a lot of computing time and computing resources are saved, and the cost of flow mark prediction is reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and the originals and elements are not necessarily drawn to scale.

[0037] Figure 1 A schematic diagram of a system architecture provided for this application;

[0038] Figure 2 A schematic diagram of an optional hardware structure of a terminal 100 provided in this application;

[0039] Figure 3 A schematic diagram of the structure of a server 200 provided in this application;

[0040] Figure 4 A schematic diagram of a flow mark prediction method provided in this application;

[0041] Figure 5 A schematic diagram of the process of filling a voxel grid at various moments in a molten state in a two-dimensional space provided by the present application;

[0042] Figure 6 A schematic diagram of a flow mark prediction method based on voxel grid provided in this application;

[0043] Figure 7 A schematic diagram of the structure of a flow mark prediction device provided in this application;

[0044] Figure 8 A schematic diagram of the structure of an electronic device provided in this application. DETAILED DESCRIPTION

[0045] The following describes the embodiments of the present application in conjunction with the drawings in the embodiments of the present application. The terms used in the implementation method section of the present application are only used to explain the specific embodiments of the present application, and are not intended to limit the present application.

[0046] The embodiments of the present application are described below in conjunction with the accompanying drawings. Those skilled in the art will appreciate that, with the development of technology and the emergence of new scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0047] The terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and need not be used to describe a specific order or sequential order. It should be understood that the terms used in this way can be interchangeable under appropriate circumstances, which is only to describe the distinction mode adopted by the objects of the same attributes when describing in the embodiments of the present application. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, so that the process, method, system, product or equipment comprising a series of units need not be limited to those units, but may include other units that are not clearly listed or inherent to these processes, methods, products or equipment.

[0048] See also Figure 1 , Figure 1 A schematic diagram of a system architecture is shown. The system may include a terminal 100 and a server 200. The server 200 may include one or more servers ( Figure 1 In the example, a server is included, and the server 200 can provide the method provided in the embodiment of the present application for one or more terminals.

[0049] Among them, an application corresponding to the third-party system can be installed on the terminal 100. The above application and web page can provide an interface. The terminal 100 can receive relevant parameters entered by the user on the interface (such as the three-dimensional model and configuration file of the part to be inspected), and send the above parameters to the server 200. The server 200 can obtain the processing result based on the received parameters and return the processing result to the terminal 100.

[0050] It should be understood that in some optional implementations, the terminal 100 can also complete the action of obtaining the processing result based on the received parameters by itself without the cooperation of the server, and the embodiments of the present application are not limited to this.

[0051] Next describe Figure 1 The product form of the mid-terminal 100;

[0052] The terminal 100 in the embodiment of the present application can be a mobile phone, a tablet computer, a wearable device, a vehicle-mounted device, an augmented reality (AR) / virtual reality (VR) device, a laptop computer, an ultra-mobile personal computer (UMPC), a netbook, a personal digital assistant (PDA), etc., and the embodiment of the present application does not impose any restrictions on this.

[0053] Figure 2 An optional hardware structure diagram of the terminal 100 is shown.

[0054] refer to Figure 2 As shown, the terminal 100 may include a radio frequency unit 110, a memory 120, an input unit 130, a display unit 140, a camera 150 (optional), an audio circuit 160 (optional), a speaker 161 (optional), a microphone 162 (optional), an earphone jack 163 (optional), a processor 170, an external interface 180, a power supply 190 and other components. Those skilled in the art will appreciate that Figure 2 These are merely examples of terminals or multi-function devices and do not constitute limitations on the terminals or multi-function devices, which may include more or fewer components than those shown in the figures, or combinations of certain components, or different components.

[0055] The input unit 130 can be used to receive input digital or character information, and generate key signal input related to the user settings and function control of the portable multifunctional device. Specifically, the input unit 130 may include a touch screen 131 (optional) and / or other input devices 132. The touch screen 131 can collect the user's touch operations on or near it (such as the user's operation on or near the touch screen using any suitable object such as fingers, joints, stylus, etc.), and drive the corresponding connection device according to a pre-set program. The touch screen can detect the user's touch action on the touch screen, convert the touch action into a touch signal and send it to the processor 170, and can receive and execute the command sent by the processor 170; the touch signal at least includes the touch point coordinate information. The touch screen 131 can provide an input interface and an output interface between the terminal 100 and the user. In addition, the touch screen can be implemented using multiple types such as resistive, capacitive, infrared and surface acoustic wave. In addition to the touch screen 131, the input unit 130 can also include other input devices. Specifically, other input devices 132 may include, but are not limited to, one or more of a physical keyboard, function keys (such as a volume control key, a switch key, etc.), a trackball, a mouse, a joystick, and the like.

[0056] Among them, the input device 132 can receive input data and the like.

[0057] The display unit 140 may be used to display information input by a user or provided to a user, various menus of the terminal 100, an interactive interface, file display, and / or playback of any multimedia file.

[0058] The memory 120 can be used to store instructions and data. The memory 120 can mainly include an instruction storage area and a data storage area. The data storage area can store various data, such as multimedia files, texts, etc.; the instruction storage area can store software units such as operating systems, applications, instructions required for at least one function, or their subsets and extensions. It can also include a non-volatile random access memory; provide the processor 170 with hardware, software and data resources including management of computing and processing equipment, and support control software and applications. It is also used for the storage of multimedia files, and the storage of running programs and applications.

[0059] The processor 170 is the control center of the terminal 100. It uses various interfaces and lines to connect various parts of the entire terminal 100. By running or executing instructions stored in the memory 120 and calling data stored in the memory 120, it executes various functions of the terminal 100 and processes data, thereby controlling the terminal device as a whole. Optionally, the processor 170 may include one or more processing units; preferably, the processor 170 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface and application program, and the modem processor mainly processes wireless communication. It is understandable that the above-mentioned modem processor may not be integrated into the processor 170. In some embodiments, the processor and the memory may be implemented on a single chip, and in some embodiments, they may also be implemented separately on separate chips. The processor 170 may also be used to generate corresponding operation control signals, send them to corresponding components of the computing and processing device, read and process data in the software, especially read and process data and programs in the memory 120, so that each functional module therein performs corresponding functions, thereby controlling the corresponding components to act according to the requirements of the instructions.

[0060] Among them, the memory 120 can be used to store software codes related to the flow mark prediction method, the processor 170 can execute the steps of the flow mark prediction method, and can also schedule other units (such as the above-mentioned input unit 130 and display unit 140) to achieve corresponding functions.

[0061] The radio frequency unit 110 (optional) can be used for receiving and sending information or receiving and sending signals during a call, for example, after receiving the downlink information of the base station, it is sent to the processor 170 for processing; in addition, the designed uplink data is sent to the base station. Generally, the RF circuit includes but is not limited to an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier (Low Noise Amplifier, LNA), a duplexer, etc. In addition, the radio frequency unit 110 can also communicate with network devices and other devices through wireless communication. The wireless communication can use any communication standard or protocol, including but not limited to Global System of Mobile communication (Global System of Mobile communication, GSM), General Packet Radio Service (General Packet Radio Service, GPRS), Code Division Multiple Access (Code Division Multiple Access, CDMA), Wideband Code Division Multiple Access (Wideband Code Division Multiple Access, WCDMA), Long Term Evolution (Long Term Evolution, LTE), email, Short Messaging Service (SMS), etc.

[0062] In this embodiment of the present application, the RF unit 110 can send data to the server 200 and receive processing results sent by the server 200.

[0063] It should be understood that the radio frequency unit 110 is optional and can be replaced by other communication interfaces, such as a network port.

[0064] The terminal 100 also includes a power supply 190 (such as a battery) for supplying power to various components. Preferably, the power supply can be logically connected to the processor 170 through a power management system, so that the power management system can manage functions such as charging, discharging, and power consumption.

[0065] The terminal 100 further includes an external interface 180 , which may be a standard Micro USB interface or a multi-pin connector, and may be used to connect the terminal 100 to communicate with other devices, or to connect a charger to charge the terminal 100 .

[0066] Although not shown, the terminal 100 may also include a flashlight, a wireless fidelity (WiFi) module, a Bluetooth module, sensors with different functions, etc., which are not described in detail here. Some or all of the methods described below may be applied in the following embodiments. Figure 2 In the terminal 100 shown.

[0067] Next describe Figure 1 The product form of the server 200;

[0068] Figure 3 A structural diagram of a server 200 is provided, such as Figure 3 As shown, the server 200 includes a bus 201, a processor 202, a communication interface 203, and a memory 204. The processor 202, the memory 204, and the communication interface 203 communicate with each other via the bus 201.

[0069] The bus 201 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0070] The processor 202 may be any one or more of a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor (MP), or a digital signal processor (DSP).

[0071] The memory 204 may include a volatile memory, such as a random access memory (RAM). The memory 204 may also include a non-volatile memory, such as a read-only memory (ROM), a flash memory, a mechanical hard drive (HDD), or a solid state drive (SSD).

[0072] The memory 204 may be used to store software codes related to the flow mark prediction method, and the processor 202 may execute the steps of the flow mark prediction method of the chip, and may also schedule other units to implement corresponding functions.

[0073] It should be understood that the above-mentioned terminal 100 and server 200 can be centralized or distributed devices, and the processors in the above-mentioned terminal 100 and server 200 (such as processor 170 and processor 202) can be hardware circuits (such as application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), general-purpose processors, digital signal processors (DSP), microprocessors or microcontrollers, etc.), or a combination of these hardware circuits. For example, the processor can be a hardware system with an instruction execution function, such as a CPU, DSP, etc., or a hardware system without an instruction execution function, such as an ASIC, FPGA, etc., or a combination of the above-mentioned hardware systems without an instruction execution function and hardware systems with an instruction execution function.

[0074] Flow marks are a common appearance defect of injection molding. They are mainly caused by the local flow speed being too slow, forming water ripple-like uneven marks on the surface, which have an adverse effect on the appearance and performance of the parts. It is necessary to avoid the occurrence of flow mark defects in the part structure design and process design stage to ensure the quality of the parts.

[0075] In the prior art, a commonly used flow mark prediction method is to predict flow marks based on a numerical simulation method in commercial software, wherein the numerical simulation method includes a finite volume method (FVM) or a finite element method (FEM).

[0076] Among them, FVM is a commonly used numerical algorithm in computational fluid dynamics. The finite volume method is based on the integral form of conservation equations rather than differential equations. The integral form of conservation equations describes each control volume defined by the computational grid. The finite volume method focuses on constructing discrete equations from a physical point of view. Each discrete equation is an expression of the conservation of a physical quantity on a finite volume. The derivation process has clear physical concepts, the discrete equation coefficients have certain physical meanings, and can ensure that the discrete equation has conservation characteristics.

[0077] FEM is an effective method for solving mathematical problems. It is based on the variational principle and the weighted residual method. The basic solution idea is to divide the computational domain into a finite number of non-overlapping units. In each unit, some appropriate nodes are selected as interpolation points of the solution function. The variables in the differential equation are rewritten into linear expressions composed of the node values ​​of each variable or its derivative and the selected interpolation function. With the help of the variational principle or the weighted residual method, the differential equation is discretely solved. Different weight functions and interpolation function forms constitute different finite element methods.

[0078] Since the numerical simulation method requires discrete equations, matrix assembly, and algorithms for solving linear equations, the calculations are complex, resulting in the consumption of a large amount of computing resources and time. In addition, commercial software is expensive, making it difficult to meet the needs of rapid iterative design of plastic parts.

[0079] In order to solve the above problems, the present application provides a flow mark prediction method with strong robustness, simple technical route and fast calculation speed. Figure 4 , shows a schematic flow chart of a flow mark prediction method provided by an embodiment of the present application, such as Figure 4 As shown, the method may include:

[0080] Step S401: Obtain the three-dimensional model and configuration file of the part to be inspected.

[0081] Here, the part to be inspected refers to the part for which flow mark prediction is to be performed.

[0082] Optionally, the three-dimensional model of the part to be inspected can be obtained based on an STL model file, which is a file that describes the three-dimensional geometric information of the part to be inspected. The STL (stereolithography) file format is an interface protocol developed by 3D SYSTEMS in 1988. It is a three-dimensional graphic file format that serves rapid prototyping technology. The STL file consists of the definition of multiple triangular facets, and the definition of each triangular facet includes the three-dimensional coordinates of each fixed point of the triangle and the normal vector of the triangular facet. In an embodiment of the present application, in order to reduce the space of the model file, the size of the triangular facets in the STL file is very uneven.

[0083] The embodiment of the present application can obtain an STL model file of the part to be inspected, and then generate a three-dimensional model of the part to be inspected based on the STL model file.

[0084] It should be noted that after the three-dimensional model is generated in the embodiment of the present application, a preliminary check of the three-dimensional model is required to check whether the three-dimensional model is complete. If it is complete, it can be processed according to the subsequent steps. If it is incomplete, it is necessary to adjust the parameters of the model file and regenerate the three-dimensional model.

[0085] The above configuration file includes several parameters, which can be used as input parameters in subsequent simulation and calculation.

[0086] Step S402: Divide the three-dimensional model into a number of voxel grids according to the grid size in the configuration file.

[0087] Considering that in the real plastic injection molding process, it is difficult to obtain relevant data of the molten state filling the mold at each moment, while the relevant data in the simulation process is relatively easy to obtain, the embodiment of the present application can use the three-dimensional model of the part to be tested as the simulation object to simulate the process of the molten state filling the three-dimensional model. In order to facilitate the prediction of the flow mark generation in the process of the molten state filling the three-dimensional model, the embodiment of the present application can configure the grid size parameter in the configuration file, so the embodiment can divide the three-dimensional model into a number of voxel grids according to the grid size in the configuration file.

[0088] Optionally, the 3D model can be divided into several voxel grids by threading method, and the size of the voxel grid is the grid size set in the configuration file. Here, threading method refers to generating a cluster of rays, finding the intersection points of the rays and the triangle patches in the 3D model, and generating a cubic grid between the intersection points, which is the voxel grid.

[0089] Here, voxel is the abbreviation of volume pixel, which is the smallest unit of digital data in three-dimensional space segmentation. The volume containing voxels can be expressed by stereo rendering or extracting polygonal isosurfaces with given threshold contours.

[0090] Step S403: simulate the process of the molten state filling a plurality of voxel grids based on the parameters in the configuration file, and determine the speed at which the molten state fills the target voxel grids at each moment of the simulation as the filling speed corresponding to each moment.

[0091] The target voxel grid refers to a voxel grid that is adjacent to at least one voxel grid that has been filled with the molten state and is not filled with the molten state.

[0092] The above-mentioned process of filling a plurality of voxel grids with a molten state specifically refers to a process of injecting the molten state into a plurality of voxel grids by pushing the molten state through a simulated screw.

[0093] It should be noted that the process of filling a number of voxel grids with a molten state needs to follow the liquid flow characteristics, that is, the molten state will flow to the adjacent unfilled voxel grids around the filled voxel grids, so that the unfilled voxel grids become filled voxel grids.

[0094] In an embodiment of the present application, the simulation process of the molten state filling several voxel grids can be implemented based on the parameters in the configuration file. During the simulation process, the speed of the molten state filling the target voxel grid at each moment can also be calculated based on the parameters in the configuration file.

[0095] For ease of understanding, the process of filling the voxel grid with the molten state at each moment in the two-dimensional space is introduced by taking the two-dimensional space as an example. It should be understood that the real filling process is based on the three-dimensional space, and the process of filling the target voxel grid with the molten state in the three-dimensional space can be analogous to the two-dimensional space.

[0096] See also Figure 5 As shown in FIG. 1 , it is a schematic diagram of the process of the molten state filling the voxel grid at each moment in a two-dimensional space. At the first moment (i.e., the initial moment), the molten state has been filled in one voxel grid (the voxel grid filled with the molten state is represented by a square with a black diagonal line). Then, based on the liquid flow characteristics of the molten state, at the first moment, the molten state needs to fill the 4 adjacent unfilled voxel grids around the filled one voxel grid (the voxel grid not filled with the molten state is represented by a white square), at the second moment, the molten state needs to fill the 8 adjacent unfilled voxel grids around the filled 5 voxel grids, at the third moment, the molten state needs to fill the 12 adjacent unfilled voxel grids around the filled 13 voxel grids, and so on, until all voxel grids are filled with the molten state.

[0097] In the embodiment of the present application, the target voxel grid refers to a voxel grid adjacent to at least one voxel grid filled with the molten state and not filled with the molten state, that is, the molten state has filled n (n ≥ 1 and n is an integer) voxel grids, then the target voxel grid refers to a voxel grid adjacent to at least one voxel grid in the n voxel grids and not filled with the molten state. It should be understood that since the molten state is in a flowing state before all voxel grids are filled, the target voxel grids are different at different times before all voxel grids are filled.

[0098] by Figure 5 For example, the target voxel grid at the first moment is the 4 unfilled voxel grids at the first moment; the target voxel grid at the first moment is the 8 unfilled voxel grids at the second moment; and the target voxel grid at the third moment refers to the 12 unfilled voxel grids at the third moment.

[0099] In an optional embodiment, the embodiment of the present application can record the number of voxel grids filled by the molten state at each moment into an array S to facilitate subsequent calculations.

[0100] Since flow marks are caused by the slow local flow speed of the molten state, in order to determine whether flow marks will be generated, this embodiment can determine the speed of the molten state filling the target voxel grid at each moment during the simulation process.

[0101] For the convenience of subsequent description, the speed at which the molten state fills the target voxel grid at each moment is defined as the filling speed corresponding to each moment.

[0102] Step S404: Determine whether flow marks will be generated when the molten state fills the target voxel grid at each moment according to the filling speed corresponding to each moment.

[0103] The flow mark prediction method provided by the present application can divide the three-dimensional model of the part to be detected into several voxel grids according to the grid size in the configuration file, simulate the process of the molten state filling several voxel grids based on the parameters in the configuration file, and can determine the speed of the molten state filling the target voxel grid at each moment of the simulation. According to the calculated speed, it can be determined whether flow marks will be generated when the molten state fills the target voxel grid at each moment. It can be seen that the present application can simulate the injection molding process based on the three-dimensional model of the part to be detected, and in the simulation process, it can determine the speed of the molten state filling the target voxel grid at each moment of the simulation, and then predict whether flow marks will be generated at each moment of the simulation process. Since there is no need to use complex numerical simulation methods in commercial software, a lot of computing time and computing resources are saved, and the cost of flow mark prediction is reduced.

[0104] In some embodiments of the present application, the process of the above-mentioned step S403 "simulating the process of filling a number of voxel grids with a molten state based on the parameters in the configuration file, and determining the speed at which the molten state fills the target voxel grids at each moment of the simulation as the filling speed corresponding to each moment" is introduced.

[0105] Optionally, the process of "simulating the process of filling several voxel grids with a molten state based on the parameters in the configuration file" may include: determining the voxel grid where the injection gate is located according to the injection gate position information in the configuration file, taking the voxel grid where the injection gate is located as the first voxel grid filled with a molten state, and simulating the process of filling the target voxel grid with a molten state.

[0106] The injection gate position information in the above configuration file is information describing the position of the injection gate. Optionally, the injection gate position information may be coordinate data of the injection gate, such as three-dimensional coordinate data.

[0107] Of course, the injection gate location information may also be other information, such as the location of the injection gate described in natural language, etc., and this application does not limit this.

[0108] The above-mentioned injection gate refers to the position for allowing the molten state to enter the mold in the real plastic injection molding process, that is, the molten state is pushed into the mold by the screw through the injection gate. For the simulation process of the embodiment of the present application, the injection gate needs to be corresponded to the voxel grid, and for this purpose, it is necessary to determine the voxel grid where the injection gate is located. Optionally, the voxel grid where the injection gate is located refers to the voxel grid closest to the position corresponding to the injection gate on the three-dimensional model.

[0109] In the embodiment of the present application, the voxel grid where the injection gate is located can be used as the first voxel grid filled in the molten state. For example, the voxel grid where the injection gate is located refers to Figure 5 The filled voxel grid at the first moment. After the filled first voxel grid is determined, the process of filling the target voxel grid in the molten state can be simulated based on the filled first voxel grid and the parameters in the configuration file.

[0110] During the simulation process, the embodiment of the present application can also determine the speed at which the molten state fills the target voxel grid at each moment of the simulation.

[0111] Optionally, a speed detection device may be provided during the simulation process, and the speed detection device is used to detect the speed at which the molten state fills the target voxel grid at each moment, so as to obtain the filling speed corresponding to each moment.

[0112] Since the additional speed detection device will increase the cost, in order to reduce the cost, the inventor of this case conducted in-depth research and thought that the molten state flows under the push of the screw, so the speed of the molten state filling the target voxel grid at each moment should be related to the speed of the screw pushing the molten state at each moment. Based on this, the screw speed curve can be written in the configuration file, and the screw speed curve reflects the speed of the screw pushing the molten state at each moment. Therefore, the embodiment of the present application can determine the speed of the screw pushing the molten state at each moment according to the screw speed curve in the configuration file, and then obtain the filling speed corresponding to each moment according to the speed of the screw pushing the molten state at each moment.

[0113] In one possible implementation, the process of "obtaining the filling speed corresponding to each moment according to the speed at which the screw pushes the molten state at each moment" may include: determining the total number of target voxel grids filled by the molten state at each moment; calculating the surface area of ​​the target voxel grid filled by the molten state at each moment according to the total number and the grid size; calculating the filling speed corresponding to each moment according to the surface area and the speed at which the screw pushes the molten state at each moment.

[0114] For ease of understanding, we will still use two-dimensional space as an example to explain. Figure 5As shown, the total number of target voxel grids filled by the molten state at the first moment is 4, the total number of target voxel grids filled by the molten state at the second moment is 8, the total number of target voxel grids filled by the molten state at the third moment is 12, and so on.

[0115] It should be noted that the total number obtained in the above two-dimensional space, such as 4, 8, and 12, is only used to explain the step of "determining the total number of molten state filling the target voxel grid at each moment". The total number obtained is not the total number determined in the real three-dimensional space and cannot be used as the actual calculation process of the filling speed corresponding to each moment.

[0116] Optionally, the following formula (1) can be used to calculate the surface area of ​​the target voxel grid filled by the molten state at each moment, and the following formula (2) can be used to calculate the filling speed corresponding to each moment.

[0117] Formula (1)

[0118] in, represents the surface area of ​​the target voxel grid filled by the molten state at each moment, represents the total amount of molten state filling the target voxel grid at each moment, Indicates the grid size.

[0119] Formula (2)

[0120] in, It indicates the speed at which the screw pushes the molten state at each moment. Indicates the screw diameter, Indicates the filling speed corresponding to each moment.

[0121] Optionally, the present application can obtain a corresponding filling speed at each moment, and the filling speeds corresponding to each moment can be recorded in an array V, then the filling speeds in array V should correspond one to one to the total number in the previous array S.

[0122] In other embodiments of the present application, the process of step S404 "determining whether flow marks will be generated when the molten state fills the target voxel grid at each moment according to the filling speed corresponding to each moment" is introduced.

[0123] In one possible implementation, considering that flow marks are caused by too slow local flow speed of the molten state, that is, flow marks are easily generated when the speed of the molten state is uneven when filling the target voxel grid, then for each moment, the filling speed corresponding to the moment can be compared with the filling speed corresponding to one or more moments before the moment, and based on the comparison result, it is determined whether flow marks will be generated when the molten state fills the target voxel grid at the moment.

[0124] In another possible implementation, the flow mark critical speed can be obtained, which refers to the critical speed at which flow marks are generated, and then based on the relationship between the filling speed corresponding to each moment and the critical speed, it is determined whether flow marks will be generated when the molten state fills the target voxel grid at each moment.

[0125] Specifically, for each moment, determine whether the filling speed corresponding to the moment is greater than the flow mark critical speed. If so, it is determined that the molten state will not produce flow marks when filling the target voxel grid at this moment. If not, it is determined that the molten state will produce flow marks when filling the target voxel grid at this moment.

[0126] Optionally, the flow mark critical velocity may be obtained based on the material of the part to be tested and the mold temperature.

[0127] Optionally, the material and mold temperature of the part to be tested may be written into a configuration file. After the configuration file is obtained in step S401, the embodiment of the present application may obtain the critical flow mark speed through experiments based on the material and mold temperature of the part to be tested in the configuration file.

[0128] In summary, since the voxel grid is the smallest grid that can be divided into a three-dimensional model, and in the embodiment of the present application, the molten state can only fill one target voxel grid at each moment, the embodiment of the present application performs flow mark prediction by dividing the voxel grid, and can predict all possible flow marks that may be generated in the process of the molten state filling several voxel grids, and the prediction accuracy is relatively high.

[0129] In order to enable those skilled in the art to better understand the present application, a complete example of flow mark prediction is shown below.

[0130] See also Figure 6 As shown in FIG. 1 , a flow mark prediction method based on voxel grid is provided in an embodiment of the present application. Figure 6 As shown, the method includes:

[0131] Step S601: Obtain the three-dimensional model and configuration file of the part to be inspected.

[0132] Step S602: Divide the three-dimensional model into a number of voxel grids according to the grid size in the configuration file.

[0133] Step S603 , determining the voxel grid where the injection gate is located according to the injection gate position information in the configuration file, and taking the voxel grid where the injection gate is located as the first voxel grid filled in the molten state.

[0134] Step S604 , simulating the process of the molten state filling the target voxel grid, determining the total number of the target voxel grid filled by the molten state at each moment of the simulation, and recording it in the array S.

[0135] In the simulation process, after recording the total number of target voxel grids filled by the molten state at a certain moment, it is determined whether the molten state has filled all voxel grids. If so, step S605 is executed. If not, the total number of target voxel grids filled by the molten state at the next moment is continuously recorded.

[0136] Step S605, calculate the filling speed corresponding to each moment according to the total number of target voxel grids filled with the molten state at each moment of the simulation and the grid size, screw diameter and screw speed curve in the configuration file, and record them in the array V.

[0137] Step S606: Obtain the critical flow mark speed according to the material of the part to be inspected and the mold temperature in the configuration file.

[0138] Step S607: Compare each filling speed in the array V with the flow mark critical speed, and determine whether flow marks will be generated when the molten state fills the target voxel grid at each moment according to the comparison result.

[0139] Step S608: For each moment of the simulation, if flow marks will be generated when the molten state fills the target voxel grid at that moment, the position of the target voxel grid at that moment is determined.

[0140] That is, after obtaining the judgment result of whether flow marks will be generated, the embodiment of the present application can further correspond the judgment result to the voxel grid to obtain the flow mark generation position in the three-dimensional model of the part to be inspected.

[0141] Since the three-dimensional model can well reflect the shape of the part to be inspected, the embodiment of the present application performs a simulation of the injection molding process based on the three-dimensional model of the part to be inspected and performs flow mark prediction based on the simulation process, which can well predict the flow mark distribution.

[0142] Further, after the flow mark generation location is determined according to step S608 or after it is determined that the flow mark will be generated according to step S607, the parameters in the configuration file and / or the three-dimensional model and / or the part mold may be adjusted to eliminate the flow mark.

[0143] In summary, the embodiments of the present application propose an algorithm that can quickly predict flow mark defects in the injection molding process. It can predict the distribution of flow mark defects based on the specific part shape (i.e., three-dimensional model) and the injection molding process. The main advantages are as follows: (1) It is simple and efficient. Compared with the traditional method that takes dozens of hours to solve a set of equations, this method can complete the calculation within 10 seconds on a single core, which is very fast; (2) It is robust. For any complex parts, there will be no calculation divergence or non-physical situations; (3) The present application can better reproduce the injection molding filling process, so that the flow mark position can be accurately predicted.

[0144] A flow mark prediction method provided by an embodiment of the present application is introduced above, and a device for executing the flow mark prediction method is introduced below.

[0145] See also Figure 7 , Figure 7 A schematic diagram of the structure of a flow mark prediction device provided in an embodiment of the present application is shown in FIG. Figure 7 As shown, the device may include:

[0146] The information acquisition module 701 is used to obtain the three-dimensional model and configuration file of the part to be inspected;

[0147] A grid division module 702, for dividing the three-dimensional model into a plurality of voxel grids according to the grid size in the configuration file;

[0148] A simulation calculation module 703 is used to simulate the process of the molten state filling a plurality of voxel grids based on the parameters in the configuration file, and determine the speed at which the molten state fills a target voxel grid at each moment of the simulation as the filling speed corresponding to each moment, wherein the target voxel grid refers to a voxel grid adjacent to at least one voxel grid filled by the molten state and not filled by the molten state;

[0149] The flow mark prediction module 704 is used to determine whether flow marks will be generated when the molten state fills the target voxel grid at each moment according to the filling speed corresponding to each moment.

[0150] In a possible implementation, when simulating the process of filling a plurality of voxel grids with a molten state based on the parameters in the configuration file, the simulation calculation module may be specifically used to:

[0151] Determine the voxel grid where the injection gate is located according to the injection gate position information in the configuration file;

[0152] The voxel grid where the injection gate is located is taken as the first voxel grid filled in the molten state, and the process of filling the target voxel grid in the molten state is simulated.

[0153] In a possible implementation, the simulation calculation module may be used to determine the speed at which the molten state fills the target voxel grid at each moment of the simulation as the filling speed corresponding to each moment:

[0154] Determine the speed at which the screw pushes the molten state at each moment according to the screw speed curve in the configuration file;

[0155] According to the speed at which the screw pushes the molten state at each moment, the filling speed corresponding to each moment is obtained.

[0156] In a possible implementation, when the above simulation calculation module obtains the filling speed corresponding to each moment according to the speed at which the screw pushes the molten state at each moment, it can be specifically used to:

[0157] Determine the total amount of the target voxel grid filled by the molten state at each time instant;

[0158] Based on the total number and the grid size, the surface area of ​​the target voxel grid filled by the molten state at each moment is calculated;

[0159] The filling speed at each moment is calculated based on the surface area and the speed at which the screw pushes the molten state at each moment.

[0160] In a possible implementation, when the flow mark prediction module determines whether flow marks will be generated when the molten state fills the target voxel grid at each moment according to the filling speed corresponding to each moment, it can be specifically used to:

[0161] Obtaining a critical flow mark speed, wherein the critical flow mark speed is obtained based on the material of the part to be inspected and the mold temperature;

[0162] For each moment, determine whether the filling speed corresponding to the moment is greater than the flow mark critical speed. If so, it is determined that the molten state will not produce flow marks when filling the target voxel grid at this moment. If not, it is determined that the molten state will produce flow marks when filling the target voxel grid at this moment.

[0163] In a possible implementation, the flow mark prediction device provided in the embodiment of the present application may further include: a flow mark position determination module.

[0164] The flow mark position determination module is used to determine the position of the target voxel grid at each moment if flow marks will be generated when the molten state fills the target voxel grid at that moment.

[0165] The present application also provides an electronic device in an embodiment. Figure 8 As shown, it shows a schematic diagram of the structure of an electronic device suitable for implementing the embodiment of the present application. The electronic device in the embodiment of the present application may include but is not limited to fixed terminals such as mobile phones, laptops, PDAs (personal digital assistants), PADs (tablet computers), desktop computers, etc. Figure 8 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0166] like Figure 8As shown, the electronic device may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 801, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 802 or a program loaded from a storage device 808 to a random access memory (RAM) 803. When the electronic device is powered on, various programs and data required for the operation of the electronic device are also stored in the RAM 803. The processing device 801, the ROM 802, and the RAM 803 are connected to each other via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0167] Typically, the following devices may be connected to the I / O interface 805: input devices 806 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; output devices 807 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 808 including, for example, a memory card, a hard disk, etc.; and communication devices 809. The communication device 809 may allow the electronic device to communicate with other devices wirelessly or by wire to exchange data. Although Figure 8 An electronic device having various devices is shown, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead.

[0168] An embodiment of the present application also provides a computer program product, including computer-readable instructions. When the computer-readable instructions are executed on an electronic device, the electronic device implements any flow mark prediction method provided in the embodiment of the present application.

[0169] A computer-readable storage medium is also provided in an embodiment of the present application. The storage medium carries one or more computer programs. When the one or more computer programs are executed by an electronic device, the electronic device can implement any flow mark prediction method provided in the embodiment of the present application.

[0170] It should also be noted that the device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the drawings of the device embodiments provided by the present application, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines.

[0171] Through the description of the above implementation mode, the technicians in the field can clearly understand that the present application can be implemented by means of software plus necessary general hardware, and of course, it can also be implemented by special hardware including special integrated circuits, special CPUs, special memories, special components, etc. In general, all functions completed by computer programs can be easily implemented by corresponding hardware, and the specific hardware structure used to implement the same function can also be various, such as analog circuits, digital circuits or special circuits. However, for the present application, software program implementation is a better implementation mode in more cases. Based on such an understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a readable storage medium, such as a computer floppy disk, a U disk, a mobile hard disk, a ROM, a RAM, a disk or an optical disk, etc., including a number of instructions to enable a computer device (which can be a personal computer, a training device, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0172] In the above embodiments, all or part of the embodiments may be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or part of the embodiments may be implemented in the form of a computer program product.

[0173] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from a website site, a computer, a training device, or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, training device, or data center. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a training device, a data center, etc. that includes one or more available media integrations. The available medium may be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)), etc.

Claims

1. A flow mark prediction method, It is characterized in that include: Obtain the 3D model and configuration file of the part to be inspected; Dividing the three-dimensional model into a plurality of voxel grids according to a grid size in the configuration file; Simulating the process of the molten state filling the plurality of voxel grids based on the parameters in the configuration file, determining the speed of the molten state filling a target voxel grid at each moment of the simulation as the filling speed corresponding to each moment, wherein the target voxel grid refers to a voxel grid adjacent to at least one voxel grid filled by the molten state and not filled by the molten state; According to the filling speed corresponding to each moment, it is determined whether flow marks will be generated when the molten state fills the target voxel grid at each moment.

2. The flow mark prediction method according to claim 1, It is characterized in that The simulating the process of filling the plurality of voxel grids with a molten state based on the parameters in the configuration file comprises: Determine the voxel grid where the injection gate is located according to the injection gate position information in the configuration file; The voxel grid where the injection gate is located is taken as the first voxel grid filled with the molten state, and a process of the molten state filling the target voxel grid is simulated.

3. The flow mark prediction method according to claim 1, It is characterized in that Determining the speed at which the molten state fills the target voxel grid at each moment of the simulation as the filling speed corresponding to each moment includes: determining the speed at which the screw pushes the molten state at each moment according to the screw speed curve in the configuration file; According to the speed at which the screw pushes the molten state at each moment, the filling speed corresponding to each moment is obtained.

4. The flow mark prediction method according to claim 3, It is characterized in that The method of obtaining the filling speed corresponding to each moment according to the speed at which the screw pushes the molten state at each moment comprises: Determining the total amount of the target voxel grid filled by the molten state at each time instant; Calculating the surface area of ​​the target voxel grid filled by the molten state at each moment according to the total number and the grid size; The filling speed corresponding to each moment is calculated based on the surface area and the speed at which the screw pushes the molten state at each moment.

5. The flow mark prediction method according to any one of claims 1 to 4, It is characterized in that The determining, according to the filling speed corresponding to each moment, whether flow marks will be generated when the molten state fills the target voxel grid at each moment, comprises: Obtaining a critical flow mark speed, wherein the critical flow mark speed is obtained based on the material of the part to be inspected and the mold temperature; For each moment, determine whether the filling speed corresponding to the moment is greater than the flow mark critical speed. If so, determine that the molten state will not produce flow marks when filling the target voxel grid at this moment. If not, determine that the molten state will produce flow marks when filling the target voxel grid at this moment.

6. The flow mark prediction method according to claim 5, It is characterized in that Also includes: For each of the moments, if flow marks will be generated when the molten state fills the target voxel grid at the moment, the position of the target voxel grid at the moment is determined.

7. A flow mark prediction device, It is characterized in that include: An information acquisition module is used to obtain a three-dimensional model and configuration file of the part to be inspected; A grid division module, used for dividing the three-dimensional model into a plurality of voxel grids according to the grid size in the configuration file; a simulation calculation module, configured to simulate the process of the molten state filling the plurality of voxel grids based on the parameters in the configuration file, and determine the speed at which the molten state fills a target voxel grid at each moment of the simulation as the filling speed corresponding to each moment, wherein the target voxel grid refers to a voxel grid adjacent to at least one voxel grid filled by the molten state and not filled by the molten state; The flow mark prediction module is used to determine whether flow marks will be generated when the molten state fills the target voxel grid at each moment according to the filling speed corresponding to each moment.

8. A computer program product, It is characterized in that The method comprises computer-readable instructions, and when the computer-readable instructions are executed on an electronic device, the electronic device implements the flow mark prediction method according to any one of claims 1 to 6.

9. An electronic device, It is characterized in that The method comprises at least one processor and a memory connected to the processor, wherein: The memory is used to store computer programs; The processor is used to execute the computer program so that the electronic device can implement the flow mark prediction method according to any one of claims 1 to 6.

10. A computer storage medium, It is characterized in that The storage medium carries one or more computer programs, and when the one or more computer programs are executed by an electronic device, the electronic device can implement the flow mark prediction method as described in any one of claims 1 to 6.

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