A method for dynamically adjusting sheet metal connecting parameters based on multi-level rule determination

Abstract

The present application relates to the technical field of machining process control, and particularly relates to a sheet material connection parameter dynamic adjustment method based on multistage rule determination, comprising: constructing a three-stage rule determination system, including a material safety layer, a quality guarantee layer and a process optimization layer; based on material characteristics obtained by finite element numerical simulation as process parameter input, performing rule determination in turn according to the hierarchical priority order; real-time calculation of material stress field distribution and thermal deformation data adjustment of safety threshold; calling the corresponding multistage rule tree of the material type, performing iterative operation from the leaf node to the root node of the multistage rule tree, obtaining the final process parameters of the material and performing systematic verification; generating the equipment control instruction set in the standard format according to the verified process parameters, and outputting to the execution end. The present application can significantly improve the machining safety, quality stability and process optimization effect, while reducing the equipment debugging cost, enhancing the process parameter reliability and compatibility.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of mechanical processing process control, in particular to a plate connection parameter dynamic adjustment method based on multi-level rule judgment. BACKGROUND

[0002] In the field of mechanical processing process control, hot assisted flow drilling and riveting process as an important connection technology, the accurate setting of its process parameters has a decisive influence on the processing quality, safety and efficiency. However, the adjustment of process parameters in the prior art usually depends on artificial experience or single rule based on fixed threshold, such as simple judgment according to material thickness or pressure range, lacking systematic hierarchical division and conflict processing mechanism. Such traditional method exposes many problems in practical application. First of all, in the case of multiple rules in parallel, the priority is not clear, which leads to the difficulty in efficiently resolving the conflict of process parameters, and further affects the process stability and consistency. Secondly, it is difficult to optimize the coordination between safety and quality requirements, which may cause material damage or substandard product quality due to improper process parameter setting, and it is difficult to meet the demand of modern industry for high precision and high reliability. In addition, the existing technology often lacks simulation verification and standardized output mechanism after adjusting the process parameters, resulting in poor process stability, low equipment compatibility, increasing the debugging cost and processing risk. In view of the above defects, it is urgent to develop a process parameter adjustment method which can hierarchically coordinate rules, intelligently resolve conflicts and guarantee reliable output, so as to realize the overall consideration of safety, quality and process optimization, and improve the efficiency and precision of process parameter adjustment, and provide a more scientific and efficient solution for hot assisted flow drilling and riveting process. SUMMARY

[0003] The present application provides a plate connection parameter dynamic adjustment method based on multi-level rule judgment, which realizes intelligent dynamic adjustment of process parameters by constructing hierarchical rule system, conflict resolution strategy and parameter verification mechanism, aiming at the problems of low conflict processing efficiency, difficult to balance safety and quality, and insufficient process stability in the existing hot assisted flow drilling and riveting process.

[0004] The present application provides a plate connection parameter dynamic adjustment method based on multi-level rule judgment, which includes the following steps:

[0005] S1. Construct a three-level rule judgment system, including material safety layer, quality guarantee layer and process optimization layer, and set the hierarchical priority order as: material safety layer > quality guarantee layer > process optimization layer;

[0006] S2. Based on the material characteristics set obtained by finite element numerical simulation as process parameter input, execute rule judgment in turn according to the hierarchical priority order:

[0007] In the material safety layer, the safety of the process parameters is determined based on a material characteristic rule set, and if a safety threshold is triggered, a correction is performed in priority;

[0008] In the quality assurance layer, the process parameters are compensated and adjusted based on a structure parameter rule set, and if there are multiple rule conflicts, a weighted summation strategy within the layer is used to resolve them;

[0009] In the process optimization layer, the process parameters are optimized based on a process requirement rule set, and if there are cross-layer rule conflicts, a strategy of high-level rules overriding low-level rules is used to handle them;

[0010] S3. Real-time calculation of material stress field distribution and thermal deformation data adjustment safety threshold, including:

[0011] The safety boundary of the heating temperature is reviewed, and if it exceeds the preset fluctuation range, it is corrected to the boundary value;

[0012] Based on the adjusted pressure parameters, a pressure stress field simulation is performed, and if the simulation result exceeds the material strength threshold, a pressure adjustment instruction is generated;

[0013] The time parameter is normalized and quantized, and rounded to the set precision unit;

[0014] S4. Retrieve the multi-level rule tree corresponding to the material type, the root node and each intermediate node in the multi-level rule tree correspond to an initial material attribute and a parameter adjustment rule, and each leaf node of the multi-level rule tree corresponds to a threshold. From the leaf node to the root node of the multi-level rule tree, iterative operation is performed to obtain the final process parameters of the material and perform systematic verification;

[0015] S5. The verified process parameters are generated into a device control instruction set in a standard format and output to the execution end.

[0016] Further preferably, the material characteristic set is obtained by finite element numerical simulation, including but not limited to thermal conductivity, strength, thickness, and visual diameter, etc.

[0017] Further preferably, the parameter adjustment rules stored in the multi-level rule tree, i.e. the rule set used by each layer of the three-level rule determination system, include: material characteristic rule set, including thermal conductivity compensation rule and strength suppression rule;

[0018] Structure parameter rule set, including thickness-time mapping and diameter-pressure matching;

[0019] Process requirement rule set, including quality level compensation and precision adjustment rule.

[0020] Further preferably, the safety determination of the material safety layer includes:

[0021] Detecting whether the thickness and diameter of the material exceeds the preset threshold, if it exceeds, triggering time compensation or locking operation;

[0022] Calling the safety parameters in the material property set, executing the decision results with higher priority than other levels.

[0023] Further preferably, the compensation adjustment of the quality assurance layer includes:

[0024] According to the quality multi-level matching compensation parameters, the time parameters are weighted and corrected;

[0025] When there are multiple compensation rules conflicts, the compensation values are summed according to the preset weight.

[0026] Further preferably, the optimization determination of the process optimization layer includes:

[0027] According to the accuracy level requirements, the pressure parameters are dynamically adjusted;

[0028] When the process parameters do not meet the optimization rules, the process parameter re-optimization process is triggered.

[0029] Further preferably, in S4, the current material properties are matched with the leaf nodes of the multi-level rule tree, and the parameter data corresponding to each leaf node is obtained. In particular, the matching process adopts a recursive layer-by-layer manner, ensuring that the parameter data of each leaf node is accurately extracted and recorded.

[0030] Further preferably, the iterative operation is performed from the leaf nodes to the root nodes of the multi-level rule tree, including:

[0031] First, the process parameters are extracted layer by layer from the leaf nodes upwards; second, the extracted process parameters are corrected in combination with the parameter adjustment rules of each intermediate node; finally, the corrected process parameters are transmitted to the root node to generate the final process parameters; the rule set includes but is not limited to the material property rule set, the structure parameter rule set and the process requirement rule set, and the rule sets are connected through explicit logical relationships, ensuring the systematicness and consistency of the process parameter adjustment.

[0032] Further preferably, the systematic verification includes:

[0033] Temperature safety boundary review: correcting the heating temperature to within the preset fluctuation range, the preset fluctuation range is ±15% of the initial set value;

[0034] Pressure stress field simulation: calling the finite element analysis module to simulate the pressure stress field distribution, if the equivalent stress exceeds the set proportion of the material yield strength, a pressure adjustment instruction is generated, the pressure adjustment instruction includes a hierarchical adjustment strategy, and the adjustment amplitude of each level is ±5% of the initial pressure value until the equivalent stress meets the requirements;

[0035] Time parameter normalization and quantization: The calculated time parameters are rounded to the nearest integer and then normalized and quantized using a rounding algorithm.

[0036] The generation of the equipment control instruction set conforms to the ISO 6983 standard format, wherein the accuracy of temperature parameters is 1°C, the accuracy of pressure parameters is 0.1 MPa, and the accuracy of time parameters is 0.5 seconds.

[0037] The beneficial effects of this invention are as follows: Through a multi-level rule tree dynamic matching technology, the method achieves comprehensive evaluation of material properties and precise adjustment of process parameters. Furthermore, the three-level rule judgment system clarifies the priority of each level, prioritizing processing safety while coordinating quality and process optimization needs, significantly improving the scientific rigor and rationality of process parameter adjustments. In particular, the dual conflict resolution strategy effectively solves the conflict problem when multiple rules are used in parallel through weighted summation within each level and cross-level coverage mechanisms, improving the efficiency of process parameter adjustments. In addition, through pressure stress field simulation and thermal deformation data analysis, combined with a quantitative verification mechanism, the reliability of process parameters and process stability are enhanced. Finally, the standardized instruction output module generates equipment control instruction sets based on the ISO6983 standard, improving equipment compatibility and reducing debugging costs.

[0038] In summary, the present invention achieves intelligent dynamic adjustment of thermally assisted flow drilling and riveting process parameters through the above technical solutions, significantly improving processing safety, quality and process stability, and providing important technical support for related fields. Attached Figure Description

[0039] Figure 1 This is a flowchart of the present invention.

[0040] Figure 2 Diagram of module composition;

[0041] Figure 3 For each level of rule set;

[0042] Figure 4 This is a flowchart for hierarchical determination and conflict handling;

[0043] Figure 5 This is a flowchart for the systematic verification process. Detailed Implementation

[0044] The invention will now be explained in further detail with reference to the accompanying drawings.

[0045] like Figure 1 As shown, a method for dynamically adjusting sheet metal connection parameters based on multi-level rule determination includes the following steps:

[0046] S1. Construct a three-level rule-based judgment system, including a material safety layer, a quality assurance layer, and a process optimization layer, and set the priority order of the levels as: material safety layer > quality assurance layer > process optimization layer;

[0047] S2. The material property set obtained from finite element numerical simulation is used as the process parameter input, and the rule judgment is executed sequentially according to the aforementioned hierarchical priority order:

[0048] In the material safety layer, the safety of process parameters is determined based on the set of material property rules. If a safety threshold is triggered, the correction is performed first.

[0049] In the quality assurance layer, process parameters are compensated and adjusted based on the set of structural parameter rules. If there are multiple rule conflicts, a weighted summation strategy within the layer is used to resolve them.

[0050] In the process optimization layer, process parameters are optimized based on the process requirement rule set. If there is a cross-level rule conflict, the strategy of higher-level rules covering lower-level rules is adopted.

[0051] S3. Real-time calculation of material stress field distribution and thermal deformation data to adjust safety thresholds, including:

[0052] The heating temperature is checked for safety boundaries, and if it exceeds the preset fluctuation range, it is corrected to the boundary value.

[0053] Based on the adjusted pressure parameters, a pressure stress field simulation is performed. If the simulation result exceeds the material strength threshold, a pressure adjustment command is generated.

[0054] The time parameters are standardized and quantized, and rounded to the nearest integer according to the set precision unit.

[0055] S4. Retrieve the multi-level rule tree corresponding to the material type. The root node and each intermediate node in the multi-level rule tree correspond to an initial material property and a parameter adjustment rule. Each leaf node in the multi-level rule tree corresponds to a threshold. Perform iterative calculations from the leaf nodes to the root node of the multi-level rule tree to obtain the final process parameters of the material and perform systematic verification.

[0056] S5. Generate a set of equipment control instructions from the verified process parameters in a standard format and output it to the execution end.

[0057] In practical applications, operators first input initial parameters such as material type and target quality grade through the process parameter input panel. The system then calls upon safety thresholds and compensation rules from the material rule database based on these inputs. For example... Figure 2As shown, in the input area, a set of material properties, including but not limited to thermal conductivity, strength, thickness, and visual diameter, is obtained through finite element numerical simulation. Thermal conductivity and strength are obtained through a material detection unit, and thickness and visual diameter are obtained through a geometric measurement unit. This data is then transmitted to a tree-like rule database. The processing area includes a tree-like rule database and a conflict resolution processor. The tree-like rule database comprises a rule storage module and a logic execution module. It stores a multi-level rule tree structure, where the root node and each intermediate node correspond to an initial material property and a parameter adjustment rule, and the leaf nodes correspond to an initial threshold. The matching process of the multi-level rule tree adopts a layer-by-layer recursive approach, ensuring that the parameter data of each leaf node is accurately extracted and recorded. For example, for a specific material with a thickness of 5 mm and a diameter of 10 mm, the system will automatically retrieve the corresponding rule set from the tree-like rule database, match these rules with the current material processing properties, obtain the final process parameters, and output the execution command.

[0058] The conflict resolution processor plays a crucial role throughout the parameter tuning process. It resolves conflicts arising from multiple rules operating in parallel through intra-level weighted summation and cross-level coverage mechanisms. For example, in a scenario where the material safety layer requires reducing pressure parameters to ensure safety, while the process optimization layer requires increasing pressure parameters to improve accuracy, the conflict resolution processor prioritizes the material safety layer's rules to ensure processing safety. Furthermore, the conflict resolution processor supports dynamic threshold calculation and iterative optimization of compensation coefficients, further enhancing the flexibility and scientific rigor of parameter tuning. Figure 2 As shown, the output area includes a parameter instruction generator and a security verification module. The parameter instruction generator is used to generate a set of device control instructions, and the security verification module performs systematic verification.

[0059] The multi-level rule tree stores parameter adjustment rules, which are the rule sets used at each level of the three-level rule determination system, such as... Figure 3 As shown, it specifically includes: a set of material property rules, including thermal conductivity compensation rules and strength suppression rules;

[0060] Structural parameter rule set, including thickness-time mapping and diameter-pressure matching;

[0061] The process requirement rule set includes quality level compensation and precision adjustment rules.

[0062] For example, if the material thickness exceeds a preset threshold of 8 mm, a time compensation operation is triggered; if the diameter exceeds the safe range of 15 mm, the equipment operation is locked. The equipment locking operation is controlled by the logic execution module, ensuring that equipment operation is stopped under unsafe conditions to protect the safety of operators and equipment. Next, the system enters the quality assurance layer. This layer uses a weighted summation strategy based on the structural parameter rule set to resolve multiple rule conflicts, ensuring a dynamic balance between time parameters and quality requirements. The weighted summation strategy assigns preset weights to different rules and calculates their comprehensive impact value to determine the final direction of process parameter adjustment. For example, in a scenario where two conflicting rules exist simultaneously: rule A requires an increase in heating time of 2 seconds, and rule B requires a decrease in heating time of 1 second, the system will calculate the comprehensive adjustment value based on the weights of rule A and rule B, which are 0.6 and 0.4 respectively, ultimately determining an increase in heating time of 0.8 seconds. Finally, in the process optimization layer, the system adjusts the pressure parameters according to the process requirement rule set. If there is a conflict with a lower-level rule, the higher-level rule will override it, thus ensuring the overall optimization effect of the process parameters. For example, when the process optimization layer requires increasing pressure parameters to improve accuracy, if this operation conflicts with the constraints of the material safety layer, the system will prioritize the rules of the material safety layer to ensure processing safety.

[0063] like Figure 4 As shown, the process parameter adjustment procedure includes:

[0064] The first step is to determine the material safety layer. If the material's thermal conductivity is less than the material's thermal conductivity threshold K0, temperature compensation + ΔT1 is applied, where ΔT1 is the temperature compensation value; otherwise, the process is skipped. If the material's thermal conductivity is greater than or equal to the material's thermal conductivity threshold K0, temperature compensation is skipped, and it is determined whether the temperature increase / decrease rule is triggered simultaneously. If the temperature increase / decrease rule is triggered simultaneously, the priority comparator is activated, and the higher-level compensation rule is executed; otherwise, the process proceeds to the quality assurance layer determination.

[0065] In the quality assurance layer determination, there are two branches: diameter determination and thickness determination.

[0066] In the thickness determination branch, when the riveting thickness is greater than the thickness threshold... At the same time, time compensation + Δt1 is also performed, where Δt1 is the first time compensation value; if the riveting thickness is less than or equal to Then determine whether there is a rule conflict;

[0067] In the diameter determination branch, if the rivet diameter is greater than the diameter threshold D0, execute time compensation + Δt1, where Δt2 is the second time compensation value; then determine whether there is a rule conflict.

[0068] If there is a rule conflict, the compensation values ​​are weighted and summed, Δt = W1Δt1 + W2Δt2; Δt is the weighted time compensation value, W1 is the weight of the first time compensation value, and W2 is the weight of the second time compensation value. If there is no rule conflict, the process optimization layer is entered for judgment.

[0069] The process optimization layer determination includes accuracy level branches and quality level branches.

[0070] In the quality level branch, if the quality level Q is greater than the quality level threshold Q0, pressure compensation + ΔP1 is performed, where ΔP1 is the first pressure compensation value. If the quality level Q is less than or equal to the quality level threshold Q0, the process proceeds to the accuracy level branch, where it is determined whether the pressure adjustment exceeds the limit. In the accuracy level branch, if the accuracy level A is greater than the accuracy level threshold... The process involves applying pressure compensation plus ΔP2, where ΔP2 is the second pressure compensation value; otherwise, it checks if the pressure adjustment exceeds the limit. If the pressure adjustment exceeds the limit, the parameters are rolled back to a safe value; if the pressure adjustment does not exceed the limit, the judgment process is completed, and an optimized process parameter set is output, thereby achieving precise adjustment and optimization of process parameters. Figure 3 As shown, the rule set of an intermediate node in a certain layer includes thickness-time mapping rules and diameter-pressure matching rules. The system corrects the extracted process parameters based on these rules. The corrected process parameters are passed to the root node through the logic execution module, ultimately generating a complete set of process parameters including temperature, pressure, and time parameters. It should be noted that the rule set includes, but is not limited to, material property sets, structural parameter rule sets, and process requirement rule sets. These rule sets are connected by explicit logical relationships to ensure the systematic nature and consistency of process parameter adjustments.

[0071] The generated final process parameters must undergo rigorous verification to ensure they meet the requirements of industrial equipment and processing needs. For example... Figure 5 As shown, the parameter verification process includes three main steps: temperature safety boundary review, pressure stress field simulation, and time parameter standardization and quantification.

[0072] Temperature safety boundary review: The system corrects the heating temperature to a preset fluctuation range, which is ±15% of the initial setting. For example, if the initial setting temperature is 200℃, the allowable fluctuation range is 170℃ to 230℃. If the temperature parameter is detected to exceed this range, it is automatically corrected to the boundary value. The correction process is implemented using a linear interpolation algorithm to ensure the smoothness of temperature parameter adjustment.

[0073] Pressure stress field simulation: The system calls the finite element analysis module to simulate the pressure stress field distribution. If the equivalent stress exceeds a set proportion of the material's yield strength (e.g., 80%), a pressure adjustment command is generated. For example, if the yield strength of a material is 500 MPa, and the system detects that the maximum equivalent stress reaches 420 MPa, a pressure graded adjustment command is generated. The pressure adjustment command includes a graded adjustment strategy, with each adjustment increment being ±5% of the initial pressure value, until the equivalent stress meets the requirements.

[0074] Time parameter normalization and quantization: The calculated time parameters are normalized and quantized by rounding to the nearest whole number (e.g., 0.5 seconds) using a rounding algorithm to ensure the accuracy and executability of the time parameters. For example, if the calculated heating time is 12.3 seconds, the system will quantize it as 12.5 seconds.

[0075] Finally, the verified process parameters are used to generate an equipment control instruction set through the ISO 6983 standard instruction generation module, ensuring that the accuracy of temperature, pressure, and time parameters meets the requirements of industrial equipment. Specifically, the accuracy of the temperature parameter is 1°C, the pressure parameter is 0.1 MPa, and the time parameter is 0.5 seconds.

[0076] This invention achieves intelligent dynamic adjustment of process parameters for heat-assisted flow drilling and riveting through the aforementioned technical solution, significantly improving processing safety, quality, and process stability. In practical applications, such as in the automotive manufacturing industry, a company uses this method to perform heat-assisted flow drilling and riveting on aluminum alloy sheets. Operators input the material type as aluminum alloy and the target quality level as high through the process parameter input panel. The system then calls the finite element numerical simulation module to obtain the material property set and generates preliminary process parameters by matching a multi-level rule tree through a tree-like rule database. Subsequently, the system sequentially executes material safety layer determination, quality assurance layer compensation adjustment, and process optimization layer parameter optimization, ultimately generating a complete set of process parameters including a temperature of 220℃, a pressure of 450MPa, and a time of 15 seconds. The parameter verification module rigorously reviews the generated process parameters to ensure they meet industrial equipment requirements and generates a set of equipment control instructions through the ISO6983 standard instruction generation module, which is then transmitted to the connected equipment for execution. Actual processing results show that using this method significantly improves processing safety, achieves a finished product qualification rate of over 99%, significantly enhances process stability, and substantially reduces debugging costs.

[0077] In summary, this invention achieves comprehensive evaluation of material properties and precise adjustment of process parameters through a multi-level rule tree dynamic matching technology. The three-level rule judgment system clearly defines the priority of each level, prioritizing processing safety while coordinating quality and process optimization needs, significantly improving the scientific rigor and rationality of process parameter adjustments. The dual conflict resolution strategy effectively solves the conflict problem when multiple rules are used in parallel through weighted summation within each level and cross-level coverage mechanisms, improving the efficiency of process parameter adjustment. The reliability of process parameters and process stability are enhanced by combining pressure stress field simulation and thermal deformation data analysis with a quantitative verification mechanism. The standardized instruction output module generates equipment control instruction sets based on the ISO 6983 standard, improving equipment compatibility and reducing debugging costs. This invention provides important technical support for related fields and has broad application prospects and promotional value.

Claims

1. A method for dynamically adjusting sheet metal connection parameters based on multi-level rule determination, characterized in that, Includes the following steps: S1. Construct a three-level rule-based judgment system, including a material safety layer, a quality assurance layer, and a process optimization layer, and set the priority order of the levels as: material safety layer > quality assurance layer > process optimization layer; S2. The material property set obtained from finite element numerical simulation is used as the process parameter input, and the rule judgment is executed sequentially according to the aforementioned hierarchical priority order: In the material safety layer, the safety of process parameters is determined based on the set of material property rules. If a safety threshold is triggered, the correction is performed first. In the quality assurance layer, process parameters are compensated and adjusted based on the set of structural parameter rules. If there are multiple rule conflicts, a weighted summation strategy within the layer is used to resolve them. In the process optimization layer, process parameters are optimized based on the process requirement rule set. If there is a cross-level rule conflict, the strategy of higher-level rules covering lower-level rules is adopted. S3. Real-time calculation of material stress field distribution and thermal deformation data to adjust safety thresholds, including: The heating temperature is checked for safety boundaries, and if it exceeds the preset fluctuation range, it is corrected to the boundary value. Based on the adjusted pressure parameters, a pressure stress field simulation is performed. If the simulation result exceeds the material strength threshold, a pressure adjustment command is generated. The time parameters are standardized and quantized, and rounded to the nearest integer according to the set precision unit. S4. Retrieve the multi-level rule tree corresponding to the material type. The root node and each intermediate node in the multi-level rule tree correspond to an initial material property and a parameter adjustment rule. Each leaf node in the multi-level rule tree corresponds to a threshold. Perform iterative calculations from the leaf nodes to the root node of the multi-level rule tree to obtain the final process parameters of the material and perform systematic verification. S5. Generate a set of equipment control instructions from the verified process parameters in a standard format and output it to the execution end.

2. The method for dynamically adjusting sheet metal connection parameters according to claim 1, characterized in that, The material property set is obtained through finite element numerical simulation, and the material property set includes, but is not limited to, thermal conductivity, strength, thickness, and visual diameter.

3. The method for dynamically adjusting sheet metal connection parameters according to claim 1, characterized in that, The multi-level rule tree stores parameter adjustment rules, which are the rule sets used at each level of the three-level rule decision system, including: Material property rule set, including thermal conductivity compensation rule and strength suppression rule; Structural parameter rule set, including thickness-time mapping and diameter-pressure matching; The process requirement rule set includes quality level compensation and precision adjustment rules.

4. The method for dynamically adjusting sheet metal connection parameters according to claim 1, characterized in that, The safety assessment of the material safety layer includes: The system detects whether the material thickness and diameter exceed preset thresholds. If they do, it triggers a time compensation or locking operation. The safety parameters in the material property set are invoked, and the judgment results are executed with higher priority than those at other levels.

5. The method for dynamically adjusting sheet metal connection parameters according to claim 1, characterized in that, The compensation adjustment of the quality assurance layer includes: The time parameters are weighted and corrected based on the multi-level quality matching compensation parameters; When multiple compensation rules conflict, the compensation values ​​are summed according to preset weights.

6. The method for dynamically adjusting sheet metal connection parameters according to claim 1, characterized in that, The optimization determination of the process optimization layer includes: The pressure parameters are dynamically adjusted according to the accuracy level requirements; When the process parameters do not meet the optimization rules, the process parameter re-optimization process is triggered.

7. The method for dynamically adjusting sheet metal connection parameters according to claim 1, characterized in that, In S4, the current material properties are matched with the leaf nodes of the multi-level rule tree to obtain the parameter data corresponding to each leaf node. The matching process adopts a recursive approach to ensure that the parameter data of each leaf node is accurately extracted and recorded.

8. The method for dynamically adjusting sheet metal connection parameters according to claim 1, characterized in that, Iterative calculations are performed from the leaf nodes to the root node of the multi-level rule tree, including: First, process parameters are extracted layer by layer from the leaf nodes upwards. Second, the extracted process parameters are corrected by combining the parameter adjustment rules of each intermediate node. Finally, the corrected process parameters are passed to the root node to generate the final process parameters. The rule set includes, but is not limited to, material property rule set, structural parameter rule set, and process requirement rule set. The rule sets are connected by clear logical relationships to ensure the systematicness and consistency of process parameter adjustment.

9. The method for dynamically adjusting sheet metal connection parameters according to claim 1, characterized in that, The systematic verification includes: Temperature safety boundary review: Correct the heating temperature to a preset fluctuation range, which is ±15% of the initial setting value; Pressure stress field simulation: The finite element analysis module is called to simulate the distribution of pressure stress field. If the equivalent stress exceeds the set ratio of the material yield strength, a pressure adjustment command is generated. The pressure adjustment command includes a graded adjustment strategy, with each adjustment range being ±5% of the initial pressure value, until the equivalent stress meets the requirements. Time parameter normalization and quantization: The calculated time parameters are rounded to the nearest integer and then normalized and quantized using a rounding algorithm.

10. The method for dynamically adjusting sheet metal connection parameters according to claim 1, characterized in that, The generation of the equipment control instruction set conforms to the ISO 6983 standard format, wherein the accuracy of temperature parameters is 1°C, the accuracy of pressure parameters is 0.1 MPa, and the accuracy of time parameters is 0.5 seconds.

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