A method for controlling uniformity of explosive welding

Abstract

The present application provides a method for controlling the uniformity of explosive welding, which relates to the technical field of explosive welding. The method comprises connecting an explosive welding device, determining whether the substrate layer and the composite layer are locally welded, and outputting the local welding area if the substrate layer and the composite layer are locally welded, performing heat conduction simulation analysis on multiple heat-guiding partitions on the local welding area, and obtaining multiple identified heat-guiding partitions, inputting the multiple identified heat-guiding partitions into a welding uniformity control model, and outputting a control parameter group, and controlling the explosive welding device to perform explosive welding operations according to the control parameter group. The present application solves the technical problem that the existing technology lacks independent adjustment means for the heat distribution of different welding areas, resulting in uneven heat distribution at the welding interface, thereby affecting the bonding strength of the welding interface, and achieves the technical effect of improving the uniformity and bonding strength of the welding interface, thereby improving the overall welding quality.

Description

Technical Field

[0001] The present application relates to the technical field of explosion welding, and in particular to a method for controlling uniformity of explosion welding. Background Art

[0002] Explosion welding is a solid-state welding method that achieves metal connection by applying controllable explosive energy on the metal surface. An explosive layer is set on the substrate layer and the composite layer, and the impact force generated by the explosion of the explosive is used to combine the two layers of metal.

[0003] However, during the explosion welding process, the non-uniformity of the explosion force field, the difference in material properties, the control accuracy of process parameters and the non-uniformity of the temperature field will lead to uneven heat distribution at the welding interface. At present, in terms of uniformity control, fixed parameters such as the amount of explosives and spacing are mostly used for overall control. However, this method is usually based on experience and experimental results, lacking scientificity and accuracy. Especially under complex welding conditions, such as non-planar bonding interfaces or multi-layer composite materials, the heat distribution cannot be accurately controlled, resulting in insufficient or excessive heat in local areas. Materials in different regions may not be able to achieve good fusion due to thermal differences, resulting in a decrease in the bonding strength of the welding interface. When subjected to external forces, cracks and other defects are prone to appear in the welding parts, which ultimately affects the overall welding quality. Summary of the invention

[0004] The present application provides a method for controlling the uniformity of explosive welding, which solves the technical problem in the prior art that the heat distribution of the welding interface is uneven due to the lack of independent adjustment means for the heat distribution of different welding areas, thereby affecting the bonding strength of the welding interface. The application achieves the technical effect of improving the uniformity and bonding strength of the welding interface, thereby improving the overall welding quality.

[0005] In view of the above problems, the present application provides a method for controlling uniformity of explosive welding, the method comprising: connecting an explosive welding device, the explosive welding device comprising a substrate layer, a composite layer and a thermal guide layer, the thermal guide layer being provided with an explosive layer and a detonating device, the detonating device being used to detonate the explosive layer, and the composite layer being welded to the substrate layer by thermal guidance through the thermal guide layer; determining whether the substrate layer and the composite layer are locally welded, and if the substrate layer and the composite layer are locally welded, outputting a local welding area; performing heat conduction simulation analysis on a plurality of thermal guide partitions on the local welding area to obtain a plurality of identified thermal guide partitions, wherein the plurality of thermal guide partitions are obtained by dividing the thermal guide layer into regions, and each thermal guide partition is independently controlled; inputting the plurality of identified thermal guide partitions into a welding uniformity control model, and outputting a control parameter group, the control parameter group comprising control parameters of the explosive layer and control parameters of the detonating device; and controlling the explosive welding device to perform an explosive welding operation according to the control parameter group.

[0006] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0007] By connecting the explosive welding device, the necessary physical basis and conditions are provided for the subsequent welding operation. By identifying the local welding area, the welding area that needs to be focused on can be accurately located, providing a basis for the subsequent heat conduction simulation analysis, ensuring the pertinence and effectiveness of the welding process. By performing heat conduction simulation analysis on multiple heat-guiding partitions on the local welding area, the heat conduction relationship between the local welding area and the heat-guiding partition is deeply understood, and the identified heat-guiding partitions that have an important impact on the welding uniformity are identified, thereby providing a scientific basis for independently controlling these partitions and ensuring a more uniform heat distribution during the welding process. By inputting the identified heat-guiding partition into the welding uniformity control model and outputting a control parameter group containing the control parameters of the explosive layer and the detonator, the conversion from heat conduction analysis to actual welding parameter adjustment is realized. Through the intelligent calculation of the welding uniformity control model, accurate and targeted control parameters are provided for explosive welding. According to the control parameter group, the explosive welding device is controlled to perform explosive welding operations to ensure that the welding process is carried out according to the optimized parameters, thereby improving the uniformity of the welding interface and the welding quality.

[0008] In summary, this application forms a scientific and accurate explosion welding uniformity control method by connecting an explosion welding device, identifying local welding areas, performing heat conduction simulation analysis, inputting a welding uniformity control model, and performing actual welding operations according to a control parameter group. This method achieves accurate heat distribution by accurately controlling the heat distribution of different welding areas, making the heat distribution during welding more uniform, significantly improving the uniformity and bonding strength of the welding interface, thereby improving the overall welding quality, and providing an intelligent and refined solution for high-quality material bonding under complex welding conditions.

[0009] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 A schematic flow chart of a method for uniformity control of explosion welding provided in an embodiment of the present application.

[0011] Figure 2 A schematic diagram of a flow chart for obtaining multiple identified thermal guidance partitions in a method for uniformity control of explosion welding provided in an embodiment of the present application. DETAILED DESCRIPTION

[0012] The embodiment of the present application provides a method for controlling the uniformity of explosion welding, thereby solving the technical problem in the prior art that the heat distribution of the welding interface is uneven, which in turn affects the bonding strength of the welding interface due to the lack of independent adjustment means for the heat distribution of different welding areas. The technical effect of improving the uniformity and bonding strength of the welding interface and thus improving the overall welding quality is achieved.

[0013] like Figure 1 As shown, an embodiment of the present application provides a method for controlling uniformity of explosion welding, the method comprising:

[0014] Step S1: Connecting an explosive welding device, the explosive welding device includes a substrate layer, a composite layer and a heat guide layer, the heat guide layer is provided with an explosive layer and a detonating device, the detonating device is used to detonate the explosive layer, and the composite layer is welded to the substrate layer by heat guidance through the heat guide layer.

[0015] Specifically, the explosion welding device is a combination of equipment used to achieve explosion welding. It mainly includes a substrate layer, a composite layer and a heat guide layer. The substrate layer, as the basic bearing material, is usually a metal material with strong performance, such as a steel plate. The composite layer is a metal layer welded to the substrate, which may be a metal with different properties, such as an aluminum plate or a stainless steel plate. The heat guide layer is an intermediate layer used to guide and distribute heat to ensure uniform transfer of heat energy. An explosive layer and a detonating device are arranged on the heat guide layer, wherein the explosive layer is the source of explosion energy, releasing instantaneous high pressure and heat through combustion, and the detonating device is a control device for igniting the explosive, such as an electric detonator. During the explosion welding process, the explosive layer is detonated by the detonating device, and the instantaneous high pressure and heat generated by the explosion are transferred to the composite layer and the substrate layer through the heat guide layer, prompting the two to be tightly combined in a solid form.

[0016] Before explosive welding, the various components of the explosive welding device must first be connected according to the design requirements. First, place the substrate layer, then set the composite layer on it, and then install the explosive layer and detonation device on the specific heat guide layer to ensure that the components are firmly connected and accurately positioned. The explosive welding device provides the basic hardware environment for explosive welding, provides the basic physical structure for subsequent welding operations, and ensures that the connection relationship between the components meets the welding requirements.

[0017] Step S2: determining whether the substrate layer and the composite layer are partially welded, and if the substrate layer and the composite layer are partially welded, outputting the local welding area.

[0018] Specifically, the welding design requirements are obtained interactively to determine whether the substrate layer and the composite layer are locally welded, that is, only some areas of the substrate layer and the composite layer need to be effectively welded during the welding process, rather than the entire contact surface. If the substrate layer and the composite layer are locally welded, the specific position coordinates of the local welding are determined according to the design requirements and output as the local welding area. By identifying the local welding area, accurate regional information is provided for the subsequent heat conduction simulation analysis to ensure the pertinence and effectiveness of the welding process.

[0019] Step S3: performing heat conduction simulation analysis on the multiple thermal boot partitions on the local welding area to obtain multiple identified thermal boot partitions, wherein the multiple thermal boot partitions are obtained by dividing the thermal boot layer into regions, and each thermal boot partition is independently controlled.

[0020] Specifically, the thermal guidance partition is a plurality of independently controllable areas divided in the thermal guidance layer, so as to adjust the thermal requirements of different areas in a targeted manner. Using computer simulation software (such as ANSYS or COMSOL), the data of the determined local welding area and the plurality of independently controlled thermal guidance partitions set in the thermal guidance layer are input into the software for heat conduction simulation analysis. The software will calculate the distribution of heat flow in each partition according to the set heat conduction equation and the thermophysical property parameters of the material (such as thermal conductivity, etc.), thereby obtaining a plurality of identified thermal guidance partitions. Taking the composite structure of welding copper and aluminum as an example, the geometric model, material properties, etc. of the local welding area and thermal guidance partition of the copper-aluminum composite structure are input into the ANSYS software, and the thermal analysis module of the software is used for simulation calculation to determine a plurality of identified thermal guidance partitions. These identified thermal guidance partitions are thermal guidance partitions that have an important influence on the uniformity of welding obtained by heat conduction simulation analysis during the explosive welding process. By independently controlling the heat conduction of these identified thermal guidance partitions, the heat distribution during the explosive welding process can be precisely controlled, thereby improving the uniformity and quality of welding.

[0021] Step S4: input the multiple identified thermal guidance partitions into a welding uniformity control model, and output a control parameter group, wherein the control parameter group includes control parameters of the explosive layer and control parameters of the detonation device.

[0022] Specifically, the welding uniformity control model is a model based on a machine learning algorithm, which is used to predict the uniformity of explosive welding based on the input control parameter group. These control parameter groups include the control parameters of the explosive layer and the control parameters of the detonator. The control parameters of the explosive layer include the amount of explosives, the distribution density of explosives, etc., and the control parameters of the detonator include the detonation time, the detonation sequence, etc.

[0023] The data of multiple identified heat-guiding partitions are input into the pre-established welding uniformity control model. The model predicts the uniformity of explosive welding under different control parameters by learning from a large amount of welding experimental data. Based on the prediction results of the welding uniformity control model, optimization algorithms such as genetic algorithms or particle swarm optimization algorithms are used to optimize the control parameters, determine the control parameter group with the highest welding uniformity under the current welding requirements, and realize the conversion from heat conduction analysis to actual welding parameter adjustment. Through the intelligent calculation of the model, accurate and targeted control parameters can be provided for different heat-guiding partitions, thereby improving welding uniformity and local bonding strength.

[0024] Step S5: controlling the explosion welding device to perform explosion welding operation according to the control parameter group.

[0025] Specifically, according to the control parameter group obtained in step S4, the automatic control system is used to operate the explosive welding device. For example, if the control parameters of the explosive layer require adjustment of the amount of explosives, the automatic control system will accurately control the amount of explosives added; if the control parameters of the detonating device require adjustment of the detonation time, the control system will trigger the detonating device according to the set time. In actual operation, a programmable logic controller (PLC) can be used to achieve automatic control to ensure that the welding process is carried out according to the optimized parameters, thereby improving the uniformity and quality of welding and reducing the occurrence of welding defects.

[0026] Further, such as Figure 2 As shown, step S3 includes:

[0027] Step S31: defining the welding coordinate range of the local welding area.

[0028] Step S32: performing heat conduction simulation analysis on the multiple heat guide partitions provided in the heat guide layer based on the Fourier heat conduction equation, and outputting multiple heat conduction simulation data sets, wherein the multiple heat guide partitions correspond to the multiple heat conduction simulation data sets.

[0029] Step S33: determining a plurality of heat conduction coordinate ranges according to the plurality of heat conduction simulation data sets.

[0030] Step S34: coordinate mapping the welding coordinate range with the multiple heat conduction coordinate ranges, identifying the thermal boot partition corresponding to the local welding area, and outputting the multiple identified thermal boot partitions.

[0031] Specifically, the welding coordinate range refers to the specific coordinate position of the local welding area in two-dimensional or three-dimensional space. In the local welding area, in order to accurately describe its position and size, a coordinate system is used to define the local welding range. According to a predetermined coordinate system (such as a Cartesian coordinate system), the boundaries of the local welding area in the direction of each coordinate axis are determined to clarify the welding coordinate range of the local welding area. For example, if the local welding area is a rectangular area, in a two-dimensional Cartesian coordinate system, it is necessary to determine its minimum and maximum coordinate values ​​in the x-axis and y-axis directions, so as to define the welding coordinate range. The welding coordinates provide precise position and range information for the subsequent correlation analysis of the local welding area with the thermal guide partition, making the analysis more accurate and targeted.

[0032] The Fourier heat conduction equation is the basic equation that describes the phenomenon of heat conduction. It is based on the principle that heat conducts from high-temperature areas to low-temperature areas, and quantitatively describes the relationship between temperature changes over time and space through mathematical formulas. The heat-guiding layer is divided into several partitions (such as a 4×4 grid) in advance, and the material properties of each partition (such as thermal conductivity, thickness) are determined. The relevant parameters of multiple heat-guiding partitions set in the heat-guiding layer (such as geometric shape, material thermal conductivity, etc.), as well as initial conditions (such as heat released by explosives) and boundary conditions (such as ambient temperature) are input into the heat conduction simulation software, and then the heat conduction simulation analysis is performed based on the Fourier heat conduction equation. During the simulation process, the software will calculate the temperature, heat flow and other thermal parameters at different times and positions in each heat-guiding partition according to the Fourier heat conduction equation, and finally output multiple heat conduction simulation data sets. Each heat conduction simulation data set corresponds to a heat-guiding partition, which contains various thermal information about the heat-guiding partition during the simulation process, such as temperature changes at different positions, heat flux density and other information.

[0033] From the obtained multiple heat conduction simulation data sets, the heat conduction coordinate range corresponding to each heat conduction simulation data set is determined according to the temperature change range or the effective action range of the heat flux density and other information. Similar to the welding coordinate range, the heat conduction coordinate range is a coordinate range defined to determine the distribution of the heat conduction phenomenon in the heat guide partition, which determines the effective action range of heat in each heat guide partition during the heat conduction process.

[0034] The welding coordinate range of the local welding area is mapped to multiple heat conduction coordinate ranges. Specifically, the coordinate ranges of the two are compared to find the parts that overlap or are associated in the coordinates, thereby identifying the thermal guidance partitions corresponding to the local welding area, and outputting these identified partitions as multiple identified thermal guidance partitions. Through coordinate mapping, the thermal guidance partitions corresponding to the local welding area are accurately determined. These identified thermal guidance partitions provide clear control objects for subsequent welding uniformity control, avoid ineffective heat transfer in non-welding areas, and ensure the uniformity and high quality of the welding process.

[0035] Further, if the thermal conductivity of the multiple thermal guide partitions arranged in the thermal guide layer is different, step S33 includes:

[0036] Each of the plurality of heat conduction simulation data sets includes a temperature distribution and a heat flux density of a corresponding heat conduction partition; a temperature threshold and a heat flux density threshold are set; and the plurality of heat conduction simulation data sets are screened according to the temperature threshold and the heat flux density threshold to obtain a plurality of heat conduction coordinate ranges.

[0037] Specifically, in explosive welding, the heat guide layer is a material layer used to control the heat conduction path. Through the thermal conductivity of this layer, the heat energy released by the explosive can be accurately transferred to the welding area. The heat guide layer is divided into multiple zones, each of which is responsible for a different heat transfer task. The thermal conductivity (such as thermal conductivity) of each zone may vary depending on the material. When determining multiple heat conduction coordinate ranges, the differences in thermal conductivity of multiple heat guide zones need to be considered.

[0038] When the thermal conductivity of multiple thermal guide partitions set in the thermal guide layer is different, the heat conduction speed and conduction efficiency in different partitions will be different. Through the thermal conduction simulation analysis, each of the multiple thermal conduction simulation data sets obtained contains the temperature distribution and heat flux density of the corresponding thermal guide partition. The temperature distribution describes the temperature change of each thermal guide partition, which can be expressed as a series of temperature values ​​at different time points, or a temperature distribution diagram in a steady state. The heat flux density describes the heat flow rate per unit area of ​​each thermal guide partition.

[0039] Set the temperature threshold and heat flux threshold. These two thresholds are determined based on actual welding requirements, material properties, and past experience, and are used to filter the boundary values ​​of the heat conduction coordinate range. Areas where the temperature exceeds the temperature threshold and the heat flux exceeds the heat flux threshold can be considered as key areas of heat transfer in the thermal guidance partition. Filter multiple heat conduction simulation data sets. For each data set, check whether the temperature distribution meets the temperature threshold requirements and whether the heat flux meets the heat flux threshold requirements. The areas corresponding to the data sets that meet these conditions are determined as valid areas, and then multiple heat conduction coordinate ranges are obtained.

[0040] By setting a threshold for screening, the heat conduction area that does not meet the welding requirements can be excluded, making the obtained heat conduction coordinate range more targeted and effective. This screening can focus on the heat conduction area that has a practical impact on the welding process, providing a more accurate data basis for the subsequent accurate determination of the heat conduction partition corresponding to the local welding area, which helps to improve the uniformity of heat distribution during explosive welding, improve welding quality, avoid local overheating or overcooling, and thus enhance the bonding strength of the welding interface.

[0041] Further, if the thermal conductive properties of the multiple thermal conductive partitions provided in the thermal conductive layer are the same, step S33 includes:

[0042] Step S331: randomly acquiring a first heat conduction simulation data set corresponding to a first thermal boot partition, screening the first heat conduction simulation data set according to the temperature threshold and the heat flux density threshold, and acquiring a first heat conduction coordinate range.

[0043] Step S332: identifying a first initial coordinate range corresponding to the first hot boot partition.

[0044] Step S333: Compare the first initial coordinate range with the first heat conduction coordinate range, and output a heat conduction radius.

[0045] Step S334: updating the initial coordinate ranges of other thermal guidance partitions with the heat conduction radius, and outputting a plurality of heat conduction coordinate ranges.

[0046] Specifically, if the thermal conductivity of multiple thermal guide partitions set in the thermal guide layer is the same, it means that the heat propagation speed, efficiency and other characteristics in each thermal guide partition in the thermal guide layer are consistent. When determining the thermal conduction coordinate range, first randomly select a thermal guide partition from multiple thermal guide partitions, record it as the first thermal guide partition, and extract the first thermal conduction simulation data set corresponding to the first thermal guide partition from multiple thermal conduction simulation data sets. The first thermal conduction simulation data set is screened according to the aforementioned set temperature threshold and heat flux density threshold, and the coordinate range that satisfies both the temperature threshold and the heat flux density threshold is found, and determined as the first thermal conduction coordinate range. This range determines the effective heat conduction area related to welding in the first thermal guide partition.

[0047] By predefining the structure and layout of the thermal boot layer or from the design parameters of the thermal boot partition, the first initial coordinate range corresponding to the first thermal boot partition is identified. This range is the original coordinate range of the first thermal boot partition in the entire thermal boot layer, which is used to describe its initial position and size.

[0048] The first initial coordinate range and the first heat conduction coordinate range are compared. For example, the distance difference between the center coordinates of the two can be calculated or the average distance between the boundaries of the two ranges can be calculated. Through this comparison and calculation, a heat conduction radius representing the heat conduction range is obtained. This radius can reflect the average distance of heat conduction from the initial range to the effective heat conduction range in the first heat conduction partition and other related information.

[0049] Based on the calculated heat conduction radius, the initial coordinate ranges of other heat-guiding partitions are updated. The updated coordinate ranges are output as multiple heat conduction coordinate ranges, which will be used for subsequent operations such as coordinate mapping with local welding areas. By updating the initial coordinate ranges of other heat-guiding partitions, multiple heat conduction coordinate ranges are obtained. In this way, when the thermal conductivity of the heat-guiding partitions is the same, the heat conduction conditions of the first partition are used to quickly determine the heat conduction coordinate ranges of all partitions, thereby improving the calculation efficiency and providing accurate data for subsequent operations such as coordinate mapping.

[0050] Furthermore, step S4 of the embodiment of the present application includes:

[0051] Step S41: Obtain a control parameter sample group, the control parameter sample group includes a control parameter sample of the explosive layer, a control parameter sample of the detonation device, and a label sample characterizing welding uniformity, wherein the welding uniformity is obtained by a uniformity detection device, and the uniformity detection device is connected to the explosive welding device.

[0052] Step S42: constructing a welding uniformity control model according to the control parameter sample group.

[0053] Step S43: taking the multiple identified thermal guidance partitions as input quantities, performing parameter optimization based on the welding uniformity control model, and outputting an optimal solution of a control parameter group, wherein the optimal solution of the control parameter group includes the thickness of the explosive layer and the position of the detonation device.

[0054] Specifically, during multiple explosion welding experiments or actual welding operations, samples of control parameters of the explosive layer and samples of control parameters of the detonator are collected. These sample data can be obtained from equipment settings, operation records, etc. during the welding process. A label sample representing welding uniformity is obtained using a uniformity detection device connected to the explosion welding device. This uniformity detection device uses technical means such as ultrasonic detection and X-ray detection to measure the uniformity after welding and convert the results into corresponding label samples. The control parameter samples of the explosive layer, the control parameter samples of the detonator, and the label samples representing welding uniformity are combined to form a control parameter sample group. The control parameter sample group provides a rich data basis for constructing a welding uniformity control model. These data include control parameters and corresponding welding uniformity conditions under different welding conditions, so that the welding uniformity control model can learn the relationship between control parameters and welding uniformity.

[0055] According to the collected control parameter sample groups, a deep learning framework such as TensorFlow or PyTorch is used to build a welding uniformity control model using machine learning algorithms (such as linear regression, support vector machine, neural network, etc.). For example, a neural network-based modeling method can be selected, and the control parameter samples of the explosive layer and the control parameter samples of the detonator are used as neurons in the input layer, and the label samples representing the welding uniformity are used as neurons in the output layer. Several hidden layers are set in the middle to build a neural network model. At the same time, a suitable training algorithm, such as the back propagation algorithm, should be selected to train the model so that the model can accurately predict the welding uniformity based on the input control parameters. During the model training process, the selected neural network algorithm (such as a multi-layer perceptron based on the back propagation algorithm) is used. Each time a set of control parameter samples is input, the model calculates the predicted welding uniformity based on the current connection weights, and then calculates the error between the predicted value and the true label sample. Based on this error, the connection weights of the neural network are adjusted through the back propagation algorithm. This process will be repeated on a large number of control parameter samples until the prediction error of the model reaches an acceptable level or meets the preset stop condition (such as reaching the maximum number of training iterations or the error converges to a certain extent). Through such a training process, the model gradually learns the relationship between control parameters and welding uniformity, so that it can accurately predict uniformity.

[0056] The data of multiple identified thermal guidance partitions are quantitatively input into the constructed welding uniformity control model as input. Based on the welding uniformity control model, optimization algorithms such as genetic algorithm and particle swarm optimization algorithm are used to optimize parameters, and the control parameter group with the highest welding uniformity is determined as the optimal solution of the control parameter group. In the specific optimization process, different control parameter groups are generated by the optimization algorithm. Each time a control parameter group is generated, the control parameter group and the data of multiple identified thermal guidance partitions are input into the welding uniformity control model. The model will predict the corresponding explosion welding uniformity according to the current connection weight and internal algorithm. The optimization algorithm is used to compare the explosion welding uniformity corresponding to different control parameter groups, and the control parameter group is iteratively searched to finally determine the optimal solution of the control parameter group, including the optimal control parameters such as the thickness of the explosive layer and the position of the detonator, so that the welding uniformity is optimized.

[0057] Furthermore, before step S4, the following steps are included:

[0058] Step S4-1: constructing a detonation path planning model, and connecting the detonation path planning model with the welding uniformity control model.

[0059] Step S4-2: Obtain the detonation position distribution of the detonation device.

[0060] Step S4-3: the detonation path planning model performs detonation path planning for the multiple identified thermal boot partitions according to the detonation position distribution to obtain a first detonation path.

[0061] Step S4-4: enabling the welding uniformity control model to perform parameter optimization according to the first detonation path, and outputting an optimal solution of a control parameter group.

[0062] Specifically, the detonation path planning model is an algorithm model used to design and optimize the detonation path. Through a reasonable detonation sequence and path, the heat is evenly distributed to achieve the best welding effect. According to the existing data or theoretical heat conduction characteristics, the detonation path planning model is constructed, and the model input is designed as multiple identified heat-guided partitions, and combined with the heat conduction characteristics such as temperature distribution and heat flux density, the influence of different detonation paths on heat distribution is simulated. For example, the shortest path algorithm in graph theory (such as Dijkstra algorithm or A* algorithm) can be used as the basis to build the model, and the detonation position is regarded as a node in the graph to find the shortest or optimal path from a starting detonation position to other detonation positions.

[0063] The constructed detonation path planning model is connected to the welding uniformity control model. This connection can be achieved through a data interface, so that the detonation path information output by the detonation path planning model can be received by the welding uniformity control model and used as an important input for its parameter optimization. Constructing and connecting the detonation path planning model provides an integrated framework for the subsequent detonation path planning and parameter optimization of the welding uniformity control model, so that the two models can work together to improve the efficiency and quality of the explosive welding process.

[0064] By analyzing the design layout and welding requirements of the explosive welding device, the detonation position distribution of the detonation device is obtained. Accurate detonation position distribution information provides the necessary input data for the detonation path planning model, so that the model can plan a reasonable detonation path based on this position information.

[0065] The detonation path planning model takes the obtained detonation position distribution as input, and plans the detonation path considering the distribution of multiple identified thermal guidance partitions. Based on the selected algorithm (such as the Dijkstra algorithm or A* algorithm mentioned above), the optimal path from an initial detonation position to other detonation positions is calculated. This optimal path must consider how to achieve better welding uniformity when the explosion energy passes through multiple identified thermal guidance partitions, and finally obtain the first detonation path.

[0066] The welding uniformity control model receives the first detonation path information as an important input parameter. When performing parameter optimization, the model will adjust the control parameters such as the thickness of the explosive layer and the position of the detonator according to the first detonation path. For example, if the first detonation path is to detonate from the center of the welding area to the periphery, then the welding uniformity control model will consider the effects of heat conduction and explosion energy at different positions according to this order during the optimization process, and adjust the corresponding control parameters to achieve better welding uniformity. The optimal solution of the control parameter group obtained by performing parameter optimization according to the first detonation path can better adapt to the actual situation in the explosion welding process, improve welding uniformity, and thus improve the quality of explosion welding.

[0067] Further, step S4-3 includes:

[0068] Step S4-31: The detonation path planning model includes an objective function, and the total path length and the guide partition temperature difference are calculated according to the objective function, and the path scoring result is output.

[0069] Step S4-32: Obtaining the first detonation path with the highest score in the path scoring results.

[0070] Specifically, in the detonation path planning model, the objective function is a mathematical expression used to measure the quality of the detonation path. The objective function comprehensively considers multiple factors that affect welding uniformity, such as the total path length and the guide partition temperature difference. By quantitatively calculating these factors, a value that can reflect the quality of the path is obtained, that is, the path score result. The higher the value of the path score result, the better the path performs in meeting the welding uniformity requirements. Among them, the total path length refers to the sum of the distances traveled by the detonator from the starting position to each detonation point according to a certain detonation path. The total path length will affect the loss of explosion energy during propagation and the propagation time, and thus affect the uniformity of welding. The guide partition temperature difference refers to the temperature difference caused by uneven heat transfer in different guide partitions during the explosion welding process. The size of this temperature difference will affect the quality of welding, and too large a temperature difference may lead to uneven welding.

[0071] According to the principle of explosive welding and the requirements for welding uniformity, the specific form of the objective function is determined. For example, the total path length and the guide partition temperature difference can be weighted to construct the objective function. For each possible detonation path, the detonation path planning model needs to calculate the total path length by calculating the sum of the distances between the detonation points. At the same time, the temperature data of each guide partition is obtained according to the aforementioned heat conduction simulation data set, and the guide partition temperature difference is calculated. The calculated total path length and guide partition temperature difference are substituted into the objective function to calculate the path scoring result of each possible detonation path. By calculating the path scoring result through the objective function, factors such as the total path length and the guide partition temperature difference that have an important impact on welding uniformity can be comprehensively considered, thereby objectively evaluating the advantages and disadvantages of different detonation paths and providing a basis for selecting the best detonation path.

[0072] After obtaining the path scoring results of all possible detonation paths, these scoring results are compared to find the path with the highest score as the first detonation path. This first detonation path performs best after comprehensively considering factors such as the total path length and the temperature difference of the guide partition, thus providing the most favorable detonation path for the subsequent parameter optimization of the welding uniformity control model.

[0073] Furthermore, the expression of the objective function in step S4-31 is as follows:

[0074] ;in, is the objective function, The weight optimized for the total path length, To guide the weight of the partition temperature difference optimization, is the total number of detonation points, The tipping point and the tipping point The Euclidean distance between is the actual temperature of the ith thermal boot partition, is the target temperature, and n is the total number of multiple hot boot partitions.

[0075] Specifically, the objective function f takes into account the total path length and the guide partition temperature difference, two factors that have an important impact on welding uniformity, through the weighted summation calculation method. This term represents the sum of the Euclidean distances between the detonation points, i.e. the total length of the path. By summing the Euclidean distances of all adjacent detonation points, we can get a value related to the total length of the entire detonation path. When optimizing the detonation path, we hope to shorten the distance between the detonation points as much as possible, which not only saves time and energy, but also reduces the energy loss during the path detonation process. The smaller the total path length value, the more compact the detonation path is in space, and the less the loss of explosion energy during propagation is, which helps to improve welding uniformity.

[0076] This item represents the temperature difference of the boot partition. By calculating the square of the difference between the actual temperature of each thermal boot partition and the target temperature, and summing the squares of these differences of all thermal boot partitions, a value reflecting the temperature difference of the overall boot partition can be obtained. During the welding process, the temperature of each thermal boot partition should be as close to the target temperature as possible. Keep it consistent. Too large a temperature difference will lead to uneven heat and affect the welding effect. It is the ideal temperature value that can complete welding according to the welding process requirements. The smaller the guide zone temperature difference value is, the closer the temperature of each heat guide zone is to the target temperature, and the better the welding uniformity is.

[0077] The value of determines the balance between total path length optimization and temperature difference optimization. If the value is larger, it means that the optimization of the total length of the path is more important, and the detonation path with a shorter total length is preferred. The larger the value, the more attention is paid to the optimization of temperature difference, and the detonation path with smaller temperature difference is preferred. The size of can be adjusted according to the actual welding situation, balancing the importance of the total path length and the guide partition temperature difference in evaluating the quality of the detonation path to achieve the best welding effect. For example, in some cases, it may be desirable to reduce the guide partition temperature difference first, in which case you can increase In other cases, if the total path length has a greater impact on the welding effect, you can increase Finally, the f value calculated by the objective function is used to evaluate the advantages and disadvantages of different detonation paths, and the detonation path with the largest f value is selected as the optimal path.

[0078] In summary, the method for controlling uniformity of explosive welding provided in the embodiment of the present application has the following technical effects:

[0079] By connecting the explosive welding device, the necessary physical basis and conditions are provided for the subsequent welding operation. By identifying the local welding area, the welding area that needs to be focused on can be accurately located, providing a basis for the subsequent heat conduction simulation analysis, ensuring the pertinence and effectiveness of the welding process. By performing heat conduction simulation analysis on multiple heat-guiding partitions on the local welding area, the heat conduction relationship between the local welding area and the heat-guiding partition is deeply understood, and the identified heat-guiding partitions that have an important impact on the welding uniformity are identified, thereby providing a scientific basis for independently controlling these partitions and ensuring a more uniform heat distribution during the welding process. A welding uniformity control model is constructed. By inputting the identified heat-guiding partition into the welding uniformity control model, a control parameter group containing the control parameters of the explosive layer and the detonation device is output, realizing the conversion from heat conduction analysis to actual welding parameter adjustment. Through the intelligent calculation of the welding uniformity control model, accurate and targeted control parameters are provided for explosive welding. In addition, a detonation path planning model is introduced to optimize the detonation path to ensure that the total path length is the shortest and the temperature difference of the guide partition is the smallest. The optimal path is calculated through the objective function, thereby enhancing the uniformity of welding. The explosion welding device is controlled to perform explosion welding operation according to the control parameter group, ensuring that the welding process is carried out according to the optimized parameters, thereby improving the uniformity of the welding interface and the welding quality.

[0080] In general, the embodiment of the present application forms a set of scientific and accurate explosion welding uniformity control methods by connecting the explosion welding device, identifying the local welding area, performing heat conduction simulation analysis, inputting the welding uniformity control model, and performing actual welding operations according to the control parameter group. By accurately controlling the heat distribution of different welding areas, the accurate distribution of heat is achieved, making the heat distribution during the welding process more uniform, significantly improving the uniformity and bonding strength of the welding interface, thereby improving the overall welding quality, and providing an intelligent and refined solution for high-quality material bonding under complex welding conditions.

[0081] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for controlling uniformity of explosive welding, characterized in that: The method comprises: Connecting an explosive welding device, the explosive welding device comprising a substrate layer, a composite layer and a heat guide layer, the heat guide layer being provided with an explosive layer and a detonating device, the detonating device being used to detonate the explosive layer, and the composite layer being welded to the substrate layer by heat conduction through the heat guide layer; Determine whether the substrate layer and the composite layer are partially welded, and if the substrate layer and the composite layer are partially welded, output a local welding area; Performing heat conduction simulation analysis on a plurality of thermal boot partitions on the local welding area to obtain a plurality of identified thermal boot partitions, wherein the plurality of thermal boot partitions are obtained by dividing the thermal boot layer into regions, and each thermal boot partition is independently controlled; Input the plurality of identified thermal guidance partitions into a welding uniformity control model, and output a control parameter group, wherein the control parameter group includes control parameters of the explosive layer and control parameters of the detonation device; The explosion welding device is controlled to perform explosion welding operation according to the control parameter group.

2. The method for controlling uniformity of explosion welding according to claim 1, characterized in that: Performing heat conduction simulation analysis on the multiple heat-guiding partitions on the local welding area to obtain multiple identified heat-guiding partitions, the method comprising: Defining a welding coordinate range of the local welding area; Performing heat conduction simulation analysis on a plurality of heat guide partitions provided in the heat guide layer based on the Fourier heat conduction equation, and outputting a plurality of heat conduction simulation data sets, wherein the plurality of heat guide partitions correspond to the plurality of heat conduction simulation data sets; Determining a plurality of heat conduction coordinate ranges according to the plurality of heat conduction simulation data sets; Coordinate mapping is performed between the welding coordinate range and the plurality of heat conduction coordinate ranges, and the thermal boot partition corresponding to the local welding area is identified, and output as a plurality of identified thermal boot partitions.

3. The method for controlling uniformity of explosion welding according to claim 2, characterized in that: If the thermal conductivity of the plurality of thermal guide zones provided in the thermal guide layer is different, a method for determining a plurality of thermal conduction coordinate ranges according to the plurality of thermal conduction simulation data sets is provided. include: wherein each of the plurality of heat conduction simulation data sets comprises a temperature distribution and a heat flux density corresponding to a heat conduction partition; Set temperature threshold and heat flux threshold; The plurality of heat conduction simulation data sets are screened according to the temperature threshold and the heat flux density threshold to obtain a plurality of heat conduction coordinate ranges.

4. The method for controlling uniformity of explosion welding according to claim 3, characterized in that: If the thermal conductive zones of the thermal conductive layer have the same thermal conductive properties, the method for determining the thermal conductive coordinate ranges according to the thermal conductive simulation data sets includes: randomly acquiring a first heat conduction simulation data set corresponding to a first thermal boot partition, screening the first heat conduction simulation data set according to the temperature threshold and the heat flux density threshold, and acquiring a first heat conduction coordinate range; Identifying a first initial coordinate range corresponding to the first hot boot partition; Outputting a heat conduction radius according to a comparison between the first initial coordinate range and the first heat conduction coordinate range; The initial coordinate ranges of other thermal guidance partitions are updated with the thermal conduction radius, and a plurality of thermal conduction coordinate ranges are output.

5. The method for controlling uniformity of explosion welding according to claim 1, characterized in that: The plurality of identified thermal guidance zones are input into a welding uniformity control model, and a control parameter group is output, including: Acquire a control parameter sample group, the control parameter sample group includes a control parameter sample of the explosive layer, a control parameter sample of the detonation device, and a label sample characterizing welding uniformity, wherein the welding uniformity is acquired by a uniformity detection device, and the uniformity detection device is connected to the explosive welding device; Constructing a welding uniformity control model according to the control parameter sample group; The multiple identified thermal guidance partitions are quantitatively used as input, parameter optimization is performed based on the welding uniformity control model, and an optimal solution of a control parameter group is output, wherein the optimal solution of the control parameter group includes the thickness of the explosive layer and the position of the detonation device.

6. The method for controlling uniformity of explosion welding according to claim 1, characterized in that: Before inputting the plurality of identified thermal guidance zones into a welding uniformity control model, the method includes: Constructing a detonation path planning model, and connecting the detonation path planning model with the welding uniformity control model; Obtaining the detonation position distribution of the detonation device; The detonation path planning model performs detonation path planning on the multiple identified thermal guidance partitions according to the detonation position distribution to obtain a first detonation path; The welding uniformity control model is instructed to perform parameter optimization according to the first detonation path, and an optimal solution of a control parameter group is output.

7. The method for controlling uniformity of explosion welding according to claim 6, characterized in that: The detonation path planning model performs detonation path planning on the multiple identified thermal guidance partitions according to the detonation position distribution to obtain a first detonation path, and the method includes: The detonation path planning model includes an objective function, according to which the total path length and the guided partition temperature difference are calculated, and a path scoring result is output; A first detonation path with the highest score in the path scoring results is obtained.

8. The method for controlling uniformity of explosion welding according to claim 7, characterized in that: The expression of the objective function is as follows: ； in, is the objective function, The weight optimized for the total path length, To guide the weight of the partition temperature difference optimization, is the total number of detonation points, The tipping point and the tipping point The Euclidean distance between is the actual temperature of the ith thermal boot partition, is the target temperature, and n is the total number of multiple hot boot partitions.

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