A continuous fiber reinforced conductive resin-based composite material-based conductive path design method and system

Abstract

The present application belongs to the technical field of composite material additive manufacturing, and discloses a conductive path design method and system based on continuous fiber reinforced conductive resin matrix composite, which comprises the following steps: co-extruding 3D printing of conductive resin filaments and continuous fiber pre-impregnated filaments, applying a non-uniform field to the conductive resin filaments during 3D printing to guide the secondary distribution of conductive filler particles in the conductive resin filaments, and then realizing the design of the conductive path in the 3D printed forming component. In the process of 3D printing, the resin matrix becomes a molten state, and the internal conductive filler particles are guided by the field to be secondarily distributed, thereby realizing the design of the conductive path. Thus, the conductive path and the corresponding printing path in the component can be spatially decoupled, thereby realizing flexible design of the conductive path.

Description

Technical Field

[0001] This invention belongs to the technical field of additive manufacturing of composite materials, and more specifically, relates to a conductive path design method and system based on continuous fiber reinforced conductive resin matrix composite materials. Background Technology

[0002] Continuous fiber reinforced resin matrix composites have become indispensable structural materials in aerospace, automotive, wind turbine blades, and high-end equipment due to their excellent specific strength, specific modulus, and designability. In recent years, with the urgent need for functions such as intelligent structures, lightning protection, structural health monitoring, electromagnetic shielding, and electrostatic control, the integrated structure-function design and manufacturing of continuous fiber reinforced resin matrix composites has gradually become a research hotspot. Among these, the electrical functionalization of continuous fiber reinforced resin matrix composites is key to realizing their multi-scenario engineering applications.

[0003] However, many challenges remain in the integrated design and manufacturing of mechanical load-bearing and electrical functions for continuous fiber reinforced resin matrix composites. On one hand, the resin matrix in traditional continuous fiber reinforced resin matrix composites is typically an insulator, while the continuous fibers, although partially conductive, exhibit significant directional resistivity distribution, influenced by fiber continuity and contact conditions. On the other hand, during continuous fiber 3D printing, the conductive path of the component is often deeply coupled with the printing path, making flexible control impossible. Therefore, the overall electrical performance of continuous fiber reinforced resin matrix composite components is difficult to actively design and stably control.

[0004] To address these issues, much work has focused on enhancing the conductivity of resin matrices by adding conductive fillers such as carbon nanotubes and graphene. However, traditional material modification methods mostly only address the control of component resistance, introducing new problems such as uneven distribution of conductive fillers and disordered conductive networks within the material. Furthermore, the core issue of the continuous fiber 3D printing process limiting the conductive path design remains unresolved. During service, molded components are highly susceptible to issues such as localized conductivity redundancy and insufficient conductivity in critical areas. The randomly distributed conductive networks within the components also make accurate monitoring of their health status difficult. These problems severely restrict the coordinated design of load-bearing capacity and electrical functionality in continuous fiber reinforced resin matrix composites. Summary of the Invention

[0005] In view of the above-mentioned defects or improvement needs of the prior art, the present invention provides a conductive path design method and system based on continuous fiber reinforced conductive resin matrix composite material, which aims to solve the problem that the existing conductive path design is limited by the printing path.

[0006] To achieve the above objectives, according to one aspect of the present invention, a method for designing conductive paths based on continuous fiber reinforced conductive resin matrix composites is provided. The steps are as follows: co-extruding conductive resin filaments and continuous fiber prepreg filaments for 3D printing; applying a non-uniform field to the conductive resin filaments during the 3D printing process to guide the secondary distribution of conductive filler particles in the conductive resin filaments, thereby realizing the design of conductive paths in the 3D printed component.

[0007] Furthermore, during the co-extrusion 3D printing process, the spatial and temporal characteristics of the field signal are coordinated and controlled to achieve secondary guided distribution of conductive filler particles in the region corresponding to the predetermined path, thereby completing the field control design of the conductive path.

[0008] Furthermore, the parameters of the field signal, including the spatial coordinates of the field, the start time of the field, and the intensity of the field, are adjusted based on the printing path.

[0009] Furthermore, the conductive path is divided into a first conductive path and a second conductive path. The first conductive path is the ideal path for current to pass through, and the second conductive path is the non-ideal path for current to pass through. During the printing process, a non-uniform electric field is applied to drive the conductive filler particles in the deposition lines on both sides of the first conductive path to move towards each other, thereby enriching the conductive filler particles and reducing the resistance of the first conductive path. A non-uniform electric field is applied to drive the conductive filler particles in the deposition lines on both sides of the second conductive path to move away from each other, thereby isolating the conductive filler particles and increasing the resistance of the second conductive path.

[0010] Furthermore, the preparation steps of the conductive resin filament are as follows: (1) After pretreatment of thermoplastic resin particles and conductive filler particles, thermoplastic resin particles, conductive filler particles and auxiliary materials are put into a high-speed mixer. Finally, the high-speed mixer is started to mix the thermoplastic resin particles, conductive filler particles and auxiliary materials evenly. (2) The obtained uniformly mixed raw material is poured into a twin-screw extruder and melt-blended extrusion is performed. A series of post-processing operations are performed on the extruded cylindrical material to obtain cylindrical conductive masterbatch. (3) The obtained cylindrical conductive masterbatch is poured into a single screw extruder and melt extruded. Finally, the obtained conductive resin filament is post-processed to obtain conductive resin filament.

[0011] Furthermore, the extrusion parameters of single-screw extruders and twin-screw extruders are optimized based on intelligent algorithms.

[0012] Furthermore, a forward mapping model is first established using the response surface methodology to obtain the mapping relationship between the optimization design variables and the optimization objective. Then, a reverse optimization model is established using a genetic algorithm. The reverse optimization model solves for the optimal parameter combination based on the mapping relationship. The optimization design variables include the feeding section temperature, melting section temperature, mixing section temperature, homogenization section temperature, die temperature, and screw speed. The optimization objective includes the volume resistivity of the conductive masterbatch. With extrusion efficiency .

[0013] Furthermore, a second-order response surface model was used to analyze the volume resistivity. With extrusion efficiency The fitting was performed separately, and the corresponding formulas are as follows:

[0014] in, and The constant term is obtained by fitting multiple regression using the least squares method. and The coefficients of the first-order term obtained by fitting multiple regression using the least squares method are given. and The coefficients of the quadratic term are obtained by fitting multiple regression using the least squares method. and These are the interaction term coefficients obtained by fitting multiple regression using the least squares method; To optimize the encoded values ​​of design variables, .

[0015] The present invention also provides a robotic co-extrusion 3D printing system, which includes a host computer, a printing component, and a field generating device disposed on the printing component. The printing component is used to co-extrude conductive resin filaments and continuous fiber prepreg filaments for 3D printing. During the 3D printing process, the host computer is used to control the field generating device to apply a non-uniform field to the conductive resin filaments to guide the secondary distribution of conductive filler particles in the conductive resin filaments, thereby realizing the design of conductive paths in the 3D printed components.

[0016] Furthermore, the printing assembly includes a six-axis industrial robot, a print head, and a printing platform. The print head is installed at the end of the six-axis industrial robot. The host computer is connected to the six-axis industrial robot, the print head, and the printing platform, respectively. The six-axis industrial robot drives the print head to perform printing on the printing platform. The field generating device is embedded in the surface of the printing platform, with both surfaces flush. The field generating device is connected to the host computer through the printing platform.

[0017] In summary, compared with the prior art, the conductive path design method and system based on continuous fiber-reinforced conductive resin matrix composites provided by this invention have the following advantages: 1. During the 3D printing process, a non-uniform field is applied to the conductive resin filament to guide the secondary distribution of conductive filler particles within the filament, thereby enabling the design of conductive paths in the 3D printed component. Specifically, during 3D printing, the resin matrix becomes molten, and the field guides the secondary distribution of internal conductive filler particles, thus achieving the design of conductive paths. This allows for spatial decoupling of the conductive paths from the corresponding printing paths within the component, enabling flexible design of the conductive paths.

[0018] 2. This invention uses conductive filler particles to modify thermoplastic resin and proposes an intelligent material preparation process for continuous fiber reinforced conductive resin matrix composites, including raw material pretreatment and component proportioning, conductive masterbatch preparation, etc.; it adopts a working logic of twin-screw granulation and single-screw filamentation working in synergy, and deeply integrates intelligent algorithms to optimize extrusion parameters, giving full play to the advantages of both twin-screw extruders and single-screw extruders, and jointly ensuring the quality of the prepared conductive resin filaments.

[0019] 3. This invention establishes a complete methodological framework from conductive resin preparation to conductive path design, freeing the design of conductive paths from the constraints of 3D printing paths. It forms an integrated in-situ field-assisted co-extrusion 3D printing solution with decoupled control of the printing path and conductive path. This solution can be used to control the volume resistivity of the formed part, design its complex internal three-dimensional conductive network, and formulate the self-healing route of its resin matrix through conductive path design. Under normal conditions, this invention achieves the following effects: after parameter optimization, the volume resistivity of the conductive masterbatch is reduced by 32.7%, the extrusion efficiency is increased by 17%, the consistency rate of the extruded filament diameter is increased to 95.6%, and the resistance of the formed component is reduced by 91.8% after conductive path design.

[0020] 4. During the printing process, a non-uniform electric field is applied to drive the conductive filler particles in the deposition lines on both sides of the first conductive path to move towards each other, thereby enriching the conductive filler particles and reducing the resistance of the first conductive path. Conversely, a non-uniform electric field is applied to drive the conductive filler particles in the deposition lines on both sides of the second conductive path to move away from each other, thereby isolating the conductive filler particles and increasing the resistance of the second conductive path. Through the coordinated operation of the first and second conductive paths, various conductive paths can be flexibly designed and manufactured. Compared to randomly distributed conductive paths, the proposed electric field-guided conductive path design method can reduce the volume resistivity of the component along a certain direction (e.g., the Y-axis) by more than 90%. Attached Figure Description

[0021] Figure 1 This is a flowchart illustrating the process of preparing and designing conductive paths for continuous fiber-reinforced conductive resin-based composite materials for 3D printing, as provided in an embodiment of the present invention. Figure 2 This is a schematic diagram of a conductive resin filament preparation system for 3D printing provided by the present invention. Figure 3 This is a schematic diagram of a robotic co-extrusion 3D printing system provided by the present invention; Figure 4 (a) and (b) in the figure are respectively the microscopic cross-sectional view of the conductive polylactic acid (CB-PLA) filament prepared in the specific embodiment provided by the present invention and the tensile property test result of the co-extruded 3D printed monofilament; Figure 5 This is a schematic diagram of the design principle of the print path-conductive path co-design method in a specific embodiment of the present invention; Figure 6 (a), (b), (c), and (d) are diagrams of four conductive path schemes designed for a typical hexagonal honeycomb structure in specific embodiments provided by the present invention. Figure 7 This is a comparison chart of the resistance data of the four conductive paths designed in the specific embodiments provided by the present invention.

[0022] In all the accompanying drawings, the same reference numerals are used to denote the same elements or structures, wherein: 1-co-rotating twin-screw extruder, 2-cooling water tank, 3-hot air blower, 4-pelletizer, 5-single-screw extruder, 6-traction machine, 7-automatic winding machine, 8-printing nozzle, 9-six-axis industrial robot, 10-host computer, 11-printing platform, 12-microelectrode array. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0024] This invention establishes a complete methodology from conductive material preparation to conductive path design based on the reconfigurable characteristics of continuous fiber reinforced resin matrix composites. It provides a conductive path design method based on continuous fiber reinforced conductive resin matrix composites, enabling spatial decoupling of conductive paths and printing paths in the target part, thus achieving flexible conductive path design. Simultaneously, it can also design complex three-dimensional conductive networks within the part, further realizing the integrated structure-function design and manufacturing of continuous fiber reinforced conductive resin matrix composites, promoting the functional application of high-performance continuous fiber reinforced conductive resin matrix composites in multi-condition engineering scenarios. The method established in this invention achieves innovation in both process and control dimensions, realizing overall parametric scientific design, and achieving the following significant effects: under normal conditions, after parameter optimization, the volume resistivity of the conductive masterbatch is reduced by 32.7%, the extrusion efficiency is increased by 17%, the diameter consistency rate of extruded filaments is increased to 95.6%, and the resistance of the formed component is reduced by 91.8% after conductive path design.

[0025] The conductive path design method mainly includes the following steps: co-extruding conductive resin filaments and continuous fiber prepreg filaments for 3D printing; applying a non-uniform field to the conductive resin filaments during the 3D printing process to guide the secondary distribution of conductive filler particles in the conductive resin filaments, thereby realizing the design of conductive paths in the 3D printed components.

[0026] Specifically, a field generation device is set on the printing platform, and the spatial and temporal characteristics of the field signal are coordinated and controlled during the co-extrusion 3D printing process to achieve secondary guidance and distribution of conductive filler particles in the region corresponding to the predetermined path, thereby completing the field control design of the conductive path.

[0027] The field generating device is presented in the form of a micro-unit array, including but not limited to physical field arrays such as electrode arrays, electromagnetic coil arrays, and ultrasonic source arrays, as well as their multi-physical field coupling forms.

[0028] The field control design integrates the field signal and the 3D printing path into the printing equipment control system (such as a CNC system). The printing equipment control system adjusts the parameters of the field signal based on the printing path, including but not limited to the spatial coordinates of the field, the start time of the field, and the intensity of the field.

[0029] The timing synchronization control of the printing path and field signal can be achieved by customizing control commands in the printing equipment control system, including but not limited to various types of control systems such as Siemens, FANUC, Beckhoff, and ROS.

[0030] The method for preparing the conductive resin filament is as follows: (1) Raw material preparation and pretreatment: First, the thermoplastic resin particles and conductive filler particles are pretreated. Then, the thermoplastic resin particles, conductive filler particles and auxiliary materials are put into a high-speed mixer in a certain proportion. Finally, the high-speed mixer is started to mix the above materials evenly.

[0031] Thermoplastic resin particles serve as carriers for conductive filler particles, including but not limited to thermoplastic resins such as polylactic acid (PLA), polyamide (PA), and polyurethane (TPU). Continuous fiber prepregs serve as reinforcing phase materials in co-extrusion 3D printing systems, including but not limited to continuous fiber prepregs such as carbon fiber, glass fiber, and aramid fiber.

[0032] Pretreatment processes are used to ensure the quality of the conductive masterbatch prepared in subsequent steps, including but not limited to particle drying and surface modification of conductive filler particles. Auxiliary materials are used to ensure thorough mixing between the conductive filler particles and the thermoplastic resin particles, including but not limited to dispersants, antioxidants, and coupling agents.

[0033] Screw components need to be assembled and installed in a prescribed order to achieve specific functions, including but not limited to conveying elements, kneading blocks, mixing discs, etc.

[0034] (2) Melt blending and granulation: First, the screw elements are assembled and the extrusion parameters are optimized based on the intelligent algorithm. Then, the uniformly mixed raw material obtained in step (1) is poured into the twin screw extruder and melt blended extrusion is carried out. Finally, a series of post-processing operations are performed on the extruded cylindrical material to obtain cylindrical conductive masterbatch.

[0035] Intelligent algorithms are used to optimize the combination of extrusion parameters that balances extrusion efficiency and extrusion quality. These include, but are not limited to, intelligent algorithms and their combinations, such as response surface methodology, particle swarm optimization, ant colony optimization, genetic algorithms, and neural networks.

[0036] Extrusion parameters are used to ensure the density, uniformity, and other properties of the extruded material, including but not limited to the temperature of each zone of the extruder, screw speed, and feed rate.

[0037] Post-processing operations are used to ensure that conductive masterbatch that meets functional requirements is obtained, including but not limited to cooling, conductivity testing, cutting and granulation.

[0038] (3) Filament extrusion molding: First, the extrusion parameters of the single screw extruder are optimized based on the intelligent algorithm. Then, the cylindrical conductive masterbatch obtained in step (2) is poured into the single screw extruder and melt extruded. Finally, the conductive resin filament is post-processed and the winding step is completed.

[0039] Among them, extrusion parameters are used to ensure the density, uniformity and other indicators of the extruded material, including but not limited to the temperature of each area of ​​the extruder, screw speed and feed rate.

[0040] Post-processing operations are used to ensure that qualified conductive resin filaments are obtained, including but not limited to cooling and filament diameter detection.

[0041] This invention also provides a conductive resin filament preparation system for 3D printing, including a conductive masterbatch preparation module and a resin filament extrusion module; the conductive masterbatch preparation module includes a twin-screw extruder, a cooling system, a drying system, and a pelletizing device; the resin filament extrusion module includes a single-screw extruder, a cooling system, a drying system, a traction device, and a winding device; the conductive masterbatch preparation module and the resin filament extrusion module cooperate with each other, after the conductive masterbatch preparation module completes the melt blending and granulation step, the obtained conductive masterbatch is poured into the resin filament extrusion module for extrusion molding of conductive resin filaments, and the two share a set of cooling and drying systems.

[0042] This invention also provides a robotic co-extrusion 3D printing system. This system employs co-extrusion 3D printing technology and enables field control design of conductive paths in the printed sample. It includes a 3D printing platform; the 3D printing platform comprises a six-axis industrial robot, a printing nozzle, a printing platform, a field generation device, and a host computer; the printing nozzle is mounted at the end of the six-axis industrial robot, and the host computer is connected to the six-axis industrial robot, the printing nozzle, and the printing platform respectively. The six-axis industrial robot drives the printing nozzle to perform printing on the printing platform; the field generation device is embedded in the surface of the printing platform, with both surfaces flush, and the field generation device is connected to the host computer through the printing platform.

[0043] The host computer includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it performs the 3D printing conductive path design method for continuous fiber reinforced conductive resin matrix composite materials as described above. The host computer serves as the control system for the printing equipment.

[0044] In one embodiment, a six-axis industrial robot, a printing nozzle, and a printing platform constitute a printing assembly. The printing assembly is used to co-extrude conductive resin filaments and continuous fiber prepreg filaments for 3D printing. During the 3D printing process, the host computer controls the field generating device to apply a non-uniform field to the conductive resin filaments to guide the secondary distribution of conductive filler particles in the conductive resin filaments, thereby realizing the design of conductive paths in the 3D printed component.

[0045] The conductive path design method aims to improve the electrical properties of continuous fiber composite materials, forming a complete method system from conductive material preparation to conductive path design. This method can improve the conductivity of continuous fiber reinforced resin matrix composite systems and can flexibly design the required conductive paths by combining 3D printing molding process and geometric features of the molded components, realizing spatial decoupling between conductive paths and printing paths, thereby achieving the goal of integrated load-bearing and functional design and manufacturing of continuous fiber reinforced resin matrix composite materials.

[0046] The present invention will be further described in detail below with reference to specific embodiments.

[0047] The present invention provides a method for preparing continuous fiber-reinforced conductive resin matrix composites for 3D printing and designing conductive paths, a conductive resin filament preparation system for 3D printing, and a robotic co-extrusion 3D printing system.

[0048] like Figure 1 As shown, this embodiment provides a method for preparing continuous fiber-reinforced conductive resin-based composite materials for 3D printing and designing conductive paths, including the following steps: (1) Raw material preparation and pretreatment: First, the polylactic acid (PLA) particles and nano carbon black particles are pretreated. Then, the polylactic acid (PLA) particles, nano carbon black particles and related auxiliary materials are put into a high-speed mixer in a certain proportion. Finally, the high-speed mixer is started to mix them evenly.

[0049] (2) Melt blending and granulation: First, the screw elements are assembled and the extrusion parameters are optimized based on the intelligent algorithm. Then, the uniformly mixed raw material obtained in step (1) is poured into the co-rotating twin screw extruder and melt blended extrusion is carried out. Finally, a series of post-processing operations are performed on the extruded round strip material to obtain cylindrical conductive masterbatch.

[0050] (3) Filament extrusion molding: First, the extrusion parameters of the single screw extruder are optimized based on the intelligent algorithm. Then, the cylindrical conductive masterbatch obtained in step (2) is poured into the single screw extruder and melt extruded. Finally, the extruded filament is post-processed and the winding step is completed. (4) Co-extrusion 3D printing: The conductive polylactic acid (PLA) filament prepared in step (3) and the continuous carbon fiber prepreg filament are simultaneously fed into the printing nozzle for in-situ impregnation to achieve co-extrusion 3D printing. (5) Field control design of conductive path: A field generating device is arranged on the printing platform to apply a non-uniform field to the conductive polylactic acid (PLA) filament. During the co-extrusion 3D printing process, the spatial and temporal characteristics of the field signal are coordinated to achieve the secondary guided distribution of conductive filler particles in the specified path, thereby completing the field control design of the conductive path.

[0051] The method for preparing and designing conductive paths of continuous fiber reinforced conductive resin matrix composites aims to improve the electrical properties of continuous fiber composites, forming a complete method system from conductive material preparation to conductive path design. This method can improve the conductivity of continuous fiber reinforced resin matrix composite systems and can flexibly design the required conductive paths by combining 3D printing forming process and geometric features of formed components, realizing spatial decoupling between conductive paths and printing paths, thereby achieving the goal of integrated load-bearing and functional design and manufacturing of continuous fiber reinforced resin matrix composites.

[0052] Furthermore, the pretreatment operations used in this specific embodiment include drying and surface modification. The drying process mainly targets polylactic acid (PLA) particles, which are placed in a vacuum drying oven and dried at 80°C for 5 hours to reduce the moisture content to below 0.02%. The surface modification mainly targets nano-carbon black particles. First, the coupling agent is dissolved in anhydrous ethanol to prepare a 10% mass fraction coupling agent solution. Then, the obtained coupling agent solution is added to the nano-carbon black particles. The amount of coupling agent solution should be 2.5% of the mass of the nano-carbon black particles. The mixture is stirred at 2000 rpm for 15 minutes using a high-speed mixer. Finally, the particles are dried at 80°C for 2 hours to remove the ethanol solvent, resulting in surface-modified nano-carbon black particles. The surface-modified carbon black particles have amino and other active functional groups introduced on their surface, which can improve their compatibility and dispersion uniformity with the polylactic acid (PLA) matrix. The coupling agent used in this specific embodiment is a silane coupling agent, specifically model KH550, i.e. Aminopropyltriethoxysilane.

[0053] Furthermore, the auxiliary materials used in this specific embodiment include dispersants and antioxidants; the dispersant is polyethylene wax, which is used to prevent the agglomeration of nano carbon black particles, significantly reduce melt viscosity and improve extrusion fluidity; the antioxidant is a compound of main antioxidant and auxiliary antioxidant, with antioxidant 1010 as the main antioxidant and antioxidant 168 as the auxiliary antioxidant, which is used to avoid oxidation chain reaction and provide long-term thermal stability; The specific details of the antioxidants used in this embodiment are as follows: the ratio of primary antioxidant 1010 to secondary antioxidant 168 is 1:1; and the amount used is 0.5% of the mass of polylactic acid (PLA) particles.

[0054] Furthermore, the above materials need to be mixed to obtain a mixed raw material. The mass ratio of each component in the mixed raw material used in this specific embodiment is as follows: Polylactic acid (PLA) particles: surface-modified nano-carbon black particles: dispersant: antioxidant = 100:30:2:0.5.

[0055] Furthermore, the raw materials are placed in a high-speed mixer for uniform mixing, with the preferred parameters being a rotation speed of 28,000 rpm and a mixing time of 6 minutes.

[0056] Furthermore, in this specific embodiment, a co-rotating twin-screw extruder is used as the core equipment for the melt blending and granulation step. The screw adopts a modular design, and the threaded elements are connected to the mandrel via involute splines. The installation sequence of the screw elements is as follows: The device comprises a first conveying element, a 45° angle kneading block, a toothed mixing disc, a reverse kneading block, and a second conveying element. The first conveying element is used to rapidly convey materials, the 45° angle kneading block is used to apply high shear stress to the materials to break up agglomerates of nano-carbon black particles, the toothed mixing disc is used to tumble and stir the materials to achieve uniform distribution and mixing, the reverse kneading block is used to increase the residence time of the materials and establish local pressure, and the second conveying element is used to establish stable extrusion pressure at the die head.

[0057] The first conveying element is located below the feed inlet, and its primary task is to transport materials quickly. Therefore, a threaded element with a large lead is selected, and its lead is shown in the following formula:

[0058] in, The lead of the first conveying element, The diameter is the screw diameter.

[0059] The second conveying element is located in front of the die head (at the end of the screw). Its primary task is to ensure the stability of the extrusion pressure at the die head. Therefore, a threaded element with a small lead is selected, and its lead is shown in the following formula:

[0060] in, For the lead of the second conveying element, The diameter is the screw diameter.

[0061] Furthermore, in this specific embodiment, a response surface methodology-genetic algorithm coupling strategy is employed to optimize the extrusion parameters of the twin-screw extruder. In this coupling strategy, the response surface methodology serves as a surrogate model, and the genetic algorithm acts as the optimizer. Specifically, the relationship between the two is as follows: first, a forward mapping model is established using the response surface methodology to obtain the mapping relationship between the optimization design variables and the optimization objective; then, a reverse optimization model is established using the genetic algorithm, which solves for the optimal parameter combination based on the mapping relationship. The optimization design variables include the feeding section temperature, melting section temperature, mixing section temperature, homogenization section temperature, die temperature, and screw speed; the optimization objective includes the volume resistivity of the conductive masterbatch. With extrusion efficiency .

[0062] Furthermore, the volume resistivity of the conductive masterbatch With extrusion efficiency Defined as the optimization objective, the temperature of Zone 1 (feeding section) is... Temperature of Zone 2 (Melting Section) Temperature in Zone 3 (Mixed Section) Temperature in Zone 4 (Homogenization Section) Die head (die) temperature and screw speed Defined as optimization design variables; the value range of each variable is based on empirical values ​​( =190℃ =200℃ =210℃ =205℃ =200℃ Centered on 400 rpm, extend outwards by 20°C~30°C and 150 rpm to both sides to cover a sufficient process window; in summary, the optimization space for the design variables can be obtained as follows:

[0063] Furthermore, to reduce the number of experiments and ensure model accuracy, this specific embodiment employs the Box-Behnken (BBD) design method to design the experimental matrix (with 6 factors). Each factor has 3 level values ​​(coded as -1, 0, and 1), corresponding to the lower limit, center value, and upper limit value of the optimized design variable, respectively. 66 sets of experiments (including 6 sets of experiments with repeated center points) are planned for the 6 optimized design variables. Each set of experiments independently prepares conductive masterbatch, and its volume resistivity is repeatedly tested. And record the extrusion efficiency ; Furthermore, a second-order response surface model was used to analyze the volume resistivity. With extrusion efficiency The specific fitting results obtained by performing fitting separately are shown below:

[0064] in, and The constant term is obtained by fitting multiple regression using the least squares method. and The coefficients of the first-order term obtained by fitting multiple regression using the least squares method are given. and The coefficients of the quadratic term are obtained by fitting multiple regression using the least squares method. and These are the interaction term coefficients obtained through least squares multiple regression fitting. The fitting process was based on 66 sets of BBD experimental data and was completed in Design-Expert software to minimize the sum of squared residuals between the predicted and measured values ​​of the response surface model. In the final model, only terms with a significance level less than 0.05 were retained, and non-significant terms were removed. To optimize the encoded values ​​of design variables, and To optimize the central values ​​of the design variables, the following steps are taken:

[0065] Among them, the center value of the temperature-related optimization design variables The center values ​​of the speed-related optimization design variables are given at temperatures of 190℃, 200℃, 210℃, 205℃, and 200℃, respectively. 350 rpm; step size of temperature-related optimization design variables All temperatures are 20°C, and the step size of the speed-related optimization design variables is... It is 200 rpm.

[0066] Furthermore, a bi-objective optimization model (i.e., a reverse optimization model) that can be used for genetic algorithms (NSGA-II) is established, with the specific objective function shown below:

[0067] in, and This is the second-order surface response fitting model (i.e., the forward mapping model). The goal is to make and To reach the minimum value, the objective function The optimization direction is to make Minimize, objective function The optimization direction is to make The maximization constraint is the optimization space given above, and the extrusion process is free of degradation, bubbles, and stable output.

[0068] Furthermore, a response surface methodology-genetic algorithm coupling strategy is adopted for parameter optimization; The first step is to obtain the experimental matrix using the Box-Behnken (BBD) design method, and then use the data to fit a second-order response surface model to obtain... and This establishes a positive mapping relationship; where the coefficient of determination... The model can explain more than 95% of the response variation, and the corrected coefficient of determination... This indicates that the model has not overfitted, and the lack of fit coefficient is [not specified]. This indicates that the model does not have any missing higher-order terms. The above accuracy judgment criteria refer to GB / T 27407-2010. Overall, it shows that the response surface model constructed in this specific embodiment meets the accuracy requirements. The second step is to find the minimum value of the objective function within the given optimization space using the NSGA-II algorithm; As a reverse optimization target, several sets of extrusion parameter combinations for initial filling are automatically generated within the optimization space, including the temperature of Zone 1 (feeding section). Temperature of Zone 2 (Melting Section) Temperature in Zone 3 (Mixed Section) Temperature in Zone 4 (Homogenization Section) Die head (die) temperature and screw speed This is the initial population. Based on the non-dominated sorting and crowding principle, the best members are selected from the initial population to enter the next generation population. The remaining members generate new populations through crossover and mutation and enter the next generation population. The above population reproduction process is iterated repeatedly. After the iteration is completed, the Pareto optimal solution set is output.

[0069] In this specific embodiment, the NSGA-II optimization model was established on Matlab R2024a; the population size was 200, balancing computational efficiency and search breadth; the maximum number of iterations was 300, ensuring convergence to a stable Pareto front; the termination condition was set to stop iteration when either of the following conditions was met: 1) reaching the maximum number of iterations of 300, 2) no update to the Pareto front for 50 consecutive generations; the crossover probability was 0.85, ensuring that offspring inherit characteristics from their parents; the mutation probability was 0.08, ensuring uniform mutation; the mutation distribution index was 20, used to control the mutation amplitude; the crossover probability was... The distribution index is 20, used to control the similarity between offspring and parents. The above parameters are based on the following: the population size of 200 is 33 times the number of optimization design variables of 6, which is within the recommended range (20~40 times); the crossover probability of 0.85 and the mutation probability of 0.08 are both within the commonly used parameter range of genetic algorithms (crossover probability 0.8~0.95, mutation probability 0.01~0.1), where the mutation probability is slightly higher than the conventional value of 0.05, in order to enhance the ability of the population to escape local optima and prevent premature convergence.

[0070] Furthermore, the resulting Pareto optimal solution set contains 45 non-dominated solutions. This specific embodiment selects the optimal solution from these based on the concept of utopia. First, the utopia point is defined, which is the volume resistivity. and extrusion efficiency The virtual points formed when each reaches the theoretical optimal value; the point in the Pareto solution set that is closest to the Utopia point is defined as the optimal solution, and this shortest distance... The calculation formula is as follows:

[0071] in, and For the Pareto set solution, the first k The function value of each solution. and For Pareto solution lumped volume resistivity and extrusion efficiency The theoretically optimal values ​​that can be achieved respectively.

[0072] Furthermore, in this specific embodiment, the screw diameter of the co-rotating twin-screw extruder is... The diameter is 50 mm, and the aspect ratio is 40:1. Based on the above response surface methodology-genetic algorithm coupling strategy, the extrusion parameters are as follows: Zone 1 (Feeding Section) 185℃; Zone 2 (Melting Section) 200℃; Zone 3 (Mixed Section) 210℃; Fourth Zone (Equalization Section) 205℃; Machine head (die) 200℃; Screw speed 430rpm.

[0073] The response surface model predictions and validation test results for the optimal solution are shown in Table 1 below: Table 1. Response surface model predictions and validation test results for the optimal solution.

[0074] Compared with unoptimized empirical parameters ( =190℃ =200℃ =210℃ =205℃ =200℃ Compared to 400 rpm, this optimal solution reduces the volume resistivity of the prepared conductive masterbatch from 0.052 Ω. m decreased to 0.035Ω m, a decrease of 32.7%; extrusion efficiency increased from about 13.5 kg / h to 15.8 kg / h, an increase of 17.0%.

[0075] Further, the subsequent operation steps are as follows: start the heating system and keep it warm for 15 minutes after each area reaches the set temperature; start the screw motor and run it at a low speed of 75 rpm, while adding the mixed raw materials into the hopper; after the melt is stably extruded, gradually increase the screw speed to the optimized value of 430 rpm; the high shear force generated by the screw element on the material breaks down the carbon black agglomerates and disperses them evenly in the polylactic acid (PLA) matrix, and the extruded melt is extruded through the die to form a round strip material with a diameter of 3 mm.

[0076] Furthermore, the extruded cylindrical material is passed through a cooling water tank with the water temperature controlled at 25℃ and the cooling area being 2.8m long. A hot air blower is used to dry the surface moisture of the material strip, with the temperature controlled at 50℃. Finally, the dried material strip is fed into a pelletizer, with the pelletizing speed consistent with the extrusion speed and the pellet length controlled within the range of 2-3mm, to obtain cylindrical conductive masterbatch.

[0077] Furthermore, random samples were taken from the obtained cylindrical conductive masterbatch, and the volume resistivity of the conductive masterbatch was tested using the four-probe method according to GB / T 15662, and compared with the target value. Volume resistivity is a physical quantity that measures the internal resistance characteristics of a material, and its calculation formula is as follows:

[0078] in, For volume resistivity, This is the measured resistance value. This refers to the cross-sectional area of ​​the cylindrical conductive masterbatch. The length of the cylindrical conductive masterbatch; in this specific embodiment, the target volume resistivity is... The value is set at 0.05Ω. m, and the cross-sectional area of ​​the cylindrical conductive masterbatch Approximately 7.069 × 10 -6 m 2 ,length Approximately 3mm; if If the obtained conductive masterbatch is qualified, it can be used to continue the filament extrusion molding step; if If the carbon black particles are not properly dispersed, the resulting conductive masterbatch will be rejected and returned to the melt blending and granulation step for secondary processing. To better ensure the quality of the prepared conductive masterbatch, its cross-section is observed using an electron microscope to ensure that the carbon black particles are uniformly dispersed and free of visible agglomerates.

[0079] Furthermore, in this specific embodiment, the single-screw extruder used in the filament extrusion molding step has a screw diameter of 25mm and an aspect ratio of 30:1; the die diameter is 1.75mm; the subsequent extrusion parameters are also set based on the aforementioned response surface methodology-genetic algorithm coupling strategy. The optimized result is an extrusion temperature of 200℃ and a screw speed of 40rpm. Under these parameters, the diameter uniformity rate of the extruded conductive resin filaments (the proportion of filament lengths with diameters falling within the tolerance range of 1.75±0.05mm to the total length) increases from approximately 82.3% to 95.6%.

[0080] Further, the subsequent operating steps are as follows: start the heating system and keep it at the set temperature for 10 minutes; start the screw motor and run it at a low speed of 40 rpm; after the melt is extruded from the die, gradually adjust the screw speed to ensure that the surface of the extruded filament is smooth and free of air bubbles, and finally stabilize the screw speed at 80 rpm.

[0081] Furthermore, the extruded filaments undergo cooling and drying processes using a cooling water tank and a hot air blower. The dried filaments are then passed through a traction machine at a traction speed of 8 m / min, which is adjusted to match the extrusion speed. A laser diameter measuring device is installed in the traction machine to monitor the filament diameter in real time; in this specific embodiment, a target filament diameter is set. The diameter is 1.75mm, and the tolerance is controlled within ±0.05mm. If the requirements are met, the extruded conductive polylactic acid (CB-PLA) filament will be wound up by an automatic winding machine. If the requirements are not met, the process parameters will be adjusted and the filament extrusion molding process will be repeated.

[0082] Furthermore, the obtained conductive polylactic acid (CB-PLA) filaments and continuous carbon fiber prepreg filaments are in-situ impregnated inside the nozzle to achieve co-extrusion 3D printing; in addition, a field generation device is arranged during the co-extrusion 3D printing process to achieve field control design of the conductive path in the formed part; the details of this specific embodiment are as follows: The parameters for the co-extrusion 3D printing process were set as follows: nozzle temperature 230℃, printing speed 8mm / s, printing layer thickness 0.3mm, deposition line spacing 0.65mm, and printing platform temperature 60℃. This embodiment uses a microelectrode array as the field generating device. During the printing process, a non-uniform electric field can be applied to exert a directional driving force (dielectrophoresis force) on the nano-carbon black particles, causing them to migrate and accumulate in the uncured resin along a specified direction, thereby constructing a conductive network at a designated location. The microelectrode array consists of multiple independently controllable electrode units. The electrode units are made of high-purity copper and arranged as follows: the electrode units are arranged in a matrix, with an adjacent electrode spacing of 0.5-2 mm to ensure continuous and controllable electric field coverage; the diameter of a single electrode unit is 0.3-1 mm, which can be selected according to the printing accuracy requirements; polyimide is filled between adjacent electrode units as an insulating material to prevent short circuits and electric field crosstalk. The dielectric force experienced by nano-carbon black particles in a non-uniform electric field is determined by the theory of time-averaged dielectric force, specifically as follows:

[0083] in, The time-averaged dielectrophoretic force over one period; The radius of the nano-carbon black particles is taken as 60 nm in this embodiment; The dielectric constant of polylactic acid (PLA) melt is 7.08 × 10⁻⁶ in this embodiment. -11 F / m; The complex permittivity of the carbon black particles is denoted as . Let be the complex permittivity of polylactic acid (PLA), and ; denoted as the root mean square value of the electric field strength.

[0084] The directionality of dielectrophoretic forces is determined by an orientation factor, as shown below:

[0085] in, As the orientation factor, and frequency Related. Because ,Right now ,so This indicates that carbon black particles move towards the location of the maximum electric field strength, a phenomenon known as positive dielectric electrophoresis.

[0086] This embodiment uses a six-axis industrial robot as the foundation of the entire co-extrusion 3D printing system. The control system adopts the SINUMERIK 840D sl CNC system, which can realize the coupled synchronous control of custom M commands and 3D printing G codes. A hexagonal honeycomb structure is used as the printing object, and its conductive path is designed for field control through a microelectrode array. Specifically, the microelectrode array is connected to the electrical control module of the 3D printing system, and the CNC system controls its switching via a PLC. While writing the G code for the hexagonal honeycomb structure printing path, the control logic of the microelectrode array is also written into it to achieve coordinated control of the printing path and the conductive path. The CNC system reads the X / Y / Z coordinate values ​​of the end print nozzle in real time. When the nozzle coordinates fall into the preset conductive range, the corresponding electrode array is triggered to output a non-uniform electric field.

[0087] Furthermore, in this specific embodiment, six custom M-instructions are allocated to the microelectrode array in the SINUMERIK 840D sl CNC system. These instructions can be directly written into the G-code program, read by the CNC system, and responded to quickly. They are used for field control design strategies that add conductive paths in the printed path G-code, as follows: The M500 command is used to activate a specified electrode unit and set the field strength. The M501 command is used to shut down a specified electrode unit. The M502 command is used to shut down all active electrode units. The M503 command is used to set the pulse frequency of a specified electrode unit; The M504 instruction is used to set the duty cycle of a specified electrode unit; The M505 instruction is used for synchronization time in buffer field control design.

[0088] Furthermore, this specific embodiment incorporates a print path-conductive path collaborative design and visualization program in the host computer, with the specific workflow as follows: 1) Import the STL file of the target part. The built-in program can automatically generate the default printing path - conductive path 3D printing G-code and visualize it. 2) Based on the color differentiation of different paths in the visualization cloud map, customize the conductive path and flexibly insert M500~M505 commands to complete the conductive path design; 3) The resistance value of the target part under the designed conductive path is predicted based on the dielectric electrophoresis theory and field control parameters as a theoretical reference value.

[0089] like Figure 2As shown, this embodiment provides a conductive resin filament preparation system for 3D printing, including a co-rotating twin-screw extruder 1, a cooling water tank 2, a hot air blower 3, a pelletizer 4, a single-screw extruder 5, a traction machine 6, and an automatic winding machine 7. The co-rotating twin-screw extruder 1, the cooling water tank 2, the hot air blower 3, and the pelletizer 4 form a conductive masterbatch preparation module for obtaining cylindrical conductive masterbatches. The single-screw extruder 5, the cooling water tank 2, the hot air blower 3, the traction machine 6, and the automatic winding machine 7 form a resin filament extrusion module for obtaining conductive resin filaments. The conductive masterbatch preparation module and the resin filament extrusion module cooperate with each other. After the conductive masterbatch preparation module completes the melt blending and granulation step, the obtained conductive masterbatch is poured into the resin filament extrusion module for extrusion molding of conductive resin filaments. Both modules share a set of cooling water tank 2 and hot air blower 3.

[0090] like Figure 3 As shown, this embodiment provides a robotic co-extrusion 3D printing system, including a printing nozzle 8, a six-axis industrial robot 9, a host computer 10, a printing platform 11, and a microelectrode array 12. The printing nozzle 8 is installed at the end of the six-axis industrial robot 9. The host computer 10 is connected to the six-axis industrial robot 9, the printing nozzle 8, and the printing platform 11, respectively. The six-axis industrial robot 9 drives the printing nozzle 8 to perform printing on the printing platform 11. The microelectrode array 12 is embedded on the surface of the printing platform 11, with both surfaces flush. The microelectrode array 12 is connected to the host computer 10 through the printing platform 11. The host computer 10 includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it executes the above-mentioned 3D printing conductive path design method for continuous fiber reinforced conductive resin matrix composite material.

[0091] This specific embodiment is based on, as follows Figure 2 The conductive resin filament preparation system for 3D printing shown herein prepared conductive polylactic acid (CB-PLA) filaments containing nano-carbon black particles, which are named CB-PLA for easy distinction; the microscopic cross-section of the prepared CB-PLA filaments is shown below. Figure 4 As shown in (a), uniformly distributed nano-carbon black particles with no visible agglomerates can be clearly seen. The volume fraction is about 26.5%, the mass fraction is about 52.3%, and the average diameter is about 120 nm.

[0092] This specific embodiment is based on, as follows Figure 3The robotic co-extrusion 3D printing system shown here instructs for in-situ impregnation of conductive polylactic acid (CB-PLA) filaments with continuous carbon fiber prepreg filaments to achieve co-extrusion 3D printing, which is named CCF / CB-PLA. For comparison with the material prepared in this embodiment, commercially available ordinary polylactic acid (PLA) filaments were also co-extruded with continuous carbon fiber prepreg filaments for 3D printing, and this was also named CCF / PLA. In this embodiment, the diameter of the continuous carbon fiber prepreg filaments used was 0.35 mm, and the diameters of both the conductive polylactic acid (CB-PLA) filaments and the ordinary polylactic acid (PLA) filaments were 1.75 mm. Tensile properties were tested on the two co-extruded 3D printed filaments, and the results are as follows: Figure 4 As shown in Figure (b), the tensile strength of both CCF / CB-PLA monofilament and CCF / PLA monofilament is around 130 MPa, indicating that the CCF / CB-PLA monofilament prepared in this embodiment can have better electrical properties without sacrificing mechanical properties.

[0093] Combining the above-mentioned conductive polylactic acid (CB-PLA) filament and CCF / CB-PLA co-extrusion 3D printing process, this specific embodiment uses a method and system for preparing and designing conductive paths of continuous fiber reinforced conductive resin matrix composites for 3D printing to perform collaborative design of printing paths and conductive paths for typical hexagonal honeycomb structures. The specific design principles are as follows: Figure 5 As shown, the smallest unit in the printing path is a hexagonal honeycomb with a side length of 15mm and a wall thickness of 1.2mm. The overall printing thickness is set to 2.1mm, meaning 7 layers are stacked and printed. The conductive path design results are divided into two types: the first conductive path ( Figure 5 (middle green path), second conductive path ( Figure 5 (Red path in the middle). The first conductive path is the ideal path for current to pass through. During the printing process, the microelectrode array applies a non-uniform electric field to drive the nano-carbon black particles in the deposition lines on both sides of the first conductive path to move towards each other, thereby enriching the carbon black particles and reducing the resistance of the first conductive path. The second conductive path is the non-ideal path for current to pass through. During the printing process, the microelectrode array applies a non-uniform electric field to drive the nano-carbon black particles in the deposition lines on both sides of the second conductive path to move away from each other, thereby isolating the carbon black particles and increasing the resistance of the second conductive path. In actual printing, through the coordinated operation of the first and second conductive paths, various conductive paths can be flexibly designed and manufactured. Furthermore, compared to randomly distributed conductive paths, the electric field-guided conductive path design method proposed in this embodiment can reduce the volume resistivity of the component along a certain direction (e.g., the Y-axis direction) by more than 90%. Detailed conductive path design examples Figure 6As shown, a total of four conductive path schemes were designed; among them, Figure 6 The conductive path in (a) is the lowest resistance path. Its design principle follows the series-parallel logic of resistors, which can significantly reduce the resistance of the hexagonal honeycomb structure along the Y-axis in this embodiment. Figure 6 (b) Figure 6 (c) Figure 6 (d) shows more complex application cases of the conductive path design and manufacturing method proposed in this embodiment. Based on this, different conductive paths can be designed for the printing path of each layer, thereby realizing complex spatial conductive network design. The measured resistance data of the four conductive paths designed in this embodiment are as follows: Figure 7 As shown, compared to the random circuit distribution without conductive path design, the four designed conductive paths all reduced the resistance value by more than 70%; especially... Figure 6 The lowest resistance path shown in (a) reduces the resistance of the hexagonal honeycomb structure by 91.84% along the Y-axis.

[0094] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for designing conductive paths based on continuous fiber-reinforced conductive resin matrix composites, characterized in that, The steps are as follows: Conductive resin filaments and continuous fiber prepregs are co-extruded and 3D printed. During the 3D printing process, a non-uniform field is applied to the conductive resin filaments to guide the secondary distribution of conductive filler particles in the conductive resin filaments, thereby realizing the design of conductive paths in the 3D printed components.

2. The conductive path design method based on continuous fiber-reinforced conductive resin matrix composite material as described in claim 1, characterized in that: In the co-extrusion 3D printing process, the spatial and temporal characteristics of the field signal are coordinated and controlled to achieve secondary guided distribution of conductive filler particles in the region corresponding to the predetermined path, thereby completing the field control design of the conductive path.

3. The conductive path design method based on continuous fiber-reinforced conductive resin matrix composite material as described in claim 1, characterized in that: The parameters of the field signal are adjusted based on the printing path, including the spatial coordinates of the field, the start time of the field, and the intensity of the field.

4. The conductive path design method based on continuous fiber-reinforced conductive resin matrix composite material as described in claim 1, characterized in that: The conductive path is divided into a first conductive path and a second conductive path. The first conductive path is the ideal path for current to pass through, while the second conductive path is the non-ideal path for current to pass through. During the printing process, a non-uniform electric field is applied to drive the conductive filler particles in the deposition lines on both sides of the first conductive path to move towards each other, thereby enriching the conductive filler particles and reducing the resistance of the first conductive path. A non-uniform electric field is applied to drive the conductive filler particles in the deposition lines on both sides of the second conductive path to move away from each other, thereby isolating the conductive filler particles and increasing the resistance of the second conductive path.

5. The conductive path design method based on continuous fiber-reinforced conductive resin matrix composite material as described in any one of claims 1-4, characterized in that: The preparation steps of the conductive resin filament are as follows: (1) After pretreatment of thermoplastic resin particles and conductive filler particles, thermoplastic resin particles, conductive filler particles and auxiliary materials are put into a high-speed mixer. Finally, the high-speed mixer is started to mix the thermoplastic resin particles, conductive filler particles and auxiliary materials evenly. (2) The obtained uniformly mixed raw material is poured into a twin-screw extruder and melt-blended extrusion is performed. A series of post-processing operations are performed on the extruded cylindrical material to obtain cylindrical conductive masterbatch. (3) The obtained cylindrical conductive masterbatch is poured into a single screw extruder and melt extruded. Finally, the obtained conductive resin filament is post-processed to obtain conductive resin filament.

6. The conductive path design method based on continuous fiber-reinforced conductive resin matrix composite material as described in claim 5, characterized in that: The extrusion parameters of single-screw extruders and twin-screw extruders are optimized based on intelligent algorithms.

7. The conductive path design method based on continuous fiber-reinforced conductive resin matrix composite material as described in claim 6, characterized in that: First, a forward mapping model is established using the response surface methodology. This model obtains the mapping relationship between the optimization design variables and the optimization objective. Then, a reverse optimization model is established using a genetic algorithm. This model solves for the optimal parameter combination based on the mapping relationship. The optimization design variables include the feeding section temperature, melting section temperature, mixing section temperature, homogenization section temperature, die temperature, and screw speed. The optimization objective includes the volume resistivity of the conductive masterbatch. With extrusion efficiency .

8. The conductive path design method based on continuous fiber-reinforced conductive resin matrix composite material as described in claim 7, characterized in that: A second-order response surface model was used to study the volume resistivity. With extrusion efficiency The fitting was performed separately, and the corresponding formulas are as follows: in, and The constant term is obtained by fitting multiple regression using the least squares method. and The coefficients of the first-order term obtained by fitting multiple regression using the least squares method are given. and The coefficients of the quadratic term are obtained by fitting multiple regression using the least squares method. and These are the interaction term coefficients obtained by fitting multiple regression using the least squares method; To optimize the encoded values ​​of design variables, .

9. A robotic co-extrusion 3D printing system, characterized in that: The printing system includes a host computer, a printing component, and a field generating device mounted on the printing component. The printing component is used to co-extrude conductive resin filaments and continuous fiber prepreg filaments for 3D printing. During the 3D printing process, the host computer controls the field generating device to apply a non-uniform field to the conductive resin filaments to guide the secondary distribution of conductive filler particles in the conductive resin filaments, thereby realizing the design of conductive paths in the 3D printed components.

10. The robotic co-extrusion 3D printing system as described in claim 9, characterized in that: The printing assembly includes a six-axis industrial robot, a print head, and a printing platform. The print head is mounted at the end of the six-axis industrial robot. The host computer is connected to the six-axis industrial robot, the print head, and the printing platform, respectively. The six-axis industrial robot drives the print head to perform printing on the printing platform. The field generating device is embedded in the surface of the printing platform, with both surfaces flush. The field generating device is connected to the host computer through the printing platform.

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