An automatic optimization control method for resistance spot welding

Abstract

The invention discloses an automatic optimization control method for resistance spot welding, which relates to the technical field of resistance spot welding. The method collects welding object parameters and material information, selects a suitable electrode cap, and calculates an ideal welding current value; establishes a historical database and a prediction model to predict the combination state of the best current and pressure, and optimizes the welding process; integrates the ideal parameters into control parameters, and controls the spot welding equipment to automatically complete the spot welding work; performs a centering test before welding to avoid abnormal welding situations; the invention automatically adjusts the welding parameters in the resistance spot welding process through intelligent algorithms and historical data analysis, improves efficiency and stability, reduces defective products, and saves energy, so as to achieve higher quality welding and higher production efficiency.

Description

Technical Field

[0001] The invention relates to the technical field of resistance spot welding, and in particular to an automatic optimization control method for resistance spot welding. Background Art

[0002] Resistance spot welding is a metal welding process that applies pressure and current between the metal parts to be connected, causing local resistance heating between the two metal parts to reach a molten or plastic state, thereby achieving the connection of the metal parts. This process is commonly used in the fields of automobile manufacturing, home appliance manufacturing, and metal product manufacturing because it can achieve high-speed and efficient metal connection.

[0003] In the prior art, resistance spot welding control usually relies on manual experience to set welding parameters, such as current value, pressure value and welding time. This method has the following defects: the setting of welding parameters depends on the experience and skills of the operator, which leads to inconsistency and human errors in parameter settings, affecting the stability of welding quality; when welding different materials or changing welding conditions, welding parameters need to be adjusted manually, which is time-consuming and may lead to the omission of optimal parameters. Due to the inaccurate parameter setting, different batches of welding products may have inconsistent welding quality problems, affecting the consistency and reliability of the products. A large amount of data is generated during the welding process, but the prior art often does not effectively use this data to optimize the welding process, resulting in the value of the data not being fully utilized. Existing resistance spot welding control methods generally lack intelligence and cannot automatically identify and optimize problems in the welding process, limiting the automation and intelligent development of welding technology.

[0004] Therefore, how to provide an automatic optimization control method for resistance spot welding to improve the automation level and welding quality of the welding process has become an urgent problem to be solved in this field. Summary of the invention

[0005] The purpose of the present invention is to automatically adjust the welding parameters in the resistance spot welding process through intelligent algorithms and historical data analysis to achieve higher quality welding and higher production efficiency.

[0006] To achieve the above object, the present invention provides the following solutions:

[0007] An automatic optimization control method for resistance spot welding, comprising:

[0008] Collect the thickness, initial temperature and various material parameters of welding materials;

[0009] Multiple types of electrode caps are pre-set;

[0010] Calculating the expected welding temperature based on the collected thickness, initial temperature and various material parameters of the welding material;

[0011] Selecting a corresponding type of electrode cap according to the expected welding temperature, and recording a shape factor of the selected electrode cap;

[0012] Presetting an ideal welding time, and calculating an ideal output current value of the spot welding device in combination with the expected welding temperature and various material parameters;

[0013] Establish a historical database to classify and record the current value, pressure value and corresponding welding results of various types of welding materials in the historical spot welding process;

[0014] Establishing a range prediction model, and training it based on the historical data in the historical database, and outputting a plurality of the range prediction models after training;

[0015] Substituting the current ideal output current value and the pressure range of the spot welding device into the corresponding range prediction model, and outputting the ideal pressure range;

[0016] Calculate the ideal pressure range by combining the ideal pressure range with the shape coefficient, and take the median of the pressure values ​​in the ideal pressure range as the ideal pressure value;

[0017] Integrating the ideal output current value, the ideal pressure value and the ideal welding time into control parameters;

[0018] The spot welding equipment is controlled based on the control parameters to automatically complete the spot welding work.

[0019] Preferably, in the above-mentioned automatic optimization control method for resistance spot welding, the various material parameters include:

[0020] The quality, heat capacity, thermal efficiency, maximum and minimum thickness of the welding material during the historical spot welding process, and thermal conductivity of the welding material;

[0021] The presetting of multiple types of electrode caps includes: the types of electrode caps are classified based on material and structure, wherein the structural categories are convex type, concave type and flat head type;

[0022] The contact surface between the raised electrode cap and the welding material is provided with multiple layers of annular ridges, spiral ridges or radial ridges;

[0023] The contact surface between the recessed electrode cap and the welding material is provided with a welding surface, an annular ridge, a circumference and a groove, the groove is located in the central area of ​​the contact surface, the upper edge of the groove is transitionally connected with the welding surface through a smooth fillet, and the circumference is the outer diameter of the welding surface; the shape of the groove is a spherical surface, and the annular ridge is provided on the welding surface;

[0024] The flat-head electrode cap comprises a welding contact section, a consumable section and a mounting section. The contact section adopts a conical structure, and the contact surface at the top of the contact section is a plane. The angle between the contact section and the consumable section is 120° to 145°.

[0025] Preferably, in the above-mentioned automatic optimization control method for resistance spot welding, the expected welding temperature is calculated based on the thickness, initial temperature and various material parameters of the collected welding material, the corresponding type of electrode cap is selected according to the expected welding temperature, and the shape coefficient of the selected electrode cap is recorded, which specifically includes the following steps:

[0026] Expected temperature calculation: Establish an expected temperature calculation model, the expected temperature calculation model is ;

[0027] in, is the expected temperature value, representing the temperature required for welding; is the thermal conductivity, is the initial temperature of the welding material, is the thickness of the welding material, and They are the maximum thickness and minimum thickness of the welding material in the historical spot welding process respectively;

[0028] The thermal conductivity coefficient collected , Initial temperature of welding material , the thickness of welding material , the maximum and minimum thickness of the welding material during the historical spot welding process and Substitute into the expected temperature calculation model to obtain the expected temperature value ;

[0029] Material category screening: the expected temperature value Match the spot welding temperature range corresponding to each type of electrode cap material to obtain the expected temperature value. The electrode cap;

[0030] Structural category screening: based on the thickness of the welding material, the spot welding requirements and the expected temperature values Select the electrode cap with the corresponding structure;

[0031] Setting a first thickness threshold and a first temperature threshold applicable to the flat-head electrode cap; setting a second temperature threshold applicable to the convex electrode cap; setting a third temperature threshold applicable to the concave electrode cap;

[0032] If the thickness of the welding material is greater than the first thickness threshold, the expected temperature value When the temperature is lower than the first temperature threshold and the spot welding requirement is uniform welding, the flat-head electrode cap is selected;

[0033] If the expected temperature of the welding material When the temperature is higher than the second temperature threshold and the spot welding requirement is deep penetration welding, the convex electrode cap is selected;

[0034] If the expected temperature of the welding material When the temperature is higher than the third temperature threshold and the spot welding requirement is fine welding, the recessed electrode cap is selected;

[0035] The electrode cap of this category is determined and used according to the material of the selected electrode cap and the structure of the electrode cap, and the shape coefficient Ca of the electrode cap is recorded.

[0036] Preferably, in the above-mentioned automatic optimization control method for resistance spot welding, the ideal welding time is pre-set, and the ideal output current value of the spot welding device is calculated in combination with the expected welding temperature and various material parameters using the following formula:

[0037]

[0038] in, is the ideal output current value, is the thermal efficiency of the welding material, For the quality of welding materials, is the heat capacity of the welding material, The temperature change required for welding, is the resistance of the welding material; For the preset ideal welding time, Error bias term, based on experience setting; is the expected temperature value, representing the temperature required for welding; is the initial temperature of the welding material.

[0039] Preferably, in the above-mentioned automatic optimization control method for resistance spot welding, the establishing of the range prediction model, and the training based on the historical data in the historical database, and the output of the multiple range prediction models after the training specifically include the following steps:

[0040] Establish the range prediction model, the range prediction model is:

[0041] ;

[0042] Wherein, x is an input vector, i.e., each set of current values ​​and pressure values ​​in the historical database; is the analysis result, that is, the corresponding welding result. If the welding result is qualified, >0, and assign according to the welding effect A decimal number in the interval (0, 1). If the welding result is unqualified, <0, and given according to the welding effect A decimal number in the interval (-1, 0); is the support vector; The category label corresponding to each support vector =+1 means the welding is qualified. =-1 means welding is unqualified; For each support vector The Lagrange multiplier of ; is the bias term, The function is used to pass the model through the sample points The distance to the decision boundary is converted into a class label to determine which side of the decision boundary the sample point is on;

[0043] Each set of historical data in the historical database is used as the input vector x and the analysis result Substitute it into the range prediction model for training, and generate the support vectors in the range prediction model corresponding to various types of welding materials , category label , Lagrange multipliers , bias term ;

[0044] Support vectors in the range prediction model corresponding to the welding materials of each type of material , category label , Lagrange multipliers , bias term Output the trained multiple range prediction models.

[0045] Preferably, in the above-mentioned automatic optimization control method for resistance spot welding, the step of substituting the current ideal output current value and the pressure range of the spot welding equipment into the corresponding range prediction model to output the ideal pressure range specifically includes the following steps:

[0046] Arranging various pressure values ​​provided by the spot welding device during historical spot welding processes in the historical database, and integrating the various pressure values ​​into a pressure range set;

[0047] The ideal output current value and each pressure data in the pressure range set are used as input vector x, and are sequentially substituted into the range prediction model corresponding to the welding material to generate a corresponding number of analysis results. ;

[0048] For each analysis result Filter and retain >0, and arranging the pressure values ​​according to their numerical values ​​and integrating them into the ideal pressure range.

[0049] Preferably, in the above-mentioned automatic optimization control method for resistance spot welding, the step of calculating the ideal pressure range by combining the ideal pressure range with the shape coefficient and taking the median of the pressure values ​​in the ideal pressure range as the ideal pressure value specifically includes the following steps:

[0050] A pressure estimation model is established, and the pressure to be applied by the spot welding equipment is determined based on the pressure estimation model; the pressure estimation model is ;in, is the i-th pressure value in the ideal pressure range, The pressure value The corresponding original contact area of ​​the electrode cap, is the shape factor of the electrode cap, is the actual contact area of ​​the electrode cap; The pressure value The corresponding pressure value, i.e., the pressure that the spot welding equipment needs to apply;

[0051] Substitute each pressure value in the ideal pressure range into the pressure estimation model in combination with the actual contact area of ​​the selected electrode cap, and output each corresponding pressure value. , integrated into the desired pressure range;

[0052] The data in the ideal pressure range are sorted from large to small or from small to large, and the median is taken as the ideal pressure value.

[0053] Preferably, in the above-mentioned automatic optimization control method for resistance spot welding, between the step of "selecting the corresponding type of electrode cap according to the expected welding temperature, and recording the shape coefficient of the selected electrode cap" and the step of "presetting the ideal welding time, and calculating the ideal output current value of the spot welding device in combination with the expected welding temperature and the various material parameters", it also includes: detecting the centering of the group of electrode caps by a centering detection device;

[0054] The centering detection device comprises:

[0055] A spot welding test piece, the spot welding test piece comprising: an upper test piece and a lower test piece, the upper test piece and the lower test piece are of the same size, and the upper test piece and the lower test piece are aligned and stacked;

[0056] A pressure sensor is disposed between the upper test piece and the lower test piece, and is used to collect the pressure value and deformation state of the upper test piece and the lower test piece, and convert the pressure value and deformation state into an electronic image through a computer;

[0057] A guiding component connected to the spot welding device and used to guide the spot welding device to clamp the spot welding test piece and apply pressure;

[0058] The computer is used to analyze the electronic images of the upper test piece and the lower test piece to determine the pressure difference, deformation difference and concentricity of the upper test piece and the lower test piece; pre-set the pressure difference threshold, deformation difference threshold and concentricity difference threshold, and respectively compare the pressure difference, deformation difference and concentricity with the pressure difference threshold, deformation difference threshold and concentricity difference threshold to determine the concentricity of the electrode cap.

[0059] Preferably, in the above-mentioned automatic optimization control method for resistance spot welding, the detecting the centering of the electrode cap by the centering detection device further comprises:

[0060] Controlling the spot welding equipment to apply pressure to the spot welding test piece at an ideal pressure value;

[0061] The difference between the actual pressure value and the ideal pressure value applied to the spot welding test piece is analyzed to obtain an analysis result, and the abnormal conditions of the spot welding equipment and the electrode cap are determined based on the analysis result.

[0062] Preferably, in the above-mentioned automatic optimization control method for resistance spot welding, after the step of "controlling the spot welding equipment to automatically complete the spot welding work based on the control parameters", it also includes:

[0063] After the spot welding is completed, the ideal output current value, the ideal pressure value and the spot welding effect of the spot welding are stored as historical data in the historical database, and used as training data to update the range prediction model.

[0064] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0065] 1. This application predicts the temperature required for welding, thereby selecting a suitable electrode cap to avoid unnecessary losses caused by excessively high or low temperatures, improve welding efficiency and reduce material energy consumption.

[0066] 2. This application meets different welding requirements by selecting different types of electrode caps, reduces the debugging and adjustment time during the welding process, and improves production efficiency and work efficiency.

[0067] 3. This application calculates the ideal output current value and controls the current parameters during the welding process to meet the ideal requirements, avoids energy waste caused by excessive or insufficient current, achieves energy optimization of the welding process, and thus maintains the consistency and stability of the welding process.

[0068] 4. This application predicts the optimal current and pressure combination through analysis of the historical database and training range prediction model, which helps to improve welding quality and stability, reduce defects and defective products, make the welding process more efficient and stable, reduce adjustment time, and improve production efficiency; by calculating the appropriate pressure value, it helps to ensure the stable operation of spot welding equipment and extend the service life of the equipment.

[0069] 5. The solution of this application can be integrated into the automation system, making the spot welding process more intelligent and automated, reducing manual intervention and improving the automation level of the production line. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0071] Figure 1 A flow chart of an automatic optimization control method for resistance spot welding provided by the present invention;

[0072] Figure 2 It is a schematic diagram of the structure of a three-knife-cutting annular raised electrode cap;

[0073] Figure 3 Schematic diagram of the structure of the cross-divided annular raised electrode cap

[0074] Figure 4 It is a schematic diagram of the structure of a spiral convex electrode cap;

[0075] Figure 5 It is a schematic diagram of the structure of a recessed electrode cap;

[0076] Figure 6 It is a schematic diagram of the structure of a flat-head electrode cap;

[0077] Figure 7 It is a structural schematic diagram of the centering detection device.

[0078] In the figure, 1, annular ridge; 2, spiral ridge; 3, groove; 4, annular ridge; 5, circumference; 6, welding surface; 7, contact section; 8, consumable section; 9, installation section; 10, electrode cap; 11, spot welding equipment; 12, upper test piece; 13, lower test piece; 14, pressure sensor. DETAILED DESCRIPTION

[0079] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0080] The purpose of the present invention is to automatically adjust the welding parameters in the resistance spot welding process through intelligent algorithms and historical data analysis to achieve higher quality welding and higher production efficiency.

[0081] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0082] Embodiment 1

[0083] In one embodiment, see Figure 1-6 , an automatic optimization control method for resistance spot welding, comprising:

[0084] Step 1: Collect the thickness, initial temperature and various material parameters of the welding material.

[0085] The material parameters include: the quality of the welding material, heat capacity, thermal efficiency, the maximum and minimum thickness of the welding material in the historical spot welding process, and thermal conductivity;

[0086] It should be noted that the material parameters collected in this embodiment include the mass of the welding material, heat capacity value, thermal efficiency, thickness change in the historical spot welding process, and thermal conductivity, etc. The collection method is a conventional technical means and is not elaborated in this embodiment; these parameters are used to analyze and control heat transfer and material performance changes in the welding process. Among them, the thermal conductivity is obtained based on the thermal conductivity of the material, and the thermal conductivity of each material is converted into the thermal conductivity by normalization; assuming that the material of the welding material is magnesium, the thermal conductivity of magnesium is 160W / (m*k), and the thermal conductivity of copper is 401W / (m*k); assuming that the highest thermal conductivity in the historical spot welding process is the thermal conductivity of copper, and the lowest thermal conductivity is the thermal conductivity of magnesium;

[0087] Then the normalized thermal conductivity of copper = (401-minimum value) / (maximum value-minimum value)

[0088] =(401-160) / ((401-160)

[0089] =241 / 241

[0090] =1;

[0091] The calculation process of thermal conductivity of other materials is similar;

[0092] By collecting various material parameters, the heat transfer during the welding process can be controlled more accurately, thereby improving welding quality and efficiency.

[0093] In general, step one aims to achieve a more accurate, efficient and flexible resistance spot welding process through the detailed collection of material parameters.

[0094] Step 2: pre-set multiple types of electrode caps.

[0095] like Figure 2-6 As shown, multiple types of electrode caps are pre-set, including: the types of electrode caps are classified based on material and structure, wherein the structural categories are convex, concave and flat;

[0096] The raised electrode cap is provided with multiple layers of annular ridges 1, spiral ridges 2 or radial ridges on its contact surface with the welding material;

[0097] The recessed electrode cap is provided with a welding surface 6, an annular ridge 4, a circumference 5 and a groove 3 on its contact surface with the welding material. The groove 3 is located in the central area of ​​the contact surface. The upper edge of the recess 3 is transitionally connected with the welding surface 6 through a smooth fillet. The circumference 5 is the outer diameter of the welding surface 6. The shape of the groove 3 is a spherical surface, and the annular ridge 4 is provided on the welding surface.

[0098] The flat-head electrode cap comprises a welding contact section 7, a consumable section 8 and a mounting section 9. The contact section 7 adopts a conical structure, and the contact surface at the top of the contact section 7 is a plane. The angle between the contact section 7 and the consumable section 8 is 120° to 145°.

[0099] It should be noted that different types of electrode cap structures (convex, concave, flat head) provide different contact methods and heat transfer characteristics to meet different welding requirements.

[0100] The raised electrode cap with ridges is often used to improve welding effect and extend the service life of the electrode. For the raised electrode cap of this embodiment, it includes but is not limited to multi-layer annular ridges 1, spiral ridges 2 or radial ridge structures, and also includes the following:

[0101] Conical ridge: The top of the electrode cap is conical, which can make the arc focus more concentrated and improve the welding quality.

[0102] Cylindrical ridge: The top of the electrode cap is cylindrical, which is suitable for some special welding tasks, such as welding with higher requirements on materials.

[0103] Square ridge: The top of the electrode cap is square in shape, which can provide a larger contact area, increase the contact area with the workpiece, and improve heat transfer efficiency.

[0104] V-shaped ridge: The top of the electrode cap is V-shaped, which can make the arc focus on the weld more easily and improve the welding quality.

[0105] It should be noted that the specific ridge structure to be selected during the application process depends on the requirements of the welding task and the characteristics of the workpiece, so it needs to be selected according to the specific situation in actual application. At the same time, electrode caps from different manufacturers and brands may also have other designed ridge structures to meet different needs.

[0106] For the multi-layer annular ridge 1, it is necessary to perform a cross segmentation or a three-knife cutting on the multi-layer annular ridge 1; cutting the multi-layer annular ridge can improve the effect of resistance spot welding to a certain extent. Cross segmentation or three-knife cutting can increase the contact area of ​​the weld edge, help improve the welding quality, and reduce the spatter phenomenon generated by welding, thereby improving the efficiency and quality of welding.

[0107] Specifically, the electrode cap with a flat head structure (flat head type) has a larger contact area, which can provide a more uniform welding temperature distribution. This makes it suitable for welding thick plates or workpieces that require greater welding strength. Flat head electrode caps are usually used in situations where a stable welding process is required.

[0108] The ridged (convex) electrode cap will result in a higher temperature in the weld area because it concentrates the current into a smaller area. This can be used to weld thin-walled workpieces or where deep penetration welding is required. However, too high a temperature may cause the material around the weld to overheat, affecting the quality of the weld and the dimensional accuracy of the workpiece.

[0109] The concave structure (concave type) of the electrode cap will form a local lower temperature area during the welding process, which helps to avoid overheating and reduce deformation around the weld. This structure is suitable for welding heat-sensitive materials or welding processes that require particularly delicate processes.

[0110] Different types of electrode cap structures can provide more flexible options to adapt to welding materials of different shapes and materials, thereby improving welding quality and stability.

[0111] Step three, calculate the expected welding temperature based on the collected welding material thickness, initial temperature and various material parameters.

[0112] Step three specifically includes the following steps:

[0113] Expected temperature calculation: Establish an expected temperature calculation model. The expected temperature calculation model is ;

[0114] in, is the expected temperature value, representing the temperature required for welding; is the thermal conductivity, is the initial temperature of the welding material, is the thickness of the welding material, and They are the maximum thickness and minimum thickness of the welding material in the historical spot welding process respectively;

[0115] The thermal conductivity , Initial temperature of welding material , the thickness of welding material , the maximum and minimum thickness of the welding material during the historical spot welding process and Substitute into the expected temperature calculation model to obtain the expected temperature value ;

[0116] The expected temperature calculation model obtains the maximum and minimum thicknesses (dmax and dmin) of the welding material, as well as the current thickness (d0) from historical data. The ratio of thickness change ((d0-dmin) / (dmax-d0)) is calculated, which reflects the change of the current thickness relative to the historical thickness. The difference (k-T0) between the thermal conductivity (k) and the initial temperature (T0) is multiplied by the thickness change ratio to obtain a correction related to the thermal conductivity of the material and the temperature difference. This correction is added to the initial temperature (T0) to obtain the expected welding temperature (Ty).

[0117] The purpose of this model is to compensate for the effect of varying weld material thickness on the welding temperature, ensuring high quality welds at all thicknesses. In this way, the stability and consistency of the welding process can be improved, thereby improving weld quality.

[0118] This step achieves automated optimization of welding parameters through scientific calculation and intelligent screening, which helps to improve the efficiency and reliability of the resistance spot welding process.

[0119] Step 4: Select the corresponding type of electrode cap according to the expected welding temperature, and record the shape factor of the selected electrode cap.

[0120] The specific steps of step 4 include:

[0121] Material category screening: the expected temperature value Match the spot welding temperature range corresponding to various electrode cap materials to obtain the expected temperature value Electrode cap;

[0122] Structural category screening: based on the thickness of the welding material, the spot welding requirements and the expected temperature values Select the electrode cap with the corresponding structure;

[0123] Setting a first thickness threshold and a first temperature threshold applicable to a flat-head electrode cap; setting a second temperature threshold applicable to a convex electrode cap; setting a third temperature threshold applicable to a concave electrode cap;

[0124] If the thickness of the welding material is greater than the first thickness threshold, the expected temperature value When the temperature is lower than the first temperature threshold and the spot welding requirement is uniform welding, a flat-head electrode cap is selected;

[0125] If the expected temperature of the welding material When the temperature is higher than the second temperature threshold and the spot welding requirement is deep penetration welding, a convex electrode cap is selected;

[0126] If the expected temperature of the welding material When the temperature is higher than the third temperature threshold and the spot welding requirement is fine welding, a recessed electrode cap is selected;

[0127] The electrode cap of this category is determined and used according to the material of the selected electrode cap and the structure of the electrode cap, and the shape coefficient Ca of the electrode cap is recorded.

[0128] It should be noted that the shape coefficient Ca represents the ratio of the actual welding area of ​​the electrode cap to the original contact area during the spot welding process, which changes according to the structural category of the electrode cap and is obtained from the historical spot welding process.

[0129] Step 5: Preset the ideal welding time and calculate the ideal output current value of the spot welding equipment based on the expected welding temperature and various material parameters.

[0130] In step 5, "calculating the ideal output current value of the spot welding equipment in combination with the expected welding temperature and various material parameters" specifically includes the following formula:

[0131] ;

[0132] in, is the ideal output current value, is the thermal efficiency of the welding material, For the quality of welding materials, is the heat capacity of the welding material, The temperature change required for welding, is the resistance of the welding material; For the preset ideal welding time, Error bias term, based on experience setting; is the expected temperature value, representing the temperature required for welding; is the initial temperature of the welding material.

[0133] It should be noted that the current calculation model is based on the law of conservation of energy and Ohm's law to calculate the ideal output current value.

[0134] The quality, heat capacity and thermal efficiency of the welding material, as well as the temperature change required for welding , which affects the amount of heat required during welding. Resistance (R) is one of the properties of welding materials, which affects the voltage drop when current passes through the welding materials. The preset ideal welding time (t) is to determine and specify the time scale of the welding process.

[0135] By calculating the ideal output current value, the current controller or resistance welding machine settings can be adjusted according to the actual situation to achieve the desired welding effect. By considering factors such as the thermal efficiency, quality, heat capacity and temperature change of the welding material, the heat required during the welding process can be more accurately estimated and the current control can be adjusted accordingly to improve the welding quality and efficiency.

[0136] The error bias term (E) can be used to correct the difference between the theoretical model and the actual situation to improve the accuracy of the calculation results.

[0137] Step six, establish a historical database to classify and record the current value, pressure value and corresponding welding results of various types of welding materials in the historical spot welding process.

[0138] It should be noted that there are many ways to monitor the pressure value of metal. The following are some common methods:

[0139] Strain gauge method: Attach the strain gauge to the metal surface. When the metal is under pressure, it will deform, causing the resistance value in the strain gauge to change. By measuring the change in resistance value, the stress and pressure on the metal can be calculated.

[0140] Acoustic wave detection method: Using ultrasonic technology, a beam of high-frequency sound waves is sent on the metal surface. When the sound waves encounter internal defects or deformations of the metal, they will be reflected back. By measuring the intensity of the reflected signal, the internal stress state of the metal can be determined.

[0141] Optical microscopy method: By observing the texture, cracks, deformation and other characteristics of the metal surface under an optical microscope and combining it with the principles of material mechanics, the stress and pressure of the metal can be inferred.

[0142] Simulation method: Using finite element analysis software, through modeling and simulation calculation of metal materials, the stress and pressure distribution of metal under different loads can be obtained.

[0143] It is necessary to select appropriate methods for monitoring according to specific application scenarios and requirements to ensure the accuracy and reliability of the monitoring results.

[0144] Step seven, establish a range prediction model, train it based on the historical data in the historical database, and output multiple range prediction models after the training is completed.

[0145] Step seven specifically includes the following steps:

[0146] Establish a range prediction model, the range prediction model is:

[0147] ;

[0148] Among them, x is the input vector, that is, each set of current values ​​and pressure values ​​in the historical database; is the analysis result, that is, the corresponding welding result. If the welding result is qualified, >0, and assign according to the welding effect A decimal number in the interval (0, 1). If the welding result is unqualified, <0, and given according to the welding effect A decimal number in the interval (-1, 0); is the support vector; The category label corresponding to each support vector =+1 means the welding is qualified. =-1 means welding is unqualified; For each support vector The Lagrange multiplier of ; is the bias term, The function is used to pass the model through the sample points The distance to the decision boundary is converted into a class label to determine which side of the decision boundary the sample point is on;

[0149] Take each set of historical data in the historical database as input vector x and analysis result Substitute it into the range prediction model for training and generate the support vectors in the range prediction model corresponding to various types of welding materials , category label , Lagrange multipliers , bias term ;

[0150] Support vectors in the range prediction model for welding materials based on various materials , category label , Lagrange multipliers , bias term Output the trained multiple range prediction models.

[0151] It should be noted that is the analysis result, that is, the corresponding welding result. If the welding result is qualified, >0, and assign according to the welding effect A decimal number in the interval (0, 1). If the welding result is unqualified, <0, and assigned according to the welding effect A decimal in the interval (-1, 0), the principle of assigning a numerical value is based on the actual welding effect; in some embodiments, the effect is determined by visual inspection by a technician and then a numerical value is assigned; in other embodiments, images of the welding parts are collected by image recognition technology, and the images are analyzed in combination with a trained deep learning algorithm (recurrent neural network model, etc.) to assign a numerical value.

[0152] The range prediction model is established based on the support vector machine algorithm. The support vector machine SVM describes a SVM classifier based on the kernel function. The role of the kernel function is to allow the SVM to find the optimal classification hyperplane in the high-dimensional space without explicitly mapping the data to this high-dimensional space. The kernel function parameters can be determined by methods such as cross-validation.

[0153] Step eight, substitute the current ideal output current value and the pressure range of the spot welding equipment into the corresponding range prediction model, and output the ideal pressure range.

[0154] Step eight specifically includes the following steps:

[0155] Arrange various pressure values ​​provided by the spot welding equipment during the historical spot welding process in the historical database, and integrate the various pressure values ​​into a pressure range set;

[0156] The ideal output current value and each pressure data in the pressure range set are used as input vector x, and are substituted into the range prediction model corresponding to the welding material in turn to generate the corresponding number of analysis results. ;

[0157] For each analysis result Filter and retain For each pressure value >0, arrange the pressure values ​​according to their numerical values ​​and integrate them into the ideal pressure range.

[0158] Assume that we have a historical database that records the current value, pressure value and corresponding welding results (i.e., effect coefficient) of different welding materials during spot welding. To simplify the discussion, we take a certain welding material as an example for calculation.

[0159]

[0160] Substituting the data in the above historical database into the range prediction model for training, obtaining various parameters in the model, wherein the parameters are obtained by existing technical means (such as cross validation, least squares method, etc.), which will not be elaborated in the embodiment; outputting the trained range prediction model;

[0161] Now we want to make a prediction. Suppose we input a specific current value and a set of ideal pressure ranges, and we want the model to predict the corresponding analysis results.

[0162] Input vector: Assume that we choose a current value of 10KA and an ideal pressure range set of [50N / cm2, 60N / cm2, 70N / cm2].

[0163] Prediction model calculation: Substitute the above input vector into the support vector machine model to generate the corresponding number of analysis results f(x).

[0164] Analysis result screening: Screen each analysis result, retain each pressure value with f(x)>0, and then arrange them by numerical value and integrate them into the ideal pressure range.

[0165] The beneficial effect of this step is that through the analysis of the historical database and the training model, the best current and pressure combination can be predicted, which helps to improve the welding quality and stability and reduce the generation of defects and defective products. Make the welding process more efficient and stable, reduce adjustment time, and improve production efficiency. Avoid excessive use of resources or unnecessary equipment adjustments, thereby reducing production costs. According to the data obtained in the historical database, the appropriate pressure value can be calculated, which helps to ensure the stable operation of the spot welding equipment and extend the service life of the equipment.

[0166] Step 9: Calculate the ideal pressure range by combining the ideal pressure range with the shape coefficient, and take the median of the pressure values ​​in the ideal pressure range as the ideal pressure value.

[0167] Step nine specifically includes the following steps:

[0168] A pressure estimation model is established, and the pressure required to be applied by the spot welding equipment is determined based on the pressure estimation model; the pressure estimation model is ;in, is the i-th pressure value in the ideal pressure range, The pressure value The corresponding original contact area of ​​the electrode cap, is the shape factor of the electrode cap, is the actual contact area of ​​the electrode cap; The pressure value The corresponding pressure value is the pressure that the spot welding equipment needs to apply;

[0169] Substitute each pressure value in the ideal pressure range into the pressure estimation model in combination with the actual contact area of ​​the selected electrode cap, and output each corresponding pressure value. , integrated into the ideal pressure range;

[0170] Sort the data in the ideal pressure range from large to small or from small to large, and take the median as the ideal pressure value.

[0171] It should be noted that the median has less impact on outliers and can better reflect the trend of the data than the mean. In the obtained range data, there may be some extreme values ​​that deviate from the normal, which may have a greater impact on the calculated average, while the median can better resist this impact. The median is not affected by the shape of the distribution. Whether the data is normally distributed, skewed distributed or other distribution forms, the median can provide a relatively reasonable estimate. Therefore, when selecting the ideal pressure value, the median can be used for various types of welding materials and process parameters.

[0172] The median is relatively stable compared to the extreme value, so using the median as the ideal value can reduce fluctuations caused by noise or a small number of abnormal values ​​in historical data. This ensures that the set pressure value is relatively stable during the actual spot welding process, improving the reliability and consistency of production.

[0173] In some embodiments, the median as an ideal value also has its limitations. In some cases, if the data set has specific distribution characteristics or deviations, other statistical indicators such as the average or weighted average may be more suitable as the ideal value. Therefore, in specific applications, a suitable ideal value can be selected according to actual needs and data characteristics.

[0174] Step ten, integrating the ideal output current value, the ideal pressure value and the ideal welding time into control parameters.

[0175] Step eleven: controlling the spot welding equipment based on the control parameters to automatically complete the spot welding work.

[0176] The principle of the above embodiment is: the automatic optimization control method provided by this embodiment is an optimization design for the resistance spot welding process, and achieves the best spot welding effect based on the characteristics and material parameters of the welding material. Its principle is to collect information about the welding material, select a suitable electrode cap, calculate the ideal welding parameters, and make real-time adjustments in combination with the historical database and range prediction model, and finally achieve the purpose of automatically controlling the spot welding equipment to obtain the best welding quality.

[0177] The beneficial effects of the above embodiments are:

[0178] Improve welding quality: By selecting the appropriate electrode cap, ideal output current value and pressure range according to the characteristics and material parameters of the welding material, it is possible to ensure that the parameters during the welding process are in the optimal state, thereby improving the welding quality and stability.

[0179] Reduce human errors: By automatically controlling spot welding equipment, errors and subjective factors in human operation are reduced, and welding consistency and repeatability are improved.

[0180] Save time and cost: Through the application of predictive models and historical databases, the optimal welding parameters can be quickly determined, saving debugging time and material waste, thereby reducing production costs.

[0181] Improve production efficiency: The automatic optimization control method makes the welding process more intelligent and efficient, and improves the production efficiency and capacity utilization of the production line.

[0182] Example 2

[0183] In one embodiment, see Figure 7 , an automatic optimization control method for resistance spot welding, wherein between step 4 "selecting a corresponding type of electrode cap according to the expected welding temperature, and recording the shape coefficient of the selected electrode cap" and step 5 "presetting an ideal welding time, and calculating an ideal output current value of the spot welding device in combination with the expected welding temperature and various material parameters" further includes: detecting the centering of the group of electrode caps by a centering detection device;

[0184] The centering detection device includes:

[0185] The spot welding test piece includes: an upper test piece 12 and a lower test piece 13, the upper test piece 12 and the lower test piece 13 are of the same size (the material is not limited, and this will not be elaborated), and the upper test piece 12 and the lower test piece 13 are aligned and stacked;

[0186] The pressure sensor 14 is disposed between the upper test piece 12 and the lower test piece 13, and is used to collect the pressure value and deformation state of the upper test piece 12 and the lower test piece 13, and convert the pressure value and deformation state into an electronic image through a computer;

[0187] A guide component connected to the spot welding device 11 and used to guide the spot welding device 11 to clamp the spot welding test piece and apply pressure;

[0188] The computer is used to analyze the electronic images of the upper test piece 12 and the lower test piece 13 to determine the pressure difference, deformation difference and concentricity of the upper test piece 12 and the lower test piece 13; the pressure difference threshold, deformation difference threshold and concentricity difference threshold are pre-set, and the pressure difference, deformation difference and concentricity are respectively compared with the pressure difference threshold, deformation difference threshold and concentricity difference threshold to determine the concentricity of the electrode cap.

[0189] It should be noted that if Figure 5 As shown, the principle of the centering detection device is to detect the centering of the electrode cap 10 through the joint action of the spot welding test piece, the pressure sensor and the guide component. Specifically, when the upper test piece 12 and the lower test piece 13 are subjected to pressure, the pressure sensor 14 will collect their pressure values ​​and deformation states, and convert these data into electronic images and send them to the computer for analysis. The guide component is responsible for guiding the spot welding device 11 with the electrode cap 10 to clamp the spot welding test piece and apply pressure to ensure that the test piece is in a suitable position.

[0190] The computer will analyze the electronic images of the upper test piece 12 and the lower test piece 13 to determine the difference in pressure, deformation, and concentricity between the two. A pre-set difference threshold is used to compare the analysis results to determine the degree of alignment of the electrode cap. The benefits of this method include:

[0191] Automation: By using computers to analyze data and set thresholds, automatic detection of the neutrality of the electrode cap is achieved, improving production efficiency.

[0192] Accuracy: Using pressure sensors and deformation state data, the alignment of the electrode cap can be evaluated more accurately, avoiding human errors.

[0193] Instant adjustment: Once the computer detects that the electrode cap is not aligned, it can make adjustments and warnings immediately to ensure welding quality.

[0194] In order to further optimize the above embodiment, the centering of the electrode cap is detected by a centering detection device, which further includes:

[0195] Controlling the spot welding device 11 to apply pressure to the spot welding test piece at an ideal pressure value;

[0196] The difference between the actual pressure value and the ideal pressure value received by the spot welding test piece is analyzed to obtain an analysis result, and the abnormal conditions of the spot welding device 11 and the electrode cap 10 are determined based on the analysis result.

[0197] It should be noted that the principle of this embodiment is to determine whether the working state of the electrode cap 10 is normal by comparing the actual pressure value of the spot welding test piece with the preset ideal pressure value. The specific steps are as follows:

[0198] 1. Control the spot welding equipment 11 to apply pressure to the spot welding test piece according to a preset ideal pressure value.

[0199] 2. Monitor the actual pressure value of the spot welding specimen in real time and compare it with the ideal pressure value.

[0200] 3. Analyze the difference between the actual pressure value and the ideal pressure value to determine whether there is any abnormality in the electrode cap 10, such as pressure instability, deviation, etc.

[0201] This embodiment can timely detect abnormal conditions of the electrode cap 10 by real-time monitoring of the actual pressure value to avoid bad welding. Possible abnormalities of the electrode cap 10 can be detected in advance, and measures can be taken to prevent failures and reduce downtime.

[0202] In order to further optimize the above embodiment, after the spot welding is completed, step 11 "controlling the spot welding equipment to automatically complete the spot welding work based on the control parameters" also includes:

[0203] After the spot welding is completed, the ideal output current value, ideal pressure value and spot welding effect of this spot welding are stored as historical data in the historical database and used as training data to update the range prediction model.

[0204] It should be noted that after each spot welding is completed, the ideal output current value, ideal pressure value and spot welding effect are recorded and stored in the historical database. These historical data are used to update and optimize the prediction model so as to better control the welding parameters and improve the welding quality in the future spot welding process.

[0205] This embodiment can improve the accuracy and adaptability of the model by continuously collecting historical data to train the prediction model, thereby improving the automation level and quality control capability of the spot welding process; by continuously updating the prediction model, continuous optimization of welding parameters can be achieved, and production efficiency and product quality can be improved;

[0206] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0207] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. An automatic optimization control method for resistance spot welding, characterized in that: include: Collect the thickness, initial temperature and various material parameters of welding materials; Multiple types of electrode caps are pre-set; Calculating the expected welding temperature based on the collected thickness, initial temperature and various material parameters of the welding material; Selecting a corresponding type of electrode cap according to the expected welding temperature, and recording a shape factor of the selected electrode cap; Presetting an ideal welding time, and calculating an ideal output current value of the spot welding device in combination with the expected welding temperature and various material parameters; Establish a historical database to classify and record the current value, pressure value and corresponding welding results of various types of welding materials in the historical spot welding process; Establishing a range prediction model, and training it based on the historical data in the historical database, and outputting a plurality of the range prediction models after training; Substituting the current ideal output current value and the pressure range of the spot welding device into the corresponding range prediction model, and outputting the ideal pressure range; Calculate the ideal pressure range by combining the ideal pressure range with the shape coefficient, and take the median of the pressure values ​​in the ideal pressure range as the ideal pressure value; Integrating the ideal output current value, the ideal pressure value and the ideal welding time into control parameters; The spot welding equipment is controlled based on the control parameters to automatically complete the spot welding work.

2. The automatic optimization control method for resistance spot welding according to claim 1, characterized in that: The material parameters include: The quality, heat capacity, thermal efficiency, maximum and minimum thickness of the welding material during the historical spot welding process, and thermal conductivity of the welding material; The presetting of multiple types of electrode caps includes: the types of electrode caps are classified based on material and structure, wherein the structural categories are convex type, concave type and flat head type; The contact surface between the protruding electrode cap and the welding material is provided with multiple layers of annular ridges, spiral ridges or radial ridges; The contact surface between the recessed electrode cap and the welding material is provided with a welding surface, an annular ridge, a circumference and a groove, the groove is located in the central area of ​​the contact surface, the upper edge of the groove is transitionally connected with the welding surface through a smooth fillet, and the circumference is the outer diameter of the welding surface; the shape of the groove is a spherical surface, and the annular ridge is provided on the welding surface; The flat-head electrode cap comprises a welding contact section, a consumable section and a mounting section. The contact section adopts a conical structure, and the contact surface at the top of the contact section is a plane. The angle between the contact section and the consumable section is 120° to 145°.

3. The automatic optimization control method for resistance spot welding according to claim 2, characterized in that: The method of calculating the expected welding temperature based on the thickness, initial temperature and various material parameters of the collected welding material, selecting an electrode cap of a corresponding type according to the expected welding temperature, and recording the shape coefficient of the selected electrode cap specifically includes the following steps: Expected temperature calculation: Establish an expected temperature calculation model, the expected temperature calculation model is ; in, is the expected temperature value, representing the temperature required for welding; is the thermal conductivity, is the initial temperature of the welding material, is the thickness of the welding material, and They are the maximum thickness and minimum thickness of the welding material in the historical spot welding process respectively; The thermal conductivity coefficient collected , Initial temperature of welding material , the thickness of welding material , the maximum and minimum thickness of the welding material during the historical spot welding process and Substitute into the expected temperature calculation model to obtain the expected temperature value ; Material category screening: the expected temperature value Match the spot welding temperature range corresponding to each type of electrode cap material to obtain the expected temperature value. The electrode cap; Structural category screening: based on the thickness of the welding material, the spot welding requirements and the expected temperature values Select the electrode cap with the corresponding structure; Setting a first thickness threshold and a first temperature threshold applicable to the flat-head electrode cap; setting a second temperature threshold applicable to the convex electrode cap; setting a third temperature threshold applicable to the concave electrode cap; If the thickness of the welding material is greater than the first thickness threshold, the expected temperature value When the temperature is lower than the first temperature threshold and the spot welding requirement is uniform welding, the flat-head electrode cap is selected; If the expected temperature of the welding material When the temperature is higher than the second temperature threshold and the spot welding requirement is deep penetration welding, the convex electrode cap is selected; If the expected temperature of the welding material When the temperature is higher than the third temperature threshold and the spot welding requirement is fine welding, the recessed electrode cap is selected; The electrode cap of this category is determined and used according to the material of the selected electrode cap and the structure of the electrode cap, and the shape coefficient Ca of the electrode cap is recorded.

4. The automatic optimization control method for resistance spot welding according to claim 1, characterized in that: The preset ideal welding time and the ideal output current value of the spot welding device are calculated in combination with the expected welding temperature and various material parameters using the following formula: ； in, is the ideal output current value, is the thermal efficiency of the welding material, For the quality of welding materials, is the heat capacity of the welding material, The temperature change required for welding, is the resistance of the welding material; For the preset ideal welding time, Error bias term, based on experience setting; is the expected temperature value, representing the temperature required for welding; is the initial temperature of the welding material.

5. The automatic optimization control method for resistance spot welding according to claim 1, characterized in that: The step of establishing a range prediction model, training the model based on the historical data in the historical database, and outputting a plurality of the range prediction models after training specifically comprises the following steps: Establish the range prediction model, the range prediction model is: ； Wherein, x is an input vector, i.e., each set of current values ​​and pressure values ​​in the historical database; is the analysis result, that is, the corresponding welding result. If the welding result is qualified, >0, and assign according to the welding effect A decimal number in the interval (0, 1). If the welding result is unqualified, <0, and assigned according to the welding effect A decimal number in the interval (-1, 0); is the support vector; For each support vector, the corresponding category label is =+1 means the welding is qualified. =-1 means welding is unqualified; For each support vector The Lagrange multiplier of ; is the bias term, The function is used to pass the model through the sample points The distance to the decision boundary is converted into a class label to determine which side of the decision boundary the sample point is on; Each set of historical data in the historical database is used as the input vector x and the analysis result Substitute it into the range prediction model for training, and generate the support vectors in the range prediction model corresponding to various types of welding materials , category label , Lagrange multipliers , bias term ; Support vectors in the range prediction model corresponding to the welding materials of each type of material , category label , Lagrange multipliers , bias term Output the trained multiple range prediction models.

6. The automatic optimization control method for resistance spot welding according to claim 5, characterized in that: Substituting the current ideal output current value and the pressure range of the spot welding equipment into the corresponding range prediction model to output the ideal pressure range specifically includes the following steps: Arranging various pressure values ​​provided by the spot welding device during historical spot welding processes in the historical database, and integrating the various pressure values ​​into a pressure range set; The ideal output current value and each pressure data in the pressure range set are used as input vector x, and are sequentially substituted into the range prediction model corresponding to the welding material to generate a corresponding number of analysis results. ; For each analysis result Filter and retain >0, and arranging the pressure values ​​according to their numerical values ​​and integrating them into the ideal pressure range.

7. The automatic optimization control method for resistance spot welding according to claim 1, characterized in that: The step of calculating the ideal pressure range by combining the ideal pressure range with the shape coefficient and taking the median of the pressure values ​​in the ideal pressure range as the ideal pressure value specifically comprises the following steps: A pressure estimation model is established, and the pressure to be applied by the spot welding equipment is determined based on the pressure estimation model; the pressure estimation model is ;in, is the i-th pressure value in the ideal pressure range, The pressure value The corresponding original contact area of ​​the electrode cap, is the shape factor of the electrode cap, is the actual contact area of ​​the electrode cap; The pressure value The corresponding pressure value, i.e., the pressure that the spot welding equipment needs to apply; Substitute each pressure value in the ideal pressure range into the pressure estimation model in combination with the actual contact area of ​​the selected electrode cap, and output each corresponding pressure value. , integrated into the desired pressure range; The data in the ideal pressure range are sorted from large to small or from small to large, and the median is taken as the ideal pressure value.

8. The automatic optimization control method for resistance spot welding according to claim 1, characterized in that: Between the step of "selecting the electrode cap of the corresponding type according to the expected welding temperature, and recording the shape coefficient of the selected electrode cap" and the step of "presetting the ideal welding time, and calculating the ideal output current value of the spot welding device in combination with the expected welding temperature and various material parameters", it also includes: detecting the centering of the group of electrode caps by a centering detection device; The centering detection device comprises: A spot welding test piece, the spot welding test piece comprising: an upper test piece and a lower test piece, the upper test piece and the lower test piece are of the same size, and the upper test piece and the lower test piece are aligned and stacked; A pressure sensor is disposed between the upper test piece and the lower test piece, and is used to collect the pressure value and deformation state of the upper test piece and the lower test piece, and convert the pressure value and deformation state into an electronic image through a computer; A guiding component connected to the spot welding device and used to guide the spot welding device to clamp the spot welding test piece and apply pressure; The computer is used to analyze the electronic images of the upper test piece and the lower test piece to determine the pressure difference, deformation difference and concentricity of the upper test piece and the lower test piece; pre-set the pressure difference threshold, deformation difference threshold and concentricity difference threshold, and respectively compare the pressure difference, deformation difference and concentricity with the pressure difference threshold, deformation difference threshold and concentricity difference threshold to determine the concentricity of the electrode cap.

9. The automatic optimization control method for resistance spot welding according to claim 8, characterized in that: The method of detecting the centering of the electrode cap by a centering detection device further comprises: Controlling the spot welding equipment to apply pressure to the spot welding test piece at an ideal pressure value; The difference between the actual pressure value and the ideal pressure value applied to the spot welding test piece is analyzed to obtain an analysis result, and the abnormal conditions of the spot welding equipment and the electrode cap are determined based on the analysis result.

10. The automatic optimization control method for resistance spot welding according to claim 1, characterized in that: After the step of "controlling the spot welding equipment to automatically complete the spot welding work based on the control parameters", the method further includes: After the spot welding is completed, the ideal output current value, the ideal pressure value and the spot welding effect of the spot welding are stored as historical data in the historical database, and used as training data to update the range prediction model.

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