Welding distortion control method and apparatus, box, washing and sweeping vehicle, and storage medium

Abstract

The present disclosure relates to a welding deformation control method and device, a box body, a washing and sweeping vehicle and a storage medium. The welding deformation control method comprises: establishing a finite element model of a box body component; based on the finite element model, performing welding deformation prediction and extracting deformation data of a key position of the box body component; in the case that the deformation data does not meet the design requirements of the box body component, obtaining influencing factors of the welding deformation; determining the sensitivity of each influencing factor to the deformation of the key position, wherein the sensitivity is used to quantify the deformation control effect of each influencing factor; and determining a target deformation control scheme according to the sensitivity of each influencing factor, wherein the target deformation control scheme comprises at least one influencing factor. The present disclosure can combine advanced finite element simulation technology and multi-objective decision-making method to realize comprehensive quantitative evaluation and priority ranking of various influencing factors in the welding process.

Description

Technical Field

[0001] This disclosure relates to the field of welding process technology, and in particular to a welding deformation control method and apparatus, a housing, a sweeper truck, and a storage medium. Background Technology

[0002] As an important piece of equipment for urban sanitation, the body of a sweeper truck is usually made of thin stainless steel sheet through welding. Due to its complex structure and dense welds, this technology is prone to problems such as angular deformation, bending deformation, and wavy deformation during the welding process. These problems seriously affect the assembly accuracy and service performance of the sweeper truck. Summary of the Invention

[0003] The inventors discovered through research that how to effectively develop a comprehensive and practical welding deformation control strategy has become one of the major technical challenges currently faced.

[0004] The inventors' research also revealed that related technical control methods mainly rely on empirical process techniques, such as rigid fixing, anti-deformation methods, and reserving shrinkage allowances. While these methods can alleviate welding deformation to some extent, their application is highly dependent on the practical experience of technicians, lacking systematicity and repeatability. They are difficult to adapt to varying product structures and often neglect a comprehensive assessment of the additional working hours, fixture costs, and operational complexity brought about by the control measures themselves, making it difficult to balance deformation control effectiveness with production costs.

[0005] In view of at least one of the above technical problems, this disclosure provides a welding deformation control method and device, a housing, a sweeper truck and a storage medium, which can combine advanced finite element simulation technology and multi-objective decision-making methods to achieve comprehensive quantitative evaluation and priority ranking of various influencing factors in the welding process.

[0006] According to one aspect of this disclosure, a method for controlling welding deformation is provided, comprising: Establish a finite element model of the box-shaped components; Based on the finite element model, welding deformation is predicted, and deformation data at key locations of the box-shaped components are extracted. When the deformation data does not meet the design requirements of the box-shaped component, the influencing factors of the welding deformation are obtained; Determine the sensitivity of each influencing factor to deformation at the key location, wherein the sensitivity is used to quantify the deformation control effect of each influencing factor; Based on the sensitivity of each influencing factor, a target deformation control scheme is determined, wherein the target deformation control scheme includes at least one of the influencing factors.

[0007] In some embodiments of this disclosure, determining the target deformation control scheme based on the sensitivity of each influencing factor includes: The control efficiency of each influencing factor is determined based on its sensitivity and consumption value. The target deformation control scheme is determined based on the sensitivity of each influencing factor and the control efficiency of each influencing factor.

[0008] In some embodiments of this disclosure, determining the target deformation control scheme based on the sensitivity of each influencing factor and the control efficiency of each influencing factor includes: The sensitivity of each influencing factor is normalized to determine the weight coefficient of each influencing factor; The target deformation control scheme is determined based on the weight coefficient of each influencing factor and the control efficiency of each influencing factor.

[0009] In some embodiments of this disclosure, the influencing factors include at least one of the following: weld leg size, welding method, welding sequence, joint gap, tooling constraints, and intermittent welding.

[0010] In some embodiments of this disclosure, the consumption value includes at least one of implementation consumption, process complexity, process reliability and stability, the implementation consumption includes at least one of equipment consumption, labor time consumption and material consumption, and the process complexity includes at least one of operation difficulty and training consumption.

[0011] In some embodiments of this disclosure, when the influencing factors are quantified factors, determining the sensitivity of each influencing factor to the deformation of the key location includes: For each influencing factor, the reduction in the maximum deformation at the critical location caused by a change in the influencing factor is taken as the sensitivity of the influencing factor.

[0012] In some embodiments of this disclosure, the quantification factors include at least one of weld leg size, joint gap, and tooling constraints.

[0013] In some embodiments of this disclosure, when the influencing factors are discrete variables, determining the sensitivity of each influencing factor to the deformation at the key location includes: For each discrete variable factor, in the case that each discrete variable factor is a discrete variable, determine the maximum deformation at the key location, wherein each discrete variable factor includes at least one discrete variable; Based on the maximum deformation amount corresponding to each discrete variable, determine the maximum difference of the maximum deformation amount, and use the maximum difference as the sensitivity of the influencing factor.

[0014] In some embodiments of this disclosure, the discrete variable factors include at least one of welding method, welding sequence, and intermittent welding.

[0015] In some embodiments of this disclosure, determining the target deformation control scheme based on the sensitivity of each influencing factor includes: Based on the sensitivity of each influencing factor, all influencing factors are ranked from largest to smallest. The combination of the top N influencing factors in the sorted list is used as a candidate deformation control scheme, where N is greater than 1 and less than the total number of all influencing factors; Welding deformation is predicted using the target deformation control scheme, and deformation data at key locations of the box-type components are extracted. Determine whether the deformation data meets the design requirements of the box-shaped component; If the deformation data meets the design requirements of the box-shaped component, the candidate deformation control scheme will be used as the target deformation control scheme.

[0016] In some embodiments of this disclosure, determining the target deformation control scheme based on the sensitivity of each influencing factor further includes: If the deformation data does not meet the design requirements of the box-shaped component, let N equal N+1; Then, the steps of taking the combination of the top N influencing factors in the sorted list as candidate deformation control schemes, using the target deformation control scheme to predict welding deformation, extracting deformation data at key locations of the box component, and determining whether the deformation data meets the design requirements of the box component are repeated until the deformation data meets the design requirements of the box component, and then taking the candidate deformation control scheme as the target deformation control scheme.

[0017] According to another aspect of this disclosure, a welding deformation control device is provided, comprising: The model building module is configured to build finite element models of the box-shaped components; The data acquisition module is configured to predict welding deformation based on the finite element model and extract deformation data at key locations of the box-shaped components. The factor acquisition module is configured to acquire the influencing factors of the welding deformation when the deformation data does not meet the design requirements of the box component; A sensitivity determination module is configured to determine the sensitivity of each influencing factor to the deformation of the key location, wherein the sensitivity is used to quantify the deformation control effect of each influencing factor; A control scheme determination module is configured to determine a target deformation control scheme based on the sensitivity of each of the influencing factors, wherein the target deformation control scheme includes at least one of the influencing factors.

[0018] According to another aspect of this disclosure, a welding deformation control device is provided, comprising: The memory is configured to store instructions; and A processor coupled to the memory is configured to execute the welding deformation control method as described in any of the above embodiments based on instructions stored in the memory.

[0019] According to another aspect of this disclosure, a housing is provided, including a welding deformation control device as described in any of the above embodiments.

[0020] According to another aspect of this disclosure, an engineering machine is provided, including a housing as described in any of the above embodiments.

[0021] According to another aspect of this disclosure, a sweeper truck is provided, including a housing as described in any of the above embodiments.

[0022] According to another aspect of this disclosure, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions that, when executed by a processor, implement the welding deformation control method as described in any of the above embodiments.

[0023] According to another aspect of this disclosure, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, it implements the welding deformation control method as described in any of the above embodiments.

[0024] This disclosure can combine advanced finite element simulation technology with multi-objective decision-making methods to achieve a comprehensive quantitative assessment and priority ranking of various influencing factors in the welding process. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is a schematic diagram of some embodiments of the welding deformation control method disclosed herein.

[0027] Figure 2 This is a schematic diagram of some other embodiments of the welding deformation control method disclosed herein.

[0028] Figure 3 This is a schematic diagram of a finite element model for predicting welding deformation of box components in some embodiments of this disclosure.

[0029] Figure 4 This is a graph showing the variation of the maximum welding deformation at key locations of the box-shaped components with load step in some embodiments of this disclosure.

[0030] Figure 5 This is a schematic diagram illustrating typical factors affecting welding deformation in some embodiments of this disclosure.

[0031] Figure 6 This is a comparison diagram of welding deformation at key locations of box components under different influencing factors in some embodiments of this disclosure.

[0032] Figure 7 This is a schematic diagram of some embodiments of the welding deformation control device disclosed herein.

[0033] Figure 8 This is a schematic diagram of the structure of some other embodiments of the welding deformation control device disclosed herein. Detailed Implementation

[0034] The technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit this disclosure or its application or use. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without creative effort are within the scope of protection of this disclosure.

[0035] Unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of this disclosure.

[0036] At the same time, it should be understood that, for ease of description, the dimensions of the various parts shown in the accompanying drawings are not drawn according to actual scale.

[0037] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0038] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0039] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0040] The inventors' research also revealed that related welding simulation technologies mostly remain at the "simulation verification" stage, meaning they are used to explain or predict deformation results after the welding process is determined, failing to be deeply integrated into the front end of process design. Furthermore, the simulation analysis process is usually conducted in isolation, without a linkage mechanism with manufacturing cost modeling and engineering feasibility assessment. It lacks a closed-loop integrated framework from "simulation analysis → factor quantification → cost trade-off → decision output," limiting its guiding value and engineering transformation capabilities in actual production.

[0041] Currently, there is a lack of systematic quantitative evaluation systems for the factors affecting welding deformation. Various factors, such as welding sequence, heat input parameters (current, voltage, speed), fixture settings, assembly gaps, weld leg dimensions, and welding methods, all significantly influence the final deformation morphology. However, a unified evaluation index has not yet been established for the degree of influence, interaction relationships, and control costs of these factors. This makes it impossible to prioritize different control measures and achieve an optimal balance between technical feasibility and economic rationality.

[0042] The inventors discovered through research that the control strategy for welding deformation of related box-type components mainly revolves around three stages: "prevention-control-correction," namely, prediction and prevention, process control, and post-weld correction. The related patented technologies can be summarized into the following categories: (1) Prediction and prevention: Welding deformation is mainly predicted by simulation and anti-deformation measures are prevented before welding.

[0043] (2) Process control: mainly through process parameter optimization, such as welding sequence, direction, energy input, etc., to reduce heat input and uneven stress from the source; rigid constraint and tooling fixture control method, applying external constraints during welding to forcibly suppress deformation, is the most direct and widely used method.

[0044] (3) Post-weld straightening: This includes mechanical straightening (press, roller pressing) and flame heating straightening (point, line, triangular heating), which is widely used in steel structure manufacturing. It can effectively eliminate residual deformation and improve assembly accuracy. The straightening process relies on experience and lacks a unified standard and evaluation system.

[0045] (4) Multi-method fusion welding deformation control strategy.

[0046] The inventors discovered through research that the relevant technologies for controlling welding deformation of box-type components have the following technical problems: (1) In the prediction and prevention stage, the practicality is limited by the reliance on simulation accuracy and idealized assumptions. The simulation modeling is complex and relies on experience. Numerical simulation requires precise setting of material properties, heat source models and boundary conditions. The simplification of complex welds and phase transformation behavior (such as using contact pairs to replace actual phase transformation) leads to a large deviation between the prediction results and the actual results. The anti-deformation design lacks quantitative basis: the current anti-deformation is mostly based on experience or ideal models, without considering the dynamic changes and cumulative effects in the welding process, resulting in insufficient accuracy of the prefabricated shape.

[0047] (2) Process control stage: The limitations of rigid constraints and parameter optimization, poor flexibility and adaptability of tooling fixtures, and the fact that the internal support tooling is adjustable but relies on mechanical structures (cam pairs, tension springs) to achieve constraints, making it difficult to respond to welding thermal deformation in real time, and its versatility for different box sizes is limited; rigid constraints are prone to introducing residual stress, which may lead to secondary deformation or cracking risks. Process optimization relies on data and algorithms, but lacks real-time performance; machine learning is used to optimize the welding sequence, but a large amount of historical data is required to train the model, and the algorithm output is a "predefined scheme", which cannot be dynamically adjusted according to real-time changes in the welding process.

[0048] (3) Post-weld straightening stage: Mechanical straightening (such as press) and flame heating straightening are highly dependent on the operator's experience and lack quantitative control standards, which can easily lead to over-straightening or damage to material properties; real-time control technology is not yet mature; dynamic control can be achieved through digital twin and sensor monitoring, but the system is complex, costly, and relies on high-precision models and sensors, resulting in low reliability and difficulty in promotion in actual production.

[0049] (4) Multi-method fusion strategy: The system is not complex and lacks coordination. We have tried to combine multiple methods such as pre-deformation, tooling, and sequential control, but there are still problems: insufficient multi-stage coordination, the pre-control and correction links operate independently and lack closed-loop feedback throughout the process; the prediction model requires a lot of experimental data to support it and is sensitive to material properties and structural boundary conditions, making it difficult to transfer to new structures; the implementation cost is high and the efficiency is low; the complex tooling, simulation and sensing system increases equipment investment and production cycle, making it difficult to apply to small and medium-sized production scenarios.

[0050] In view of at least one of the above technical problems, this disclosure provides a welding deformation control method and apparatus, a housing, a sweeper truck, and a storage medium. The present disclosure will be described below through specific embodiments.

[0051] Figure 1 This is a schematic diagram of some embodiments of the welding deformation control method disclosed herein. Figure 2The diagram illustrates other embodiments of the welding deformation control method of this disclosure. Preferably, this embodiment can be executed by the welding deformation control device of this disclosure, the housing of this disclosure, the sweeper truck of this disclosure, or the engineering machinery of this disclosure. Figure 1 and Figure 2 As shown, Figure 1 or Figure 2 The method of the embodiment may include at least one of steps 1 to 5. Figure 2 The embodiment may also include step 6.

[0052] In step 1, a finite element model of the box-shaped component is established.

[0053] In some embodiments of this disclosure, the housing component may be a housing component of a sweeper or other engineering machinery.

[0054] In some embodiments of this disclosure, such as Figure 2 As shown, Figure 1 or Figure 2 Step 1 of the embodiment may include at least one of steps 11 to 16.

[0055] In step 11, the model of the sweeper truck body is simplified and the mid-surface is extracted.

[0056] In some embodiments of this disclosure, step 11 may include: simplifying the geometric model of the box component, including removing minor components such as stiffeners that have little impact on welding deformation, deleting engineering features such as chamfers and fillets, and extracting the mid-surface of each part of the box component based on the above simplification.

[0057] In step 12, the mesh is defined to define the joints.

[0058] In step 13, constraint boundary conditions are applied.

[0059] In some embodiments of this disclosure, step 13 may include: establishing a finite element model of the box component based on the shell element, assigning material properties and thickness properties to the model components respectively; and applying constraint boundary conditions to the model based on the actual situation.

[0060] In some embodiments of this disclosure, the constraint boundary conditions mainly consider welding fixture constraints (if there are fixtures), and to avoid overall model movement, three-point constraints are used, such as... Figure 3 The triangle shape shown. Figure 3 This is a schematic diagram of a finite element model for predicting welding deformation of box components in some embodiments of this disclosure.

[0061] In step 14, the weld joint types are statistically analyzed.

[0062] In some embodiments of this disclosure, step 14 may include: obtaining typical weld joint types of the box components, including butt joints, lap joints, T-joints, etc., and establishing a list of weld joints.

[0063] In step 15, the welded joints are merged.

[0064] In some embodiments of this disclosure, step 15 may include: merging the above-mentioned joint list according to the calculation method of the inherent deformation of the welded joint, wherein the welded joint type, base material performance parameters, base material thickness, welding heat input, etc. affect the value and distribution of the inherent deformation of the welded joint, while factors such as the length of the welded joint can be ignored, and the joint list is merged according to the above-mentioned influencing factors.

[0065] In step 16, the inherent deformation data is obtained.

[0066] In some embodiments of this disclosure, step 16 may include: calculating the welding inherent deformation data of each joint, such as longitudinal shrinkage inherent deformation, transverse shrinkage inherent deformation, longitudinal bending inherent deformation, and transverse bending inherent deformation, and storing them in a database.

[0067] In some embodiments of this disclosure, the calculation methods mainly include at least one of the following methods: experimental testing, deformation inversion, empirical formula, and strain integral.

[0068] In step 2, based on the finite element model, welding deformation is predicted, and deformation data at key locations of the box-shaped components are extracted.

[0069] In some embodiments of this disclosure, step 2 may include: solving welding deformation simulation.

[0070] In some embodiments of this disclosure, such as Figure 2 As shown, Figure 1 or Figure 2 Step 2 of the embodiment may include at least one of steps 21 to 22.

[0071] In step 21, retrieve the inherent deformation data.

[0072] In some embodiments of this disclosure, step 21 may include: retrieving the inherent deformation data of each welded joint in the structural component from the inherent deformation database based on the finite element model of the box component.

[0073] In some embodiments of this disclosure, the inherent deformation data may include various types such as longitudinal shrinkage inherent deformation, transverse shrinkage inherent deformation, longitudinal bending inherent deformation, and transverse bending inherent deformation.

[0074] In step 22, welding deformation is predicted.

[0075] In some embodiments of this disclosure, step 22 may include: loading inherent deformation data into the weld of the finite element model; performing a welding deformation prediction through a single elastic calculation to obtain a deformation cloud map of the structural component.

[0076] In some embodiments of this disclosure, step 22 may include: loading four data points of the inherent strain onto the weld location, causing elastic deformation near the weld through the four data points, thereby obtaining the deformation of the entire structural component.

[0077] In step 3, if the deformation data does not meet the design requirements of the box-shaped component, the influencing factors of the welding deformation are obtained.

[0078] In some embodiments of this disclosure, such as Figure 2 As shown, Figure 1 or Figure 2 Step 3 of the embodiment may include at least one of steps 31 to 33.

[0079] In step 31, the deformation at key locations is extracted.

[0080] In some embodiments of this disclosure, step 31 may include: deformation feature analysis and key location deformation extraction.

[0081] In some embodiments of this disclosure, such as Figure 3 As shown, the key location is the black curve set on the upper surface of the box structure. Figure 3 The curve in the middle is a straight line.

[0082] In some embodiments of this disclosure, step 31 may include: analyzing the deformation trend and magnitude of the box-shaped component based on simulation results using cloud maps, curve graphs, etc.; determining whether the deformation trend of the box-shaped component in the simulation model matches the actual deformation results in production by examining X, Y, Z and overall cloud maps; and determining the rationality of the deformation based on the method of weld shrinkage caused by welding deformation. Secondly, to facilitate data comparison and analysis, the simulation results and measured results of welding deformation at typical locations of the box-shaped component are compared. The error in the average deformation amount, maximum deformation amount, etc., is used to determine the conformity between the finite element simulation results and the measured results, as shown in Table 1. Table 1 is a schematic diagram of the deviation analysis between the key locations and curve prediction structures of the box-shaped component and the measured results in some embodiments of this disclosure. The purpose of this step is to ensure the correctness of the finite element model and provide model support for the subsequent deformation control scheme formulation. Generally, the error (i.e., conformity) between the finite element simulation results and the measured results is controlled within 15%.

[0083] Table 1

[0084] In step 32, the maximum deformation of the critical deformation region is determined, and it is judged whether the maximum deformation of the critical deformation region meets the design requirements of the box-type component. If the design requirements of the box-type component are met, the following steps are executed: Figure 2 Step 6 of the embodiment is to output the control scheme; otherwise, if the design requirements of the box component are met, step 33 is executed.

[0085] In some embodiments of this disclosure, step 32 may include: determining the maximum allowable value for the critical deformation area based on design requirements (these requirements are mentioned in the product design and involve a lot of content, mainly reflected in the allowable deformation amount in the technical drawings). Figure 2 (meeting the requirements) and extracting the curves of key deformation areas from the simulation results to analyze the deformation trend of these areas; simultaneously, extracting the variation of the maximum welding deformation in these areas with the load step (e.g., Figure 4 As shown in the figure, the load step with the largest deformation is obtained, which helps to determine which weld or welds have the greatest impact on the maximum deformation of the area, and then to focus on proposing control measures for the welds with the greatest impact. Figure 2 The requirement mentioned in the text mainly refers to whether the maximum value of the key deformation area meets the requirements of the drawing.

[0086] Figure 4 This is a graph showing the variation of the maximum welding deformation at key locations of the box-type components with load step in some embodiments of this disclosure. For example... Figure 4 As shown, the horizontal axis represents the weld number, so there is no unit (the weld number means that there are more than 200 welds in the sweeper truck body, and the weld number 1 is welded first, which also determines the welding order). Figure 4 The data extracted shows the variation of the maximum deformation in the X, Y, and Z directions with the weld number.

[0087] In step 33, the key factors affecting deformation (influencing factors) are selected to design an experimental scheme.

[0088] In some embodiments of this disclosure, step 33 may include: selecting typical factors that affect welding deformation based on the finite element model of the box component, such as weld leg size, welding method, welding sequence, joint gap, tooling constraints, etc.

[0089] In some embodiments of this disclosure, the influencing factors may include at least one of the following: weld leg size, welding method, welding sequence, joint gap, tooling constraints, and intermittent welding. The tooling constraints are dimensional constraints of the box component in the length, width, height, and other directions. The welding method optimization is to optimize from the current welding method to an efficient welding method. The current welding method may be gas shielded welding, and the efficient welding method may be laser welding.

[0090] In other embodiments of this disclosure, such as Figure 2 As shown, the influencing factors may include at least one of the following: welding structure optimization, welding sequence optimization, welding joint optimization, welding reverse deformation, use of intermittent welding, high-efficiency welding method, process parameter optimization, welding tooling constraints, etc.

[0091] Figure 5 This is a schematic diagram illustrating typical factors affecting welding deformation in some embodiments of this disclosure. For example... Figure 5 As shown, in the welding deformation control scheme, the influencing factors can include design stage factors and manufacturing stage factors. Design stage factors can include structural design factors and joint design factors. Structural design factors include at least one of the following: selecting a structural form with good weldability, and rationally arranging the weld layout and joint position. Joint design factors include at least one of the following: designing a reasonable weld leg size, and adopting an intermittent welding method. Manufacturing stage factors include pre-welding factors and in-welding factors. Pre-welding factors include at least one of the following: welding anti-deformation, welding tooling constraints, controlling a reasonable gap, and pre-stretching. In-welding factors include at least one of the following: selecting an efficient welding method, optimizing welding process parameters, and optimizing the welding sequence.

[0092] In step 4, the sensitivity of each influencing factor to the deformation at the key location is determined, wherein the sensitivity is used to quantify the deformation control effect of each influencing factor.

[0093] In some embodiments of this disclosure, step 4 may include: using a parametric scanning method to analyze the sensitivity of each factor to the maximum deformation at the key location.

[0094] In some embodiments of this disclosure, when the influencing factors are quantifiable factors, determining the sensitivity of each influencing factor to the deformation of the key position includes: for each influencing factor, taking the reduction in the maximum deformation of the key position caused by a unit change in the influencing factor as the sensitivity of the influencing factor.

[0095] In some embodiments of this disclosure, the quantification factors may include at least one of weld leg size, splice gap, and tooling constraints.

[0096] In some embodiments of this disclosure, for quantifiable factors, such as solder pad size, the deformation control effect of each factor is quantified by the reduction in maximum deformation at critical locations caused by a unit change (i.e., the reduction in maximum deformation at critical locations caused by a change in solder pad size per mm).

[0097] In some embodiments of this disclosure, step 4 may include at least one of steps 41 to 42.

[0098] In step 41, for each discrete variable factor, the maximum deformation at the key location is determined when the discrete variable factor is a discrete variable, wherein each discrete variable factor includes at least one discrete variable.

[0099] In some embodiments of this disclosure, the discrete variable factors include at least one of welding method, welding sequence, and intermittent welding.

[0100] In some embodiments of this disclosure, the welding method may include two discrete variables: gas-shielded welding (the current welding method) and laser welding.

[0101] In some embodiments of this disclosure, intermittent welding may include two discrete variables: intermittent welding and not intermittent welding.

[0102] In some embodiments of this disclosure, the welding sequence may include four discrete variables: a bottom-up welding sequence; a top-down welding sequence; an inside-out welding sequence; and an outside-in welding sequence.

[0103] In step 42, based on the maximum deformation amount corresponding to each discrete variable, the maximum difference of the maximum deformation amount is determined, and the maximum difference is used as the sensitivity of the influencing factor.

[0104] In some embodiments of this disclosure, taking welding sequence as an example, the application process of the parametric scanning method is illustrated. Its main content is to fix the other influencing factors, change only the welding sequence of the model, record the welding deformation calculation, and calculate the sensitivity of the welding sequence by comparing the magnitude of welding deformation under different welding sequence schemes.

[0105] In some embodiments of this disclosure, for the welding sequence, step 4 may include at least one of steps 401 to 404.

[0106] In step 401, since the welding sequence is a discrete variable, four typical strategies are selected: Current approach: Based on the baseline value, the welding sequence is adopted from bottom to top; Option A: Use a top-down welding sequence; Option B: Adopt a welding sequence from the inside out; Option C: Adopt a welding sequence from the outside in.

[0107] In step 402, the maximum curve deformation results at the key locations were determined to be 78.7 mm, 78.19 mm, 78.74 mm, and 79.13 mm, respectively.

[0108] In step 403, since the welding sequence cannot be continuously quantified, the range method is used to evaluate its influence, as shown in formula (1).

[0109] Rseq=Dmax-Dmin=79.13-78.19=0.94mm (1)

[0110] In formula (1), Rseq refers to the sensitivity of the welding sequence, Dmax is the maximum welding deformation, and Dmin is the minimum welding sequence deformation.

[0111] The above-described embodiments of the present disclosure show that the different welding sequences of the housing result in low differences, indicating that this factor has a small impact.

[0112] In some embodiments of this disclosure, the sensitivity of each factor to welding deformation can also be analyzed, as shown in Table 2 and... Figure 6 As shown in Table 2, which is a schematic table illustrating the sensitivity of each influencing factor in some embodiments of this disclosure. Figure 6 This is a comparison diagram of welding deformation at key locations of box components under different influencing factors in some embodiments of this disclosure. Figure 6 The middle horizontal axis represents the key location curve (see...). Figure 3 The location of the black curve at the top of the model shown is marked with an arrow. Figure 6 The vertical axis data refers to the Z-axis deformation at different positions on the curve. Figure 6 Different influencing factors include the original model, sequence optimization, splice gap optimization, increased constraints, laser welding method, intermittent welding, and reduced weld leg size.

[0113] Table 2

[0114] In step 5, a target deformation control scheme is determined based on the sensitivity of each influencing factor, wherein the target deformation control scheme includes at least one of the influencing factors.

[0115] In some embodiments of this disclosure, such as Figure 2 As shown, step 5 may include at least one of steps 51 to 52.

[0116] In step 51, the control efficiency of each influencing factor is determined based on the sensitivity of each influencing factor and the consumption value of each influencing factor, wherein the control efficiency can be a unit cost deformation control benefit index.

[0117] In some embodiments of this disclosure, step 51 may include: calculating the unit cost deformation control benefit index for each factor.

[0118] In some embodiments of this disclosure, the consumption value may include at least one of the consumption values ​​such as implementation consumption, process complexity, process reliability and stability, the implementation consumption includes at least one of the consumption values ​​such as equipment consumption, labor time consumption and material consumption, and the process complexity includes at least one of the consumption values ​​such as operation difficulty and training consumption.

[0119] In step 52, the target deformation control scheme is determined based on the sensitivity of each influencing factor and the control efficiency of each influencing factor.

[0120] In some embodiments of this disclosure, step 52 may include: comprehensively considering control effects and benefit indicators to determine the final control scheme.

[0121] In some embodiments of this disclosure, step 52 may include: multi-factor impact analysis and quantitative assessment.

[0122] In some embodiments of this disclosure, step 52 may include at least one of steps 521 to 523.

[0123] In step 521, the sensitivity of each influencing factor is normalized to determine the weight coefficient of each influencing factor.

[0124] In some embodiments of this disclosure, step 521 may include: normalizing the sensitivity data calculated above according to formula (2) to construct weight coefficients.

[0125] (2)

[0126] In formula (2), n represents the analytical factors; in this example, n = 6. Let be the weight coefficient of the i-th factor. Let be the sensitivity of the i-th factor; Let be the sensitivity of the j-th factor.

[0127] In step 522, a weighted ranking table of influencing factors is constructed, as shown in Table 3; at the same time, a knowledge base is established to provide support for the selection of subsequent influencing factors.

[0128] Table 3

[0129] In step 523, a cost efficiency (control efficiency) evaluation model for each typical factor is established, the cost change of a single set of enclosures under each factor is calculated, and the results are ranked.

[0130] In some embodiments of this disclosure, the unit deformation cost is a multi-dimensional indicator that takes into account factors such as increased working hours and operational difficulty (such as reduced efficiency due to gap adjustment).

[0131] In some embodiments of this disclosure, step 523 may include: a comprehensive evaluation of cost efficiency and effectiveness.

[0132] In some embodiments of this disclosure, step 523 may include: based on the above calculation results, comprehensively considering implementation costs (equipment investment, increased working hours, material consumption), process complexity (operational difficulty, training costs), process reliability and stability, etc., establishing a cost efficiency evaluation model for each typical factor, calculating the cost change of a single set of enclosures under each factor, and ranking them, as shown in Table 4. Table 4 is a comparison table of enclosure component costs under different influencing factors in some embodiments of this disclosure.

[0133] Table 4

[0134] The notes in Table 4 indicate the reasons for the changes in unit deformation cost. Taking laser welding as an example, compared with the original solution, new equipment was invested and the equipment investment was large, which theoretically should have increased the unit deformation cost. However, due to the improvement of welding efficiency, the unit deformation cost will decrease.

[0135] In step 524, the target deformation control scheme is determined based on the weight coefficient of each influencing factor and the control efficiency of each influencing factor.

[0136] In some embodiments of this disclosure, step 524 may include: based on effect weights and cost efficiency, performing combined calculations on the above-mentioned typical factors using a benefit-priority hierarchical combination method (maximum deformation, lowest cost), simultaneously selecting the optimal combination, and outputting a comprehensive control scheme including recommended welding sequence, weld leg size, process parameters, and anti-deformation measures. Based on the above work, a knowledge base is established to support rapid decision-making for welding deformation control schemes for similar structures in the future.

[0137] In some embodiments of this disclosure, step 524 may consider the permutations and combinations of various influencing factors.

[0138] In some embodiments of this disclosure, step 524 may include at least one of steps 501 to 506.

[0139] In step 501, all influencing factors are sorted in descending order of their sensitivity.

[0140] In step 502, the combination of the top N influencing factors in the sorted list is taken as a candidate deformation control scheme, where N is greater than 1 and less than the total number of all influencing factors.

[0141] In step 503, the target deformation control scheme is used to predict welding deformation and extract deformation data at key locations of the box-shaped components.

[0142] In step 504, it is determined whether the deformation data meets the design requirements of the box-shaped component. If the deformation data meets the design requirements of the box-shaped component, step 505 is executed; otherwise, if the deformation data does not meet the design requirements of the box-shaped component, step 506 is executed.

[0143] In step 505, the candidate deformation control scheme is selected as the target deformation control scheme.

[0144] In step 506, let N equal N+1; then, repeat the steps of taking the combination of the top N influencing factors in the sorted list as a candidate deformation control scheme, using the target deformation control scheme to predict welding deformation, extracting deformation data at key positions of the box component, and determining whether the deformation data meets the design requirements of the box component (i.e., repeat steps 501 to 504).

[0145] In some embodiments of this disclosure, step 524 may include: firstly, selecting all high-priority and low-cost influencing factors as the basic solution, including laser welding, intermittent welding, and reduced weld leg size; combining the above three factors and performing deformation prediction, the welding deformation at the critical position is 12.79mm, and determining whether the deformation meets the drawing requirements; if it does not meet the drawing requirements, then adding the lowest unit deformation cost from the remaining factors with positive costs to supplement it, the selected factor being tooling constraints; repeating this process until the welding deformation at the critical position meets the requirements.

[0146] In step 6, the output control scheme is determined.

[0147] In some embodiments of this disclosure, step 6 may include: outputting the final optimization scheme according to the above control logic.

[0148] The above embodiments of this disclosure provide a new method for controlling welding deformation. This method is based on a systematic analysis method, combined with advanced finite element simulation technology and multi-objective decision-making method, to achieve a comprehensive quantitative evaluation and priority ranking of various influencing factors in the welding process. At the same time, the above embodiments of this disclosure also take cost-effectiveness into account, in order to reduce production costs while ensuring welding quality.

[0149] The present invention discloses a method for controlling welding deformation of sweeper truck body components based on "simulation-driven, factor quantification, cost-benefit assessment, and closed-loop optimization".

[0150] The above embodiments of this disclosure provide a systematic and quantifiable method for controlling welding deformation of a sweeper truck body. Through simulation prediction, factor analysis, and cost-efficiency evaluation, an optimal control scheme is formed, achieving a balance between minimizing deformation and manufacturing costs.

[0151] The embodiments of this disclosure, by establishing a finite element simulation model of the welding process, can predict the deformation trend of the sweeper truck body in advance, accurately identify the area of ​​maximum deformation, avoid the blindness of traditional empirical methods, and improve the scientificity and pertinence of process formulation. At the same time, the embodiments of this disclosure comprehensively analyze the influence of multiple factors such as welding sequence, fixture layout, and heat input on deformation, quantify the control effect of each factor, and conduct a comprehensive evaluation in combination with cost, achieving a balance between technical effect and economic efficiency. The control scheme formed by the embodiments of this disclosure can directly guide on-site production, effectively reduce welding deformation, improve the assembly accuracy and product quality of the body, and reduce rework and tooling investment, thus having good practicality and promotion value.

[0152] The above-described embodiments of this disclosure are highly targeted, namely applicable to the formulation of welding deformation control schemes for sweeper truck bodies.

[0153] The above-described embodiments of this disclosure address the technical problem of the difficulty in formulating welding deformation control schemes. For the first time, finite element simulation, multi-factor sensitivity analysis, and cost-benefit assessment are integrated into the welding deformation control of box bodies, breaking through the limitations of related technical empirical methods or single simulation analysis, and improving the scientific nature and pertinence of the deformation control scheme.

[0154] Figure 7 These are schematic diagrams of some embodiments of the welding deformation control device disclosed herein. Figure 7 As shown, the welding deformation control device disclosed herein may include a model establishment module 71, a data acquisition module 72, a factor acquisition module 73, a sensitivity determination module 74, and a control scheme determination module 75.

[0155] Model building module 71 is configured to build finite element models of box-shaped components.

[0156] The data acquisition module 72 is configured to predict welding deformation based on the finite element model and extract deformation data at key locations of the box-shaped components.

[0157] The factor acquisition module 73 is configured to acquire the influencing factors of the welding deformation when the deformation data does not meet the design requirements of the box component.

[0158] In some embodiments of this disclosure, the influencing factors may include at least one of the following: weld leg size, welding method, welding sequence, joint gap, tooling constraints, and intermittent welding.

[0159] The sensitivity determination module 74 is configured to determine the sensitivity of each influencing factor to the deformation of the key location, wherein the sensitivity is used to quantify the deformation control effect of each influencing factor.

[0160] In some embodiments of this disclosure, when the influencing factor is a quantifiable factor, the sensitivity determination module 74 can be configured to, for each influencing factor, take the reduction in the maximum deformation of the key position caused by a unit change in the influencing factor as the sensitivity of the influencing factor.

[0161] In some embodiments of this disclosure, the quantification factors may include at least one of weld leg size, splice gap, and tooling constraints.

[0162] In some embodiments of this disclosure, when the influencing factor is a discrete variable factor, the sensitivity determination module 74 can be configured to determine the maximum deformation amount of the key position for each discrete variable factor, wherein each discrete variable factor includes at least one discrete variable; and determine the maximum difference of the maximum deformation amount based on the maximum deformation amount corresponding to each discrete variable, and use the maximum difference as the sensitivity of the influencing factor.

[0163] In some embodiments of this disclosure, the discrete variable factors may include at least one of welding method, welding sequence, and intermittent welding.

[0164] The control scheme determination module 75 is configured to determine a target deformation control scheme based on the sensitivity of each of the influencing factors, wherein the target deformation control scheme includes at least one of the influencing factors.

[0165] In some embodiments of this disclosure, the control scheme determination module 75 may be configured to determine the control efficiency of each influencing factor based on the sensitivity of each influencing factor and the consumption value of each influencing factor; and to determine the target deformation control scheme based on the sensitivity of each influencing factor and the control efficiency of each influencing factor.

[0166] In some embodiments of this disclosure, the consumption value includes at least one of implementation consumption, process complexity, process reliability and stability, the implementation consumption includes at least one of equipment consumption, labor time consumption and material consumption, and the process complexity includes at least one of operation difficulty and training consumption.

[0167] In some embodiments of this disclosure, when the control scheme determination module 75 determines the target deformation control scheme based on the sensitivity of each influencing factor and the control efficiency of each influencing factor, it can be configured to normalize the sensitivity of each influencing factor to determine the weight coefficient of each influencing factor; and determine the target deformation control scheme based on the weight coefficient of each influencing factor and the control efficiency of each influencing factor.

[0168] In some embodiments of this disclosure, the control scheme determination module 75 can be configured to sort all influencing factors in descending order of their sensitivity; take the combination of the top N influencing factors in the sorted list as a candidate deformation control scheme, where N is greater than 1 and less than the total number of all influencing factors; use the target deformation control scheme to predict welding deformation and extract deformation data at key locations of the box-type component; determine whether the deformation data meets the design requirements of the box-type component; and if the deformation data meets the design requirements of the box-type component, use the candidate deformation control scheme as the target deformation control scheme.

[0169] In some embodiments of this disclosure, the control scheme determination module 75 may also be configured to, when the deformation data does not meet the design requirements of the box component, set N equal to N+1; then repeatedly execute the operation of taking the combination of the top N influencing factors in the sorted list as a candidate deformation control scheme, using the target deformation control scheme to predict welding deformation, extracting deformation data at key positions of the box component, and determining whether the deformation data meets the design requirements of the box component, until the deformation data meets the design requirements of the box component, and then taking the candidate deformation control scheme as the target deformation control scheme.

[0170] In some embodiments of this disclosure, the welding deformation control device of this disclosure may also be configured to perform the welding deformation control method described in any of the above embodiments of this disclosure.

[0171] The embodiments of this disclosure provide a method for formulating and controlling welding deformation control strategies for box-type components. The embodiments of this disclosure comprehensively analyze the influence of multiple factors such as welding sequence, fixture layout, and heat input on deformation, quantify the control effect of each factor, and conduct a comprehensive evaluation in combination with cost, thereby achieving a balance between technical effectiveness and economic efficiency, and realizing a leap from "experience-based trial and error" to "quantitative optimization" in control schemes.

[0172] The above embodiments of this disclosure transform the optimized control scheme into a knowledge graph (such as a triple rule base of "fixture spacing-deformation amount-cost"), and solidify the optimized process parameters into work instructions to guide on-site production.

[0173] Figure 8 The diagram shows the structure of some other embodiments of the welding deformation control device disclosed herein. For example... Figure 8 As shown, the welding deformation control device includes a memory 81 and a processor 82.

[0174] The memory 81 is used to store instructions, and the processor 82 is coupled to the memory 81. The processor 82 is configured to implement the welding deformation control method described in any of the above embodiments of this disclosure based on the instructions stored in the memory.

[0175] like Figure 8 As shown, the welding deformation control device also includes a communication interface 83 for information exchange with other devices. Additionally, the welding deformation control device includes a bus 84, through which the processor 82, communication interface 83, and memory 81 communicate with each other.

[0176] The memory 81 may include high-speed RAM, and may also include non-volatile memory, such as at least one disk drive. The memory 81 may also be a memory array. The memory 81 may also be divided into blocks, and these blocks may be combined into virtual volumes according to certain rules.

[0177] Furthermore, processor 82 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present disclosure.

[0178] The present invention discloses an apparatus and method for predicting, analyzing and controlling the deformation of the box-shaped components generated during the welding process in the above embodiments, which is particularly applicable to the welding deformation control of large thin-walled metal structural components such as sweeper truck boxes.

[0179] According to another aspect of this disclosure, a housing is provided, including a welding deformation control device as described in any of the above embodiments.

[0180] According to another aspect of this disclosure, an engineering machine is provided, including a housing as described in any of the above embodiments.

[0181] According to another aspect of this disclosure, a sweeper truck is provided, including a housing as described in any of the above embodiments.

[0182] According to another aspect of this disclosure, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, it implements the welding deformation control method as described in any of the above embodiments.

[0183] According to another aspect of this disclosure, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions that, when executed by a processor, implement the welding deformation control method as described in any of the above embodiments.

[0184] In some embodiments of this disclosure, the computer-readable storage medium may be a non-transitory computer-readable storage medium.

[0185] Those skilled in the art will understand that embodiments of this disclosure can be provided as methods, apparatus, or computer program products. Therefore, this disclosure can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this disclosure can take the form of a computer program product embodied on one or more computer-usable non-transitory storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0186] This disclosure is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0187] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0188] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0189] The welding deformation control device, model building module, data acquisition module, factor acquisition module, sensitivity determination module, and control scheme determination module described above can be implemented as a general-purpose processor, programmable logic controller (PLC), digital signal processor (DSP), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic device, discrete hardware component, or any suitable combination thereof for performing the functions described in this application.

[0190] This concludes the detailed description of the present disclosure. To avoid obscuring the concept of the disclosure, some details known in the art have not been described. Those skilled in the art will fully understand how to implement the technical solutions disclosed herein based on the above description.

[0191] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware, or by a program instructing the relevant hardware to implement them. The program can be stored in a non-transitory computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0192] The description in this disclosure is provided for illustrative and descriptive purposes only and is not intended to be exhaustive or to limit the disclosure to its forms. Many modifications and variations will be apparent to those skilled in the art. The embodiments were chosen and described in order to better illustrate the principles and practical application of this disclosure and to enable those skilled in the art to understand this disclosure and to design various embodiments with various modifications suitable for a particular purpose.

Claims

1. A method for controlling welding deformation, comprising: Establish a finite element model of the box-shaped components; Based on the finite element model, welding deformation is predicted, and deformation data at key locations of the box-shaped components are extracted. When the deformation data does not meet the design requirements of the box-shaped component, the influencing factors of the welding deformation are obtained; Determine the sensitivity of each influencing factor to deformation at the key location, wherein the sensitivity is used to quantify the deformation control effect of each influencing factor; Based on the sensitivity of each influencing factor, a target deformation control scheme is determined, wherein the target deformation control scheme includes at least one of the influencing factors.

2. The welding deformation control method according to claim 1, wherein, The step of determining the target deformation control scheme based on the sensitivity of each influencing factor includes: The control efficiency of each influencing factor is determined based on its sensitivity and consumption value. The target deformation control scheme is determined based on the sensitivity of each influencing factor and the control efficiency of each influencing factor.

3. The welding deformation control method according to claim 2, wherein, The step of determining the target deformation control scheme based on the sensitivity and control efficiency of each influencing factor includes: The sensitivity of each influencing factor is normalized to determine the weight coefficient of each influencing factor; The target deformation control scheme is determined based on the weight coefficient of each influencing factor and the control efficiency of each influencing factor.

4. The welding deformation control method according to any one of claims 1 to 3, wherein, The influencing factors include at least one of the following: weld leg size, welding method, welding sequence, joint gap, tooling constraints, and intermittent welding.

5. The welding deformation control method according to claim 2 or 3, wherein, The consumption value includes at least one of implementation consumption, process complexity, process reliability and stability. The implementation consumption includes at least one of equipment consumption, labor time consumption and material consumption. The process complexity includes at least one of operation difficulty and training consumption.

6. The welding deformation control method according to any one of claims 1 to 3, wherein, When the influencing factors are quantifiable factors, determining the sensitivity of each influencing factor to the deformation at the key location includes: For each influencing factor, the reduction in the maximum deformation at the critical location caused by a change in the influencing factor is taken as the sensitivity of the influencing factor.

7. The welding deformation control method according to claim 6, wherein, The quantification factors include at least one of the following: weld leg size, joint gap, and tooling constraints.

8. The welding deformation control method according to any one of claims 1 to 3, wherein, When the influencing factors are discrete variables, determining the sensitivity of each influencing factor to the deformation at the key location includes: For each discrete variable factor, in the case that each discrete variable factor is a discrete variable, determine the maximum deformation at the key location, wherein each discrete variable factor includes at least one discrete variable; Based on the maximum deformation amount corresponding to each discrete variable, determine the maximum difference of the maximum deformation amount, and use the maximum difference as the sensitivity of the influencing factor.

9. The welding deformation control method according to claim 8, wherein, The discrete variable factors include at least one of welding method, welding sequence, and intermittent welding.

10. The welding deformation control method according to any one of claims 1 to 3, wherein, The step of determining the target deformation control scheme based on the sensitivity of each influencing factor includes: Based on the sensitivity of each influencing factor, all influencing factors are ranked from largest to smallest. The combination of the top N influencing factors in the sorted list is used as a candidate deformation control scheme, where N is greater than 1 and less than the total number of all influencing factors; Welding deformation is predicted using the target deformation control scheme, and deformation data at key locations of the box-type components are extracted. Determine whether the deformation data meets the design requirements of the box-shaped component; If the deformation data meets the design requirements of the box-shaped component, the candidate deformation control scheme will be used as the target deformation control scheme.

11. The welding deformation control method according to claim 10, wherein, The step of determining the target deformation control scheme based on the sensitivity of each influencing factor further includes: If the deformation data does not meet the design requirements of the box-shaped component, let N equal N+1; Repeat the steps of taking the combination of the top N influencing factors in the sorted list as a candidate deformation control scheme, using the target deformation control scheme to predict welding deformation, extracting deformation data at key locations of the box component, and determining whether the deformation data meets the design requirements of the box component, until the deformation data meets the design requirements of the box component, and then taking the candidate deformation control scheme as the target deformation control scheme.

12. A welding deformation control device, comprising: The model building module is configured to build finite element models of the box-shaped components; The data acquisition module is configured to predict welding deformation based on the finite element model and extract deformation data at key locations of the box-shaped components. The factor acquisition module is configured to acquire the influencing factors of the welding deformation when the deformation data does not meet the design requirements of the box component; A sensitivity determination module is configured to determine the sensitivity of each influencing factor to the deformation of the key location, wherein the sensitivity is used to quantify the deformation control effect of each influencing factor; A control scheme determination module is configured to determine a target deformation control scheme based on the sensitivity of each of the influencing factors, wherein the target deformation control scheme includes at least one of the influencing factors.

13. A welding deformation control device, comprising: The memory is configured to store instructions; as well as A processor coupled to the memory, the processor being configured to execute the welding deformation control method as described in any one of claims 1 to 11 based on instructions stored in the memory.

14. A housing comprising the welding deformation control device as described in claim 12 or 13.

15. An engineering machine, comprising the housing as described in claim 14.

16. A sweeper truck, comprising the housing as described in claim 14.

17. A computer-readable storage medium, wherein, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the welding deformation control method as described in any one of claims 1 to 11.

18. A computer program product comprising a computer program, wherein, When the computer program is executed by the processor, it implements the welding deformation control method as described in any one of claims 1 to 11.

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