CN117574700A - Plastic mold CAE (computer aided engineering) die flow analysis method, device, equipment and storage medium - Google Patents

Plastic mold CAE (computer aided engineering) die flow analysis method, device, equipment and storage medium Download PDF

Info

Publication number
CN117574700A
CN117574700A CN202311369623.1A CN202311369623A CN117574700A CN 117574700 A CN117574700 A CN 117574700A CN 202311369623 A CN202311369623 A CN 202311369623A CN 117574700 A CN117574700 A CN 117574700A
Authority
CN
China
Prior art keywords
analysis
file
mold
cae
gridding
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202311369623.1A
Other languages
Chinese (zh)
Inventor
杜正勇
杜黎明
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shenzhen Haijie Precision Mould & Plastic Co ltd
Original Assignee
Shenzhen Haijie Precision Mould & Plastic Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Shenzhen Haijie Precision Mould & Plastic Co ltd filed Critical Shenzhen Haijie Precision Mould & Plastic Co ltd
Priority to CN202311369623.1A priority Critical patent/CN117574700A/en
Publication of CN117574700A publication Critical patent/CN117574700A/en
Pending legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G06F30/23—Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G06F30/27—Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/0464—Convolutional networks [CNN, ConvNet]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2113/00—Details relating to the application field
    • G06F2113/08—Fluids
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2113/00—Details relating to the application field
    • G06F2113/22—Moulding
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30—Computing systems specially adapted for manufacturing

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Evolutionary Computation (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Hardware Design (AREA)
  • Geometry (AREA)
  • Artificial Intelligence (AREA)
  • Software Systems (AREA)
  • Medical Informatics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Biomedical Technology (AREA)
  • Biophysics (AREA)
  • Computational Linguistics (AREA)
  • Data Mining & Analysis (AREA)
  • General Health & Medical Sciences (AREA)
  • Molecular Biology (AREA)
  • Computing Systems (AREA)
  • Mathematical Physics (AREA)
  • Injection Moulding Of Plastics Or The Like (AREA)

Abstract

The invention relates to the technical field of plastic molds, and discloses a CAE (computer aided engineering) die flow analysis method, device and equipment for a plastic mold and a storage medium, wherein the method comprises the following steps: acquiring a mold file to be analyzed, and gridding the mold file to obtain a gridding file; carrying out structural feature recognition on the meshed file to obtain feature grid points; according to a preset analysis parameter generation model and the characteristic grid points, matching is carried out, and analysis parameters are obtained, wherein the analysis parameters comprise product types, sprue positions, sprue quantity and runner structures; acquiring injection molding materials and molding conditions input by a user; and analyzing and calculating the die file according to the analysis parameters, the injection molding materials and the molding conditions, and generating an analysis result. The method can realize test analysis by generating various parameters according to the preset model, reduce the dependence on manpower when selecting the parameters, and improve the accuracy of analysis results.

Description

Plastic mold CAE (computer aided engineering) die flow analysis method, device, equipment and storage medium
Technical Field
The invention relates to the technical field of plastic molds, in particular to a CAE (computer aided engineering) die flow analysis method, device and equipment for a plastic mold and a storage medium.
Background
At present, when CAE software is used for carrying out performance analysis and simulation on engineering or products, the following three processes are generally carried out: pretreatment: modeling a solid and parameterizing; finite element analysis: the system comprises a finite element library, a material library and related algorithms, a constraint processing algorithm, a finite element system assembly module and a static force, dynamic force, vibration and linear and nonlinear solution library; post-treatment: and processing and checking the finite element analysis result required by the user according to engineering or product models and design requirements, and providing the finite element analysis result to the user in a graphical mode to assist the user in judging the rationality of the calculation result and the design scheme.
During finite element analysis, the selection of parameters has a large influence on analysis results. The existing method needs to select various parameters manually according to experience values for experimental analysis, and has large dependence on manpower. In addition, if the experience of the operator is insufficient, the parameters selected by the operator cannot fully correspond to the die to be analyzed, which may result in inaccurate analysis results.
Disclosure of Invention
The invention provides a CAE model flow analysis method, device and equipment for a plastic die and a storage medium, so as to realize test analysis by generating various parameters according to a preset model, reduce the dependence on manpower when selecting the parameters, and improve the accuracy of analysis results.
In order to solve the above technical problems, the present invention provides a CAE flow analysis method for a plastic mold, including:
acquiring a mold file to be analyzed, and gridding the mold file to obtain a gridding file;
carrying out structural feature recognition on the meshed file to obtain feature grid points;
according to a preset analysis parameter generation model and the characteristic grid points, matching is carried out, and analysis parameters are obtained, wherein the analysis parameters comprise product types, sprue positions, sprue quantity and runner structures;
acquiring injection molding materials and molding conditions input by a user;
and analyzing and calculating the die file according to the analysis parameters, the injection molding materials and the molding conditions, and generating an analysis result.
Preferably, the performing structural feature recognition on the gridding file to obtain feature grid points includes:
searching the gridding file according to a preset range value, and judging whether a target characteristic structure exists in the range value, wherein the target characteristic structure comprises one or more of a pouring gate, a die cavity, a suture line and a thickness change structure;
if yes, determining the grid where the target feature structure is located as a feature grid point; if not, replacing the next grid for searching.
Preferably, the method further comprises:
when the target feature structure is judged to comprise a mold cavity, calculating mold supporting force according to the number of the mold cavities;
judging whether the mold supporting force is smaller than the pre-acquired mold locking force, and if not, generating an analysis result comprising unqualified mold locking force.
Preferably, the method further comprises:
when the target feature structure is judged to comprise a suture line and a thickness change structure, obtaining the time for filling the mould by the flow wave in the mould flow analysis;
judging whether the time for filling the die is larger than a preset time preset value, and if so, generating an analysis result comprising hysteresis.
Preferably, the method further comprises:
and when the analysis result comprises that the mold locking force is unqualified or hysteresis exists, generating parameter adjustment suggestions for the mold file.
Preferably, the generating parameter adjustment suggestions for the mold file includes: one or more of changing the design of the plastic part, changing the design of the mold, and adjusting the molding conditions.
Preferably, the process for constructing the analysis parameter generating model includes:
acquiring a history mould file, history gridding file data, history characteristic grid points and history analysis parameters;
and carrying out convolutional neural network training on the initial convolutional neural network through the history mould file, the history gridding file data, the history characteristic grid points and the history analysis parameters to obtain an analysis parameter generation model after training is completed.
In a second aspect, the present invention provides a CAE die flow analysis apparatus for a plastic die, comprising:
the gridding module is used for acquiring a die file to be analyzed, gridding the die file and obtaining a gridding file;
the characteristic identification module is used for carrying out structural characteristic identification on the meshed file to obtain characteristic grid points;
the parameter generation module is used for generating a model according to a preset analysis parameter and matching the characteristic grid points to obtain the analysis parameter, wherein the analysis parameter comprises a product category, a gate position, a gate quantity and a runner structure;
the condition input module is used for acquiring injection molding materials and molding conditions input by a user;
and the analysis and calculation module is used for carrying out analysis and calculation on the die file according to the analysis parameters, the injection molding materials and the molding conditions and generating an analysis result.
In a third aspect, the present invention also provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, where the processor implements the CAE flow analysis method of the plastic mold according to any one of the above when executing the computer program.
In a fourth aspect, the present invention further provides a computer readable storage medium, where the computer readable storage medium includes a stored computer program, where when the computer program runs, the device where the computer readable storage medium is located is controlled to execute the CAE flow analysis method of the plastic mold according to any one of the above.
Compared with the prior art, the invention has the following beneficial effects:
compared with the prior art, the CAE model flow analysis method for the plastic mould disclosed by the embodiment of the invention obtains the characteristic grid points by carrying out structural characteristic identification on the gridding file. And then, generating a model according to the preset analysis parameters and matching the model with the characteristic grid points to obtain the analysis parameters. And finally, analyzing and calculating the die file according to the analysis parameters, the injection molding materials and the molding conditions, and generating an analysis result. Therefore, the analysis parameters are obtained by matching the analysis parameter generation model with the characteristic grid points, so that the manual setting of the analysis parameters is avoided, the whole analysis process is independent of experience of operators, the selection efficiency of the analysis parameters can be improved, errors caused by manual selection are avoided, and the accuracy of analysis results can be improved.
Drawings
FIG. 1 is a schematic flow chart of a CAE model flow analysis method for a plastic mold according to a first embodiment of the present invention;
fig. 2 is a schematic structural diagram of a CAE flow analysis device for a plastic mold according to a second embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a first embodiment of the present invention provides a CAE flow analysis method for a plastic mold, comprising the steps of:
s11, acquiring a die file to be analyzed, and gridding the die file to obtain a gridding file;
s12, carrying out structural feature recognition on the meshed file to obtain feature grid points;
s13, generating a model according to preset analysis parameters and matching the model with the characteristic grid points to obtain analysis parameters, wherein the analysis parameters comprise product types, gate positions, gate quantity and flow channel structures;
s14, acquiring injection molding materials and molding conditions input by a user;
s15, analyzing and calculating the die file according to the analysis parameters, the injection molding materials and the molding conditions, and generating an analysis result.
In step S11, a mold file to be analyzed is obtained, and the mold file is gridded to obtain a gridded file. This step belongs to the preprocessing process, and some processing needs to be performed on the model before CAE analysis, including model establishment, grid division and the like. The model is established as the basis of CAE analysis, and the actual structure needs to be accurately reflected. Meshing is the discretization of a model into many small units to facilitate simulation and analysis on a computer.
In step S12, performing structural feature recognition on the meshed file to obtain feature grid points, including:
searching the gridding file according to a preset range value, and judging whether a target characteristic structure exists in the range value, wherein the target characteristic structure comprises one or more of a pouring gate, a die cavity, a suture line and a thickness change structure;
if yes, determining the grid where the target feature structure is located as a feature grid point; if not, replacing the next grid for searching.
In this embodiment, before the analysis parameters are automatically generated using the analysis parameter generation model, some feature grid points need to be identified, and the analysis parameters of this time are matched by the feature grid points. When feature grid points are identified, looping can be conducted according to a preset range value, traversing is conducted in the range in the looping, and therefore feature grid points are identified according to the target feature structure until all grid traversal is completed, and feature grid points are obtained through screening.
In step S13, matching is performed between a model and the feature grid points according to a preset analysis parameter, so as to obtain an analysis parameter, where the analysis parameter includes a product category, a gate position, a gate number, and a runner structure.
In this embodiment, the process for constructing the analysis parameter generating model includes:
acquiring a history mould file, history gridding file data, history characteristic grid points and history analysis parameters;
and carrying out convolutional neural network training on the initial convolutional neural network through the history mould file, the history gridding file data, the history characteristic grid points and the history analysis parameters to obtain an analysis parameter generation model after training is completed.
In step S14, the injection molding material and the molding conditions input by the user are acquired. The injection molding materials are needed raw materials for molding the mold to be analyzed, and the raw materials are selected by a user and then input into analysis software. The molding conditions include material temperature, maximum injection speed, metering amount, residual amount, total amount of material, injection time, injection pressure upper limit value, injection pressure actual value, dwell pressure, dwell time, cooling time, cycle time, short shot, molding condition table, and the like.
In step S15, the mold file is analyzed and calculated according to the analysis parameters, the injection molding material and the molding conditions, and an analysis result is generated.
In this embodiment, a finite element analysis model may be constructed, and a solution result may be obtained by an iterative solution method. Finite element is one of the most widely applied CAE techniques, and in the finite element solving process, the computing efficiency can be improved through the effective combination of finite element and machine learning.
In order to facilitate an understanding of the invention, some preferred embodiments of the invention will be described further below.
In one implementation, the method further comprises:
when the target feature structure is judged to comprise a mold cavity, calculating mold supporting force according to the number of the mold cavities;
judging whether the mold supporting force is smaller than the pre-acquired mold locking force, and if not, generating an analysis result comprising unqualified mold locking force.
In this embodiment, the die flow analysis includes analysis of the clamping force and the stretching force. The mold clamping force requirements are calculated as follows:
F＝p*n*f
wherein F represents the mold supporting force; p is the projection area of the finished product in the direction of a switch mode, and the unit cm 2 The appearance size of the finished product is calculated; n represents the number of mold cavities; f represents the in-mold pressure (kg/cm 2), which varies depending on the raw material, and is generally 350 to 400kg/cm2.
The previously obtained mold clamping force is input by the user according to the mold clamping force in the actual injection molding machine. The machine clamping force needs to be greater than the mold supporting force, and for safety, the machine clamping force needs to be greater than 1.17 times of the mold supporting force.
In one implementation, the method further comprises:
when the target feature structure is judged to comprise a suture line and a thickness change structure, obtaining the time for filling the mould by the flow wave in the mould flow analysis;
judging whether the time for filling the die is larger than a preset time preset value, and if so, generating an analysis result comprising hysteresis.
It is to be noted that the hysteresis effect (hysteresis) or hysteresis mark is a defect of the surface of a molded article, which is caused by the flow of the melt through a thin-meat region or a region of abrupt change in the thickness of the meat, resulting in stagnation of the flow. When the melt adhesive is injected into the mold cavity with variable thickness, the thick area and the area with smaller resistance are filled, and as a result, the flow of the thin area is stopped, and the stopped melt adhesive can not continue to flow until the part outside the thin area is filled. However, the melt adhesive which stagnates too long may solidify in advance at the stagnation position, and a hysteresis mark is generated when the solidified melt adhesive is pushed to the surface of the molded article.
In this embodiment, when it is determined that the target feature includes a suture thread and a thickness variation structure, a flow wave filling-up time in the die flow analysis is obtained. Illustratively, timing is started when the plastic flows in the mold cavity to the stitch and/or thickness variation structure, and is ended when the plastic flow wave fills the mold, resulting in a mold fill time. The time pre-estimated value is stored in software in advance and can be set according to an empirical value.
It should be noted that when there are sutures and structures with varying thickness, the melt adhesive may solidify in advance at the stagnation position, and when the solidified melt adhesive is pushed to the surface of the plastic part, hysteresis marks may be generated. If the dead time of the melt adhesive is short, no hysteresis mark is generated. In the invention, by judging the time of the suture and the thickness change structure, whether hysteresis marks are generated or not is analyzed, the phenomenon that a special structure is directly judged to generate hysteresis is avoided, and the accuracy of an analysis result is further improved.
In one implementation, the method further comprises:
and when the analysis result comprises that the mold locking force is unqualified or hysteresis exists, generating parameter adjustment suggestions for the mold file.
The generating parameter adjustment suggestions for the mold file includes: one or more of changing the design of the plastic part, changing the design of the mold, and adjusting the molding conditions.
Illustratively, when the analysis result includes a failure in mold clamping force, the parameter adjustment recommendation includes a change in the mold design, a change in the mold design. For example, reducing the variation in the thickness of the molding, altering the components in the molding design that cause excessive pressure, or altering the mold design so that the mold can withstand more pressure.
Illustratively, when the analysis result includes the presence of hysteresis, the parameter adjustment recommendation includes adjusting a molding condition. For example, increasing the temperature of the melt adhesive, or increasing the injection pressure.
Illustratively, when the analysis result includes the existence of hysteresis, the parameter adjustment recommendation includes altering the mold design. For example, the gate position is moved away from the thin-meat region or the region of abrupt change in meat thickness according to a preset displacement, and the moved gate position data is used as an adjustment suggestion for changing the mold design. In this embodiment, the hysteresis effect can be delayed by changing the gate position or ended in a short time. At the same time, the hysteresis effect can be reduced by moving the casting away from the thin meat area.
It should be noted that, the flow of the plastic in the cavity is known in advance by CAE analysis, the thickness difference of each region is different, and the difference of the flow in the cavity is also very large, especially when flowing to the hole region. Because of the narrow structure volume, the problems of short shot and burrs are easy to occur. Therefore, the area easy to flow is selected to properly place the gate position so as to obtain better molding pressure, and better gate design can be found through analysis so as to obtain good molding results.
Compared with the prior art, the CAE model flow analysis method for the plastic mould disclosed by the embodiment of the invention obtains the characteristic grid points by carrying out structural characteristic identification on the gridding file. And then, generating a model according to the preset analysis parameters and matching the model with the characteristic grid points to obtain the analysis parameters. And finally, analyzing and calculating the die file according to the analysis parameters, the injection molding materials and the molding conditions, and generating an analysis result. Therefore, the analysis parameters are obtained by matching the analysis parameter generation model with the characteristic grid points, so that the manual setting of the analysis parameters is avoided, the whole analysis process is independent of experience of operators, the selection efficiency of the analysis parameters can be improved, errors caused by manual selection are avoided, and the accuracy of analysis results can be improved.
Referring to fig. 2, a second embodiment of the present invention provides a CAE flow analysis apparatus for a plastic mold, comprising:
the gridding module is used for acquiring a die file to be analyzed, gridding the die file and obtaining a gridding file;
the characteristic identification module is used for carrying out structural characteristic identification on the meshed file to obtain characteristic grid points;
the parameter generation module is used for generating a model according to a preset analysis parameter and matching the characteristic grid points to obtain the analysis parameter, wherein the analysis parameter comprises a product category, a gate position, a gate quantity and a runner structure;
the condition input module is used for acquiring injection molding materials and molding conditions input by a user;
and the analysis and calculation module is used for carrying out analysis and calculation on the die file according to the analysis parameters, the injection molding materials and the molding conditions and generating an analysis result.
It should be noted that, the device for analyzing the CAE flow of the plastic mold provided by the embodiment of the present invention is used for executing all the flow steps of the method for analyzing the CAE flow of the plastic mold in the above embodiment, and the working principles and beneficial effects of the two correspond one to one, so that the description is omitted.
The embodiment of the invention also provides terminal equipment. The terminal device includes: a processor, a memory, and a computer program stored in the memory and executable on the processor, such as a plastic mold CAE mold flow analysis program. The steps of the above embodiments of the CAE flow analysis method of the plastic mold are implemented when the processor executes the computer program, for example, step S11 shown in fig. 1. Alternatively, the processor may implement the functions of the modules/units in the above-described device embodiments when executing the computer program, for example, an analysis calculation module.
The computer program may be divided into one or more modules/units, which are stored in the memory and executed by the processor to accomplish the present invention, for example. The one or more modules/units may be a series of computer program instruction segments capable of performing the specified functions, which instruction segments are used for describing the execution of the computer program in the terminal device.
The terminal equipment can be a desktop computer, a notebook computer, a palm computer, an intelligent tablet and other computing equipment. The terminal device may include, but is not limited to, a processor, a memory. It will be appreciated by those skilled in the art that the above components are merely examples of terminal devices and do not constitute a limitation of terminal devices, and may include more or fewer components than described above, or may combine certain components, or different components, e.g., the terminal devices may also include input and output devices, network access devices, buses, etc.
The processor may be a central processing unit (Central Processing Unit, CPU), other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like, which is a control center of the terminal device, and which connects various parts of the entire terminal device using various interfaces and lines.
The memory may be used to store the computer program and/or module, and the processor may implement various functions of the terminal device by running or executing the computer program and/or module stored in the memory and invoking data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program (such as a sound playing function, an image playing function, etc.) required for at least one function, and the like; the storage data area may store data (such as audio data, phonebook, etc.) created according to the use of the handset, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, smart Media Card (SMC), secure Digital (SD) Card, flash Card (Flash Card), at least one disk storage device, flash memory device, or other volatile solid-state storage device.
Wherein the terminal device integrated modules/units may be stored in a computer readable storage medium if implemented in the form of software functional units and sold or used as stand alone products. Based on such understanding, the present invention may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the computer readable medium contains content that can be appropriately scaled according to the requirements of jurisdictions in which such content is subject to legislation and patent practice, such as in certain jurisdictions in which such content is subject to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.
It should be noted that the above-described apparatus embodiments are merely illustrative, and the units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. In addition, in the drawings of the embodiment of the device provided by the invention, the connection relation between the modules represents that the modules have communication connection, and can be specifically implemented as one or more communication buses or signal lines. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
The foregoing embodiments have been provided for the purpose of illustrating the general principles of the present invention, and are not to be construed as limiting the scope of the invention. It should be noted that any modifications, equivalent substitutions, improvements, etc. made by those skilled in the art without departing from the spirit and principles of the present invention are intended to be included in the scope of the present invention.

Claims (10)

1. A method for CAE flow analysis of a plastic mold, comprising:
acquiring a mold file to be analyzed, and gridding the mold file to obtain a gridding file;
carrying out structural feature recognition on the meshed file to obtain feature grid points;
according to a preset analysis parameter generation model and the characteristic grid points, matching is carried out, and analysis parameters are obtained, wherein the analysis parameters comprise product types, sprue positions, sprue quantity and runner structures;
acquiring injection molding materials and molding conditions input by a user;
and analyzing and calculating the die file according to the analysis parameters, the injection molding materials and the molding conditions, and generating an analysis result.
2. The method for CAE flow analysis of plastic molds according to claim 1, wherein said performing structural feature recognition on the gridding file to obtain feature grid points includes:
searching the gridding file according to a preset range value, and judging whether a target characteristic structure exists in the range value, wherein the target characteristic structure comprises one or more of a pouring gate, a die cavity, a suture line and a thickness change structure;
if yes, determining the grid where the target feature structure is located as a feature grid point; if not, replacing the next grid for searching.
3. The plastic mold CAE flow analysis method of claim 2, further comprising:
when the target feature structure is judged to comprise a mold cavity, calculating mold supporting force according to the number of the mold cavities;
judging whether the mold supporting force is smaller than the pre-acquired mold locking force, and if not, generating an analysis result comprising unqualified mold locking force.
4. The plastic mold CAE flow analysis method of claim 2, further comprising:
when the target feature structure is judged to comprise a suture line and a thickness change structure, obtaining the time for filling the mould by the flow wave in the mould flow analysis;
judging whether the time for filling the die is larger than a preset time preset value, and if so, generating an analysis result comprising hysteresis.
5. The method of claim 3 or 4, further comprising:
and when the analysis result comprises that the mold locking force is unqualified or hysteresis exists, generating parameter adjustment suggestions for the mold file.
6. The method of claim 5, wherein generating parameter adjustment recommendations for the mold file comprises: one or more of changing the design of the plastic part, changing the design of the mold, and adjusting the molding conditions.
7. The method for CAE flow analysis of plastic molds according to claim 1, wherein said process of constructing said analysis parameter generating model comprises:
acquiring a history mould file, history gridding file data, history characteristic grid points and history analysis parameters;
and carrying out convolutional neural network training on the initial convolutional neural network through the history mould file, the history gridding file data, the history characteristic grid points and the history analysis parameters to obtain an analysis parameter generation model after training is completed.
8. A CAE die flow analysis apparatus for a plastic die, comprising:
the gridding module is used for acquiring a die file to be analyzed, gridding the die file and obtaining a gridding file;
the characteristic identification module is used for carrying out structural characteristic identification on the meshed file to obtain characteristic grid points;
the parameter generation module is used for generating a model according to a preset analysis parameter and matching the characteristic grid points to obtain the analysis parameter, wherein the analysis parameter comprises a product category, a gate position, a gate quantity and a runner structure;
the condition input module is used for acquiring injection molding materials and molding conditions input by a user;
and the analysis and calculation module is used for carrying out analysis and calculation on the die file according to the analysis parameters, the injection molding materials and the molding conditions and generating an analysis result.
9. A terminal device comprising a processor, a memory and a computer program stored in the memory and configured to be executed by the processor, the processor implementing the plastic mold CAE-flow analysis method according to any one of claims 1 to 7 when the computer program is executed.
10. A computer readable storage medium, characterized in that the computer readable storage medium comprises a stored computer program, wherein the computer program, when run, controls a device in which the computer readable storage medium is located to perform the CAE-model analysis method of a plastic mould according to any one of claims 1 to 7.
CN202311369623.1A 2023-10-19 2023-10-19 Plastic mold CAE (computer aided engineering) die flow analysis method, device, equipment and storage medium Pending CN117574700A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202311369623.1A CN117574700A (en) 2023-10-19 2023-10-19 Plastic mold CAE (computer aided engineering) die flow analysis method, device, equipment and storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202311369623.1A CN117574700A (en) 2023-10-19 2023-10-19 Plastic mold CAE (computer aided engineering) die flow analysis method, device, equipment and storage medium

Publications (1)

Publication Number Publication Date
CN117574700A true CN117574700A (en) 2024-02-20

Family

ID=89861337

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202311369623.1A Pending CN117574700A (en) 2023-10-19 2023-10-19 Plastic mold CAE (computer aided engineering) die flow analysis method, device, equipment and storage medium

Country Status (1)

Country Link
CN (1) CN117574700A (en)

Similar Documents

Publication Publication Date Title
CN111898265B (en) Method for determining injection molding process parameters of plastic products and method for establishing coefficient library of plastic products
JP6779316B2 (en) Molding condition estimation method for injection molding machine
CN103093062A (en) Parametric analysis method of effect of injection molding process to plastic part buckling deformation
CN105228808A (en) For operating the method for the machine of processing plastic
CN107972243A (en) Shooting Technique optimization method and Shooting Technique based on SOM neutral nets
CN109614651A (en) A kind of high-precision evaluation method of moulding machined parameters and deformation relationship
CN117592222B (en) Casting simulation method, system and medium based on injection mold
Moayyedian et al. Gate design and filling process analysis of the cavity in injection molding process
CN117574700A (en) Plastic mold CAE (computer aided engineering) die flow analysis method, device, equipment and storage medium
CN117574695A (en) Injection mold simulation pouring method, system and medium
US10384386B2 (en) Method for setting up a molding system
CN112770890B (en) Method for controlling a machine for processing plastics
CN112541248B (en) Automatic modular flow analysis system and method
US5871676A (en) Method for setting a program profile in the control of the injection speed of injection molding machine
CN115114777A (en) Injection mold pouring simulation method, device, equipment and storage medium
Lanvers et al. Injection Moulding Made Trasparent) New Development in Process Simulation
CN113748008A (en) Software implementation method for processing simulation results created by finite element analysis software
US11602876B2 (en) Machine learning device and design support device
Sapounas et al. A simulation-based robust methodology for operator guidance on injection moulding machine settings
CN115545367A (en) Abnormality monitoring method in injection molding process, electronic device, and storage medium
Yablochnikov et al. An integrated approach to development and simulation manufacturing processes of optical products
CN116766544B (en) Hot runner valve needle control method, device, equipment and storage medium
Pavani et al. Mold flow analysis on fan part using plastic advisor
JP2002137274A (en) Apparatus and method for determining injection molding condition, and program recording medium
CN110688802B (en) Equivalent processing method, system and medium for glue injection runner in filling analysis of metal rubber composite product

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination