A Multi-Machine Collaborative Fused Wire Additive Manufacturing Method and System Based on Regional Temperature Prediction

Abstract

This invention provides a multi-machine collaborative arc-fuse additive manufacturing method and system based on regional temperature prediction, applicable to the arc-fuse additive manufacturing of large-format magnesium and aluminum alloy components. The method includes: obtaining the temperature T at any point A on the end face of the component when forming the i-th layer under a single actuator through simulation. iA The curve showing the change over time is based on the single-layer forming time t. i The interlayer temperature control range T1~T2 corresponds to the re-addition time range [t] iA1‑ t iA0 , t iA2‑ t iA0 Determine the range n of the number of partitions in this layer. i By adopting multi-actuator partitioned collaborative additive manufacturing, optimizing the partitioning method and the path planning of each partition, the temperature control between layers of each partition is realized and local overheating is eliminated without the need for external auxiliary heat sources, thereby improving the utilization rate of additive manufacturing heat sources.

Description

Technical Field

[0001] This invention relates to the field of arc wire deposition forming technology, specifically to a multi-machine collaborative arc wire additive manufacturing method and system based on regional temperature prediction, applicable to the arc wire additive manufacturing of large-format magnesium and aluminum alloy components. Background Technology

[0002] Arc additive manufacturing, as a rapid manufacturing technology, boasts high flexibility and material utilization, and has broad application prospects in aerospace, weaponry, and other equipment fields. Currently, however, arc additive manufacturing still faces significant challenges in shape and property control, one key reason being the control of interlayer temperature. When the interlayer temperature is too high, "flowing" or nodules easily occur at the edges of the formed part, severely reducing forming accuracy. Some metallic materials may also experience elemental segregation, hot cracking, and other defects, significantly reducing mechanical properties. Conversely, when the interlayer temperature is too low, defects such as incomplete fusion, porosity, and cracks easily form, severely impacting the part yield. Furthermore, in the process of large-format magnesium and aluminum alloy component fused wire additive manufacturing, the excessively rapid heat dissipation rate of the formed part and insufficient heat accumulation lead to excessively low interlayer temperatures and excessively large temperature gradients, easily resulting in forming defects.

[0003] To address the aforementioned challenges, researchers currently employ auxiliary or composite heat sources for forming, and use infrared thermometers to monitor temperature information in real time. They then adaptively adjust external cooling devices or additive manufacturing process parameters to achieve interlayer temperature control and reduce temperature gradients.

[0004] Patent document CN106670623B (application number: 201710177806.1) discloses a device for actively controlling the interlayer temperature in arc additive manufacturing. This device achieves interlayer temperature control by heating and cooling a substrate or part using an electromagnetic induction heating device and a cooling device. This method employs an auxiliary heat / cold source and can be used for interlayer temperature control during the forming of large-format parts, but it does not improve the utilization rate of the additive manufacturing heat source.

[0005] Patent document CN117259929A ​​(application number: 202311309070.0) discloses an additive manufacturing apparatus suitable for large-size rotating body structures. This apparatus can form large-size rotating body components without being limited by the radius size of the rotating body or the irregular curve of the generatrix. However, it is only applicable to rotating body components and does not involve interlayer temperature control methods or additive heat source utilization.

[0006] Patent document CN119368930A (application number: 202411557066.0) discloses an additive manufacturing apparatus and method with multiple heat sources and multiple wires fed synchronously. A single actuator is equipped with a composite heat source and a multi-arc process is used to greatly improve the heat input of additive manufacturing, but it does not solve the problem of interlayer temperature control when forming large-format parts.

[0007] Patent document CN118404164A (application number: 202410509469.1) discloses an additive manufacturing method and apparatus based on a multi-wire arc combination with thermo-mass balance. The assembled multi-wire multi-arc composite gun body, through thermo-mass balance conditions, allows the arc heat to be mainly used to melt the wire, reducing the arc heat input acting on the substrate and the additive sample. It is suitable for parts with low heat dissipation rate, but not suitable for large-format component fused wire additive manufacturing, and does not involve interlayer temperature control methods.

[0008] In summary, while using auxiliary or composite heat sources in conjunction with infrared thermometers can achieve interlayer temperature control, it has certain limitations when dealing with the fused wire additive manufacturing of large-format parts: ① The multi-machine collaborative process is complex, and without simulation optimization, interlayer temperature control of large-format components is difficult to achieve, and local overheating problems are prone to occur, failing to maximize the utilization of each additive heat source; ② The heat dissipation conditions and temperature field distribution of the formed parts change in real time, and online monitoring of temperature information and dynamic adjustment of process parameters have little effect on interlayer temperature control.

[0009] This invention sets the interlayer temperature range of the formed component and predicts the re-addition time range. After dividing the sheet into sections, it uses multiple actuators to perform collaborative additive manufacturing. It also optimizes the iterative sectioning method, path planning for each section, and process parameters to achieve interlayer temperature control in each section and eliminate local low temperature problems. This effectively improves the utilization rate of heat sources and ultimately realizes multi-machine collaborative filament additive manufacturing without external auxiliary heat sources. Summary of the Invention

[0010] To address the shortcomings of existing technologies, the purpose of this invention is to provide a multi-machine collaborative fused wire additive manufacturing method and system based on regional temperature prediction.

[0011] A multi-machine collaborative fused wire additive manufacturing method based on regional temperature prediction according to the present invention includes:

[0012] Step S1: Simulate and obtain the temperature of any point A on the end face of the formed component at the i-th layer under the condition of a single actuator without an external heating source. With time Change curve;

[0013] Step S2: Based on the temperature at any point A on the end face With time Variation curves and preferred interlayer temperature control range ~ Determine the re-addition time range; determine the range of the number of end face partitions of the i-th layer based on the re-addition time range;

[0014] Step S3: Determine the number of end face partitions in the i-th layer based on the range of the number of end face partitions in the i-th layer. Each partition is formed by one actuator. By optimizing the iterative partitioning method, the path planning of each partition and the process parameters, the preset requirements are met for any point in each partition. The forming time of each partition by a single actuator is determined.

[0015] Preferably, step S2 includes:

[0016] Step S2.1: Based on the temperature at any point A on the end face With time Variation curves and preferred interlayer temperature control range ~ Determine the time range for re-addition. ;in, This indicates the time when the i-th layer begins to form. The temperature at time point A is Based on the preferred interlayer temperature control range ~ Determine the time it takes for the temperature to drop to T1. and the time to drop to T2 ;

[0017] Step S2.2: Based on the positions of multiple end face points A, according to Get multiple The scope; among which, Indicates the completion time of the i-th layer;

[0018] Step S2.3: Based on ni= Get the range of the number of partitions in the i-th level .

[0019] Preferably, step S2.1 includes:

[0020] The preferred interlayer temperature control range T1~T2 for magnesium alloy arc-fused wire additive manufacturing is 100~70℃;

[0021] The preferred interlayer temperature control range T1~T2 for aluminum alloy arc wire additive manufacturing is 110~50℃.

[0022] Preferably, step S3 includes:

[0023] Step S3.1: Simulate and obtain the temperature of any point A' on the end face of the i-th layer in the k-th region without an external heating source. With time The curve of change;

[0024] Step S3.2: Determine the start time of forming the i-th layer based on the preferred interlayer temperature control range T1~T2. and Initial temperature at time point A' K-zone begins to form time and this Temperature at time point A' The lowest temperature at point A' in region k K-zone end forming time and the temperature at point A' at this time The time for the i-th layer to finish forming and Temperature at time point A' Calculate the forming time of this layer. ;

[0025] .

[0026] Preferably, the step of optimizing the iterative partitioning method, the path planning for each partition, and the process parameters to ensure that any point within each partition meets the preset requirements includes:

[0027] Any point within each partition satisfies ,in, Indicates the number of end face partitions in the i-th layer; This represents the time required for a single actuator to form the i-th layer. When the condition is met, the number of partitions in the i-th layer, the corresponding partitioning method, the path planning for each partition, and the process parameters are output. Otherwise, the number of end face partitions in the i-th layer is re-determined, and iterative optimization is triggered again until the condition is met at any point in each partition.

[0028] A multi-machine collaborative fused wire additive manufacturing system based on regional temperature prediction, provided by the present invention, includes:

[0029] Module M1: Simulates the temperature at any point A on the end face of the formed component at the i-th layer under the condition of a single actuator and no external heating source. With time Change curve;

[0030] Module M2: Temperature based on any point A on the end face With time Variation curves and preferred interlayer temperature control range ~ Determine the re-addition time range; determine the range of the number of end face partitions of the i-th layer based on the re-addition time range;

[0031] Module M3: Determines the number of end face partitions in the i-th layer based on the range of the number of end face partitions in the i-th layer. Each partition is formed by an actuator. By optimizing the iterative partitioning method, the path planning of each partition and the process parameters, the system ensures that any point in each partition meets the preset requirements and determines the forming time of each partition by a single actuator.

[0032] Preferably, the module M2 includes:

[0033] Module M2.1: Temperature based on any point A on the end face With time Variation curves and preferred interlayer temperature control range ~ Determine the time range for re-addition. ;in, This indicates the time when the i-th layer begins to form. The temperature at time point A is Based on the preferred interlayer temperature control range ~ Determine the time it takes for the temperature to drop to T1. and the time to drop to T2 ;

[0034] Module M2.2: Based on the positions of multiple end face points A, according to Get multiple The scope; among which, Indicates the completion time of the i-th layer;

[0035] Module M2.3: Based on ni= Get the range of the number of partitions in the i-th level .

[0036] Preferably, module M2.1 includes: a preferred interlayer temperature control range T1~T2 of 100~70℃ for magnesium alloy arc wire additive manufacturing; and a preferred interlayer temperature control range T1~T2 of 110~50℃ for aluminum alloy arc wire additive manufacturing.

[0037] Preferably, the module M3 includes:

[0038] Module M3.1: Simulates and obtains the temperature of any point A' on the end face of the i-th layer in the k-th region under multiple actuators without an external heating source. With time The curve of change;

[0039] Module M3.2: Determine the start time of the i-th layer forming based on the preferred interlayer temperature control range T1~T2. and Initial temperature at time point A' K-zone begins to form time and this Temperature at time point A' The lowest temperature at point A' in region k K-zone end forming time and the temperature at point A' at this time The time for the i-th layer to finish forming and Temperature at time point A' Calculate the forming time of this layer. ;

[0040] .

[0041] Preferably, the step of optimizing the iterative partitioning method, the path planning for each partition, and the process parameters to ensure that any point within each partition meets the preset requirements includes:

[0042] Any point within each partition satisfies ,in, Indicates the number of end face partitions in the i-th layer; This represents the time required for a single actuator to form the i-th layer. When the condition is met, the number of partitions in the i-th layer, the corresponding partitioning method, the path planning for each partition, and the process parameters are output. Otherwise, the number of end face partitions in the i-th layer is re-determined, and iterative optimization is triggered again until the condition is met at any point in each partition.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] 1. This invention discloses a multi-machine collaborative fused wire additive manufacturing method based on regional temperature prediction, applicable to the fused wire additive manufacturing of large-format magnesium and aluminum alloy components. Through simulation, the temperature TiA at any point A on the end face of the component being formed under a single actuator is obtained as a function of time. Based on the single-layer forming time ti and the re-addition time range [tiA1-tiA0, tiA2-tiA0] corresponding to the interlayer temperature control range T1~T2, the number of partitions ni for that layer is determined. Multi-actuator partitioned collaborative additive manufacturing is adopted, and the iterative partitioning method and path planning for each partition are optimized to achieve interlayer temperature control in each partition and eliminate local overheating, thereby improving the utilization rate of the additive heat source.

[0045] 2. This invention predicts the forming temperature curves of each zone, and controls them to be within the preferred interlayer temperature range by optimizing the zone segmentation method, the path planning of each zone, and the process parameters, thereby eliminating the problem of local overheating, effectively improving the utilization rate of the heat source of fused wire additive manufacturing, and finally realizing efficient, high-quality, and low-cost fused wire additive manufacturing with multi-machine collaboration without external auxiliary heat sources.

[0046] 3. This invention addresses the bottleneck of insufficient heat source utilization in fused wire additive manufacturing, which requires an external auxiliary heat source to control the interlayer temperature of parts with large forming areas. By setting the interlayer temperature range of the formed component and predicting the re-addition time range of each layer, the sheet is divided into sections and multiple actuators are used for collaborative additive manufacturing. The method of dividing each layer, the path planning of each section, and the process parameters are optimized and iterated to control the interlayer temperature of each section and eliminate local overheating, thereby improving the utilization rate of the fused wire additive manufacturing heat source. Ultimately, this invention achieves efficient, high-quality, and low-cost fused wire additive manufacturing with multiple machines working together without the need for an external auxiliary heat source. Attached Figure Description

[0047] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0048] Figure 1 The temperature T at any point A on the end face of the i-th layer without an external heating source for a single actuator. iA A schematic diagram of the change over time.

[0049] Figure 2 The temperature T at any point A' on the end face of the i-th layer in the k-th zone of a multi-actuator without an external heating source. kiA’ A schematic diagram of the change over time.

[0050] Figure 3 This is a schematic diagram of an additive manufacturing method for multi-machine partitioned collaboration in a typical large-size frame structure. Detailed Implementation

[0051] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.

[0052] Example 1

[0053] According to the present invention, a multi-machine collaborative fused wire additive manufacturing method based on regional temperature prediction is provided, which simulates and obtains the temperature T at any point A on the end face of the i-th layer of the formed component under single actuator without external heating source. iA The curve shows the change over time, based on the forming time t of this layer. i The interlayer temperature control range T1~T2 corresponds to the re-addition time range [t] iA1- t iA0 , t iA2- t iA0 Determine the number of partitions n in this layer. iThe range; each partition is formed by one actuator. By optimizing the partitioning method, the path planning of each partition and the process parameters, the interlayer temperature of each partition is controlled and the local overheating problem is eliminated, realizing multi-machine collaborative fused wire additive manufacturing without external auxiliary heat source.

[0054] The multi-machine collaborative fused wire additive manufacturing method based on regional temperature prediction includes:

[0055] Step S1: Simulate and obtain the temperature of any point A on the end face of the formed component at the i-th layer under the condition of a single actuator without an external heating source. With time Change curve;

[0056] Step S2: Based on the temperature at any point A on the end face With time Variation curves and preferred interlayer temperature control range ~ Determine the re-addition time range; determine the range of the number of end face partitions of the i-th layer based on the re-addition time range;

[0057] Specifically, the temperature at any point A on the end face With time The curve represents the temperature change at any point A over time after the i-th layer of the component is formed by a single actuator without an external heating source. This curve determines the start time of the i-th layer's forming process. and the initial temperature at point A at this time The time for the i-th layer to finish forming and the temperature at point A at this time The time required for the temperature to drop to T1 is determined based on the preferred interlayer temperature control range. and the time to drop to T2 .

[0058] The preferred interlayer temperature control range T1~T2 for magnesium alloy arc wire additive manufacturing is 100~70℃, and the preferred interlayer temperature control range T1~T2 for aluminum alloy arc wire additive manufacturing is 110~50℃.

[0059] Number of partitions n i The scope, according to (n) iA (where n is an integer), obtain the position of point A, change the position of point A to obtain the range of multiple points A; calculate n. i = .

[0060] Step S3: Determine the number of end face partitions in the i-th layer based on the range of the number of end face partitions in the i-th layer. Each partition is formed by one actuator. By optimizing the iterative partitioning method, the path planning of each partition and the process parameters, the preset requirements are met for any point in each partition. The forming time of each partition by a single actuator is determined.

[0061] Specifically, the temperature at any point A' on the end face of the i-th layer in the k-th region is obtained through simulation without an external heating source for multiple actuators. With time Based on the variation curve and the preferred interlayer temperature control range T1~T2, the starting time of the i-th layer is determined. and the initial temperature at point A' K-zone begins to form time and the temperature at point A' at this time The lowest temperature at point A' in region k K-zone end forming time and the temperature at point A' at this time The time for the i-th layer to finish forming and the temperature at point A' at this time Calculate the forming time of this layer. ; ;

[0062] Optimize the partitioning method, path planning for each partition, and process parameters so that any point A' within each partition satisfies When the conditions are met, the number of partitions in the i-th layer, the corresponding partitioning method, the path planning of each partition, and the process parameters are output; otherwise, the number of end face partitions in the i-th layer is re-determined, and iterative optimization is triggered again until the conditions are met at any point in each partition.

[0063] Output the number of partitions in the i-th layer, n k And the corresponding partitioning methods, path planning for each partition, and process parameters.

[0064] Wherein, the time of start of forming of the i-th layer With the start of formation time of region k The time for the i-th layer to finish forming With the end of forming time of zone k The overlap is not complete, and there are empty travel paths for the actual implementing agency. A certain amount of time needs to be allowed to ensure that each zone completes the same layer formation, so as to avoid the problem of misalignment and defects such as incomplete fusion at the regional overlap.

[0065] The output number of partitions nk in the i-th layer is the optimized result to meet the interlayer temperature control requirements. Using this optimization result, it can be guaranteed that all points in each partition meet the interlayer temperature control requirements during forming, and that the layer height of each partition is consistent with that of the partition, with no defects in the area overlap.

[0066] The present invention also provides a multi-machine collaborative fused wire additive manufacturing system based on regional temperature prediction. The multi-machine collaborative fused wire additive manufacturing system based on regional temperature prediction can be implemented by executing the process steps of the multi-machine collaborative fused wire additive manufacturing method based on regional temperature prediction. That is, those skilled in the art can understand the multi-machine collaborative fused wire additive manufacturing method based on regional temperature prediction as a preferred embodiment of the multi-machine collaborative fused wire additive manufacturing system based on regional temperature prediction.

[0067] Example 2

[0068] Example 2 is a preferred example of Example 1.

[0069] This embodiment takes a typical frame component with a length of 2400mm and a width of 1500mm as an example;

[0070] A multi-machine collaborative fused wire additive manufacturing method based on regional temperature prediction according to the present invention includes:

[0071] Step 1: Determine the additive manufacturing direction and optimize the additive model, then perform layer slicing and path planning to determine the forming time t of the i-th layer single actuator. i ;

[0072] Calculate the second layer (i=2), t2=160min.

[0073] Step 2: Simulate and obtain the temperature T at any point A on the end face of the i-th layer without an external heating source using a single actuator. iA Based on the time-varying curve and the preferred interlayer temperature control range T1~T2℃, the re-addition time range [t] is determined. iA1- t iA0 , t iA2- t iA0 and the number of partitions n in this layer i The range.

[0074] Set T1=90℃, T2=70℃, and calculate t at any point A. 2A1- t 2A0 =20min,t 2A2- t 2A0 =28min, according to n 2A Given a partition number range of [4, 9], change the position of point A and calculate n. 2A Value, n2= Finally, the number of partitions n2 is found to be in the range [3, 10].

[0075] Step 3: The i-th layer sheet is partitioned into n parts. k There are n, where n k ∈n iOptimize the model for each partition, perform path planning for each partition, and determine the formation time t of a single actuator in each partition. ki ;

[0076] Set n k =6, divide the second layer sheet into 6 regions, and determine the forming time t. 12 , t 22 …t 62 .

[0077] Step 4: Simulate and obtain the temperature T at any point A' on the end face of the i-th layer in the k-th region without an external heating source. kiA' Based on the curve of temperature variation with time and the optimal interlayer temperature control range T1~T2, the starting time t of the i-th layer is determined. kiA'0 and the initial temperature T at point A' at this time. kiA'0 The time t for the k region to begin forming kiA's and the temperature T at point A' at this time kiA's The lowest temperature T at point A' in region k kiA'min The forming time t of the k-zone is completed. kiA'e and the temperature T at point A' at this time kiA'e The forming time of the i-th layer is t kiA'3 and the temperature T at point A' at this time kiA'3 Calculate the forming time t of this layer. i ';

[0078] The simulation yielded the temperature T at any point A' within selected zones 1-6. 12A' T 22A' …T 62A' The curve showing the change over time is used to determine the target temperature and the corresponding time.

[0079] Step 5: Optimize the partitioning method, path planning for each partition, and process parameters so that any point A' within each partition satisfies the requirements. If yes, proceed to step 6; otherwise, repeat steps 3-5.

[0080] Within partitions 1-6, the obtained target temperatures and corresponding times are assessed to determine if they meet the temperature requirements. The division positions of the six partitions, the path planning within each partition, and the process parameters are optimized to ensure that all points within partitions 1-6 meet the requirements. If the condition is met, proceed to step 6. If multiple rounds of iterative optimization fail to solve the problem, return to step 3 and reset n. k .

[0081] Step 6: Output the number of partitions n in the i-th level k And the corresponding partitioning methods, path planning for each partition, and process parameters.

[0082] Output the partitioning positions of the 6 partitions in the second layer, the path planning and process parameters within each partition.

[0083] Those skilled in the art will understand that, in addition to implementing the system, apparatus, and their modules provided by this invention in purely computer-readable program code, the same program can be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system, apparatus, and their modules provided by this invention can be considered a hardware component, and the modules included therein for implementing various programs can also be considered structures within the hardware component; alternatively, modules for implementing various functions can be considered both software programs implementing the method and structures within the hardware component.

[0084] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A multi-machine collaborative fused wire additive manufacturing method based on regional temperature prediction, characterized in that, include: Step S1: Simulate and obtain the temperature of any point A on the end face of the formed component at the i-th layer under the condition of a single actuator without an external heating source. With time Change curve; Step S2: Based on the temperature at any point A on the end face With time Variation curves and preferred interlayer temperature control range ~ Determine the re-addition time range; determine the range of the number of end face partitions of the i-th layer based on the re-addition time range; Step S3: Determine the number of end face partitions in the i-th layer based on the range of the number of end face partitions in the i-th layer. Each partition is formed by one actuator. By optimizing the iterative partitioning method, the path planning of each partition and the process parameters, the preset requirements are met for any point in each partition. The forming time of each partition by a single actuator is determined. Step S2 includes: Step S2.1: Based on the temperature at any point A on the end face With time Variation curves and preferred interlayer temperature control range ~ Determine the time range for re-addition. ;in, This indicates the time when the i-th layer begins to form. The temperature at time point A is Based on the preferred interlayer temperature control range ~ Determine the time it takes for the temperature to drop to T1. and the time to drop to T2 ; Step S2.2: Based on the positions of multiple end face points A, according to Get multiple The scope; among which, Indicates the completion time of the i-th layer; Step S2.3: Based on n i = Get the range of the number of partitions in the i-th level .

2. The multi-machine collaborative fused wire additive manufacturing method based on regional temperature prediction according to claim 1, characterized in that, Step S2.1 includes: The preferred interlayer temperature control range T1~T2 for magnesium alloy arc-fused wire additive manufacturing is 100~70℃; The preferred interlayer temperature control range T1~T2 for aluminum alloy arc-fused wire additive manufacturing is 110~50℃.

3. The multi-machine collaborative fused wire additive manufacturing method based on regional temperature prediction according to claim 1, characterized in that, Step S3 includes: Step S3.1: Simulate and obtain the temperature of any point A' on the end face of the i-th layer in the k-th region without an external heating source. With time The curve of change; Step S3.2: Determine the start time of forming the i-th layer based on the preferred interlayer temperature control range T1~T2. and Initial temperature at time point A' K-zone begins to form time and this Temperature at time point A' The lowest temperature at point A' in region k K-zone end forming time and the temperature at point A' at this time The time for the i-th layer to finish forming and Temperature at time point A' Calculate the forming time of this layer. ; 。 4. The multi-machine collaborative fused wire additive manufacturing method based on regional temperature prediction according to claim 3, characterized in that, The optimization of the iterative partitioning method, path planning for each partition, and process parameters ensures that any point within each partition meets preset requirements, including: Any point within each partition satisfies ,in, Indicates the number of end face partitions in the i-th layer; This represents the time required for a single actuator to form the i-th layer. When the condition is met, the number of partitions in the i-th layer, the corresponding partitioning method, the path planning for each partition, and the process parameters are output. Otherwise, the number of end face partitions in the i-th layer is re-determined, and iterative optimization is triggered again until the condition is met at any point in each partition.

5. A multi-machine collaborative fused wire additive manufacturing system based on regional temperature prediction, characterized in that, include: Module M1: Simulates the temperature at any point A on the end face of the formed component at the i-th layer under the condition of a single actuator and no external heating source. With time Change curve; Module M2: Temperature based on any point A on the end face With time Variation curves and preferred interlayer temperature control range ~ Determine the re-addition time range; determine the range of the number of end face partitions of the i-th layer based on the re-addition time range; Module M3: Determine the number of end face partitions in the i-th layer based on the range of the number of end face partitions in the i-th layer. Each partition is formed by one actuator. By optimizing the iterative partitioning method, the path planning of each partition and the process parameters, the preset requirements are met for any point in each partition, and the forming time of a single actuator in each partition is determined. The module M2 includes: Module M2.1: Temperature based on any point A on the end face With time Variation curves and preferred interlayer temperature control range ~ Determine the time range for re-addition. ;in, This indicates the time when the i-th layer begins to form. The temperature at time point A is Based on the preferred interlayer temperature control range ~ Determine the time it takes for the temperature to drop to T1. and the time to drop to T2 ; Module M2.2: Based on the positions of multiple end face points A, according to Get multiple The scope; among which, Indicates the completion time of the i-th layer; Module M2.3: Based on n i = Get the range of the number of partitions in the i-th level .

6. The multi-machine collaborative fused wire additive manufacturing system based on regional temperature prediction according to claim 5, characterized in that, The module M2.1 includes: a preferred interlayer temperature control range T1~T2 of 100~70℃ for magnesium alloy arc wire additive manufacturing; and a preferred interlayer temperature control range T1~T2 of 110~50℃ for aluminum alloy arc wire additive manufacturing.

7. The multi-machine collaborative fused wire additive manufacturing system based on regional temperature prediction according to claim 5, characterized in that, The module M3 includes: Module M3.1: Simulates and obtains the temperature of any point A' on the end face of the i-th layer in the k-th region under multiple actuators without an external heating source. With time The curve of change; Module M3.2: Determine the start time of the i-th layer forming based on the preferred interlayer temperature control range T1~T2. and Initial temperature at time point A' K-zone begins to form time and this Temperature at time point A' The lowest temperature at point A' in region k K-zone end forming time and the temperature at point A' at this time The time for the i-th layer to finish forming and Temperature at time point A' Calculate the forming time of this layer. ; 。 8. The multi-machine collaborative fused wire additive manufacturing system based on regional temperature prediction according to claim 7, characterized in that, The optimization of the iterative partitioning method, path planning for each partition, and process parameters ensures that any point within each partition meets preset requirements, including: Any point within each partition satisfies ,in, Indicates the number of end face partitions in the i-th layer; This represents the time required for a single actuator to form the i-th layer. When the condition is met, the number of partitions in the i-th layer, the corresponding partitioning method, the path planning for each partition, and the process parameters are output. Otherwise, the number of end face partitions in the i-th layer is re-determined, and iterative optimization is triggered again until the condition is met at any point in each partition.

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