A method and system for optimizing a machining process of an engine connecting rod

Abstract

The application discloses an engine connecting rod machining process optimization method and system, and relates to the connecting rod machining control field, wherein the method comprises the following steps: obtaining first connecting rod application characteristic information; performing engine connecting rod performance demand analysis based on the first connecting rod application characteristic information to obtain first engine connecting rod performance demand; performing performance difference identification based on connecting rod blank performance information and the first engine connecting rod performance demand to obtain a first performance difference; if the first performance difference is greater than or equal to a preset performance difference, generating a first connecting rod blank performance adjustment instruction; and performing heat treatment adjustment on the first engine connecting rod blank according to a connecting rod blank heat treatment performance adjustment algorithm and a connecting rod blank basic information set. The technical problem of low heat treatment control adaptability, poor accuracy of the engine connecting rod blank in the prior art, and poor machining effect of the engine connecting rod are solved.

Description

Technical Field

[0001] This invention relates to the field of connecting rod machining control, and more specifically, to a method and system for optimizing the machining process of engine connecting rods. Background Technology

[0002] Connecting rods are an indispensable part of the engine structure, and the reliable operation of the engine largely depends on the quality of the connecting rods. Heat treatment is one of the key aspects of engine connecting rod machining. Current technologies suffer from low adaptability and accuracy in controlling the heat treatment of engine connecting rod blanks, leading to poor machining results. Summary of the Invention

[0003] This application provides a method and system for optimizing the machining process of engine connecting rods. It solves the technical problem of low adaptability and poor accuracy in heat treatment control of engine connecting rod blanks in existing technologies, which leads to poor machining results. It achieves the technical effect of improving the adaptability and accuracy of heat treatment control for engine connecting rod blanks, thereby improving the machining quality of engine connecting rods.

[0004] In view of the above problems, this application provides a method and system for optimizing the machining process of engine connecting rods.

[0005] In a first aspect, this application provides a method for optimizing the machining process of an engine connecting rod, wherein the method is applied to an engine connecting rod machining process optimization system, the method comprising: obtaining a first engine connecting rod blank and retrieving a basic information set of the connecting rod blank, wherein the basic information set of the connecting rod blank includes connecting rod blank structural information, connecting rod blank composition information, and connecting rod blank performance information; obtaining multi-dimensional preset connecting rod application indicators, wherein the multi-dimensional preset connecting rod application indicators include connecting rod application hard indicators and connecting rod application soft indicators; and performing engine connecting rod application information collection of the first engine connecting rod blank according to the multi-dimensional preset connecting rod application indicators to obtain the first connecting rod application characteristics. The process involves: identifying engine connecting rod performance requirements based on the first connecting rod application feature information; analyzing the first engine connecting rod performance requirements based on the connecting rod blank performance information and the first engine connecting rod performance requirements; identifying a first performance difference based on the connecting rod blank performance information and the first engine connecting rod performance requirements; determining whether the first performance difference is less than a preset performance difference; if the first performance difference is greater than or equal to the preset performance difference, generating a first connecting rod blank performance adjustment command; activating a connecting rod blank heat treatment performance adjustment algorithm based on the first connecting rod blank performance adjustment command; and performing heat treatment adjustment on the first engine connecting rod blank based on the connecting rod blank heat treatment performance adjustment algorithm and the connecting rod blank basic information set.

[0006] Secondly, this application also provides a machining process optimization system for engine connecting rods, wherein the system includes: a connecting rod blank information retrieval module, which is used to obtain a first engine connecting rod blank and retrieve a basic information set of the first engine connecting rod blank, wherein the basic information set of the connecting rod blank includes connecting rod blank structural information, connecting rod blank composition information, and connecting rod blank performance information; a connecting rod application index acquisition module, which is used to obtain multi-dimensional preset connecting rod application indices, wherein the multi-dimensional preset connecting rod application indices include connecting rod application hard indices and connecting rod application soft indices; a connecting rod application information acquisition module, which is used to perform engine connecting rod application information acquisition of the first engine connecting rod blank according to the multi-dimensional preset connecting rod application indices to obtain first connecting rod application feature information; and a connecting rod performance requirement analysis module, which analyzes the connecting rod performance requirement... The system comprises the following modules: an analysis module for analyzing engine connecting rod performance requirements based on the first connecting rod application feature information to obtain the first engine connecting rod performance requirements; a performance differentiation identification module for identifying performance differentiation based on the connecting rod blank performance information and the first engine connecting rod performance requirements to obtain a first performance differentiation; a judgment module for determining whether the first performance differentiation is less than a preset performance differentiation; an adjustment command generation module for generating a first connecting rod blank performance adjustment command if the first performance differentiation is greater than or equal to the preset performance differentiation; and a heat treatment adjustment module for activating a connecting rod blank heat treatment performance adjustment algorithm according to the first connecting rod blank performance adjustment command, and performing heat treatment adjustment on the first engine connecting rod blank according to the connecting rod blank heat treatment performance adjustment algorithm and the connecting rod blank basic information set.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages: The engine connecting rod application information of the first engine connecting rod blank is collected according to multi-dimensional preset connecting rod application indicators to obtain the application feature information of the first connecting rod. The engine connecting rod performance requirements are analyzed based on the application feature information to obtain the performance requirements of the first engine connecting rod. Performance differentiation is identified based on the connecting rod blank performance information and the first engine connecting rod performance requirements to obtain a first performance differentiation score. It is then determined whether the first performance differentiation score is less than a preset performance differentiation score. If the first performance differentiation score is greater than or equal to the preset performance differentiation score, a performance adjustment command for the first connecting rod blank is generated. The heat treatment performance adjustment algorithm for the connecting rod blank is activated, and the heat treatment of the first engine connecting rod blank is adjusted according to the heat treatment performance adjustment algorithm and the basic information set of the connecting rod blank. This achieves the technical effect of improving the adaptability and accuracy of heat treatment control of the engine connecting rod blank, thereby improving the processing quality of the engine connecting rod.

[0008] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0009] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings of the embodiments of the present invention will be briefly described below. Obviously, the drawings described below only relate to some embodiments of the present invention, and are not intended to limit the present invention.

[0010] Figure 1 This is a flowchart illustrating a method for optimizing the machining process of an engine connecting rod according to this application. Figure 2 This is a schematic diagram of the machining process optimization system for an engine connecting rod according to this application. Detailed Implementation

[0011] This application provides a method and system for optimizing the machining process of engine connecting rods. It solves the technical problem of low adaptability and accuracy in the heat treatment control of engine connecting rod blanks in existing technologies, which leads to poor machining results. It achieves the technical effect of improving the adaptability and accuracy of heat treatment control for engine connecting rod blanks, thereby improving the machining quality of engine connecting rods.

[0012] Example 1

[0013] Please see the appendix Figure 1 This application provides a method for optimizing the machining process of an engine connecting rod, wherein the method is applied to an engine connecting rod machining process optimization system, and the method specifically includes the following steps: Obtain the first engine connecting rod blank and retrieve the connecting rod blank basic information set of the first engine connecting rod blank, wherein the connecting rod blank basic information set includes connecting rod blank structural information, connecting rod blank composition information and connecting rod blank performance information; Obtain multi-dimensional preset link application indicators, wherein the multi-dimensional preset link application indicators include link application hard indicators and link application soft indicators; Based on the multi-dimensional preset connecting rod application indicators, the engine connecting rod application information of the first engine connecting rod blank is collected to obtain the first connecting rod application feature information; The system connects to the aforementioned engine connecting rod processing optimization system and reads the basic information set of the first engine connecting rod blank. Simultaneously, it collects engine connecting rod application information from the first engine connecting rod blank according to multi-dimensional preset connecting rod application indicators to obtain the first connecting rod application characteristic information. The first engine connecting rod blank can be any engine connecting rod blank that undergoes intelligent heat treatment adjustment using the aforementioned engine connecting rod processing optimization system. The basic information set of the connecting rod blank includes connecting rod blank structural information, connecting rod blank composition information, and connecting rod blank performance information. The connecting rod blank structural information includes the dimensional parameters and structural parameters corresponding to the first engine connecting rod blank. The connecting rod blank composition information includes the component composition parameters corresponding to the first engine connecting rod blank. The connecting rod blank performance information includes multiple performance parameters such as strength parameters, hardness parameters, plasticity parameters, and toughness parameters corresponding to the first engine connecting rod blank. The multi-dimensional preset connecting rod application indicators include hard indicators and soft indicators. The hard indicators refer to the application equipment indicators of the engine connecting rod. Connecting rod application soft indicators refer to the application environment indicators of engine connecting rods. The application characteristic information of the first connecting rod includes the application equipment indicator information and application environment indicator information corresponding to the first engine connecting rod blank. The application equipment indicator information includes engine parameters such as the number of engine cylinders, engine cooling method, number of engine valves, engine displacement, engine power, and engine torque corresponding to the first engine connecting rod blank. The application environment indicator information includes engine connecting rod operating environment parameters such as operating temperature, operating pressure, operating humidity, corrosiveness of the operating environment, and friction of the operating environment.

[0014] Based on the application feature information of the first connecting rod, the performance requirements of the engine connecting rod are analyzed to obtain the performance requirements of the first engine connecting rod. Specifically, based on the application feature information of the first connecting rod, the engine connecting rod performance requirements are analyzed to obtain the first engine connecting rod performance requirements, including: Multiple sample link application feature information and multiple sample link performance requirements are obtained, and the multiple sample link application feature information and the multiple sample link performance requirements have corresponding identified sample feature relationships; Set the feature information of the sample link as the input variable for link performance analysis, and set the performance requirements of the sample link as the output variable for link performance analysis. Based on the application feature information and performance requirements of the multiple sample links, multiple link performance analysis input variable parameters and multiple link performance analysis output variable parameters are obtained. Based on the knowledge graph, a link performance requirement analysis graph is constructed according to the sample feature relationship, the link performance analysis input variables, the link performance analysis output variables, the multiple link performance analysis input variable parameters, and the multiple link performance analysis output variable parameters; The first connecting rod application feature information is input into the connecting rod performance requirement analysis map to generate the first engine connecting rod performance requirements.

[0015] The system connects to the processing optimization system for engine connecting rods, retrieving application feature information and performance requirements from multiple sample connecting rods. Furthermore, there is a correspondence between the application feature information and performance requirements of these sample connecting rods. Each sample connecting rod's application feature information includes historical application equipment index information and historical application environment index information corresponding to the historical engine connecting rod blank. Each sample connecting rod's performance requirements include multiple historical performance requirement parameters, such as strength requirement parameters, hardness requirement parameters, plasticity requirement parameters, and toughness requirement parameters, corresponding to the sample connecting rod's application feature information. The sample feature relationship represents the correspondence between the application feature information and performance requirements of the multiple sample connecting rods.

[0016] Furthermore, the sample link application feature information is set as the input variable for link performance analysis, and the sample link performance requirements are set as the output variable for link performance analysis. Multiple sample link application feature information are recorded as multiple link performance analysis input variable parameters, and multiple sample link performance requirements are recorded as multiple link performance analysis output variable parameters. Then, according to the sample feature relationships, the link performance analysis input variables, link performance analysis output variables, multiple link performance analysis input variable parameters, and multiple link performance analysis output variable parameters are arranged to obtain a link performance requirement analysis graph. The first link application feature information is input into the link performance requirement analysis graph to obtain the first engine link performance requirements. The link performance requirement analysis graph is a knowledge graph constructed from the link performance analysis input variables, link performance analysis output variables, multiple link performance analysis input variable parameters, and multiple link performance analysis output variable parameters. A knowledge graph is a way of representing data information. A knowledge graph includes a schema layer and a data layer. The data layer consists of a series of facts. The schema layer is built on top of the data layer and is mainly used to standardize the expression of the series of facts in the data layer. The connecting rod performance requirement analysis map includes the input variables, output variables, and multiple input and output variable parameters arranged according to sample feature relationships. The performance requirements for the first engine connecting rod include multiple performance requirement parameters corresponding to the application feature information of the first connecting rod, such as engine connecting rod strength, engine connecting rod hardness, engine connecting rod plasticity, and engine connecting rod toughness.

[0017] Based on the performance information of the connecting rod blank and the performance requirements of the first engine connecting rod, a performance difference is identified to obtain a first performance difference. Specifically, the performance differentiation is identified based on the performance information of the connecting rod blank and the performance requirements of the first engine connecting rod to obtain a first performance differentiation, including: Obtain a database of records identifying the differences in linkage performance; The link performance discrimination recognition record library is trained using a BP neural network to generate a performance discrimination recognition network that meets the preset convergence conditions. The performance information of the connecting rod blank and the performance requirements of the first engine connecting rod are input into the performance discrimination recognition network to generate the first performance discrimination.

[0018] Determine whether the first performance difference is less than the preset performance difference; If the first performance difference is greater than or equal to the preset performance difference, a first connecting rod blank performance adjustment command is generated. The system connects to the aforementioned engine connecting rod machining process optimization system and retrieves the connecting rod performance differentiation identification record library. The connecting rod performance differentiation identification record library includes multiple connecting rod performance differentiation identification records. Each connecting rod performance differentiation identification record includes historical connecting rod blank performance information, historical engine connecting rod performance requirements, and the historical performance differentiation corresponding to the historical connecting rod blank performance information and historical engine connecting rod performance requirements.

[0019] Furthermore, the link performance discrimination recognition record library is trained using a BP neural network. Specifically, the BP neural network continuously learns and trains itself on the link performance discrimination recognition record library. When the output accuracy of the BP neural network meets the preset convergence condition, a performance discrimination recognition network is obtained. The BP neural network is a multi-layer feedforward neural network trained using an error backpropagation algorithm. The error backpropagation algorithm means that the BP neural network can perform forward and backward calculations. During forward calculation, the input information is processed layer by layer from the input layer through multiple neurons, and then forwards to the output layer. The state of each neuron only affects the state of the next layer. If the desired output cannot be obtained at the output layer, backward calculation is performed, returning the error signal along the original connection path. By modifying the weights of each neuron, the error signal is minimized. The preset convergence condition includes an output accuracy range pre-set by the aforementioned engine link processing optimization system. The performance discrimination recognition network is a BP neural network trained from the link performance discrimination recognition record library and meets the preset convergence condition. The performance discrimination recognition network includes an input layer, a hidden layer, and an output layer.

[0020] Furthermore, the performance information of the connecting rod blank and the performance requirements of the first engine connecting rod are input into a performance difference recognition network to obtain a first performance difference, and a judgment is made on whether the first performance difference is less than a preset performance difference. If the first performance difference is greater than or equal to the preset performance difference, a performance adjustment command for the first connecting rod blank is automatically generated. The first performance difference is data information used to characterize the difference between the performance information of the connecting rod blank and the performance requirements of the first engine connecting rod. The greater the difference between the performance information of the connecting rod blank and the performance requirements of the first engine connecting rod, the greater the corresponding first performance difference. The preset performance difference includes a performance difference threshold predetermined by the processing technology optimization system for the aforementioned engine connecting rod. The first connecting rod blank performance adjustment command is instruction information used to characterize that the first performance difference is greater than or equal to the preset performance difference, the difference between the performance information of the connecting rod blank and the performance requirements of the first engine connecting rod is high, and heat treatment adjustment and optimization of the first engine connecting rod blank are required.

[0021] By analyzing the performance requirements of the first connecting rod using the connecting rod performance requirement analysis map, the performance requirements of the first engine connecting rod are determined. In addition, the performance difference is identified by combining the performance information of the connecting rod blank to obtain the first performance difference. The first performance difference is then compared with the preset performance difference to adaptively generate the performance adjustment command of the first connecting rod blank, thereby improving the adaptability of the heat treatment control of the engine connecting rod blank.

[0022] According to the performance adjustment command of the first connecting rod blank, the heat treatment performance adjustment algorithm of the connecting rod blank is activated, and the heat treatment of the first engine connecting rod blank is adjusted according to the heat treatment performance adjustment algorithm of the connecting rod blank and the basic information set of the connecting rod blank.

[0023] The process of adjusting the heat treatment performance of the first engine connecting rod blank according to the heat treatment performance adjustment algorithm and the basic information set of the connecting rod blank includes: Based on the heat treatment process flow of the connecting rod blank, nodes are extracted to obtain A heat treatment process nodes, where A is a positive integer greater than 1. By comparing the performance information of the connecting rod blank with the performance requirements of the first engine connecting rod, the performance differences of the connecting rod blank are obtained. Based on the different properties of the connecting rod blank, data search is performed by traversing the A heat treatment process nodes to obtain the A-dimensional heat treatment process optimization domain. Specifically, based on the differential performance of the connecting rod blank, a data search is performed traversing the A heat treatment process nodes to obtain an A-dimensional heat treatment process optimization domain, including: Based on the A heat treatment process nodes, extract the a-th heat treatment process node, where a is a positive integer belonging to A; Based on the different performance of the connecting rod blank and the heat treatment process node a, the heat treatment records of the engine connecting rod blank are collected to obtain the heat treatment record library of node a blank. Obtain the heat treatment variable set of node a for the a-th heat treatment process node; Based on the set of heat treatment variables for node a, clustering trigger domains are performed on the heat treatment record library of blanks for node a to obtain multiple trigger domains for node a variables. The multiple trigger domains of the a-node variables are traversed and random values ​​are taken multiple times to generate the heat treatment process optimization domain of the a-th node, and the heat treatment process optimization domain of the a-th node is added to the A-dimensional heat treatment process optimization domain.

[0024] The connecting rod blank heat treatment performance adjustment algorithm is activated according to the first connecting rod blank performance adjustment command, and the heat treatment of the first engine connecting rod blank is adjusted according to the connecting rod blank heat treatment performance adjustment algorithm and the connecting rod blank basic information set. The connecting rod blank heat treatment performance adjustment algorithm includes: connecting to the machining process optimization system of the aforementioned engine connecting rod, and reading the connecting rod blank heat treatment process flow. The connecting rod blank heat treatment process flow includes A heat treatment process nodes, where A is a positive integer greater than 1. The A heat treatment process nodes include normalizing, quenching, tempering, etc. Simultaneously, the connecting rod blank performance information is compared with the first engine connecting rod performance requirements to obtain the connecting rod blank differential performance. The connecting rod blank differential performance includes performance difference parameter information between the connecting rod blank performance information and the first engine connecting rod performance requirements.

[0025] Furthermore, A heat treatment process nodes are randomly selected to obtain the a-th heat treatment process node. Connecting to the aforementioned engine connecting rod machining process optimization system, heat treatment records of the engine connecting rod blanks are collected based on the differences in the connecting rod blank properties and the a-th heat treatment process node, resulting in an a-node blank heat treatment record library. Here, the a-th heat treatment process node can be any one of the A heat treatment process nodes. And a is a positive integer belonging to A. The a-node blank heat treatment record library includes multiple node blank heat treatment records corresponding to the differences in the connecting rod blank properties and the a-th heat treatment process node. Each node blank heat treatment record includes historical connecting rod blank differences in properties and multiple historical blank heat treatment parameters corresponding to the a-th heat treatment process node. For example, when the a-th heat treatment process node is normalizing, each node blank heat treatment record includes historical normalizing heating temperature parameters, historical normalizing holding time parameters, historical normalizing cooling medium parameters, historical normalizing cooling rate parameters, etc., corresponding to the historical differences in the connecting rod blank properties and the a-th heat treatment process node.

[0026] Furthermore, the machining process optimization system for the aforementioned engine connecting rod is connected to read the heat treatment variable set corresponding to the a-th heat treatment process node. The a-th node heat treatment variable set includes multiple node control variables corresponding to the a-th heat treatment process node. For example, when the a-th heat treatment process node is normalizing, the corresponding multiple node control variables include normalizing heating temperature, normalizing holding time, normalizing cooling medium, normalizing cooling rate, etc.

[0027] Furthermore, clustering trigger domains are defined for the heat treatment record library of node a blanks according to the heat treatment variable set of node a. Specifically, the historical heat treatment parameters of multiple nodes in the heat treatment record library of node a blanks are first clustered according to the multiple node control variables within the heat treatment variable set of node a, resulting in multiple node control variable parameter records. Then, the value ranges of these multiple node control variable parameter records are extracted to obtain multiple trigger domains for node a variables. Each node control variable parameter record includes multiple historical heat treatment parameters of the same node control variable within the heat treatment record library of node a blanks. Each trigger domain for node a variables includes the value range information corresponding to each node control variable parameter record.

[0028] Furthermore, multiple random values ​​are taken from the trigger domains of multiple 'a' node variables to obtain multiple 'a' node control decisions. These multiple 'a' node control decisions are then added to the heat treatment process optimization domain of the 'a' node, and the heat treatment process optimization domain of the 'a' node is added to the A-dimensional heat treatment process optimization domain. Each 'a' node control decision includes a randomly selected parameter within each 'a' node variable trigger domain. For example, when the 'a' node heat treatment process is normalizing, each 'a' node control decision includes a random normalizing heating temperature parameter, a random normalizing holding time parameter, a random normalizing cooling medium parameter, and a random normalizing cooling rate parameter, etc., corresponding to multiple 'a' node variable trigger domains. The heat treatment process optimization domain of the 'a' node includes multiple 'a' node control decisions. The A-dimensional heat treatment process optimization domain includes A node heat treatment process optimization domains corresponding to A heat treatment process nodes. Each node heat treatment process optimization domain includes multiple node control decisions corresponding to each heat treatment process node. Moreover, the A node heat treatment process optimization domains are obtained in the same way as the heat treatment process optimization domain of the 'a' node, and will not be described further here.

[0029] Based on the A-dimensional heat treatment process optimization domain, the heat treatment decision for the first connecting rod blank is extracted; Activate the blank performance prediction submodule, combine the basic information set of the connecting rod blank to predict the heat treatment performance optimization degree of the heat treatment decision of the first connecting rod blank, and generate the first decision performance optimization degree. The module for activating the blank performance prediction submodule, combined with the basic information set of the connecting rod blank, predicts the heat treatment performance optimization degree of the heat treatment decision for the first connecting rod blank, and generates a first decision performance optimization degree, including: The blank performance prediction submodule includes a blank performance fitting unit and a blank performance optimization prediction unit. Based on the structural information and composition information of the connecting rod blank, the performance is fitted according to the blank performance fitting unit and the first connecting rod blank heat treatment decision to obtain the first decision blank fitting performance. The first decision blank fitting performance and the connecting rod blank performance information are input into the blank performance optimization prediction unit to obtain the first decision performance optimization degree.

[0030] Determine whether the performance optimization degree of the first decision meets the preset performance optimization degree; If the first decision performance optimization degree meets the preset performance optimization degree, a connecting rod blank heat treatment scheme is generated according to the first connecting rod blank heat treatment decision, and the first engine connecting rod blank is heat treated and adjusted according to the connecting rod blank heat treatment scheme.

[0031] The algorithm for adjusting the heat treatment performance of the connecting rod blank also includes: traversing the A-dimensional heat treatment process optimization domain to randomly extract and obtain the heat treatment decision for the first connecting rod blank. The first connecting rod blank heat treatment decision includes a random node control decision within each node of the A-dimensional heat treatment process optimization domain. Simultaneously, the blank performance prediction submodule is activated, which includes a blank performance fitting unit and a blank performance optimization degree prediction unit.

[0032] The structural and compositional information of the connecting rod blank is uploaded to the blank performance fitting unit. The blank performance fitting unit models the connecting rod blank according to the structural and compositional information, obtaining the connecting rod blank model. Then, the heat treatment decision for the first connecting rod blank is input into the blank performance fitting unit. The blank performance fitting unit performs simulated heat treatment on the connecting rod blank model according to the first connecting rod blank heat treatment decision, obtaining the first decision blank fitting performance. The blank performance fitting unit includes a digital twin platform as used in existing technologies. The connecting rod blank model is a three-dimensional simulation model corresponding to the connecting rod blank structural and compositional information. The first decision blank fitting performance includes multiple performance information such as strength, hardness, plasticity, and toughness of the connecting rod blank model after simulated heat treatment according to the first connecting rod blank heat treatment decision.

[0033] Furthermore, the first decision blank fitting performance and connecting rod blank performance information are input into the blank performance optimization prediction unit to obtain the first decision performance optimization degree, and it is determined whether the first decision performance optimization degree meets the preset performance optimization degree. If the first decision performance optimization degree meets the preset performance optimization degree, the first connecting rod blank heat treatment decision is output as a connecting rod blank heat treatment scheme, and the heat treatment control of the first engine connecting rod blank is performed according to the connecting rod blank heat treatment scheme, thereby improving the heat treatment effect of the engine connecting rod blank. The first decision performance optimization degree is data information used to characterize the consistency between the first decision blank fitting performance and the connecting rod blank performance information. The higher the consistency between the first decision blank fitting performance and the connecting rod blank performance information, the greater the corresponding first decision performance optimization degree. The preset performance optimization degree includes the decision performance optimization degree range pre-set and determined by the processing technology optimization system of the aforementioned engine connecting rod.

[0034] For example, when constructing the blank performance optimization prediction unit, historical data is queried according to the first decision blank fitting performance and connecting rod blank performance information to obtain multiple blank performance optimization analysis data. Each blank performance optimization analysis data includes historical decision blank fitting performance, historical connecting rod blank performance information, and the historical decision performance optimization degree corresponding to the historical decision blank fitting performance and historical connecting rod blank performance information. Then, the multiple blank performance optimization analysis data are continuously self-trained and learned to a convergent state using a fully connected neural network to obtain the blank performance optimization prediction unit. A fully connected neural network is an artificial neural network structure with a relatively simple connection method. The blank performance optimization prediction unit includes an input layer, a hidden layer, and an output layer.

[0035] The determination of whether the first decision performance optimization degree meets the preset performance optimization degree includes: If the first decision performance optimization degree does not meet the preset performance optimization degree, the second connecting rod blank heat treatment decision is extracted according to the A-dimensional heat treatment process optimization domain. Activate the blank performance prediction submodule, combine the basic information set of the connecting rod blank to predict the heat treatment performance optimization degree of the heat treatment decision of the second connecting rod blank, and generate the second decision performance optimization degree. Determine whether the second decision performance optimization degree meets the preset performance optimization degree; If the second decision performance optimization degree meets the preset performance optimization degree, the heat treatment scheme for the connecting rod blank is generated according to the second connecting rod blank heat treatment decision; If the second decision performance optimization degree does not meet the preset performance optimization degree, the optimization domain of the A-dimensional heat treatment process continues to be iteratively optimized until the heat treatment scheme of the connecting rod blank is generated.

[0036] The heat treatment performance adjustment algorithm for the connecting rod blank also includes: if the first decision performance optimization degree does not meet the preset performance optimization degree, continuing to traverse the A-dimensional heat treatment process optimization domain for random extraction to obtain the second connecting rod blank heat treatment decision. Based on the blank performance prediction submodule, the heat treatment performance optimization degree of the second connecting rod blank heat treatment decision is predicted to obtain the second decision performance optimization degree. The second connecting rod blank heat treatment decision includes a random node control decision within each node of the A-dimensional heat treatment process optimization domain. Furthermore, the second connecting rod blank heat treatment decision is different from the first connecting rod blank heat treatment decision. The second decision performance optimization degree is obtained in the same way as the first decision performance optimization degree, and will not be described again here.

[0037] Next, it is determined whether the second decision performance optimization degree meets the preset performance optimization degree. If the second decision performance optimization degree meets the preset performance optimization degree, the heat treatment decision for the second connecting rod blank is output as the heat treatment scheme for the connecting rod blank. If the second decision performance optimization degree does not meet the preset performance optimization degree, iterative optimization continues in the A-dimensional heat treatment process optimization domain until a heat treatment scheme for the connecting rod blank that meets the preset performance optimization degree is obtained. By using the connecting rod blank heat treatment performance adjustment algorithm to optimize the heat treatment control decision for the first engine connecting rod blank, the accuracy of heat treatment control for the engine connecting rod blank is improved, thereby improving the heat treatment quality of the engine connecting rod blank.

[0038] In summary, the optimized machining process method for engine connecting rods provided in this application has the following technical effects: 1. Based on multi-dimensional preset connecting rod application indicators, engine connecting rod application information is collected from the first engine connecting rod blank to obtain its application characteristic information. The engine connecting rod performance requirements are analyzed based on these characteristics to obtain its performance requirements. Performance differentiation is identified based on the connecting rod blank performance information and the first engine connecting rod performance requirements to obtain a first performance differentiation score. It is then determined whether the first performance differentiation score is less than a preset performance differentiation score. If the first performance differentiation score is greater than or equal to the preset score, a performance adjustment command for the first connecting rod blank is generated. The heat treatment performance adjustment algorithm for the connecting rod blank is activated, and heat treatment adjustment is performed on the first engine connecting rod blank based on the algorithm and the connecting rod blank's basic information set. This achieves the technical effect of improving the adaptability and accuracy of heat treatment control for the engine connecting rod blank, thereby enhancing the processing quality of the engine connecting rod.

[0039] 2. By using a heat treatment performance adjustment algorithm for connecting rod blanks to optimize heat treatment control decisions for the first engine connecting rod blank, the accuracy of heat treatment control for the engine connecting rod blank is improved, thereby improving the heat treatment quality of the engine connecting rod blank.

[0040] Example 2

[0041] Based on the same inventive concept as the engine connecting rod machining process optimization method described in the foregoing embodiments, this invention also provides an engine connecting rod machining process optimization system. Please refer to the appendix. Figure 2 The system includes: A connecting rod blank information retrieval module is used to obtain a first engine connecting rod blank and retrieve the connecting rod blank basic information set of the first engine connecting rod blank, wherein the connecting rod blank basic information set includes connecting rod blank structural information, connecting rod blank composition information and connecting rod blank performance information; A linkage application index acquisition module is used to acquire multi-dimensional preset linkage application indices, wherein the multi-dimensional preset linkage application indices include linkage application hard indices and linkage application soft indices. A connecting rod application information acquisition module is used to perform engine connecting rod application information acquisition of the first engine connecting rod blank according to the multi-dimensional preset connecting rod application index, and obtain the first connecting rod application feature information. A connecting rod performance requirement analysis module is used to analyze the engine connecting rod performance requirements based on the first connecting rod application feature information to obtain the first engine connecting rod performance requirements. A performance differentiation identification module is used to identify performance differentiation based on the performance information of the connecting rod blank and the performance requirements of the first engine connecting rod, and obtain a first performance differentiation. The judgment module is used to determine whether the first performance difference is less than a preset performance difference. An adjustment instruction generation module is used to generate a first connecting rod blank performance adjustment instruction if the first performance difference is greater than or equal to the preset performance difference. A heat treatment adjustment module is configured to activate a heat treatment performance adjustment algorithm for the connecting rod blank according to the performance adjustment command of the first connecting rod blank, and to perform heat treatment adjustment on the first engine connecting rod blank according to the heat treatment performance adjustment algorithm and the basic information set of the connecting rod blank.

[0042] Furthermore, the system also includes an engine connecting rod performance requirement generation module to perform the following steps: Multiple sample link application feature information and multiple sample link performance requirements are obtained, and the multiple sample link application feature information and the multiple sample link performance requirements have corresponding identified sample feature relationships; Set the feature information of the sample link as the input variable for link performance analysis, and set the performance requirements of the sample link as the output variable for link performance analysis. Based on the application feature information and performance requirements of the multiple sample links, multiple link performance analysis input variable parameters and multiple link performance analysis output variable parameters are obtained. Based on the knowledge graph, a link performance requirement analysis graph is constructed according to the sample feature relationship, the link performance analysis input variables, the link performance analysis output variables, the multiple link performance analysis input variable parameters, and the multiple link performance analysis output variable parameters; The first connecting rod application feature information is input into the connecting rod performance requirement analysis map to generate the first engine connecting rod performance requirements.

[0043] Furthermore, the system also includes a performance differentiation generation module to perform the following steps: Obtain a database of records identifying the differences in linkage performance; The link performance discrimination recognition record library is trained using a BP neural network to generate a performance discrimination recognition network that meets the preset convergence conditions. The performance information of the connecting rod blank and the performance requirements of the first engine connecting rod are input into the performance discrimination recognition network to generate the first performance discrimination.

[0044] Furthermore, the system also includes a connecting rod blank heat treatment optimization module to perform the following steps: Based on the heat treatment process flow of the connecting rod blank, nodes are extracted to obtain A heat treatment process nodes, where A is a positive integer greater than 1. By comparing the performance information of the connecting rod blank with the performance requirements of the first engine connecting rod, the performance differences of the connecting rod blank are obtained. Based on the different properties of the connecting rod blank, data search is performed by traversing the A heat treatment process nodes to obtain the A-dimensional heat treatment process optimization domain. Based on the A-dimensional heat treatment process optimization domain, the heat treatment decision for the first connecting rod blank is extracted; Activate the blank performance prediction submodule, combine the basic information set of the connecting rod blank to predict the heat treatment performance optimization degree of the heat treatment decision of the first connecting rod blank, and generate the first decision performance optimization degree. Determine whether the performance optimization degree of the first decision meets the preset performance optimization degree; If the first decision performance optimization degree meets the preset performance optimization degree, a connecting rod blank heat treatment scheme is generated according to the first connecting rod blank heat treatment decision, and the first engine connecting rod blank is heat treated and adjusted according to the connecting rod blank heat treatment scheme.

[0045] Furthermore, the system also includes a data search module to perform the following steps: Based on the A heat treatment process nodes, extract the a-th heat treatment process node, where a is a positive integer belonging to A; Based on the different performance of the connecting rod blank and the heat treatment process node a, the heat treatment records of the engine connecting rod blank are collected to obtain the heat treatment record library of node a blank. Obtain the heat treatment variable set of node a for the a-th heat treatment process node; Based on the set of heat treatment variables for node a, clustering trigger domains are performed on the heat treatment record library of blanks for node a to obtain multiple trigger domains for node a variables. The multiple trigger domains of the a-node variables are traversed and random values ​​are taken multiple times to generate the heat treatment process optimization domain of the a-th node, and the heat treatment process optimization domain of the a-th node is added to the A-dimensional heat treatment process optimization domain.

[0046] Furthermore, the system also includes a decision performance optimization generation module to perform the following steps: The blank performance prediction submodule includes a blank performance fitting unit and a blank performance optimization prediction unit. Based on the structural information and composition information of the connecting rod blank, the performance is fitted according to the blank performance fitting unit and the first connecting rod blank heat treatment decision to obtain the first decision blank fitting performance. The first decision blank fitting performance and the connecting rod blank performance information are input into the blank performance optimization prediction unit to obtain the first decision performance optimization degree.

[0047] Furthermore, the system also includes a heat treatment iterative optimization module to perform the following operational steps: If the first decision performance optimization degree does not meet the preset performance optimization degree, the second connecting rod blank heat treatment decision is extracted according to the A-dimensional heat treatment process optimization domain. Activate the blank performance prediction submodule, combine the basic information set of the connecting rod blank to predict the heat treatment performance optimization degree of the heat treatment decision of the second connecting rod blank, and generate the second decision performance optimization degree. Determine whether the second decision performance optimization degree meets the preset performance optimization degree; If the second decision performance optimization degree meets the preset performance optimization degree, the heat treatment scheme for the connecting rod blank is generated according to the second connecting rod blank heat treatment decision; If the second decision performance optimization degree does not meet the preset performance optimization degree, the optimization domain of the A-dimensional heat treatment process continues to be iteratively optimized until the heat treatment scheme of the connecting rod blank is generated.

[0048] The engine connecting rod machining process optimization system provided in this embodiment of the invention can execute the engine connecting rod machining process optimization method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0049] The modules included are divided according to functional logic, but are not limited to the above division, as long as they can achieve the corresponding functions; in addition, the specific names of each functional module are only for easy distinction between each other and are not used to limit the scope of protection of this invention.

[0050] This application provides a method for optimizing the machining process of engine connecting rods. The method is applied to an engine connecting rod machining process optimization system. The method includes: collecting engine connecting rod application information from a first engine connecting rod blank according to multi-dimensional preset connecting rod application indicators to obtain first connecting rod application characteristic information; analyzing the engine connecting rod performance requirements from the first connecting rod application characteristic information to obtain first engine connecting rod performance requirements; identifying performance differentiation based on the connecting rod blank performance information and the first engine connecting rod performance requirements to obtain a first performance differentiation degree; determining whether the first performance differentiation degree is less than a preset performance differentiation degree; if the first performance differentiation degree is greater than or equal to the preset performance differentiation degree, generating a performance adjustment command for the first connecting rod blank; activating a heat treatment performance adjustment algorithm for the connecting rod blank, and adjusting the heat treatment of the first engine connecting rod blank according to the heat treatment performance adjustment algorithm and the basic information set of the connecting rod blank. This solves the technical problem of low adaptability and poor accuracy of heat treatment control for engine connecting rod blanks in the prior art, leading to poor machining results for engine connecting rods. It achieves the technical effect of improving the adaptability and accuracy of heat treatment control for engine connecting rod blanks, thereby improving the machining quality of engine connecting rods.

[0051] Although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments. Without departing from the concept of the present invention, it may include more other equivalent embodiments, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for optimizing the machining process of an engine connecting rod, characterized in that, The method includes: Obtain the first engine connecting rod blank and retrieve the connecting rod blank basic information set of the first engine connecting rod blank, wherein the connecting rod blank basic information set includes connecting rod blank structural information, connecting rod blank composition information and connecting rod blank performance information; Obtain multi-dimensional preset link application indicators, wherein the multi-dimensional preset link application indicators include link application hard indicators and link application soft indicators; Based on the multi-dimensional preset connecting rod application indicators, the engine connecting rod application information of the first engine connecting rod blank is collected to obtain the first connecting rod application feature information; Based on the application feature information of the first connecting rod, the performance requirements of the engine connecting rod are analyzed to obtain the performance requirements of the first engine connecting rod. Based on the performance information of the connecting rod blank and the performance requirements of the first engine connecting rod, a performance difference is identified to obtain a first performance difference. Determine whether the first performance difference is less than the preset performance difference; If the first performance difference is greater than or equal to the preset performance difference, a first connecting rod blank performance adjustment command is generated. According to the first connecting rod blank performance adjustment command, the connecting rod blank heat treatment performance adjustment algorithm is activated, and the first engine connecting rod blank is heat treated and adjusted according to the connecting rod blank heat treatment performance adjustment algorithm and the connecting rod blank basic information set. The first engine connecting rod blank is heat-treated and adjusted according to the heat treatment performance adjustment algorithm of the connecting rod blank and the basic information set of the connecting rod blank, including: Based on the heat treatment process flow of the connecting rod blank, nodes are extracted to obtain A heat treatment process nodes, where A is a positive integer greater than 1. By comparing the performance information of the connecting rod blank with the performance requirements of the first engine connecting rod, the performance differences of the connecting rod blank are obtained. Based on the different properties of the connecting rod blank, data search is performed by traversing the A heat treatment process nodes to obtain the A-dimensional heat treatment process optimization domain. Based on the A-dimensional heat treatment process optimization domain, the heat treatment decision for the first connecting rod blank is extracted; Activate the blank performance prediction submodule, combine the basic information set of the connecting rod blank to predict the heat treatment performance optimization degree of the heat treatment decision of the first connecting rod blank, and generate the first decision performance optimization degree. Determine whether the performance optimization degree of the first decision meets the preset performance optimization degree; If the first decision performance optimization degree meets the preset performance optimization degree, a connecting rod blank heat treatment scheme is generated according to the first connecting rod blank heat treatment decision, and the first engine connecting rod blank is heat treated and adjusted according to the connecting rod blank heat treatment scheme.

2. The method as described in claim 1, characterized in that, Based on the application feature information of the first connecting rod, the engine connecting rod performance requirements are analyzed to obtain the first engine connecting rod performance requirements, including: Multiple sample link application feature information and multiple sample link performance requirements are obtained, and the multiple sample link application feature information and the multiple sample link performance requirements have corresponding identified sample feature relationships; Set the feature information of the sample link as the input variable for link performance analysis, and set the performance requirements of the sample link as the output variable for link performance analysis. Based on the application feature information and performance requirements of the multiple sample links, multiple link performance analysis input variable parameters and multiple link performance analysis output variable parameters are obtained. Based on the knowledge graph, a link performance requirement analysis graph is constructed according to the sample feature relationship, the link performance analysis input variables, the link performance analysis output variables, the multiple link performance analysis input variable parameters, and the multiple link performance analysis output variable parameters; The first connecting rod application feature information is input into the connecting rod performance requirement analysis map to generate the first engine connecting rod performance requirements.

3. The method as described in claim 1, characterized in that, Based on the performance information of the connecting rod blank and the performance requirements of the first engine connecting rod, a performance differentiation is identified to obtain a first performance differentiation, including: Obtain a database of records identifying the differences in linkage performance; The link performance discrimination recognition record library is trained using a BP neural network to generate a performance discrimination recognition network that meets the preset convergence conditions. The performance information of the connecting rod blank and the performance requirements of the first engine connecting rod are input into the performance discrimination recognition network to generate the first performance discrimination.

4. The method as described in claim 1, characterized in that, Based on the performance differences of the connecting rod blank, a data search is performed traversing the A heat treatment process nodes to obtain the A-dimensional heat treatment process optimization domain, including: Based on the A heat treatment process nodes, extract the a-th heat treatment process node, where a is a positive integer belonging to A; Based on the different performance of the connecting rod blank and the heat treatment process node a, the heat treatment records of the engine connecting rod blank are collected to obtain the heat treatment record library of node a blank. Obtain the heat treatment variable set of node a for the a-th heat treatment process node; Based on the set of heat treatment variables for node a, clustering trigger domains are performed on the heat treatment record library of blanks for node a to obtain multiple trigger domains for node a variables. The multiple trigger domains of the a-node variables are traversed and random values ​​are taken multiple times to generate the heat treatment process optimization domain of the a-th node, and the heat treatment process optimization domain of the a-th node is added to the A-dimensional heat treatment process optimization domain.

5. The method as described in claim 1, characterized in that, Activate the blank performance prediction submodule, and predict the heat treatment performance optimization degree of the first connecting rod blank heat treatment decision based on the basic information set of the connecting rod blank, and generate the first decision performance optimization degree, including: The blank performance prediction submodule includes a blank performance fitting unit and a blank performance optimization prediction unit. Based on the structural information and composition information of the connecting rod blank, the performance is fitted according to the blank performance fitting unit and the first connecting rod blank heat treatment decision to obtain the first decision blank fitting performance. The first decision blank fitting performance and the connecting rod blank performance information are input into the blank performance optimization prediction unit to obtain the first decision performance optimization degree.

6. The method as described in claim 1, characterized in that, Determining whether the first decision performance optimization degree meets the preset performance optimization degree includes: If the first decision performance optimization degree does not meet the preset performance optimization degree, the second connecting rod blank heat treatment decision is extracted according to the A-dimensional heat treatment process optimization domain. Activate the blank performance prediction submodule, combine the basic information set of the connecting rod blank to predict the heat treatment performance optimization degree of the heat treatment decision of the second connecting rod blank, and generate the second decision performance optimization degree. Determine whether the second decision performance optimization degree meets the preset performance optimization degree; If the second decision performance optimization degree meets the preset performance optimization degree, the heat treatment scheme for the connecting rod blank is generated according to the second connecting rod blank heat treatment decision; If the second decision performance optimization degree does not meet the preset performance optimization degree, the optimization domain of the A-dimensional heat treatment process continues to be iteratively optimized until the heat treatment scheme of the connecting rod blank is generated.

7. A machining process optimization system for engine connecting rods, characterized in that, The system is used to perform the method according to any one of claims 1 to 6, the system comprising: A connecting rod blank information retrieval module is used to obtain a first engine connecting rod blank and retrieve the connecting rod blank basic information set of the first engine connecting rod blank, wherein the connecting rod blank basic information set includes connecting rod blank structural information, connecting rod blank composition information and connecting rod blank performance information; A linkage application index acquisition module is used to acquire multi-dimensional preset linkage application indices, wherein the multi-dimensional preset linkage application indices include linkage application hard indices and linkage application soft indices. A connecting rod application information acquisition module is used to perform engine connecting rod application information acquisition of the first engine connecting rod blank according to the multi-dimensional preset connecting rod application index, and obtain the first connecting rod application feature information. A connecting rod performance requirement analysis module is used to analyze the engine connecting rod performance requirements based on the first connecting rod application feature information to obtain the first engine connecting rod performance requirements. A performance differentiation identification module is used to identify performance differentiation based on the performance information of the connecting rod blank and the performance requirements of the first engine connecting rod, and obtain a first performance differentiation. The judgment module is used to determine whether the first performance difference is less than a preset performance difference. An adjustment instruction generation module is used to generate a first connecting rod blank performance adjustment instruction if the first performance difference is greater than or equal to the preset performance difference. A heat treatment adjustment module is configured to activate a heat treatment performance adjustment algorithm for the connecting rod blank according to the performance adjustment command of the first connecting rod blank, and to perform heat treatment adjustment on the first engine connecting rod blank according to the heat treatment performance adjustment algorithm and the basic information set of the connecting rod blank.

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