Dry processing and forming analysis method for special-shaped parts made of carbon fiber composite materials

Abstract

The invention relates to a carbon fiber composite material special-shaped part dry method processing forming analysis method, and belongs to the technical field of carbon fiber acquisition dry method processing, and the method comprises the following steps: building an energy consumption prediction model according to historical energy consumption change characteristic data information of a processing machine tool under each processing condition data; and finally, predicting energy consumption information of each processing sub-route based on an energy consumption prediction model and the estimated cutting force information of each processing sub-route at each position, and optimizing dry processing forming of the carbon fiber composite special-shaped part according to the energy consumption information of each processing sub-route to obtain a final processing route. According to the method, the energy consumption condition of the processing route of the carbon fiber composite material special-shaped part is analyzed, so that a more excellent processing route can be performed according to the energy consumption condition, the processing energy consumption of processing the carbon fiber composite material special-shaped part can be reduced, and the processing cost of the carbon fiber composite material special-shaped part is further reduced.

Description

Technical Field

[0001] The invention relates to the technical field of carbon fiber processing, and in particular to a dry processing and forming analysis method for special-shaped parts of carbon fiber composite materials. Background Art

[0002] Carbon fiber materials have many advantages such as high specific strength, high specific stiffness, corrosion resistance and designability. They are increasingly used in aerospace, rail transit and other fields. When used in these fields, carbon fiber materials usually require secondary processing, such as milling and drilling to achieve the final dimensional accuracy and assembly requirements of the components. Statistics show that global carbon fiber consumption in 2020 increased by 4.94% year-on-year compared with 2019, reaching 107,000 tons. In the future, carbon fiber demand will continue to be in a period of rapid growth, and it is expected to reach 200,000 tons in 2025 and 400,000 tons in 2030. Therefore, the energy consumption generated by the secondary processing of carbon fiber materials will also increase rapidly. However, during the processing process, if the processing route planning is unreasonable, it will lead to an increase in the working power of the processing machine tool. When working for a long time, the energy consumption during the processing is very high, resulting in an increase in processing costs. Summary of the invention

[0003] The invention overcomes the shortcomings of the prior art and provides a dry processing and forming analysis method for special-shaped parts of carbon fiber composite materials.

[0004] To achieve the above object, the technical solution adopted by the present invention is: The first aspect of the present invention provides a dry processing and forming analysis method for special-shaped parts of carbon fiber composite materials, which specifically includes: Acquire process element information of carbon fiber composite material special-shaped parts, and construct a processing route of carbon fiber composite material special-shaped parts according to the process element information of carbon fiber composite material special-shaped parts; Setting a feed rate and a cutting depth, and analyzing a processing route of the carbon fiber composite material special-shaped part according to the feed rate and the cutting depth, and obtaining estimated cutting force information at each position of each processing sub-route; Acquire historical energy consumption change characteristic data information of the processing machine tool under each processing condition data, and construct an energy consumption prediction model according to the historical energy consumption change characteristic data information of the processing machine tool under each processing condition data; The energy consumption information of each processing sub-route is predicted based on the energy consumption prediction model and the estimated cutting force information of each processing sub-route at each position, and the dry processing of carbon fiber composite material special-shaped parts is optimized according to the energy consumption information of each processing sub-route to obtain the final processing route.

[0005] Furthermore, in the present method, process element information of the carbon fiber composite material special-shaped part is obtained, and a processing route of the carbon fiber composite material special-shaped part is constructed according to the process element information of the carbon fiber composite material special-shaped part, specifically: Acquire processing drawing information of carbon fiber composite material special-shaped parts, and obtain process element information of carbon fiber composite material special-shaped parts by extracting processing elements from the processing drawing information of the carbon fiber composite material special-shaped parts; Introducing a genetic algorithm, setting a genetic algebra based on the genetic algorithm, performing initialization planning of a processing route according to process element information of the carbon fiber composite material special-shaped part, and using the initial route information of the carbon fiber composite material special-shaped part as a population; Performing genetic inheritance on the population until a maximum genetic generation is reached, then obtaining initial route information of the carbon fiber composite material special-shaped parts, and obtaining processing distance information of each of the initial route information; A processing distance threshold is set, and when the processing distance information is less than the initial route information corresponding to the processing distance threshold, the initial route information corresponding to the processing distance information less than the processing distance threshold is used as the processing route of the carbon fiber composite material special-shaped part.

[0006] Furthermore, in this method, the feed rate and the cutting depth are set, and the processing route of the carbon fiber composite material special-shaped part is analyzed according to the feed rate and the cutting depth, and the estimated cutting force information of each processing sub-route at each position is obtained, specifically: The cutting force information of the special-shaped parts of carbon fiber composite materials under various feed rates and cutting depths is obtained through big data, and the cutting force information of the special-shaped parts of carbon fiber composite materials under various feed rates and cutting depths is input into the graph neural network. Taking the feed rate and the cutting depth as the first node and the machining cutting force information as the second node, a directed description relationship is constructed, and the first node and the second node are connected based on the directed description relationship to construct a topological structure diagram; Construct a knowledge graph, input the topological structure diagram into the knowledge graph for storage, set the feed amount and the cutting amount, and input the feed amount and the cutting amount into the knowledge graph for data matching; By data matching, the estimated cutting force information corresponding to the feed rate and the cutting depth is obtained, and the processing route of the carbon fiber composite material special-shaped part is divided to obtain a plurality of sub-routes, and the estimated cutting force information of each processing sub-route at each position is obtained.

[0007] Furthermore, in the present method, historical energy consumption change characteristic data information of the processing machine tool under each processing condition data is obtained, and an energy consumption prediction model is constructed according to the historical energy consumption change characteristic data information of the processing machine tool under each processing condition data, specifically including: Acquire historical energy consumption change characteristic data information of the processing machine tool under various processing condition data, build an energy consumption prediction model based on a deep neural network, and build a characteristic matrix according to the historical energy consumption change characteristic data information of the processing machine tool under various processing condition data; The feature matrix is ​​input into the energy consumption prediction model for training. When the loss function of the energy consumption prediction model converges to a preset value, the model parameters of the energy consumption prediction model are saved, and the energy consumption prediction model is output.

[0008] Furthermore, in this method, the energy consumption information of each processing sub-route is predicted based on the energy consumption prediction model and the estimated cutting force information of each processing sub-route at each position, specifically: Obtain energy consumption change characteristic data information of the processing machine tool within a preset time, and obtain processing distance information of each processing sub-route; Inputting the processing distance information of each processing sub-route, the estimated cutting force information of each processing sub-route at each position, and the energy consumption change characteristic data information of the processing machine tool within a preset time into the energy consumption prediction model for prediction; The energy consumption information of each processing sub-route is obtained through prediction, and the energy consumption information of each processing sub-route is output as an output result.

[0009] Furthermore, in this method, the dry processing of carbon fiber composite material special-shaped parts is optimized according to the energy consumption information of each processing sub-route to obtain the final processing route, which is specifically: According to the energy consumption information of each processing sub-route, the total energy consumption information of the processing route of each carbon fiber composite material special-shaped part is counted, and a total energy consumption threshold is set to determine whether there is a processing route for a carbon fiber composite material special-shaped part whose total energy consumption information is greater than the total energy consumption threshold; When there is a processing route for a carbon fiber composite material special-shaped part whose total energy consumption information is greater than a total energy consumption threshold, the processing route for the carbon fiber composite material special-shaped part whose total energy consumption information is greater than the total energy consumption threshold is used as the final processing route; When there is no processing route for a carbon fiber composite material special-shaped part whose total energy consumption information is greater than the total energy consumption threshold, the feed rate and cutting depth will be replanned, and the total energy consumption information of the processing route for each carbon fiber composite material special-shaped part under the feed rate and cutting depth will be obtained; When the total energy consumption information is not greater than the total energy consumption threshold, the processing routes of carbon fiber composite material special-shaped parts whose total energy consumption information is not greater than the total energy consumption threshold are obtained, and the processing routes of carbon fiber composite material special-shaped parts whose total energy consumption information is not greater than the total energy consumption threshold are sorted to obtain the processing route with the minimum total energy consumption as the final processing route.

[0010] A second aspect of the present invention provides a carbon fiber composite material special-shaped parts dry processing analysis system, comprising a memory and a processor, wherein the memory includes a carbon fiber composite material special-shaped parts dry processing analysis method program, and when the carbon fiber composite material special-shaped parts dry processing analysis method program is executed by the processor, any step of the fiber composite material special-shaped parts dry processing analysis method is implemented.

[0011] A third aspect of the present invention provides a computer-readable storage medium, comprising a program for an analysis method for dry processing and forming of special-shaped parts of carbon fiber composite materials. When the program for an analysis method for dry processing and forming of special-shaped parts of carbon fiber composite materials is executed by a processor, the steps of any one of the methods for dry processing and forming of special-shaped parts of carbon fiber composite materials are implemented.

[0012] The present invention solves the defects existing in the background technology and has the following beneficial effects: The present invention obtains the process element information of the carbon fiber composite material special-shaped parts, and constructs the processing route of the carbon fiber composite material special-shaped parts according to the process element information of the carbon fiber composite material special-shaped parts, and then sets the feed rate and the cutting amount, and analyzes the processing route of the carbon fiber composite material special-shaped parts according to the feed rate and the cutting amount, obtains the estimated cutting force information of each processing sub-route at each position, thereby obtaining the historical energy consumption change characteristic data information of the processing machine tool under each processing condition data, and constructs an energy consumption prediction model according to the historical energy consumption change characteristic data information of the processing machine tool under each processing condition data, and finally predicts the energy consumption information of each processing sub-route based on the energy consumption prediction model and the estimated cutting force information of each processing sub-route at each position, and optimizes the dry processing and forming of the carbon fiber composite material special-shaped parts according to the energy consumption information of each processing sub-route, and obtains the final processing route. The present invention analyzes the energy consumption of the processing route of the carbon fiber composite material special-shaped parts, so that a more excellent processing route can be carried out according to the energy consumption, and the processing energy consumption of the processing of the carbon fiber composite material special-shaped parts can be reduced, thereby reducing the processing cost of the carbon fiber composite material special-shaped parts. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, drawings of other embodiments can be obtained based on these drawings without paying creative work.

[0014] Figure 1 The overall flow chart of the dry processing and forming analysis method of carbon fiber composite material special-shaped parts is shown; Figure 2 A partial flow chart of the dry processing and forming analysis method for special-shaped parts of carbon fiber composite materials is shown; Figure 3 The system block diagram of the dry processing and forming analysis system for carbon fiber composite material special-shaped parts is shown. DETAILED DESCRIPTION

[0015] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0016] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0017] like Figure 1 As shown, the first aspect of the present invention provides a dry processing and forming analysis method for special-shaped parts of carbon fiber composite materials, which specifically includes: S102: Acquire process element information of the carbon fiber composite material special-shaped part, and construct a processing route of the carbon fiber composite material special-shaped part according to the process element information of the carbon fiber composite material special-shaped part; Exemplarily, the process element information includes data such as hole size, roughness, contour, slot size, etc., and the processing route can be constructed through technical means such as Mastercam, UG, and genetic algorithm planning of processing routes.

[0018] S104: setting a feed rate and a cutting depth, and analyzing a processing route of the carbon fiber composite material special-shaped part according to the feed rate and the cutting depth, and obtaining estimated cutting force information at each position of each processing sub-route; S106: Acquire historical energy consumption change characteristic data information of the processing machine tool under each processing condition data, and construct an energy consumption prediction model according to the historical energy consumption change characteristic data information of the processing machine tool under each processing condition data; S108: Predict the energy consumption information of each processing sub-route based on the energy consumption prediction model and the estimated cutting force information of each processing sub-route at each position, and optimize the dry processing of carbon fiber composite material special-shaped parts according to the energy consumption information of each processing sub-route to obtain the final processing route.

[0019] It should be noted that the present invention analyzes the energy consumption of the processing route of carbon fiber composite material special-shaped parts, so that a more excellent processing route can be carried out according to the energy consumption situation, which can reduce the processing energy consumption of processing carbon fiber composite material special-shaped parts, and then reduce the processing cost of carbon fiber composite material special-shaped parts.

[0020] like Figure 2 As shown, in S102 of this method, the path planning is mainly realized by genetic algorithm, specifically: S202: Acquire processing drawing information of the carbon fiber composite material special-shaped part, and extract processing elements from the processing drawing information of the carbon fiber composite material special-shaped part to acquire process element information of the carbon fiber composite material special-shaped part; S204: introducing a genetic algorithm, setting a genetic algebra based on the genetic algorithm, performing initialization planning of a processing route according to process element information of the carbon fiber composite material special-shaped part, and using the initial route information of the carbon fiber composite material special-shaped part as a population; S206: Perform genetic inheritance on the population until the maximum genetic generation is reached, then obtain initial route information of the carbon fiber composite material special-shaped parts, and obtain processing distance information of each initial route information; S208: Setting a processing distance threshold, when the processing distance information is less than the initial route information corresponding to the processing distance threshold, the initial route information corresponding to the processing distance information less than the processing distance threshold is used as the processing route of the carbon fiber composite material special-shaped part.

[0021] It should be noted that, through this method, it is possible to continuously inherit according to the genetic algebra, so as to obtain several processing routes whose processing distance information is less than the processing distance threshold, thereby improving the rationality of processing.

[0022] Furthermore, in this method, the feed rate and the cutting depth are set, and the processing route of the carbon fiber composite material special-shaped parts is analyzed according to the feed rate and the cutting depth, and the estimated cutting force information of each processing sub-route at each position is obtained, specifically: The cutting force information of carbon fiber composite material special-shaped parts under various feed rates and cutting depths is obtained through big data, and the cutting force information of carbon fiber composite material special-shaped parts under various feed rates and cutting depths is input into the graph neural network by introducing the graph neural network. The feed rate and the cutting depth are taken as the first node, and the machining cutting force information is taken as the second node, a directed description relationship is constructed, and the first node and the second node are connected based on the directed description relationship to construct a topological structure diagram; Construct a knowledge graph, input the topological structure graph into the knowledge graph for storage, set the feed rate and cutting depth, and input the feed rate and cutting depth into the Su knowledge graph for data matching; Through data matching, the estimated cutting force information corresponding to the feed rate and cutting depth is obtained, and the processing route of the carbon fiber composite material special-shaped parts is divided to obtain several sub-routes, and the estimated cutting force information of each processing sub-route at each position is obtained.

[0023] It should be noted that the real-time cutting force is inconsistent under different feed rates and cutting depths. For a processing route, the processing distance, feed rate and cutting depth will affect the final energy consumption value of the processing equipment. This method can estimate the estimated cutting force information of each processing sub-route at each position, thereby calculating the energy consumption of each sub-route.

[0024] Furthermore, in the present method, historical energy consumption change characteristic data information of the processing machine tool under each processing condition data is obtained, and an energy consumption prediction model is constructed according to the historical energy consumption change characteristic data information of the processing machine tool under each processing condition data, specifically including: Obtain the historical energy consumption change characteristic data information of the processing machine tool under each processing condition data, build an energy consumption prediction model based on a deep neural network, and build a feature matrix according to the historical energy consumption change characteristic data information of the processing machine tool under each processing condition data; The feature matrix is ​​input into the energy consumption prediction model for training. When the loss function of the energy consumption prediction model converges to a preset value, the model parameters of the energy consumption prediction model are saved and the energy consumption prediction model is output.

[0025] It should be noted that after a certain number of years of use, processing equipment will experience a certain degree of degradation, resulting in inconsistent energy consumption of processing equipment under different processing conditions. The processing conditions data include processing distance information, processing cutting force information, feed rate, cutting depth and other data.

[0026] Furthermore, in this method, the energy consumption information of each processing sub-route is predicted based on the energy consumption prediction model and the estimated cutting force information of each processing sub-route at each position, specifically: Obtain energy consumption change characteristic data information of the processing machine tool within a preset time, and obtain processing distance information of each processing sub-route; Inputting the processing distance information of each processing sub-route, the estimated cutting force information of each processing sub-route at each position, and the energy consumption change characteristic data information of the processing machine tool within a preset time into the energy consumption prediction model for prediction; Through prediction, the energy consumption information of each processing sub-route is obtained, and the energy consumption information of each processing sub-route is output as an output result.

[0027] It should be noted that the energy consumption information of each processing sub-route can be obtained through this method.

[0028] Furthermore, in this method, the dry processing of carbon fiber composite material special-shaped parts is optimized according to the energy consumption information of each processing sub-route to obtain the final processing route, which is specifically: According to the energy consumption information of each processing sub-route, the total energy consumption information of the processing route of each carbon fiber composite material special-shaped part is counted, and a total energy consumption threshold is set to determine whether there is a processing route for carbon fiber composite material special-shaped parts whose total energy consumption information is greater than the total energy consumption threshold; When there is a processing route for a carbon fiber composite material special-shaped part whose total energy consumption information is greater than a total energy consumption threshold, the processing route for the carbon fiber composite material special-shaped part whose total energy consumption information is greater than the total energy consumption threshold is used as the final processing route; When there is no processing route for a carbon fiber composite material special-shaped part whose total energy consumption information is greater than the total energy consumption threshold, the feed rate and cutting depth will be replanned, and the total energy consumption information of the processing route for each carbon fiber composite material special-shaped part under the feed rate and cutting depth will be obtained; When the total energy consumption information is not greater than the total energy consumption threshold, the processing routes of carbon fiber composite material special-shaped parts whose total energy consumption information is not greater than the total energy consumption threshold are obtained, and the processing routes of carbon fiber composite material special-shaped parts whose total energy consumption information is not greater than the total energy consumption threshold are sorted to obtain the processing route with the minimum total energy consumption as the final processing route.

[0029] It should be noted that this method can further improve the rationality of processing, thereby selecting a more excellent processing route to process carbon fiber composite material special-shaped parts and reduce processing costs.

[0030] In addition, the method further comprises: The energy consumption data of each carbon fiber composite material special-shaped part in each processing equipment is predicted by the energy consumption prediction model, and a processing equipment is randomly selected for each carbon fiber composite material special-shaped part for processing according to the energy consumption data of each carbon fiber composite material special-shaped part in each processing equipment, so as to construct a processing task allocation combination; Obtaining a processing energy consumption value of a randomly selected processing device in processing a carbon fiber composite material special-shaped part, and counting the processing energy consumption value of the randomly selected processing device in processing a carbon fiber composite material special-shaped part to obtain a second total energy consumption value; Setting a second total energy consumption threshold, and determining whether the second total energy consumption value is greater than the second total energy consumption threshold, and outputting a processing task allocation combination when the second total energy consumption value is not greater than the second total energy consumption threshold; When the second total energy consumption value is greater than the second total energy consumption threshold, the processing task allocation combination is updated, and processing equipment is reselected for processing until the second total energy consumption value is no greater than the second total energy consumption threshold, and the processing task allocation combination is output.

[0031] It should be noted that this method can improve the rationality of processing allocation, thereby further optimizing processing energy consumption and further reducing processing costs.

[0032] In addition, the method further comprises: Obtaining energy consumption data information of sub-components of processing equipment under various working temperature environment characteristics through big data, and inputting the energy consumption data information of sub-components of processing equipment under various working temperature environment characteristics into the knowledge graph for storage; By setting a temperature sensor on a sub-component of the processing equipment, the temperature information of the sub-component of the processing equipment is obtained through the temperature sensor, and the temperature information of the sub-component of the processing equipment is input into the knowledge graph for data matching; By data matching, the energy consumption data information of the processing equipment under the current working temperature environment characteristics of the sub-components of the processing equipment is obtained, and the real-time energy consumption data is updated according to the energy consumption data information of the processing equipment under the current working temperature environment characteristics of the sub-components of the processing equipment; The processing task allocation combination is updated based on the updated real-time energy consumption data, and processing allocation is performed according to the updated processing task allocation combination.

[0033] It should be noted that since the energy consumption required for the sub-components of the processing equipment (such as motors) to achieve the same working parameters (rotation speed) in different working environments is inconsistent, the real-time energy consumption data can be updated by this method, which can further improve the rationality of dry processing of special-shaped parts of carbon fiber composite materials.

[0034] like Figure 3As shown, the second aspect of the present invention provides a carbon fiber composite material special-shaped part dry processing forming analysis system 4, including a memory 41 and a processor 42, the memory 41 includes a carbon fiber composite material special-shaped part dry processing forming analysis method program, and when the carbon fiber composite material special-shaped part dry processing forming analysis method program is executed by the processor 42, any step of the fiber composite material special-shaped part dry processing forming analysis method is implemented, including: Acquire process element information of carbon fiber composite material special-shaped parts, and construct a processing route of carbon fiber composite material special-shaped parts according to the process element information of carbon fiber composite material special-shaped parts; Set the feed rate and cutting depth, and analyze the processing route of carbon fiber composite material special-shaped parts based on the feed rate and cutting depth to obtain the estimated cutting force information at each position of each processing sub-route; Obtaining historical energy consumption change characteristic data information of the processing machine tool under various processing condition data, and constructing an energy consumption prediction model based on the historical energy consumption change characteristic data information of the processing machine tool under various processing condition data; The energy consumption information of each processing sub-route is predicted based on the energy consumption prediction model and the estimated cutting force information of each processing sub-route at each position. According to the energy consumption information of each processing sub-route, the dry processing of carbon fiber composite special-shaped parts is optimized to obtain the final processing route.

[0035] Furthermore, in this system, the process element information of the carbon fiber composite material special-shaped parts is obtained, and the processing route of the carbon fiber composite material special-shaped parts is constructed according to the process element information of the carbon fiber composite material special-shaped parts, specifically: Acquire processing drawing information of carbon fiber composite material special-shaped parts, and extract processing elements from the processing drawing information of carbon fiber composite material special-shaped parts to obtain process element information of carbon fiber composite material special-shaped parts; Genetic algorithm is introduced, genetic algebra is set based on genetic algorithm, initialization planning of processing route is performed according to process element information of carbon fiber composite material special-shaped parts, and the initial route information of carbon fiber composite material special-shaped parts is used as population; Genetically modify the population until the maximum genetic generation is reached, then obtain the initial route information of the carbon fiber composite material special-shaped parts, and obtain the processing distance information of each initial route information; A processing distance threshold is set, and when the processing distance information is less than the initial route information corresponding to the processing distance threshold, the initial route information corresponding to the processing distance information less than the processing distance threshold is used as the processing route of the carbon fiber composite material special-shaped part.

[0036] Furthermore, in this system, the feed rate and cutting depth are set, and the processing route of the carbon fiber composite material special-shaped parts is analyzed according to the feed rate and cutting depth to obtain the estimated cutting force information of each processing sub-route at each position, specifically: The cutting force information of carbon fiber composite material special-shaped parts under various feed rates and cutting depths is obtained through big data, and the cutting force information of carbon fiber composite material special-shaped parts under various feed rates and cutting depths is input into the graph neural network by introducing the graph neural network. The feed rate and the cutting depth are taken as the first node, and the machining cutting force information is taken as the second node, a directed description relationship is constructed, and the first node and the second node are connected based on the directed description relationship to construct a topological structure diagram; Construct a knowledge graph, input the topological structure graph into the knowledge graph for storage, set the feed rate and cutting depth, and input the feed rate and cutting depth into the Su knowledge graph for data matching; Through data matching, the estimated cutting force information corresponding to the feed rate and cutting depth is obtained, and the processing route of the carbon fiber composite material special-shaped parts is divided to obtain several sub-routes, and the estimated cutting force information of each processing sub-route at each position is obtained.

[0037] Furthermore, in this system, historical energy consumption change characteristic data information of the processing machine tool under each processing condition data is obtained, and an energy consumption prediction model is constructed according to the historical energy consumption change characteristic data information of the processing machine tool under each processing condition data, specifically including: Obtain the historical energy consumption change characteristic data information of the processing machine tool under each processing condition data, build an energy consumption prediction model based on a deep neural network, and build a feature matrix according to the historical energy consumption change characteristic data information of the processing machine tool under each processing condition data; The feature matrix is ​​input into the energy consumption prediction model for training. When the loss function of the energy consumption prediction model converges to a preset value, the model parameters of the energy consumption prediction model are saved and the energy consumption prediction model is output.

[0038] Furthermore, in this system, the energy consumption information of each processing sub-route is predicted based on the energy consumption prediction model and the estimated cutting force information of each processing sub-route at each position, specifically: Obtain energy consumption change characteristic data information of the processing machine tool within a preset time, and obtain processing distance information of each processing sub-route; Inputting the processing distance information of each processing sub-route, the estimated cutting force information of each processing sub-route at each position, and the energy consumption change characteristic data information of the processing machine tool within a preset time into the energy consumption prediction model for prediction; Through prediction, the energy consumption information of each processing sub-route is obtained, and the energy consumption information of each processing sub-route is output as an output result.

[0039] Furthermore, in this system, the dry processing of carbon fiber composite material special-shaped parts is optimized according to the energy consumption information of each processing sub-route to obtain the final processing route, which is specifically: According to the energy consumption information of each processing sub-route, the total energy consumption information of the processing route of each carbon fiber composite material special-shaped part is counted, and a total energy consumption threshold is set to determine whether there is a processing route for carbon fiber composite material special-shaped parts whose total energy consumption information is greater than the total energy consumption threshold; When there is a processing route for a carbon fiber composite material special-shaped part whose total energy consumption information is greater than a total energy consumption threshold, the processing route for the carbon fiber composite material special-shaped part whose total energy consumption information is greater than the total energy consumption threshold is used as the final processing route; When there is no processing route for a carbon fiber composite material special-shaped part whose total energy consumption information is greater than the total energy consumption threshold, the feed rate and cutting depth will be replanned, and the total energy consumption information of the processing route for each carbon fiber composite material special-shaped part under the feed rate and cutting depth will be obtained; When the total energy consumption information is not greater than the total energy consumption threshold, the processing routes of carbon fiber composite material special-shaped parts whose total energy consumption information is not greater than the total energy consumption threshold are obtained, and the processing routes of carbon fiber composite material special-shaped parts whose total energy consumption information is not greater than the total energy consumption threshold are sorted to obtain the processing route with the minimum total energy consumption as the final processing route.

[0040] A third aspect of the present invention provides a computer-readable storage medium, including a program for an analysis method for dry processing and forming of special-shaped parts of carbon fiber composite materials. When the program for an analysis method for dry processing and forming of special-shaped parts of carbon fiber composite materials is executed by a processor, any step of the method for dry processing and forming of special-shaped parts of carbon fiber composite materials is implemented.

[0041] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0042] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0043] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0044] A person of ordinary skill in the art can understand that: all or part of the steps of implementing the above method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiment; and the aforementioned storage medium includes: a mobile storage device, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

[0045] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods of each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

[0046] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art who is familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A dry processing and forming analysis method for special-shaped parts of carbon fiber composite materials, characterized in that: Specifically include: Acquire process element information of carbon fiber composite material special-shaped parts, and construct a processing route of carbon fiber composite material special-shaped parts according to the process element information of carbon fiber composite material special-shaped parts; Setting a feed rate and a cutting depth, and analyzing a processing route of the carbon fiber composite material special-shaped part according to the feed rate and the cutting depth, and obtaining estimated cutting force information at each position of each processing sub-route; Acquire historical energy consumption change characteristic data information of the processing machine tool under each processing condition data, and construct an energy consumption prediction model according to the historical energy consumption change characteristic data information of the processing machine tool under each processing condition data; The energy consumption information of each processing sub-route is predicted based on the energy consumption prediction model and the estimated cutting force information of each processing sub-route at each position, and the dry processing of carbon fiber composite material special-shaped parts is optimized according to the energy consumption information of each processing sub-route to obtain the final processing route.

2. The dry processing and forming analysis method for special-shaped parts of carbon fiber composite materials according to claim 1 is characterized in that: Acquire process element information of carbon fiber composite material special-shaped parts, and construct a processing route of carbon fiber composite material special-shaped parts according to the process element information of carbon fiber composite material special-shaped parts, specifically: Acquire processing drawing information of carbon fiber composite material special-shaped parts, and obtain process element information of carbon fiber composite material special-shaped parts by extracting processing elements from the processing drawing information of the carbon fiber composite material special-shaped parts; Introducing a genetic algorithm, setting a genetic algebra based on the genetic algorithm, performing initialization planning of a processing route according to process element information of the carbon fiber composite material special-shaped part, and using the initial route information of the carbon fiber composite material special-shaped part as a population; Performing genetic inheritance on the population until a maximum genetic generation is reached, then obtaining initial route information of the carbon fiber composite material special-shaped parts, and obtaining processing distance information of each of the initial route information; A processing distance threshold is set, and when the processing distance information is less than the initial route information corresponding to the processing distance threshold, the initial route information corresponding to the processing distance information less than the processing distance threshold is used as the processing route of the carbon fiber composite material special-shaped part.

3. The dry processing and forming analysis method for special-shaped parts of carbon fiber composite materials according to claim 1 is characterized in that: The feed rate and the cutting depth are set, and the processing route of the carbon fiber composite material special-shaped part is analyzed according to the feed rate and the cutting depth, and the estimated cutting force information of each processing sub-route at each position is obtained, specifically: The cutting force information of the special-shaped parts of carbon fiber composite materials under various feed rates and cutting depths is obtained through big data, and the cutting force information of the special-shaped parts of carbon fiber composite materials under various feed rates and cutting depths is input into the graph neural network. Taking the feed rate and the cutting depth as the first node and the machining cutting force information as the second node, a directed description relationship is constructed, and the first node and the second node are connected based on the directed description relationship to construct a topological structure diagram; Construct a knowledge graph, input the topological structure diagram into the knowledge graph for storage, set the feed amount and the cutting amount, and input the feed amount and the cutting amount into the knowledge graph for data matching; By data matching, the estimated cutting force information corresponding to the feed rate and the cutting depth is obtained, and the processing route of the carbon fiber composite material special-shaped part is divided to obtain a plurality of sub-routes, and the estimated cutting force information of each processing sub-route at each position is obtained.

4. The dry processing and forming analysis method for carbon fiber composite material special-shaped parts according to claim 1 is characterized in that: Obtaining historical energy consumption change characteristic data information of the processing machine tool under various processing condition data, and building an energy consumption prediction model according to the historical energy consumption change characteristic data information of the processing machine tool under various processing condition data, specifically including: Acquire historical energy consumption change characteristic data information of the processing machine tool under various processing condition data, build an energy consumption prediction model based on a deep neural network, and build a characteristic matrix according to the historical energy consumption change characteristic data information of the processing machine tool under various processing condition data; The feature matrix is ​​input into the energy consumption prediction model for training. When the loss function of the energy consumption prediction model converges to a preset value, the model parameters of the energy consumption prediction model are saved, and the energy consumption prediction model is output.

5. The dry processing and forming analysis method for special-shaped parts of carbon fiber composite materials according to claim 1 is characterized in that: The energy consumption information of each processing sub-route is predicted based on the energy consumption prediction model and the estimated cutting force information of each processing sub-route at each position, specifically: Obtain energy consumption change characteristic data information of the processing machine tool within a preset time, and obtain processing distance information of each processing sub-route; Inputting the processing distance information of each processing sub-route, the estimated cutting force information of each processing sub-route at each position, and the energy consumption change characteristic data information of the processing machine tool within a preset time into the energy consumption prediction model for prediction; The energy consumption information of each processing sub-route is obtained through prediction, and the energy consumption information of each processing sub-route is output as an output result.

6. The dry processing and forming analysis method for special-shaped parts of carbon fiber composite materials according to claim 1 is characterized in that: The dry processing of carbon fiber composite material special-shaped parts is optimized according to the energy consumption information of each processing sub-route, and the final processing route is obtained, which is specifically: According to the energy consumption information of each processing sub-route, the total energy consumption information of the processing route of each carbon fiber composite material special-shaped part is counted, and a total energy consumption threshold is set to determine whether there is a processing route for a carbon fiber composite material special-shaped part whose total energy consumption information is greater than the total energy consumption threshold; When there is a processing route for a carbon fiber composite material special-shaped part whose total energy consumption information is greater than a total energy consumption threshold, the processing route for the carbon fiber composite material special-shaped part whose total energy consumption information is greater than the total energy consumption threshold is used as the final processing route; When there is no processing route for a carbon fiber composite material special-shaped part whose total energy consumption information is greater than the total energy consumption threshold, the feed rate and cutting depth will be replanned, and the total energy consumption information of the processing route for each carbon fiber composite material special-shaped part under the feed rate and cutting depth will be obtained; When the total energy consumption information is not greater than the total energy consumption threshold, the processing routes of carbon fiber composite material special-shaped parts whose total energy consumption information is not greater than the total energy consumption threshold are obtained, and the processing routes of carbon fiber composite material special-shaped parts whose total energy consumption information is not greater than the total energy consumption threshold are sorted to obtain the processing route with the minimum total energy consumption as the final processing route.

7. A carbon fiber composite material special-shaped parts dry processing forming analysis system, characterized in that: It comprises a memory and a processor, wherein the memory comprises a program for an analysis method for dry processing and forming of special-shaped parts of carbon fiber composite materials, and when the program for an analysis method for dry processing and forming of special-shaped parts of carbon fiber composite materials is executed by the processor, the steps of the analysis method for dry processing and forming of special-shaped parts of fiber composite materials as described in any one of claims 1 to 6 are implemented.

8. A computer-readable storage medium, characterized in that: It comprises a program for analyzing the dry processing and forming of special-shaped parts of carbon fiber composite materials. When the program for analyzing the dry processing and forming of special-shaped parts of carbon fiber composite materials is executed by a processor, the steps of the method for analyzing the dry processing and forming of special-shaped parts of fiber composite materials as described in any one of claims 1 to 6 are implemented.

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