High-strength mold structure design method and system based on cloud computing

Abstract

The present invention relates to the technical field of mold structure design, and provides a high-strength mold structure design method and system based on cloud computing, including: analyzing common damage modes and damage structures of mold structures, and calculating the utility amplitude of common damage modes on mold structures according to the damage structures; screening out key damage structures from the damage structures, calculating the material fit index between high-strength materials, modeling high-strength materials in a preset cloud computing design platform, and obtaining a simulated mold structure; drawing mechanical property curves corresponding to the simulated mold structure, and calculating the structural strength values ​​corresponding to the key damage structures; calculating the performance attenuation values ​​of the simulated mold structure in the application scenario in the cloud computing platform, screening out the target mold structure from the simulated mold structure, and determining the design scheme corresponding to the mold structure. The present invention aims to improve the accuracy of high-strength mold structure design.

Description

Technical Field

[0001] The present invention relates to the technical field of mold structure design, and in particular to a high-strength mold structure design method and system based on cloud computing. Background Art

[0002] In modern manufacturing, molds play a vital role. However, traditional mold design methods have gradually revealed many limitations in the face of increasingly complex and high-performance demands. The design requirements for high-strength molds are becoming more and more stringent, and many factors need to be considered, such as material properties, manufacturing processes, working environment, and stress and strain during use.

[0003] The existing high-strength mold structure design adopts empirical design method and analogy design method. The empirical design method mainly relies on past experience and intuition to determine the structure and parameters of the mold, over-relying on personal experience, lacking scientificity and accuracy. The analogy design method refers to the design of existing similar mold structures and optimizes them on the existing basis. These two methods cannot fully adapt to new working conditions and requirements. It is easy to cause the performance of the designed mold to be unstable, so a method that can improve the accuracy of high-strength mold structure design is needed. Summary of the invention

[0004] The present invention provides a high-strength mold structure design method and system based on cloud computing, the main purpose of which is to improve the accuracy of high-strength mold structure design.

[0005] To achieve the above object, the present invention provides a high-strength mold structure design method based on cloud computing, comprising:

[0006] Acquire a mold structure to be designed, collect mold damage data corresponding to the mold structure, analyze common damage modes and damage structures of the mold structure based on the mold damage data, and calculate the effect of the common damage modes on the mold structure according to the damage structure;

[0007] According to the utility amplitude, a key damaged structure is selected from the damaged structure, and a high-strength material of the key damaged structure is selected from a preset cloud material library, and a material compatibility index between the high-strength materials is calculated. According to the material compatibility index, a modeling operation is performed on the high-strength material in a preset cloud computing design platform to obtain a simulated mold structure;

[0008] Performing strength testing on the simulated mold structure by using a virtual testing machine in the cloud computing platform to obtain strength test data and deformation data, drawing a mechanical property curve corresponding to the simulated mold structure based on the strength test data, and calculating a structural strength value corresponding to the key damaged structure according to the mechanical property curve and the deformation data;

[0009] In determining the application scenario of the mold structure, the performance attenuation value of the simulated mold structure in the application scenario is calculated in the cloud computing platform, and the target mold structure is screened out from the simulated mold structure in combination with the structural strength value and the performance attenuation value. According to the target mold structure, the design scheme corresponding to the mold structure is determined.

[0010] Optionally, analyzing common damage modes and damage structures of the mold structure based on the mold damage data includes:

[0011] Identifying damage information in the mold damage data, and calculating information entropy corresponding to the damage information;

[0012] According to the information entropy, the damage information is filtered to obtain target damage information;

[0013] Performing feature extraction on the target damage information to obtain feature information, and extracting key characters from the feature information;

[0014] Based on the key characters, the common damage modes and damage structures of the mold structure are analyzed.

[0015] Optionally, calculating the effect of the common damage mode on the mold structure according to the damaged structure includes:

[0016] Querying the design purpose of the mold structure, and analyzing the functional attributes of the mold structure according to the design purpose;

[0017] Clarifying the structural function of the damaged structure in the mold structure, and calculating the functional correlation coefficient between the functional attribute and the structural function;

[0018] Quantifying the functional attribute and the structural function respectively to obtain a first quantization value and a second quantization value;

[0019] The functional correlation coefficient, the first quantitative value, and the second quantitative value are combined to calculate the effectiveness of the common damage mode on the mold structure.

[0020] Optionally, the calculating the functional correlation coefficient between the functional attribute and the structural function comprises:

[0021] Performing vectorization processing on the functional attribute and the structural function respectively to obtain a first functional vector and a second functional vector;

[0022] Performing feature extraction on the first function vector and the second function vector respectively to obtain a first feature vector and a second feature vector;

[0023] Calculating a vector similarity between the first feature vector and the second feature vector;

[0024] According to the vector similarity, identifying common feature vectors in the first feature vector and the second feature vector;

[0025] Respectively counting the numbers of vectors corresponding to the common eigenvector, the first eigenvector, and the second eigenvector to obtain a first vector number, a second vector number, and a third vector number;

[0026] In combination with the first vector number, the second vector number and the third vector number, the functional correlation coefficient between the functional attribute and the structural function is calculated by the following formula:

[0027]

[0028] Among them, A represents the functional correlation coefficient between functional attributes and structural functions, represents the first vector number, b represents the second vector number, and d represents the third vector number.

[0029] Optionally, calculating the material compatibility index between the high-strength materials includes:

[0030] Obtain material parameter information and parameter type corresponding to the high-strength material, and query key parameter indicators of the high-strength material;

[0031] Analyzing the correlation between the key parameter indicators and the parameter types;

[0032] According to the correlation, extracting material characteristic parameters and characteristic parameter values ​​corresponding to the high-strength material from the material parameter information;

[0033] The material compatibility index between the high-strength materials is calculated by combining the material characteristic parameters and the characteristic parameter values.

[0034] Optionally, the combining the material characteristic parameter and the characteristic parameter value to calculate the material compatibility index between the high-strength materials includes:

[0035] Dispatching historical processing data of the high-strength material, and setting a parameter difference threshold between characteristic parameters of the material according to the historical processing data;

[0036] According to the parameter difference threshold and the characteristic parameter value, the parameter fit between the material characteristic parameters is calculated by the following formula:

[0037]

[0038] Among them, D represents the parameter fit between material characteristic parameters, Ba Indicates the ath parameter value in the characteristic parameter value, B a+1 Indicates the a+1th parameter value in the characteristic parameter value, β a，a+1 Indicates the parameter difference threshold corresponding to the a-th and a+1-th parameter values ​​in the characteristic parameter value;

[0039] The parameter weights corresponding to the material characteristic parameters are allocated, and the material compatibility index between the high-strength materials is calculated by combining the parameter weights and the parameter compatibility by the following formula:

[0040]

[0041] Among them, E represents the material fit index between high-strength materials, D i Indicates the parameter fit corresponding to the i-th material characteristic parameter, C i It represents the parameter weight corresponding to the i-th material characteristic parameter, i represents the serial number of the material characteristic parameter, and t represents the total number of parameters of the material characteristic parameter.

[0042] Optionally, drawing a mechanical property curve corresponding to the simulated mold structure based on the strength test data includes:

[0043] Performing data cleaning on the strength test data to obtain target test data;

[0044] Performing repair processing on the target test data to obtain repaired test data;

[0045] Extracting data variables and variable observation values ​​in the repair test data;

[0046] Based on the data variables and the variable observation values, a mechanical property curve corresponding to the simulated mold structure is drawn.

[0047] Optionally, calculating the structural strength value corresponding to the key damaged structure according to the mechanical property curve and the deformation data includes:

[0048] Reading the yield threshold corresponding to the simulated mold structure from the mechanical characteristic curve;

[0049] Calculating the mold deformation amount corresponding to the simulated mold structure according to the deformation data;

[0050] Fitting the mechanical property curve to obtain a strain hardening coefficient and a plastic strengthening index;

[0051] Combining the yield threshold, the mold deformation, the strain hardening coefficient and the plastic strengthening index, the structural strength value corresponding to the key damaged structure is calculated by the following formula:

[0052]

[0053] Among them, F represents the structural strength value corresponding to the key damage structure, μ represents the strain hardening coefficient, ω 0 represents the yield threshold, γ represents the mold deformation, and e represents the plastic strengthening index.

[0054] Optionally, calculating the performance attenuation value of the simulated mold structure in the application scenario in the cloud computing platform includes:

[0055] Collecting application environment data in the application scenario, and analyzing environmental impact factors in the application environment data that act on the simulated mold structure;

[0056] According to the environmental influencing factors, setting the simulation boundary conditions of the simulated mold structure;

[0057] According to the simulation boundary conditions, the simulated mold structure is simulated using finite element analysis software in the cloud computing platform to obtain a simulated mold structure;

[0058] In combination with the simulated mold structure, the performance attenuation value of the simulated mold structure in the application scenario is calculated.

[0059] A high-strength mold structure design system based on cloud computing, characterized in that the system includes:

[0060] A utility amplitude calculation module is used to obtain a mold structure to be designed, collect mold damage data corresponding to the mold structure, analyze common damage modes and damage structures of the mold structure based on the mold damage data, and calculate the utility amplitude of the common damage modes on the mold structure according to the damage structure;

[0061] A structural modeling module, for selecting key damaged structures from the damaged structures according to the utility amplitude, selecting high-strength materials of the key damaged structures from a preset cloud material library, calculating material compatibility indexes between the high-strength materials, and modeling the high-strength materials in a preset cloud computing design platform according to the material compatibility indexes to obtain a simulated mold structure;

[0062] A structural strength calculation module, used to perform a strength test on the simulated mold structure using a virtual testing machine in the cloud computing platform to obtain strength test data and deformation data, draw a mechanical property curve corresponding to the simulated mold structure based on the strength test data, and calculate a structural strength value corresponding to the key damaged structure according to the mechanical property curve and the deformation data;

[0063] The design scheme determination module is used to determine the application scenario of the mold structure, calculate the performance attenuation value of the simulated mold structure in the application scenario in the cloud computing platform, combine the structural strength value and the performance attenuation value, screen out the target mold structure from the simulated mold structure, and determine the design scheme corresponding to the mold structure based on the target mold structure.

[0064] The present invention analyzes the common damage mode and damage structure of the mold structure based on the mold damage data, and can understand the damage type of the mold structure during use and the parts of the mold where damage often occurs, thereby providing a direction for the subsequent structural design of the mold structure. The present invention calculates the material fit index between the high-strength materials to understand the degree of mutual adaptation and coordination of the high-strength materials when used in combination, and judges whether they can work together without adverse effects. The present invention uses the virtual testing machine in the cloud computing platform to perform strength testing on the simulated mold structure, and can obtain strength test data and deformation data, so as to facilitate the subsequent drawing and processing of the mechanical property curve corresponding to the simulated mold structure and the calculation of the structural strength value. The present invention calculates the performance attenuation value of the simulated mold structure in the application scenario in the cloud computing platform, and can understand the quantitative value of the performance loss of the simulated mold structure in the application scenario, thereby improving the accuracy of the subsequent target mold structure screening. Therefore, a high-strength mold structure design method and system based on cloud computing provided in an embodiment of the present invention can improve the accuracy of high-strength mold structure design. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 A schematic diagram of a process flow of a high-strength mold structure design method based on cloud computing provided by one embodiment of the present invention;

[0066] Figure 2 A functional module diagram of a high-strength mold structure design system based on cloud computing provided by one embodiment of the present invention.

[0067] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0068] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0069] The embodiment of the present application provides a high-strength mold structure design method based on cloud computing. In the embodiment of the present application, the execution subject of the high-strength mold structure design method based on cloud computing includes but is not limited to at least one of the electronic devices such as the server, the terminal, etc. that can be configured to execute the method provided by the embodiment of the present application. In other words, the high-strength mold structure design method based on cloud computing can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc. The server can be an independent server, or it can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and big data and artificial intelligence platforms.

[0070] Reference Figure 1 FIG. 1 is a flow chart of a high-strength mold structure design method based on cloud computing provided by an embodiment of the present invention. In this embodiment, the high-strength mold structure design method based on cloud computing includes steps S1-S4.

[0071] S1. Obtain a mold structure to be designed, collect mold damage data corresponding to the mold structure, analyze common damage modes and damage structures of the mold structure based on the mold damage data, and calculate the effectiveness of the common damage modes on the mold structure according to the damage structure.

[0072] The present invention analyzes the common damage modes and damage structures of the mold structure based on the mold damage data, so as to understand the damage types of the mold structure during use and the parts of the mold where damage often occurs, thereby providing direction for the subsequent structural design of the mold structure, wherein the mold structure is a template used for injection molding, the mold damage data is data of damage records previously generated for the mold structure, the common damage modes are the damage types corresponding to the mold structure, such as wear or fatigue cracks, and the damage structure is the location where damage occurs in the mold structure, such as the bottom of the mold.

[0073] As an embodiment of the present invention, the common damage mode and damage structure of the mold structure are analyzed based on the mold damage data, including: identifying damage information in the mold damage data, calculating information entropy corresponding to the damage information, filtering the damage information according to the information entropy to obtain target damage information, performing feature extraction on the target damage information to obtain feature information, extracting key characters from the feature information, and analyzing the common damage mode and damage structure of the mold structure according to the key characters.

[0074] Among them, the damage information is the descriptive information in the mold damage data, the information entropy represents the degree of confusion corresponding to the damage information, and can be used as an indicator of the importance of evaluation information, the feature information is the characterization information in the target damage information, and the key characters are important characters in the feature information.

[0075] Optionally, the damage information in the mold damage data can be realized by OCR recognition technology; the information entropy corresponding to the damage information can be realized by Shannon entropy algorithm; the information entropy is compared with a preset information entropy threshold, if the information entropy is less than the information entropy threshold, the corresponding damage information is filtered out, and so on, finally obtaining the target damage information, the preset information entropy threshold can be 0.8, and can also be set according to actual application requirements; the feature extraction of the target damage information can be realized by principal component analysis; the extraction of key characters in the feature information can be realized by TF-IDF algorithm; the semantics corresponding to the key characters are analyzed to obtain the character semantics, and according to the character semantics, the common damage mode and damage structure of the mold structure are analyzed, such as if structure 1 in the mold is concave, it means that the damaged structure is structure 1, and the common damage mode is concave.

[0076] The present invention calculates the effectiveness range of the common damage mode on the mold structure based on the damage structure, so as to understand the influence of the common damage mode on the mold structure, thereby facilitating the subsequent screening and processing of key damage structures, wherein the effectiveness range represents the influence of the common damage mode on the use of the mold structure.

[0077] As an embodiment of the present invention, the calculation of the effectiveness of the common damage mode on the mold structure based on the damaged structure includes: querying the design purpose of the mold structure, analyzing the functional attributes of the mold structure based on the design purpose, clarifying the structural function of the damaged structure in the mold structure, calculating the functional correlation coefficient between the functional attributes and the structural function, quantifying the functional attributes and the structural function respectively to obtain a first quantization value and a second quantization value, and calculating the effectiveness of the common damage mode on the mold structure in combination with the functional correlation coefficient, the first quantization value and the second quantization value.

[0078] Among them, the design purpose is the functional requirement corresponding to the mold structure, the functional attribute is the specific function achieved by the mold structure to complete the task, the structural function is the functional role played by the damaged structure in the mold structure, the functional correlation coefficient represents the functional correlation degree between the functional attribute and the structural function, and the first quantitative value and the second quantitative value are respectively the quantitative values ​​corresponding to the functional attribute and the structural function.

[0079] Optionally, the design purpose of the mold structure can be obtained by querying design documents and drawings; the design requirements corresponding to the design purpose are analyzed, and the functional attributes of the mold structure are determined according to the design requirements; the structural function of the damaged structure in the mold structure can be clarified by consulting the designer; the quantitative processing of the functional attributes and the structural functions can be achieved by a scoring method, and a scoring standard is formulated, for example, 1 to 10 points, and experts or relevant personnel score the performance of each functional attribute and structural function according to actual conditions, and the obtained score is used as the quantitative value of the functional attribute and the structural function to obtain a first quantitative value and a second quantitative value; the functional association coefficient, the first quantitative value and the second quantitative value are multiplied to obtain the utility range of the common damage mode on the mold structure. For example, a functional attribute of the mold structure (such as high-precision molding) is rated 8 points, and the corresponding structural function of the damaged structure (such as a key part to ensure molding accuracy) is rated 7 points. The calculated functional association coefficient is 0.8, then the utility range = 0.8×8×7=44.8.

[0080] Further, as an optional embodiment of the present invention, the calculation of the functional correlation coefficient between the functional attribute and the structural function includes: respectively performing vectorization processing on the functional attribute and the structural function to obtain a first functional vector and a second functional vector, respectively performing feature extraction on the first functional vector and the second functional vector to obtain a first feature vector and a second feature vector, calculating the vector similarity between the first feature vector and the second feature vector, identifying the same feature vectors in the first feature vector and the second feature vector according to the vector similarity, respectively counting the number of vectors corresponding to the same feature vector, the first feature vector and the second feature vector to obtain a first vector number, a second vector number and a third vector number, and combining the first vector number, the second vector number and the third vector number to calculate the functional correlation coefficient between the functional attribute and the structural function by the following formula:

[0081]

[0082] Among them, A represents the functional correlation coefficient between functional attributes and structural functions, represents the first vector number, b represents the second vector number, and d represents the third vector number.

[0083] Among them, the first function vector and the second function vector are expression vectors between the function attributes and the structural functions, respectively, the first feature vector and the second feature vector are representative vectors in the first function vector and the second function vector, respectively, and the common feature vector is a common feature vector in the first feature vector and the second feature vector.

[0084] Furthermore, the vectorization processing of the functional attributes and the structural functions can be achieved through the word2vec algorithm; the feature extraction of the first functional vector and the second functional vector can be achieved through a decision tree algorithm, such as ID3, C4.5, etc., and decision rules can be generated to extract important feature vectors; the vector similarity between the first feature vector and the second feature vector can be calculated through a cosine similarity algorithm; when the vector similarity is 1, the common feature vectors in the first feature vector and the second feature vector are identified.

[0085] S2. According to the utility amplitude, the key damage structure is screened out from the damage structure, and the high-strength material of the key damage structure is screened out from the preset cloud material library, and the material fit index between the high-strength materials is calculated. According to the material fit index, the high-strength material is modeled in a preset cloud computing design platform to obtain a simulated mold structure.

[0086] The present invention calculates the material compatibility index between the high-strength materials to understand the degree of mutual adaptation and coordination between the high-strength materials when used in combination, and determines whether they can work together without adverse effects, wherein the key damage structure is a structure in the damage structure that plays a decisive role in the function of the mold structure, the preset cloud material library is a pre-constructed database formed by storing data of various materials on a cloud server, the high-strength material is a material with high strength in the cloud material library, and the material compatibility index indicates the degree of mutual adaptation and coordination between the high-strength materials. Optionally, the key damage structure is screened out from the damage structure according to the numerical value of the utility amplitude. For example, if the utility amplitudes are 44.8, 56, and 67, respectively, the damage structures corresponding to 56 and 67 are screened as key damage structures.

[0087] As an embodiment of the present invention, the calculation of the material compatibility index between the high-strength materials includes: obtaining material parameter information and parameter types corresponding to the high-strength materials, querying key parameter indicators of the high-strength materials, analyzing the correlation between the key parameter indicators and the parameter types, and extracting material characteristic parameters and characteristic parameter values ​​corresponding to the high-strength materials from the material parameter information based on the correlation, and calculating the material compatibility index between the high-strength materials by combining the material characteristic parameters and the characteristic parameter values.

[0088] Among them, the material parameter information is the description information of the material properties corresponding to the high-strength material, the parameter type is the parameter category corresponding to the material parameter information, such as strength, the material characteristic parameter is the key material parameter in the material parameter information, and plays a certain decisive role in the effect of the high-strength material, and the characteristic parameter value is the specific parameter value corresponding to the high-strength material.

[0089] Optionally, the material parameter information and parameter type corresponding to the high-strength material can be obtained through the material supplier; the key parameter indicators of the high-strength material can be obtained by querying the industry standards of the material industry; the analysis of the correlation between the key parameter indicators and the parameter type can be achieved through principal component analysis.

[0090] Optionally, as an optional embodiment of the present invention, the combining the material characteristic parameters and the characteristic parameter values ​​to calculate the material fit index between the high-strength materials includes: scheduling historical processing data of the high-strength materials, setting a parameter difference threshold between the material characteristic parameters according to the historical processing data, and calculating the parameter fit between the material characteristic parameters according to the parameter difference threshold and the characteristic parameter value by the following formula:

[0091]

[0092] Among them, D represents the parameter fit between material characteristic parameters, B a Indicates the ath parameter value in the characteristic parameter value, B a+1 Indicates the a+1th parameter value in the characteristic parameter value, β a，a+1 Indicates the parameter difference threshold corresponding to the a-th and a+1-th parameter values ​​in the characteristic parameter value;

[0093] And the parameter weights corresponding to the material characteristic parameters are allocated, and the material compatibility index between the high-strength materials is calculated by combining the parameter weights and the parameter compatibility by the following formula:

[0094]

[0095] Among them, E represents the material fit index between high-strength materials, D i Indicates the parameter fit corresponding to the i-th material characteristic parameter, C i It represents the parameter weight corresponding to the i-th material characteristic parameter, i represents the serial number of the material characteristic parameter, and t represents the total number of parameters of the material characteristic parameter.

[0096] Among them, the historical processing data is the data of the previous processing records of the high-strength material. According to the historical processing data, the parameter difference threshold is the limit value of the difference range allowed between the material characteristic parameters. For example, the ideal strength fit is that the difference is within ±50MPa for complete fit, then ±50MPa is the parameter difference threshold, and the parameter weight represents the importance of the material characteristic parameters. Furthermore, the historical processing data of the high-strength material can be obtained through database scheduling; the parameter difference threshold between the material characteristic parameters can be set by statistical analysis methods, and the mean, median and standard deviation of the difference of the material characteristic parameters in the historical data are calculated. The mean plus or minus a certain multiple of the standard deviation can be used as the threshold range, or the median can be directly used as the threshold; the allocation of parameter weights corresponding to the material characteristic parameters can be achieved through hierarchical analysis.

[0097] The present invention can obtain a simulated mold structure by modeling the high-strength material in a preset cloud computing design platform according to the material fit index, thereby facilitating subsequent corresponding testing of the simulated mold structure, wherein the cloud computing design platform is an online design tool based on cloud computing technology, and the simulated mold structure is a virtual model constructed by constructing the high-strength material according to the key damage structure. Furthermore, based on the material fit index, the combined material in the high-strength material is determined, and the processing conditions of the combined material are configured in the cloud computing design platform. The combined material is processed according to the processing conditions to obtain a simulated mold structure.

[0098] S3. Perform a strength test on the simulated mold structure using a virtual testing machine in the cloud computing platform to obtain strength test data and deformation data. Based on the strength test data, draw a mechanical property curve corresponding to the simulated mold structure. According to the mechanical property curve and the deformation data, calculate the structural strength value corresponding to the key damaged structure.

[0099] The present invention utilizes the virtual testing machine in the cloud computing platform to perform strength testing on the simulated mold structure, and can obtain strength test data and deformation data, so as to facilitate the subsequent drawing and processing of the mechanical property curve corresponding to the simulated mold structure and the calculation of the structural strength value, wherein the virtual testing machine is used for testing in the cloud computing platform, and the strength test data is the data obtained after the simulated mold structure is subjected to a series of tests in the virtual testing machine, such as yield strength test data, tensile strength test data and hardness test data, etc., and the deformation data is the data when the simulated mold structure is deformed during the strength test.

[0100] The present invention draws a mechanical property curve corresponding to the simulated mold structure based on the strength test data, thereby obtaining a visualized performance representation of the simulated mold structure, thereby providing a basis for the subsequent calculation of the structural strength value, wherein the mechanical property curve is a graphical representation of the change in the mechanical properties of the simulated mold structure when subjected to external force.

[0101] As an embodiment of the present invention, the method of drawing the mechanical property curve corresponding to the simulated mold structure based on the strength test data includes: performing data cleaning on the strength test data to obtain target test data, performing repair processing on the target test data to obtain repaired test data, extracting data variables and variable observation values ​​in the repaired test data, and drawing the mechanical property curve corresponding to the simulated mold structure based on the data variables and the variable observation values.

[0102] Among them, the target test data is the data obtained after the abnormal data in the strength test data is eliminated, the repair test data is the data obtained after the data eliminated in the target test data is repaired, the data variable is the characteristic attribute of the repair test data, and the variable observation value is the specific expression value corresponding to the data variable.

[0103] Optionally, data cleaning of the strength test data can be achieved through the box plot method; the repair processing of the target test data can be achieved through the mean interpolation method; the extraction of data variables and variable observation values ​​in the repaired test data can be achieved through an extraction function, and the extraction function is compiled by a scripting language, such as JS scripting language; the drawing of the mechanical property curve corresponding to the simulated mold structure can be achieved through a drawing tool, such as Visio drawing tool.

[0104] The present invention calculates the structural strength value corresponding to the key damaged structure based on the mechanical property curve and the deformation data, and can obtain the specific strength description value corresponding to the key damaged structure, thereby providing a basis for the subsequent screening of the target mold structure, wherein the structural strength value is a quantitative value of the key damaged structure's resistance to external forces.

[0105] As an embodiment of the present invention, the structural strength value corresponding to the key damaged structure is calculated according to the mechanical property curve and the deformation data, including: reading the yield threshold corresponding to the simulated mold structure from the mechanical property curve, calculating the mold deformation corresponding to the simulated mold structure according to the deformation data, fitting the mechanical property curve to obtain the strain hardening coefficient and the plastic strengthening index, and combining the yield threshold, the mold deformation, the strain hardening coefficient and the plastic strengthening index to calculate the structural strength value corresponding to the key damaged structure by the following formula:

[0106]

[0107] Among them, F represents the structural strength value corresponding to the key damage structure, μ represents the strain hardening coefficient, ω 0 represents the yield threshold, γ represents the mold deformation, and e represents the plastic strengthening index.

[0108] Among them, the yield threshold is the stress value when the simulated mold structure begins to produce obvious plastic deformation, the mold deformation is the degree of deformation of the simulated mold structure, the strain hardening coefficient and the plastic strengthening index are respectively the quantitative value of the ability of the simulated mold structure to resist continued deformation in the plastic deformation stage and the rate of strain hardening during the deformation process. Further, the position where the mechanical characteristic curve begins to deviate from the linear part is determined, and the stress value corresponding to the position is read, which is the yield threshold corresponding to the simulated mold structure. The initial volume and the volume after deformation of the simulated mold structure are determined according to the deformation data, and the difference between the two volumes is calculated to obtain the mold deformation corresponding to the simulated mold structure. The fitting processing of the mechanical property curve can be achieved by the least squares method, and the data in the mechanical property curve is substituted into a preset function model (such as σ=K(ε)^n), and then the least squares method is used to solve the strain hardening coefficient K and the plastic strengthening index n.

[0109] S4. Determine an application scenario of the mold structure, calculate the performance attenuation value of the simulated mold structure in the application scenario in the cloud computing platform, select a target mold structure from the simulated mold structure by combining the structural strength value and the performance attenuation value, and determine a design scheme corresponding to the mold structure based on the target mold structure.

[0110] The present invention calculates the performance attenuation value of the simulated mold structure in the application scenario in the cloud computing platform, so as to understand the quantitative value of the performance loss of the simulated mold structure in the application scenario, thereby improving the accuracy of subsequent target mold structure screening, wherein the simulation software is an algorithm for simulating the performance of the simulated mold structure in the application scenario, and finally obtains the degree of performance degradation of the simulated mold structure, and the performance attenuation value is the quantitative value of the performance loss of the simulated mold structure in the application scenario.

[0111] As an embodiment of the present invention, the calculation of the performance attenuation value of the simulated mold structure in the application scenario in the cloud computing platform includes: collecting application environment data in the application scenario, analyzing environmental impact factors acting on the simulated mold structure in the application environment data, setting simulation boundary conditions of the simulated mold structure according to the environmental impact factors, simulating the simulated mold structure according to the simulation boundary conditions using finite element analysis software in the cloud computing platform to obtain a simulated mold structure, and calculating the performance attenuation value of the simulated mold structure in the application scenario in combination with the simulated mold structure.

[0112] Among them, the application environment data is the relevant environmental data in the application scenario, such as temperature, humidity, pressure and other related data; the environmental influencing factors are the environmental factors in the application environment data that affect the function of the simulated mold structure; the simulation boundary conditions are the initial conditions of the simulated mold structure, such as initial temperature, initial stress distribution, etc.; the finite element analysis software is a tool for numerical simulation and analysis of various physical phenomena and engineering problems; the simulated mold structure is the structure obtained by the simulated mold structure under the action of the environmental influencing factors.

[0113] Optionally, the collection of application environment data in the application scenario can be achieved through sensors, such as temperature sensors; the analysis of environmental impact factors acting on the simulated mold structure in the application environment data can be achieved through grey correlation analysis to measure the degree of correlation between environmental factors and mold performance. The higher the correlation, the greater the impact of the environmental factors, thereby obtaining environmental impact factors; the finite element analysis software is compiled through programming software; the performance parameters corresponding to the simulation mold structure and the simulated mold structure are determined respectively, the parameter difference between the performance parameters is calculated, the parameter difference is summed, and the performance attenuation value of the simulated mold structure in the application scenario is obtained.

[0114] Finally, the present invention selects a target mold structure from the simulated mold structure by combining the structural strength value and the performance attenuation value, wherein the target mold structure has the largest structural strength value and the lowest performance attenuation value, and determines the design scheme corresponding to the mold structure according to the materials used corresponding to the target mold structure.

[0115] The present invention analyzes the common damage mode and damage structure of the mold structure based on the mold damage data, and can understand the damage type of the mold structure during use and the parts of the mold where damage often occurs, thereby providing a direction for the subsequent structural design of the mold structure. The present invention calculates the material fit index between the high-strength materials to understand the degree of mutual adaptation and coordination of the high-strength materials when used in combination, and judges whether they can work together without adverse effects. The present invention uses the virtual testing machine in the cloud computing platform to perform strength testing on the simulated mold structure, and can obtain strength test data and deformation data, so as to facilitate the subsequent drawing and processing of the mechanical property curve corresponding to the simulated mold structure and the calculation of the structural strength value. The present invention calculates the performance attenuation value of the simulated mold structure in the application scenario in the cloud computing platform, and can understand the quantitative value of the performance loss of the simulated mold structure in the application scenario, thereby improving the accuracy of the subsequent target mold structure screening. Therefore, a high-strength mold structure design method based on cloud computing provided in an embodiment of the present invention can improve the accuracy of high-strength mold structure design.

[0116] like Figure 2 , which is a functional module diagram of a high-strength mold structure design system based on cloud computing provided by one embodiment of the present invention.

[0117] The high-strength mold structure design system 100 based on cloud computing described in the present invention can be installed in an electronic device. According to the functions implemented, the high-strength mold structure design system 100 based on cloud computing can include a utility amplitude calculation module 101, a structure modeling module 102, a structure strength calculation module 103 and a design scheme determination module 104. The module described in the present invention can also be called a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0118] In this embodiment, the functions of each module / unit are as follows:

[0119] The utility amplitude calculation module 101 is used to obtain a mold structure to be designed, collect mold damage data corresponding to the mold structure, analyze common damage modes and damage structures of the mold structure based on the mold damage data, and calculate the utility amplitude of the common damage modes on the mold structure according to the damage structure;

[0120] The structural modeling module 102 is used to select key damaged structures from the damaged structures according to the utility amplitude, and select high-strength materials of the key damaged structures from a preset cloud material library, calculate the material compatibility index between the high-strength materials, and perform modeling operations on the high-strength materials in a preset cloud computing design platform according to the material compatibility index to obtain a simulated mold structure;

[0121] The structural strength calculation module 103 is used to perform strength test on the simulated mold structure using the virtual testing machine in the cloud computing platform to obtain strength test data and deformation data, draw a mechanical property curve corresponding to the simulated mold structure based on the strength test data, and calculate the structural strength value corresponding to the key damaged structure according to the mechanical property curve and the deformation data;

[0122] The design scheme determination module 104 is used to determine the application scenario of the mold structure, calculate the performance attenuation value of the simulated mold structure in the application scenario in the cloud computing platform, combine the structural strength value and the performance attenuation value, screen out the target mold structure from the simulated mold structure, and determine the design scheme corresponding to the mold structure based on the target mold structure.

[0123] In detail, each module described in the high-strength mold structure design system 100 based on cloud computing described in the embodiment of the present application is used in the same manner as described above. Figure 1 The high-strength mold structure design method based on cloud computing described in the invention has the same technical means and can produce the same technical effects, so it will not be repeated here.

[0124] In the several embodiments provided by the present invention, it should be understood that the provided methods and systems can be implemented in other ways. For example, the method embodiments described above are only illustrative, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

[0125] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A high-strength mold structure design method based on cloud computing, characterized in that: The method comprises: Acquire a mold structure to be designed, collect mold damage data corresponding to the mold structure, analyze common damage modes and damage structures of the mold structure based on the mold damage data, and calculate the effect of the common damage modes on the mold structure according to the damage structure; According to the utility amplitude, a key damaged structure is selected from the damaged structure, and a high-strength material of the key damaged structure is selected from a preset cloud material library, and a material compatibility index between the high-strength materials is calculated. According to the material compatibility index, a modeling operation is performed on the high-strength material in a preset cloud computing design platform to obtain a simulated mold structure; Performing strength testing on the simulated mold structure by using a virtual testing machine in the cloud computing platform to obtain strength test data and deformation data, drawing a mechanical property curve corresponding to the simulated mold structure based on the strength test data, and calculating a structural strength value corresponding to the key damaged structure according to the mechanical property curve and the deformation data; In determining the application scenario of the mold structure, the performance attenuation value of the simulated mold structure in the application scenario is calculated in the cloud computing platform, and the target mold structure is screened out from the simulated mold structure in combination with the structural strength value and the performance attenuation value. According to the target mold structure, the design scheme corresponding to the mold structure is determined.

2. A high-strength mold structure design method based on cloud computing as claimed in claim 1, characterized in that: The common damage modes and damage structures of the mold structure are analyzed based on the mold damage data, including: Identifying damage information in the mold damage data, and calculating information entropy corresponding to the damage information; According to the information entropy, the damage information is filtered to obtain target damage information; Performing feature extraction on the target damage information to obtain feature information, and extracting key characters from the feature information; Based on the key characters, the common damage modes and damage structures of the mold structure are analyzed.

3. The high-strength mold structure design method based on cloud computing as claimed in claim 1, characterized in that: The calculating, based on the damaged structure, the effect magnitude of the common damage mode on the mold structure comprises: Querying the design purpose of the mold structure, and analyzing the functional attributes of the mold structure according to the design purpose; Clarifying the structural function of the damaged structure in the mold structure, and calculating the functional correlation coefficient between the functional attribute and the structural function; Quantifying the functional attribute and the structural function respectively to obtain a first quantization value and a second quantization value; The functional correlation coefficient, the first quantitative value, and the second quantitative value are combined to calculate the effectiveness of the common damage mode on the mold structure.

4. A high-strength mold structure design method based on cloud computing as claimed in claim 3, characterized in that: The calculating of the functional correlation coefficient between the functional attribute and the structural function comprises: Performing vectorization processing on the functional attribute and the structural function respectively to obtain a first functional vector and a second functional vector; Performing feature extraction on the first function vector and the second function vector respectively to obtain a first feature vector and a second feature vector; Calculating a vector similarity between the first feature vector and the second feature vector; According to the vector similarity, identifying common feature vectors in the first feature vector and the second feature vector; Respectively counting the numbers of vectors corresponding to the common eigenvector, the first eigenvector, and the second eigenvector to obtain a first vector number, a second vector number, and a third vector number; In combination with the first vector number, the second vector number and the third vector number, the functional correlation coefficient between the functional attribute and the structural function is calculated by the following formula: Among them, A represents the functional correlation coefficient between functional attributes and structural functions, a represents the first vector number, b represents the second vector number, and d represents the third vector number.

5. The high-strength mold structure design method based on cloud computing according to claim 1, characterized in that: The calculating of the material compatibility index between the high-strength materials comprises: Obtain material parameter information and parameter type corresponding to the high-strength material, and query key parameter indicators of the high-strength material; Analyzing the correlation between the key parameter indicators and the parameter types; According to the correlation, extracting material characteristic parameters and characteristic parameter values ​​corresponding to the high-strength material from the material parameter information; The material compatibility index between the high-strength materials is calculated by combining the material characteristic parameters and the characteristic parameter values.

6. The high-strength mold structure design method based on cloud computing as claimed in claim 5, characterized in that: The combining the material characteristic parameter and the characteristic parameter value to calculate the material compatibility index between the high-strength materials includes: Dispatching historical processing data of the high-strength material, and setting a parameter difference threshold between characteristic parameters of the material according to the historical processing data; According to the parameter difference threshold and the characteristic parameter value, the parameter fit between the material characteristic parameters is calculated by the following formula: Among them, D represents the parameter fit between material characteristic parameters, B a Indicates the ath parameter value in the characteristic parameter value, B a+1 Indicates the a+1th parameter value in the characteristic parameter value, β a，a+1 Indicates the parameter difference threshold corresponding to the a-th and a+1-th parameter values ​​in the characteristic parameter value; The parameter weights corresponding to the material characteristic parameters are allocated, and the material compatibility index between the high-strength materials is calculated by combining the parameter weights and the parameter compatibility by the following formula: Among them, E represents the material fit index between high-strength materials, D i Indicates the parameter fit corresponding to the i-th material characteristic parameter, C i It represents the parameter weight corresponding to the i-th material characteristic parameter, i represents the serial number of the material characteristic parameter, and t represents the total number of parameters of the material characteristic parameter.

7. The high-strength mold structure design method based on cloud computing according to claim 1, characterized in that: Drawing a mechanical property curve corresponding to the simulated mold structure based on the strength test data includes: Performing data cleaning on the strength test data to obtain target test data; Performing repair processing on the target test data to obtain repaired test data; Extracting data variables and variable observation values ​​in the repair test data; Based on the data variables and the variable observation values, a mechanical property curve corresponding to the simulated mold structure is drawn.

8. The high-strength mold structure design method based on cloud computing according to claim 1, characterized in that: The calculating, based on the mechanical property curve and the deformation data, a structural strength value corresponding to the key damaged structure comprises: Reading the yield threshold corresponding to the simulated mold structure from the mechanical characteristic curve; Calculating the mold deformation amount corresponding to the simulated mold structure according to the deformation data; Fitting the mechanical property curve to obtain a strain hardening coefficient and a plastic strengthening index; Combining the yield threshold, the mold deformation, the strain hardening coefficient and the plastic strengthening index, the structural strength value corresponding to the key damaged structure is calculated by the following formula: Among them, F represents the structural strength value corresponding to the key damage structure, μ represents the strain hardening coefficient, ω0 represents the yield threshold, γ represents the mold deformation, and e represents the plastic strengthening index.

9. The high-strength mold structure design method based on cloud computing according to claim 1, characterized in that: The calculating, in the cloud computing platform, the performance attenuation value of the simulated mold structure in the application scenario includes: Collecting application environment data in the application scenario, and analyzing environmental impact factors in the application environment data that act on the simulated mold structure; According to the environmental influencing factors, setting the simulation boundary conditions of the simulated mold structure; According to the simulation boundary conditions, the simulated mold structure is simulated using finite element analysis software in the cloud computing platform to obtain a simulated mold structure; In combination with the simulated mold structure, the performance attenuation value of the simulated mold structure in the application scenario is calculated.

10. A high-strength mold structure design system based on cloud computing, characterized in that: The system comprises: A utility amplitude calculation module is used to obtain a mold structure to be designed, collect mold damage data corresponding to the mold structure, analyze common damage modes and damage structures of the mold structure based on the mold damage data, and calculate the utility amplitude of the common damage modes on the mold structure according to the damage structure; A structural modeling module, for selecting key damaged structures from the damaged structures according to the utility amplitude, selecting high-strength materials of the key damaged structures from a preset cloud material library, calculating material compatibility indexes between the high-strength materials, and modeling the high-strength materials in a preset cloud computing design platform according to the material compatibility indexes to obtain a simulated mold structure; A structural strength calculation module, used to perform a strength test on the simulated mold structure using a virtual testing machine in the cloud computing platform to obtain strength test data and deformation data, draw a mechanical property curve corresponding to the simulated mold structure based on the strength test data, and calculate a structural strength value corresponding to the key damaged structure according to the mechanical property curve and the deformation data; The design scheme determination module is used to determine the application scenario of the mold structure, calculate the performance attenuation value of the simulated mold structure in the application scenario in the cloud computing platform, combine the structural strength value and the performance attenuation value, screen out the target mold structure from the simulated mold structure, and determine the design scheme corresponding to the mold structure based on the target mold structure.

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