Adaptive adjustment method and system for process parameters of resistance spot welding of aluminum alloy

Abstract

The application provides an aluminum alloy resistance spot welding process parameter self-adaptive adjusting method and system, and relates to the technical field of welding control. The method comprises collecting working condition information, process monitoring signals and post-welding quality information; a parameter space model is constructed, the spot welding process is divided into four stages of spot welding, and process parameters are set for the four stages of spot welding based on the working condition information; a dynamic resistance curve is calculated based on the process monitoring signals, and the process parameters are adjusted to generate first process parameters; the type of spot welding defects is identified based on the process monitoring signals and the post-welding quality information, if the quality of the spot welding is determined to be unqualified according to the type of the spot welding defects, then the first process parameters are adjusted through correction rules to generate second process parameters, so that the real-time response of the welding process and the closed-loop optimization of the post-welding quality feedback can be realized, the process window is widened, the defects are effectively inhibited, the stability and consistency of the spot welding quality are significantly improved, and the method can be self-adaptive to variable materials and working conditions.

Description

Technical Field

[0001] This invention relates to the field of welding control technology, and in particular to an adaptive adjustment method and system for resistance spot welding process parameters of aluminum alloys. Background Technology

[0002] Aluminum alloys are increasingly widely used in the automotive, aerospace, and rail transportation industries due to their low density, high specific strength, and excellent corrosion resistance.

[0003] However, compared with traditional steel, aluminum alloys present the following challenges in spot welding: their surface has a dense oxide film with high and unstable resistivity; they have high thermal and electrical conductivity, requiring a larger current to form a weld nugget; they soften easily at high temperatures, leading to defects such as spatter and cracks; and their welding quality is extremely sensitive to process parameters, making it difficult to directly apply welding specifications from traditional steel. Currently, the industry often uses constant current control, stepped current, and extended pre-pressure holding stages to improve weld quality, but these methods generally suffer from narrow process windows, large fluctuations in yield, a lack of real-time response to changes in dynamic contact resistance, and failure to consider the coupled effects of aluminum alloy grade, plate thickness combination, and surface condition.

[0004] Therefore, it is necessary to provide an adaptive adjustment method and system for the resistance spot welding process parameters of aluminum alloys to solve the above-mentioned technical problems. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides an adaptive adjustment method and system for resistance spot welding process parameters of aluminum alloys. This system solves the problem that existing aluminum alloy resistance spot welding processes lack the ability to adaptively adjust parameters based on real-time welding process status and weld quality feedback, resulting in a narrow process window, high defect rate, and difficulty in adapting to varying material and working conditions.

[0006] This invention provides an adaptive adjustment method for resistance spot welding process parameters of aluminum alloys, the method comprising: Collect welding condition information, process monitoring signals, and post-weld quality results information during the resistance spot welding process of aluminum alloys; A four-dimensional parameter space model is constructed to divide the aluminum alloy resistance spot welding process into four stages of resistance spot welding. Based on the welding condition information, resistance spot welding process parameters are set for the four stages of resistance spot welding respectively. Based on the process monitoring signal, the instantaneous contact resistance is calculated and a dynamic resistance curve is generated. The resistance spot welding process parameters are adaptively adjusted according to the dynamic resistance curve to generate the first process adjustment parameters. Based on the process monitoring signal and the post-weld quality result information, the weld joint defect type is identified and generated. If the weld joint quality is determined to be unqualified according to the weld joint defect type, the first process adjustment parameter is adaptively adjusted according to the preset defect-parameter correction rule to generate the second process adjustment parameter.

[0007] Preferably, the construction of the four-dimensional parameter space model divides the aluminum alloy resistance spot welding process into four stages, and sets resistance spot welding process parameters for each of the four stages based on the welding condition information, specifically including: The resistance spot welding process consists of four stages: pre-pressure stage, main welding stage, holding stage, and return stage. Based on the total thickness of the workpiece being welded in the welding condition information The material type coefficient M is used to set the resistance spot welding process parameters for the pre-pressing stage, the main welding stage, the holding stage, and the return stage, respectively. For the pre-compression stage, the pre-compression electrode force is set. and pre-compression time ,in, Indicates the pressure reference coefficient; Indicates the reference thickness of the workpiece to be welded; This represents the preload time minus the thickness coefficient. For the main welding stage, the welding current of the i-th pulse is set. and welding time in, This represents the reference coefficient for the i-th pulse current; This represents the time reference coefficient for the i-th pulse; This represents the time base offset of the i-th pulse; N represents the number of pulses. For the maintenance phase, a maintenance electrode force is set. and duration ,in, This represents the pressure proportionality coefficient. ; Indicates duration versus thickness coefficient; For the return phase, the electrode return time is set. ,in, Indicates the electrode return speed; This indicates the electrode return stroke.

[0008] Preferably, the step of calculating the instantaneous contact resistance based on the process monitoring signal and generating a dynamic resistance curve, and adaptively adjusting the resistance spot welding process parameters according to the dynamic resistance curve to generate a first process adjustment parameter, specifically includes: Based on the main welding stage current signal and main welding stage voltage signal in the process monitoring signal, the instantaneous contact resistance is calculated according to Ohm's law, and the dynamic resistance curve is generated based on the change of the instantaneous contact resistance over time. The rate of decrease in resistance of the dynamic resistance curve is extracted by differential calculation, the peak resistance value of the dynamic resistance curve is extracted by peak detection algorithm, and the plateau resistance value of the dynamic resistance curve is extracted by mean filtering algorithm. The pulse of the main welding stage in the four stages of resistance spot welding is adaptively adjusted based on the resistance drop rate, the peak resistance value, and the plateau resistance value to generate the first process adjustment parameters.

[0009] Preferably, the step of adaptively adjusting the pulse of the main welding stage in the four stages of resistance spot welding based on the resistance decrease rate, the peak resistance value, and the plateau resistance value to generate the first process adjustment parameters specifically includes: Based on the welding condition information, the spatter suppression coefficient is obtained from a preset process parameter database. Energy compensation coefficient and stability adjustment coefficient Extract the resistance decrease rate of the current i-th pulse. Peak resistance And calculate the standard deviation of the plateau resistance value of the current i-th pulse as the fluctuation amount. ; If the resistance decrease rate of the i-th pulse Greater than the preset splash risk threshold Then adjust the first Pulse welding current ,in, ; If the resistance peak value of the i-th pulse Less than the preset energy shortage threshold And the rate of decrease in resistance of the i-th pulse Less than the preset splash risk threshold Then adjust the first Pulse welding current ; If the fluctuation of the plateau resistance value of the i-th pulse greater than the plateau period fluctuation threshold Then adjust the first Welding time of a single pulse ; If none of the above conditions are met, then the first... Pulse welding current and welding time Adjustments were made.

[0010] Preferably, the step of identifying and generating weld defect types based on the process monitoring signals and the post-weld quality result information specifically includes: The process monitoring signals are processed and feature extracted to generate current signal features, voltage signal features, and electrode displacement signal features; The current signal features, voltage signal features, and electrode displacement signal features are input into a preset typical feature model of weld joint defects, and a preliminary weld joint defect type is generated through feature matching and identification. Obtain the weld nugget geometric parameters, peel shear force values, and weld appearance inspection results from the post-weld quality results information; The geometric parameters of the weld nugget, the peeling shear force value, and the weld joint appearance inspection results are matched with a preset typical quality feature library of weld joint defects. Based on the feature matching results, the preliminary weld joint defect type is verified and corrected to generate the weld joint defect type.

[0011] Preferably, if the weld joint quality is determined to be unqualified based on the weld joint defect type, the first process adjustment parameter is adaptively adjusted using a preset defect-parameter correction rule to generate a second process adjustment parameter, specifically including: Based on a preset database of typical quality features of weld joint defects, the target weld joint defect type corresponding to the weld joint quality being unqualified is determined. The target weld joint defect type includes at least cold solder joint, spatter, adhesion, and crack. The defect-parameter correction rule is matched according to the target weld defect type, and combined with the total thickness of the workpiece to be welded in the welding condition information. The material type coefficient M is used to make targeted corrections to the first process adjustment parameters corresponding to the defect type of the target weld point; When the defect type of the target weld point is a cold weld, the welding current of the i-th pulse in the main welding stage of the four stages of resistance spot welding is... A positive correction is performed, and the pre-pressure electrode force in the pre-pressure stage of the four stages of resistance spot welding is corrected simultaneously. The corresponding correction formula is as follows: In the formula, This represents the corrected welding current reference value for the i-th pulse; This indicates the corrected preload electrode force reference value; Indicates the standard minimum melt core diameter; Indicates the actual measured diameter of the melt core; This represents the preset correction factor for the cold solder joint current; This represents the preset correction coefficient for poor soldering pressure; When the target weld defect type is spatter, the welding current of the i-th pulse in the main welding stage of the four-stage resistance spot welding is... and welding time A negative correction is performed, and the corresponding correction formula is as follows: In the formula, This represents the welding time reference value for the i-th pulse after correction; Indicates the actual splash area; Indicates the standard maximum splash area; This indicates the preset splash current attenuation coefficient; This indicates the preset splash time decay coefficient.

[0012] Preferred options also include: When the defect type of the target weld joint is adhesion, the holding electrode force and holding time in the holding stage of the four stages of resistance spot welding are negatively corrected. The corresponding correction formula is as follows: In the formula, This indicates the revised baseline value for the maintenance time; This indicates the corrected reference value for the sustaining electrode force; Indicates the actual adhesive tensile force; Indicates the standard maximum adhesive tensile force; This represents the preset adhesion time correction factor; This indicates the preset adhesion electrode force correction coefficient; When the target weld defect type is a crack, the welding current of the Nth pulse in the main welding stage of the four-stage resistance spot welding is... A positive correction is performed, and the holding electrode force in the holding stage of the four stages of resistance spot welding is corrected simultaneously. The corresponding correction formula is as follows: In the formula, This represents the corrected welding current reference value for the Nth pulse. Indicates the actual crack length; Indicates the standard maximum crack length; This represents the preset crack current correction factor; This represents the preset crack electrode force correction coefficient; The modified first process adjustment parameters are subjected to threshold boundary verification. After the verification is passed, the second process adjustment parameters are generated.

[0013] The modified first process adjustment parameters are subjected to threshold boundary verification. After the verification is passed, the second process adjustment parameters are generated.

[0014] An adaptive adjustment system for resistance spot welding process parameters of aluminum alloys, the system comprising: The information acquisition module is used to collect welding condition information, process monitoring signals and post-weld quality result information during the aluminum alloy resistance spot welding process. The parameter modeling module is used to construct a four-dimensional parameter space model, divide the aluminum alloy resistance spot welding process into four stages of resistance spot welding, and set resistance spot welding process parameters for the four stages of resistance spot welding based on the welding condition information. The resistance adjustment module is used to calculate the instantaneous contact resistance based on the process monitoring signal and generate a dynamic resistance curve, and to adaptively adjust the resistance spot welding process parameters according to the dynamic resistance curve to generate the first process adjustment parameters. The defect adjustment module is used to identify and generate weld joint defect types based on the process monitoring signals and the post-weld quality result information. If the weld joint quality is determined to be unqualified according to the weld joint defect type, the first process adjustment parameter is adaptively adjusted according to the preset defect-parameter correction rule to generate the second process adjustment parameter.

[0015] An electronic device includes a memory and a processor, wherein the memory stores a computer program, and when the processor runs the computer program stored in the memory, the processor executes the steps of the adaptive adjustment method for resistance spot welding process parameters of aluminum alloy as described in any of the above claims.

[0016] A readable storage medium storing a computer program, which, when executed by a processor, is used to implement the steps of an adaptive adjustment method for resistance spot welding process parameters of aluminum alloy as described in any of the preceding claims.

[0017] Compared with related technologies, the adaptive adjustment method and system for resistance spot welding process parameters of aluminum alloys provided by the present invention has the following beneficial effects: This invention collects welding condition information, process monitoring signals, and post-weld quality results information during the resistance spot welding process of aluminum alloys; constructs a four-dimensional parameter space model, dividing the aluminum alloy resistance spot welding process into four stages; sets resistance spot welding process parameters for each of the four stages based on the welding condition information; calculates the instantaneous contact resistance based on the process monitoring signals to generate a dynamic resistance curve; adaptively adjusts the resistance spot welding process parameters according to the dynamic resistance curve to generate the first process adjustment parameter; identifies and generates weld defect types based on the process monitoring signals and post-weld quality results information; if the weld quality is determined to be unqualified according to the weld defect type, the first process adjustment parameter is adaptively adjusted according to the preset defect-parameter correction rule to generate the second process adjustment parameter. This achieves closed-loop optimization of real-time response of the welding process and post-weld quality feedback, broadens the process window, effectively suppresses defects such as spatter and incomplete welding, significantly improves the stability and consistency of weld quality, and can adapt to varying aluminum alloy materials and working conditions.

[0018] This invention constructs a four-dimensional parametric space model to precisely divide the aluminum alloy resistance spot welding process into a pre-pressing stage, a main welding stage, a holding stage, and a return stage. Based on welding condition information, it independently sets resistance spot welding process parameters for each stage, achieving refined, staged control of the entire welding process. This effectively adapts to welding requirements with different material and thickness combinations, significantly broadening the process window. Furthermore, this invention calculates instantaneous contact resistance and generates a dynamic resistance curve by real-time acquisition of process monitoring signals. By extracting key features, it adaptively adjusts the welding current and welding time in the main welding stage, generating the first process adjustment parameters. This allows for real-time response to dynamic changes in the interface state during welding, thereby effectively improving the stability of the welding process. This invention integrates process monitoring signals and post-weld quality results information. Through feature matching, it accurately identifies weld defect types such as cold welds, spatter, adhesion, and cracks. For different weld defect types, it calls defect-parameter correction rules to make targeted corrections to the first process adjustment parameters and generate second process adjustment parameters. This achieves closed-loop optimization based on post-weld quality feedback. It can increase welding current and pre-pressure electrode force for cold welds, reduce welding current and welding time for spatter, shorten holding time and adjust holding electrode force for adhesion, and correct the final pulse welding current and holding electrode force for cracks, thereby effectively improving the pass rate and consistency of weld quality. Attached Figure Description

[0019] Figure 1 A flowchart illustrating an adaptive adjustment method for resistance spot welding process parameters of aluminum alloys, provided as an embodiment of the present invention; Figure 2 A system block diagram of an adaptive adjustment system for resistance spot welding process parameters of aluminum alloy provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] like Figure 1 The diagram shown is a flowchart of an adaptive adjustment method for resistance spot welding process parameters of aluminum alloys provided in an embodiment of the present invention. Figure 1 The execution entity of the method shown can be a software and / or hardware device. The execution entity of this application can include, but is not limited to, at least one of the following: user equipment, network equipment, etc. User equipment can include, but is not limited to, computers, smartphones, personal digital assistants (PDAs), and the aforementioned electronic devices. Network equipment can include, but is not limited to, a single network server, a server group consisting of multiple network servers, or a cloud based on cloud computing consisting of a large number of computers or network servers. Cloud computing is a type of distributed computing, consisting of a super virtual computer composed of a group of loosely coupled computers. This embodiment does not limit this. Steps S1 to S4 are detailed as follows: S1 collects welding condition information, process monitoring signals, and post-weld quality results information during the resistance spot welding process of aluminum alloys. The welding condition information consists of static parameters related to the workpiece and equipment determined before welding, specifically including the material information, geometric information, surface condition, and electrode geometric parameters of the workpiece. The process monitoring signals are dynamic physical quantities collected in real-time by sensors during the welding process, specifically including current signals, voltage signals, and electrode displacement signals during the main welding stage. The post-weld quality result information is the weld quality evaluation data obtained through inspection after welding, specifically including weld nugget geometric parameters, peel shear force values, and weld appearance inspection results.

[0022] Understandably, the use of a spherical radius design for the electrode end face in the electrode geometry parameters allows for a smooth, bell-shaped pressure distribution in the workpiece contact area, avoiding edge stress concentration. This enables more effective breaking of the oxide film on the aluminum alloy surface during the pre-pressing stage and maintains a uniform current and temperature field during the main welding stage, reducing the tendency for spatter caused by localized overheating. The selection of the electrode diameter in the electrode geometry parameters must match the total thickness and material properties of the workpiece being welded: when the plate thickness is large or the material strength is high, appropriately increasing the electrode diameter reduces the current density and prevents excessive weld nugget growth; when the plate thickness is thin or the material has extremely high thermal conductivity, selecting a smaller diameter helps to increase the current density and ensure reliable weld nugget formation.

[0023] S2, construct a four-dimensional parameter space model, divide the aluminum alloy resistance spot welding process into four stages of resistance spot welding, and set resistance spot welding process parameters for the four stages of resistance spot welding based on the welding condition information. The construction of the four-dimensional parameter space model divides the aluminum alloy resistance spot welding process into four stages. Based on the welding condition information, resistance spot welding process parameters are set for each of the four stages, specifically including: The resistance spot welding process consists of four stages: pre-pressure stage, main welding stage, holding stage, and return stage. Based on the total thickness of the workpiece being welded in the welding condition information The material type coefficient M is used to set the resistance spot welding process parameters for the pre-pressing stage, the main welding stage, the holding stage, and the return stage, respectively. For the pre-compression stage, the pre-compression electrode force is set. and pre-compression time ,in, Indicates the pressure reference coefficient; Indicates the reference thickness of the workpiece to be welded; This represents the preload time minus the thickness coefficient. For the main welding stage, the welding current of the i-th pulse is set. and welding time in, This represents the reference coefficient for the i-th pulse current; This represents the time reference coefficient for the i-th pulse; This represents the time base offset of the i-th pulse; N represents the number of pulses. For the maintenance phase, a maintenance electrode force is set. and duration ,in, This represents the pressure proportionality coefficient. ; Indicates duration versus thickness coefficient; For the return phase, the electrode return time is set. ,in, Indicates the electrode return speed; This indicates the electrode return stroke.

[0024] The four-dimensional parameter space model is a comprehensive parameter system adapted to the spot welding characteristics of aluminum alloys, constructed using the process parameters of the four stages of pre-pressing, main welding, holding, and return as control dimensions. It is used to achieve independent optimization and coordinated matching of parameters at each stage, accurately adapting to different welding conditions. The total thickness of the workpiece to be welded is the sum of the thicknesses of each layer. The material type coefficient is calibrated according to the aluminum alloy grade and heat treatment state, reflecting the differences in thermal conductivity, electrical conductivity, and mechanical properties of different materials, ensuring that the parameters are compatible with the material properties.

[0025] Next, the pressure reference coefficient is a basic parameter of the pre-compression electrode force determined based on numerous experiments. The reference thickness of the workpiece to be welded is a preset standard thickness reference. These two parameters, combined with the total thickness of the workpiece and the material type coefficient, ensure that the pre-compression electrode force accurately matches the workpiece requirements. The pre-compression time-thickness coefficient is used to ensure that the pre-compression time is dynamically adjusted according to the plate thickness to fully break down the oxide film.

[0026] Furthermore, the pulse current reference coefficient and pulse time reference coefficient are the basic parameters of current and time for each pulse, respectively. The time base offset is used to compensate for the differences in the base time of different pulses. The number of pulses is set according to the requirements of weld nugget preheating, expansion, and tempering to achieve multi-pulse fine temperature control. The pressure proportional coefficient is greater than or equal to 1 to ensure that the holding electrode force is not lower than the pre-pressure electrode force, effectively suppressing weld nugget shrinkage. The holding time-thickness coefficient is used to adapt the solidification time to the plate thickness. The electrode return speed is the rate at which the electrode retracts, and the electrode return stroke is the distance the electrode retracts. The two together determine the electrode retraction time to avoid electrode adhesion to the solder joint.

[0027] In practical applications, taking the double-layer lap welding of AA6016-T4 and AA5182-O as an example, the total thickness of the workpiece is 2.2mm, and the material type coefficient is 1.1. The pressure reference coefficient is set to 2.2kN, the reference thickness of the workpiece is 1mm, and the pre-pressure time-thickness coefficient is 150ms / mm. Based on this, the pre-pressure electrode force and pre-pressure time are set. The number of pulses in the main welding stage is 2. The first pulse has a current reference coefficient of 9kA, a pulse time reference coefficient of 30ms / mm, and a time base offset of 5ms. The second pulse has a current reference coefficient of 11kA, a pulse time reference coefficient of 40ms / mm, and a time base offset of 8ms, matching the preheating and expansion requirements of the weld nugget. The pressure proportional coefficient is 1.2, and the holding time-thickness coefficient is 80ms / mm to ensure the solidification quality of the weld nugget. The electrode return speed is 150mm / s, and the electrode return stroke is 10mm to achieve smooth electrode retraction. All coefficients have been calibrated through experiments, and the parameter settings are consistent with the actual welding conditions, ensuring welding quality.

[0028] S3, calculate the instantaneous contact resistance based on the process monitoring signal and generate a dynamic resistance curve, and adaptively adjust the resistance spot welding process parameters according to the dynamic resistance curve to generate the first process adjustment parameters. The step of calculating the instantaneous contact resistance based on the process monitoring signal and generating a dynamic resistance curve, and then adaptively adjusting the resistance spot welding process parameters according to the dynamic resistance curve to generate a first process adjustment parameter, specifically includes: Based on the main welding stage current signal and main welding stage voltage signal in the process monitoring signal, the instantaneous contact resistance is calculated according to Ohm's law, and the dynamic resistance curve is generated based on the change of the instantaneous contact resistance over time. The rate of decrease in resistance of the dynamic resistance curve is extracted by differential calculation, the peak resistance value of the dynamic resistance curve is extracted by peak detection algorithm, and the plateau resistance value of the dynamic resistance curve is extracted by mean filtering algorithm. The pulse of the main welding stage in the four stages of resistance spot welding is adaptively adjusted based on the resistance drop rate, the peak resistance value, and the plateau resistance value to generate the first process adjustment parameters.

[0029] Ohm's law is the fundamental physical principle for calculating resistance. This principle is used to convert the collected current and voltage signals from the main welding stage into instantaneous contact resistance. This instantaneous contact resistance includes key components such as the contact resistance between workpieces and the workpiece's own resistance, and its changes are directly related to the weld nugget formation process. The dynamic resistance curve, with time on the horizontal axis and instantaneous contact resistance on the vertical axis, fully presents the resistance variation throughout the entire welding process.

[0030] Specifically, differential calculations reflect the rate of temperature rise in the welding zone by calculating the rate of change of resistance over time. A peak detection algorithm captures the maximum resistance value in the dynamic resistance curve, corresponding to a critical node in the early stages of weld nugget formation. A mean filtering algorithm filters out fluctuations in the resistance value during the plateau phase, obtaining a stable plateau resistance value that reflects the state of the weld nugget during its stable expansion phase.

[0031] Understandably, the resistance drop rate reflects how quickly the resistance decays; too rapid a drop indicates a sudden rise in interface temperature, which can easily lead to spattering. The peak resistance value reflects the initial heat accumulation effect; too low a value indicates insufficient energy input. The plateau resistance value reflects the stability of the weld nugget expansion; excessive fluctuations can lead to uneven weld nugget development. The pulse in the main welding stage is an independent energy input unit in the multi-pulse welding mode. Adaptive adjustment is a closed-loop control method that adjusts pulse parameters in real time based on the aforementioned resistance characteristics. The final generated first process adjustment parameters are a combination of process parameters optimized in real time and adapted to the current welding conditions.

[0032] By using the above methods, the dynamic changes in resistance during aluminum alloy resistance spot welding are captured in real time, key characteristic parameters are accurately extracted, and the pulses in the main welding stage are adjusted adaptively to generate the first process adjustment parameters that are adapted to the current working conditions. This effectively avoids problems such as spatter, insufficient energy, and process fluctuations, and improves the stability of the welding process.

[0033] The step of adaptively adjusting the pulse of the main welding stage in the four stages of resistance spot welding based on the resistance drop rate, the peak resistance value, and the plateau resistance value to generate the first process adjustment parameters specifically includes: Based on the welding condition information, the spatter suppression coefficient is obtained from a preset process parameter database. Energy compensation coefficient and stability adjustment coefficient Extract the resistance decrease rate of the current i-th pulse. Peak resistance And calculate the standard deviation of the plateau resistance value of the current i-th pulse as the fluctuation amount. ; If the resistance decrease rate of the i-th pulse Greater than the preset splash risk threshold Then adjust the first Pulse welding current ,in, ; If the resistance peak value of the i-th pulse Less than the preset energy shortage threshold And the rate of decrease in resistance of the i-th pulse Less than the preset splash risk threshold Then adjust the first Pulse welding current ; If the fluctuation of the plateau resistance value of the i-th pulse greater than the plateau period fluctuation threshold Then adjust the first Welding time of a single pulse ; If none of the above conditions are met, then the first... Pulse welding current and welding time Adjustments were made.

[0034] The preset process parameter database is a dataset that pre-stores process coefficients and thresholds corresponding to different welding conditions. It includes spatter suppression coefficients, energy compensation coefficients, stability adjustment coefficients, spatter risk thresholds, energy deficiency thresholds, and plateau fluctuation thresholds suitable for various aluminum alloy grades, plate thickness combinations, and surface conditions. All data have been calibrated through extensive testing. The i-th pulse is any one of the multi-pulse sequences in the main welding stage, used to achieve precise temperature control in stages. The welding current is the current parameter of the pulse energy input in the main welding stage, and the welding time is the duration of energy action of each pulse; both together determine the total welding energy input. The first process adjustment parameter is a combination of pulse parameters for the main welding stage adapted to the current welding condition after feedback adjustment via the dynamic resistance curve.

[0035] Specifically, the spatter suppression coefficient is a current adjustment proportional constant used to suppress spatter defects; the energy compensation coefficient is a current adjustment proportional constant used to compensate for insufficient welding energy; and the stability adjustment coefficient is a time adjustment proportional constant used to improve the stability of the welding process, dynamically matched according to the welding conditions. The spatter risk threshold is a critical value for the rate of resistance decrease used to determine the presence of potential spatter hazards; exceeding this threshold indicates that the interface temperature rises too quickly, easily triggering spatter. The insufficient energy threshold is a critical value for the peak resistance value used to determine whether the welding energy is sufficient; falling below this threshold indicates insufficient energy required for weld nugget formation. The plateau period fluctuation threshold is a critical value for determining whether the resistance is stable during the plateau period; exceeding this threshold indicates poor welding process stability.

[0036] Understandably, the resistance decrease rate is the rate at which the resistance decays over time in the dynamic resistance curve, reflecting how quickly the temperature rises in the welding area. The resistance peak is the maximum resistance value in the dynamic resistance curve, corresponding to the heat accumulation effect in the early stages of weld nugget formation. The plateau resistance value is the resistance data in the dynamic resistance curve during the stable phase, and its standard deviation serves as the fluctuation, reflecting the stability of the resistance in this phase. The greater the fluctuation, the more unstable the welding process.

[0037] It should be noted that this invention follows the principle of "adjustment on demand." If the monitoring data of the current pulse does not trigger any adjustment threshold, it indicates that the welding process is normal. At this time, the welding current and welding time of the next pulse are not adjusted, which can avoid frequent erroneous adjustments caused by small fluctuations and ensure the continuity and stability of the welding process.

[0038] In practical applications, taking the double-layer lap welding of AA6016-T4 and AA5182-O as an example, the total thickness of the workpieces to be welded is 2.2mm, and the material type coefficient is 1.1. The spatter suppression coefficient (0.3), energy compensation coefficient (0.4), and stability adjustment coefficient (0.2) are obtained from the process parameter database. Simultaneously, the spatter risk threshold (0.8Ω / ms), energy deficiency threshold (3.5Ω), and plateau fluctuation threshold (0.2Ω) are extracted. The resistance drop rate of the first pulse is 1.0Ω / ms, the peak resistance is 3.2Ω, and the plateau resistance fluctuation is 0.3Ω. Because the resistance drop rate is greater than the spatter risk threshold, the peak resistance is lower than the energy deficiency threshold, and the fluctuation exceeds the limit, the welding current and welding time of the second pulse are adjusted. The above process, by reducing the welding current to suppress spatter and increasing the welding time to improve the stability of the weld nugget, fully demonstrates the real-time performance and precision of dynamic resistance feedback adjustment.

[0039] S4. Based on the process monitoring signal and the post-weld quality result information, identify and generate the weld joint defect type. If the weld joint quality is determined to be unqualified according to the weld joint defect type, then adaptively adjust the first process adjustment parameter through the preset defect-parameter correction rule to generate the second process adjustment parameter.

[0040] The process of identifying and generating weld joint defect types based on the process monitoring signals and the post-weld quality result information specifically includes: The process monitoring signals are processed and feature extracted to generate current signal features, voltage signal features, and electrode displacement signal features; The current signal features, voltage signal features, and electrode displacement signal features are input into a preset typical feature model of weld joint defects, and a preliminary weld joint defect type is generated through feature matching and identification. Obtain the weld nugget geometric parameters, peel shear force values, and weld appearance inspection results from the post-weld quality results information; The geometric parameters of the weld nugget, the peeling shear force value, and the weld joint appearance inspection results are matched with a preset typical quality feature library of weld joint defects. Based on the feature matching results, the preliminary weld joint defect type is verified and corrected to generate the weld joint defect type.

[0041] Signal processing and feature extraction involve filtering, denoising, and performing time-domain or frequency-domain analysis on the original process monitoring signals. The aim is to remove invalid noise and extract key information strongly correlated with weld quality. Current signal features are parameters extracted from the current signal during the main welding stage, including peak current, fluctuation amplitude, and duration. Voltage signal features are key indicators extracted from the voltage signal during the main welding stage, including peak voltage, stable voltage range, and voltage change rate. Electrode displacement signal features are feature parameters extracted from the electrode motion signal, including electrode displacement amount, motion rate, and displacement fluctuation during the stable phase. These three elements together constitute the process feature dimension for defect identification.

[0042] Next, the pre-defined typical feature model of weld joint defects is a database model built based on a large amount of aluminum alloy spot welding test data, which stores process signal defect feature templates corresponding to various defects such as incomplete welds, spatter, adhesion, and cracks. Feature matching is the process of comparing the extracted real-time process signal features with the defect feature templates in the typical feature model of weld joint defects. Based on the comparison results, the defect category is initially determined, forming a preliminary weld joint defect type.

[0043] Specifically, weld nugget geometry parameters reflect the weld nugget formation quality, including weld nugget diameter and thickness. Peel shear force values ​​are parameters of the weld joint's resistance to peeling and shearing, measured through mechanical testing, directly reflecting the weld joint's mechanical properties. Weld joint appearance inspection results are conclusions regarding the surface condition of the weld joint, including the presence of spatter, cracks, and adhesive residue.

[0044] Furthermore, the pre-defined typical quality feature library for weld joint defects is a database storing post-weld quality standard features corresponding to various defects, including threshold values ​​for weld nugget geometric parameters, acceptable ranges for peel shear force, and appearance judgment standards for different defect types. By performing secondary feature matching between the actual post-weld quality results and this feature library, the initial weld joint defect type is verified, misjudgments are eliminated, fuzzy judgments are corrected, and finally, accurate weld joint defect types are generated, ensuring the reliability and accuracy of defect identification.

[0045] If the weld joint quality is determined to be unqualified based on the weld joint defect type, then the first process adjustment parameter is adaptively adjusted according to a preset defect-parameter correction rule to generate a second process adjustment parameter, specifically including: Based on a preset database of typical quality features of weld joint defects, the target weld joint defect type corresponding to the weld joint quality being unqualified is determined. The target weld joint defect type includes at least cold solder joint, spatter, adhesion, and crack. The defect-parameter correction rule is matched according to the target weld defect type, and combined with the total thickness of the workpiece to be welded in the welding condition information. The material type coefficient M is used to make targeted corrections to the first process adjustment parameters corresponding to the defect type of the target weld point; When the defect type of the target weld point is a cold weld, the welding current of the i-th pulse in the main welding stage of the four stages of resistance spot welding is... A positive correction is performed, and the pre-pressure electrode force in the pre-pressure stage of the four stages of resistance spot welding is corrected simultaneously. The corresponding correction formula is as follows: In the formula, This represents the corrected welding current reference value for the i-th pulse; This indicates the corrected preload electrode force reference value; Indicates the standard minimum melt core diameter; Indicates the actual measured diameter of the melt core; This represents the preset correction factor for the cold solder joint current; This represents the preset correction coefficient for poor soldering pressure; When the target weld defect type is spatter, the welding current of the i-th pulse in the main welding stage of the four-stage resistance spot welding is... and welding time A negative correction is performed, and the corresponding correction formula is as follows: In the formula, This represents the welding time reference value for the i-th pulse after correction; Indicates the actual splash area; Indicates the standard maximum splash area; This indicates the preset splash current attenuation coefficient; This indicates the preset splash time decay coefficient.

[0046] The target weld defect type is a specific non-conformity category determined based on post-weld quality inspection results. A cold weld is when the weld nugget size or mechanical properties do not meet standards; spatter is metal spatter caused by excessive welding energy; adhesion is abnormal adhesion between the electrode and the weld joint; and cracks are cracking defects that occur during the solidification process of the weld nugget. The defect-parameter correction rule is a targeted parameter adjustment strategy developed for different defect causes. It clarifies the parameters to be corrected, the correction direction, and the calculation logic for each defect, ensuring that the correction measures accurately match the root cause of the defect.

[0047] Next, the cold solder joint current correction coefficient and the cold solder joint pressure correction coefficient are process constants that control the correction range of cold solder joint defects. Through experimental calibration, it is ensured that the corrected energy input and contact stability are adapted to the requirements of weld nugget formation. The spatter current attenuation coefficient and the spatter time attenuation coefficient are process constants that suppress spatter, avoiding overheating and spatter by reducing the energy input amplitude.

[0048] Understandably, the standard minimum weld nugget diameter is the lower limit of the weld nugget diameter required for a qualified weld joint, which is a quality standard specified by the industry or design. The actual weld nugget diameter is the true weld nugget size obtained through non-destructive testing after welding. The difference between the two reflects the severity of the incomplete weld. The actual spatter area is the area of ​​the spatter region measured after welding, while the standard maximum spatter area is the upper limit of the allowable spatter area. The ratio between the two is used to quantify the severity of spatter.

[0049] By employing the above methods, for different target weld defect types such as cold welds and spatter, and combining the total thickness of the workpiece and the material type coefficient, defect-parameter correction rules are precisely matched for targeted adjustment, avoiding blind parameter adjustments. Positive correction supplements the energy required for cold welds and improves contact stability, while negative correction suppresses excessive energy input from spatter. The resulting second process adjustment parameters are highly adaptable, effectively reducing the defect rate and ensuring weld quality meets standards.

[0050] In practical applications, taking the double-layer lap welding of AA6016-T4 and AA5182-O as an example, the total thickness of the workpieces to be welded is 2.2mm, the material type coefficient is 1.1, and the target weld defect type is cold weld. The standard minimum weld nugget diameter is 4.5mm, and the actual measured weld nugget diameter is 3.2mm. The cold weld current correction coefficient is 0.4 and the cold weld pressure correction coefficient is 0.2 retrieved from the process parameter database. After the first process adjustment parameters are directionally corrected in combination with the total thickness of the workpieces to be welded and the material type coefficient, the welding current and pre-pressure electrode force of each pulse in the main welding stage are positively optimized. After re-welding, the test shows that the weld nugget diameter reaches 4.6mm and the peel shear force is 6.2kN, which fully meets the quality requirements. In another working condition, if the target weld defect type is spatter, the actual spatter area is 8mm², the standard maximum spatter area is 5mm², the spatter current attenuation coefficient is 0.3, and the spatter time attenuation coefficient is 0.15. After correction, the spatter phenomenon is completely suppressed, and the weld appearance is smooth.

[0051] Also includes: When the defect type of the target weld joint is adhesion, the holding electrode force and holding time in the holding stage of the four stages of resistance spot welding are negatively corrected. The corresponding correction formula is as follows: In the formula, This indicates the revised baseline value for the maintenance time; This indicates the corrected reference value for the sustaining electrode force; Indicates the actual adhesive tensile force; Indicates the standard maximum adhesive tensile force; This represents the preset adhesion time correction factor; This indicates the preset adhesion electrode force correction coefficient; When the target weld defect type is a crack, the welding current of the Nth pulse in the main welding stage of the four-stage resistance spot welding is... A positive correction is performed, and the holding electrode force in the holding stage of the four stages of resistance spot welding is corrected simultaneously. The corresponding correction formula is as follows: In the formula, This represents the corrected welding current reference value for the Nth pulse. Indicates the actual crack length; Indicates the standard maximum crack length; This represents the preset crack current correction factor; This represents the preset crack electrode force correction coefficient; The modified first process adjustment parameters are subjected to threshold boundary verification. After the verification is passed, the second process adjustment parameters are generated.

[0052] The actual adhesion tensile force, measured by testing equipment, is the tensile force required for separation at the adhesion point, directly reflecting the severity of the adhesion defect. The standard maximum adhesion tensile force is a preset maximum tensile force threshold for judging adhesion defects, used to quantify the severity of adhesion. The preset adhesion time correction coefficient and preset adhesion electrode force correction coefficient are process constants calibrated through extensive testing, used to control the correction range of holding time and holding electrode force, respectively, ensuring that the correction amount is adapted to the severity of adhesion.

[0053] Understandably, the Nth pulse in the main welding stage is the last pulse in a multi-pulse welding sequence, typically performing functions such as tempering and reheating, and playing a crucial role in optimizing the weld nugget structure and stress release. The actual crack length is the actual crack size measured through non-destructive testing or destructive testing. The standard maximum crack length is a preset threshold for the maximum acceptable length of a crack defect, used to quantify the severity of the crack. The preset crack current correction coefficient and preset crack electrode force correction coefficient are experimentally calibrated process constants, used to control the correction amplitude of the last pulse welding current and the maintaining electrode force, respectively, ensuring that the correction measures effectively suppress crack propagation or initiation.

[0054] Next, threshold boundary verification verifies the rationality of the corrected first process adjustment parameters, ensuring that the parameters are within the limits of equipment hardware capabilities and process allowances, thus preventing welding failures or secondary defects caused by abnormal parameters. The second process adjustment parameters, after targeted correction and threshold verification, are the final combination of process parameters that can be directly used for subsequent welding or re-welding, ensuring that weld defects are effectively suppressed and welding quality meets standards.

[0055] In practical applications, taking the double-layer lap welding of AA6016-T4 and AA5182-O as an example, the total thickness of the workpieces to be welded is 2.2mm, and the material type coefficient is 1.1. If the defect type of the target weld point is adhesion, the actual adhesion tensile force is 3.2kN, the maximum adhesion tensile force is 5kN, and the adhesion time correction coefficient is adjusted to 0.2, the adhesion electrode force correction coefficient is 0.15, and the pressure proportional coefficient is 1.2. The corrected pre-pressure electrode force is 5.32kN. After negatively correcting the holding time and holding electrode force, there is no adhesion between the electrode and the weld point during rewelding, and the separation is smooth.

[0056] In another working condition, the target weld defect type was a crack, with an actual crack length of 0.8 mm and a standard maximum crack length of 2 mm. The crack current correction factor was 0.3, the crack electrode force correction factor was 0.2, the welding current of the Nth pulse was 22 kA, and the pre-load electrode force was 4.5 kN. After positive correction, the welding current of the last pulse and the holding electrode force were matched to the requirements. After re-welding, the crack was completely eliminated, the weld nugget structure was uniform, and the peel shear force reached 6.5 kN, meeting the quality requirements.

[0057] like Figure 2 The diagram shown is a system block diagram of an adaptive adjustment system for resistance spot welding process parameters of aluminum alloys provided in an embodiment of the present invention. The system includes: The information acquisition module is used to collect welding condition information, process monitoring signals and post-weld quality result information during the aluminum alloy resistance spot welding process. The parameter modeling module is used to construct a four-dimensional parameter space model, divide the aluminum alloy resistance spot welding process into four stages of resistance spot welding, and set resistance spot welding process parameters for the four stages of resistance spot welding based on the welding condition information. The resistance adjustment module is used to calculate the instantaneous contact resistance based on the process monitoring signal and generate a dynamic resistance curve, and to adaptively adjust the resistance spot welding process parameters according to the dynamic resistance curve to generate the first process adjustment parameters. The defect adjustment module is used to identify and generate weld joint defect types based on the process monitoring signals and the post-weld quality result information. If the weld joint quality is determined to be unqualified according to the weld joint defect type, the first process adjustment parameter is adaptively adjusted according to the preset defect-parameter correction rule to generate the second process adjustment parameter.

[0058] Figure 2 The apparatus of the illustrated embodiment can be used to perform corresponding actions. Figure 1 The steps in the method embodiments shown are implemented in a similar manner and have similar technical effects, and will not be repeated here.

[0059] An electronic device includes a memory and a processor, wherein the memory stores a computer program, and when the processor runs the computer program stored in the memory, the processor executes the steps of the adaptive adjustment method for resistance spot welding process parameters of aluminum alloy as described in any of the above claims.

[0060] like Figure 3 The diagram shown is a hardware structure schematic of an electronic device according to an embodiment of the present invention. The electronic device 30 includes: a processor 31, a memory 32, and a computer program; wherein... The memory 32 is used to store the computer program, and the memory may also be flash memory. The computer program is, for example, an application program or functional module that implements the above method.

[0061] Processor 31 is configured to execute the computer program stored in the memory to implement the various steps performed by the device in the above method. For details, please refer to the relevant descriptions in the preceding method embodiments.

[0062] Alternatively, the memory 32 can be either standalone or integrated with the processor 31.

[0063] When the memory 32 is a device independent of the processor 31, the device may further include: Bus 33 is used to connect the memory 32 and the processor 31.

[0064] A readable storage medium storing a computer program, which, when executed by a processor, is used to implement the steps of an adaptive adjustment method for resistance spot welding process parameters of aluminum alloy as described in any of the preceding claims.

[0065] The readable storage medium can be a computer storage medium or a communication medium. A communication medium includes any medium that facilitates the transfer of computer programs from one location to another. A computer storage medium can be any available medium accessible to a general-purpose or special-purpose computer. For example, a readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application-Specific Integrated Circuit (ASIC). Alternatively, the ASIC can be located in a user equipment. Of course, the processor and the readable storage medium can also exist as discrete components in a communication device. The readable storage medium can be a read-only memory (ROM), random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0066] The present invention also provides a program product including executable instructions stored in a readable storage medium. At least one processor of the device can read the executable instructions from the readable storage medium, and the at least one processor executes the executable instructions to cause the device to implement the methods provided in the various embodiments described above.

[0067] In the embodiments of the above-described device, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly manifested as execution by a hardware processor, or execution by a combination of hardware and software modules within the processor.

[0068] Through the above embodiments, this invention collects welding condition information, process monitoring signals, and post-weld quality result information during the aluminum alloy resistance spot welding process; constructs a four-dimensional parameter space model, dividing the aluminum alloy resistance spot welding process into four stages; sets resistance spot welding process parameters for each of the four stages based on the welding condition information; calculates the instantaneous contact resistance based on the process monitoring signals, generates a dynamic resistance curve, and adaptively adjusts the resistance spot welding process parameters according to the dynamic resistance curve to generate the first process adjustment parameter; identifies and generates weld defect types based on the process monitoring signals and post-weld quality result information; if the weld quality is determined to be unqualified according to the weld defect type, the first process adjustment parameter is adaptively adjusted according to the preset defect-parameter correction rule to generate the second process adjustment parameter. This achieves closed-loop optimization of real-time response to the welding process and post-weld quality feedback, broadens the process window, effectively suppresses defects such as spatter and incomplete welding, significantly improves the stability and consistency of weld quality, and can adapt to varying aluminum alloy materials and working conditions.

[0069] This invention constructs a four-dimensional parametric space model to precisely divide the aluminum alloy resistance spot welding process into a pre-pressing stage, a main welding stage, a holding stage, and a return stage. Based on welding condition information, it independently sets resistance spot welding process parameters for each stage, achieving refined, staged control of the entire welding process. This effectively adapts to welding requirements with different material and thickness combinations, significantly broadening the process window. Furthermore, this invention calculates instantaneous contact resistance and generates a dynamic resistance curve by real-time acquisition of process monitoring signals. By extracting key features, it adaptively adjusts the welding current and welding time in the main welding stage, generating the first process adjustment parameters. This allows for real-time response to dynamic changes in the interface state during welding, thereby effectively improving the stability of the welding process. This invention integrates process monitoring signals and post-weld quality results information. Through feature matching, it accurately identifies weld defect types such as cold welds, spatter, adhesion, and cracks. For different weld defect types, it calls defect-parameter correction rules to make targeted corrections to the first process adjustment parameters and generate second process adjustment parameters. This achieves closed-loop optimization based on post-weld quality feedback. It can increase welding current and pre-pressure electrode force for cold welds, reduce welding current and welding time for spatter, shorten holding time and adjust holding electrode force for adhesion, and correct the final pulse welding current and holding electrode force for cracks, thereby effectively improving the pass rate and consistency of weld quality.

[0070] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method of adaptive adjustment of process parameters for resistance spot welding of an aluminum alloy, characterized in that, The method includes: Collect welding condition information, process monitoring signals, and post-weld quality results information during the resistance spot welding process of aluminum alloys; A four-dimensional parameter space model is constructed to divide the aluminum alloy resistance spot welding process into four stages of resistance spot welding. Based on the welding condition information, resistance spot welding process parameters are set for the four stages of resistance spot welding respectively. Based on the process monitoring signal, the instantaneous contact resistance is calculated and a dynamic resistance curve is generated. The resistance spot welding process parameters are adaptively adjusted according to the dynamic resistance curve to generate the first process adjustment parameters. Based on the process monitoring signal and the post-weld quality result information, the weld joint defect type is identified and generated. If the weld joint quality is determined to be unqualified according to the weld joint defect type, the first process adjustment parameter is adaptively adjusted according to the preset defect-parameter correction rule to generate the second process adjustment parameter.

2. The method of claim 1, wherein the method is characterized by: The construction of the four-dimensional parameter space model divides the aluminum alloy resistance spot welding process into four stages. Based on the welding condition information, resistance spot welding process parameters are set for each of the four stages, specifically including: The resistance spot welding process consists of four stages: pre-pressure stage, main welding stage, holding stage, and return stage. based on a total thickness of a workpiece to be welded in the welding condition information a material type coefficient M, which sets the resistance spot welding process parameters for the pre-pressing stage, the main welding stage, the maintaining stage, and the return stage, respectively For the pre-pressing phase, a pre-pressing electrode force is set and a pre-pressing time wherein represents a pressure reference coefficient; represents a reference thickness of the workpiece to be welded; represents a pre-pressing time-thickness coefficient; For the main welding phase, the welding current of the i-th pulse is set and the welding time wherein denotes the i-th pulse current reference coefficient; denotes the i-th pulse time reference coefficient; denotes the time base offset of the i-th pulse; and N denotes the number of pulses. For the maintenance phase, a maintenance electrode force is set and a maintenance time wherein represents a pressure proportionality coefficient, ; represents a maintenance time-thickness coefficient; For the return phase, the electrode return time is set. ,in, Indicates the electrode return speed; This indicates the electrode return stroke.

3. The adaptive adjustment method for resistance spot welding process parameters of aluminum alloy according to claim 1, characterized in that, The step of calculating the instantaneous contact resistance based on the process monitoring signal and generating a dynamic resistance curve, and then adaptively adjusting the resistance spot welding process parameters according to the dynamic resistance curve to generate a first process adjustment parameter, specifically includes: Based on the main welding stage current signal and main welding stage voltage signal in the process monitoring signal, the instantaneous contact resistance is calculated according to Ohm's law, and the dynamic resistance curve is generated based on the change of the instantaneous contact resistance over time. The rate of decrease in resistance of the dynamic resistance curve is extracted by differential calculation, the peak resistance value of the dynamic resistance curve is extracted by peak detection algorithm, and the plateau resistance value of the dynamic resistance curve is extracted by mean filtering algorithm. The pulse of the main welding stage in the four stages of resistance spot welding is adaptively adjusted based on the resistance drop rate, the peak resistance value, and the plateau resistance value to generate the first process adjustment parameters.

4. The adaptive adjustment method for resistance spot welding process parameters of aluminum alloy according to claim 3, characterized in that, The step of adaptively adjusting the pulse of the main welding stage in the four stages of resistance spot welding based on the resistance drop rate, the peak resistance value, and the plateau resistance value to generate the first process adjustment parameters specifically includes: Based on the welding condition information, the spatter suppression coefficient is obtained from a preset process parameter database. Energy compensation coefficient and stability adjustment coefficient Extract the resistance decrease rate of the current i-th pulse. Peak resistance And calculate the standard deviation of the plateau resistance value of the current i-th pulse as the fluctuation amount. ; If the resistance decrease rate of the i-th pulse Greater than the preset splash risk threshold Then adjust the first Pulse welding current ,in, ; If the resistance peak value of the i-th pulse Less than the preset energy shortage threshold And the rate of decrease in resistance of the i-th pulse Less than the preset splash risk threshold Then adjust the first Pulse welding current ; If the fluctuation of the plateau resistance value of the i-th pulse greater than the plateau period fluctuation threshold Then adjust the first Welding time of a single pulse ; If none of the above conditions are met, then the first... Pulse welding current and welding time Adjustments were made.

5. The adaptive adjustment method for resistance spot welding process parameters of aluminum alloy according to claim 1, characterized in that, The process of identifying and generating weld joint defect types based on the process monitoring signals and the post-weld quality result information specifically includes: The process monitoring signals are processed and feature extracted to generate current signal features, voltage signal features, and electrode displacement signal features; The current signal features, voltage signal features, and electrode displacement signal features are input into a preset typical feature model of weld joint defects, and a preliminary weld joint defect type is generated through feature matching and identification. Obtain the weld nugget geometric parameters, peel shear force values, and weld appearance inspection results from the post-weld quality results information; The geometric parameters of the weld nugget, the peeling shear force value, and the weld joint appearance inspection results are matched with a preset typical quality feature library of weld joint defects. Based on the feature matching results, the preliminary weld joint defect type is verified and corrected to generate the weld joint defect type.

6. The adaptive adjustment method for resistance spot welding process parameters of aluminum alloy according to claim 1, characterized in that, If the weld joint quality is determined to be unqualified based on the weld joint defect type, then the first process adjustment parameter is adaptively adjusted according to a preset defect-parameter correction rule to generate a second process adjustment parameter, specifically including: Based on a preset database of typical quality features of weld joint defects, the target weld joint defect type corresponding to the weld joint quality being unqualified is determined. The target weld joint defect type includes at least cold solder joint, spatter, adhesion, and crack. The defect-parameter correction rule is matched according to the target weld defect type, and combined with the total thickness of the workpiece to be welded in the welding condition information. The material type coefficient M is used to make targeted corrections to the first process adjustment parameters corresponding to the defect type of the target weld point; When the defect type of the target weld point is a cold weld, the welding current of the i-th pulse in the main welding stage of the four stages of resistance spot welding is... A positive correction is performed, and the pre-pressure electrode force in the pre-pressure stage of the four stages of resistance spot welding is corrected simultaneously. The corresponding correction formula is as follows: In the formula, This represents the corrected welding current reference value for the i-th pulse; This indicates the corrected preload electrode force reference value; Indicates the standard minimum melt core diameter; Indicates the actual measured diameter of the melt core; This indicates the preset correction factor for the cold solder joint current; This represents the preset correction coefficient for poor soldering pressure; When the target weld defect type is spatter, the welding current of the i-th pulse in the main welding stage of the four-stage resistance spot welding is... and welding time A negative correction is performed, and the corresponding correction formula is as follows: In the formula, This represents the welding time reference value for the i-th pulse after correction; Indicates the actual splash area; Indicates the standard maximum splash area; This indicates the preset splash current attenuation coefficient; This indicates the preset splash time decay coefficient.

7. The adaptive adjustment method for resistance spot welding process parameters of aluminum alloy according to claim 6, characterized in that, Also includes: When the defect type of the target weld joint is adhesion, the holding electrode force and holding time in the holding stage of the four stages of resistance spot welding are negatively corrected. The corresponding correction formula is as follows: In the formula, This indicates the revised baseline value for the maintenance time; This indicates the corrected reference value for the sustaining electrode force; Indicates the actual adhesive tensile force; Indicates the standard maximum adhesive tensile force; This represents the preset adhesion time correction factor; This indicates the preset adhesion electrode force correction coefficient; When the target weld defect type is a crack, the welding current of the Nth pulse in the main welding stage of the four-stage resistance spot welding is... A positive correction is performed, and the holding electrode force in the holding stage of the four stages of resistance spot welding is corrected simultaneously. The corresponding correction formula is as follows: In the formula, This represents the corrected welding current reference value for the Nth pulse. Indicates the actual crack length; Indicates the standard maximum crack length; This represents the preset crack current correction factor; This represents the preset crack electrode force correction coefficient; The modified first process adjustment parameters are subjected to threshold boundary verification. After the verification is passed, the second process adjustment parameters are generated.

8. An adaptive adjustment system for resistance spot welding process parameters of aluminum alloys, applied to the adaptive adjustment method for resistance spot welding process parameters of aluminum alloys as described in any one of claims 1-7, characterized in that, The system includes: The information acquisition module is used to collect welding condition information, process monitoring signals and post-weld quality result information during the aluminum alloy resistance spot welding process. The parameter modeling module is used to construct a four-dimensional parameter space model, divide the aluminum alloy resistance spot welding process into four stages of resistance spot welding, and set resistance spot welding process parameters for the four stages of resistance spot welding based on the welding condition information. The resistance adjustment module is used to calculate the instantaneous contact resistance based on the process monitoring signal and generate a dynamic resistance curve, and to adaptively adjust the resistance spot welding process parameters according to the dynamic resistance curve to generate the first process adjustment parameters. The defect adjustment module is used to identify and generate weld joint defect types based on the process monitoring signals and the post-weld quality result information. If the weld joint quality is determined to be unqualified according to the weld joint defect type, the first process adjustment parameter is adaptively adjusted according to the preset defect-parameter correction rule to generate the second process adjustment parameter.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor runs the computer program stored in the memory, the processor performs the steps of the adaptive adjustment method for resistance spot welding process parameters of aluminum alloy as described in any one of claims 1-7.

10. A readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it is used to implement the steps of the adaptive adjustment method for resistance spot welding process parameters of aluminum alloy as described in any one of claims 1-7.

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