Method and apparatus for spot welding

Abstract

The present disclosure relates to a method and apparatus for spot welding, the method comprising: applying, by a controller, a preset amount of welding heat input to a welding apparatus; the controller applies the preset welding heat input quantity to the welding position by moving the welding device; measuring, by an encoder, a height change of the welding position to which the preset welding heat input amount is applied; comparing, by the controller, a real-time height change slope of the welding position measured by the encoder with a slope set in the controller; and determining, by the controller, the welding quality by comparing the calculated optimal target heat input and the actual welding heat input.

Description

Technical Field

[0001] This disclosure relates to methods and apparatus for spot welding, and more particularly to methods and apparatus for spot welding in which an optimal welding heat input is calculated and the quality of the final welded product is determined by comparing the calculated optimal welding heat input with the actual applied heat input. Background Technology

[0002] Resistance spot welding is a welding method in which an electric current is applied while the target materials are pressed against welding electrodes, and the materials are joined together by melting them using the resistive heat generated in the process. The resistance changes dynamically during this process due to the correlation between two phenomena: the increase in resistance caused by the rise in base material temperature due to the resistive heat generated when the welding current passes through the material; and the decrease in resistance caused by the increase in conductive cross-sectional area due to the growth of the weld nuggets after the base material melts and forms weld nuggets. This is called dynamic resistance.

[0003] Furthermore, various methods currently utilize equipment to inspect the quality of resistance spot welds. These methods include those that inspect quality in offline mode by analyzing the weld nugget diameter using ultrasonic waveforms, and those that estimate strength quality by measuring the depth of weld indentations. However, reliable data is difficult to ensure due to variations in external conditions during the welding process, thus hindering reliable weld quality inspections. Moreover, in most cases, because the inspection methods are not performed in real-time but rather through offline sample testing, there is a risk of large-scale resistance spot weld quality defects.

[0004] Therefore, the need for welding equipment that can accurately calculate the amount of welding heat input applied to the welding position and automatically adjust welding conditions persists. Summary of the Invention

[0005] This disclosure is configured to measure the distance between two electrodes of a welding apparatus via an encoder and to provide an optimal amount of welding heat input using the measured distance.

[0006] Another object of this disclosure is to provide a method and apparatus for spot welding to determine a welding result of normal quality by measuring the completion time of weld nugget formation after welding is completed.

[0007] The objectives of this disclosure are not limited to those described above, and other objectives not described herein may be understood from the following description and will become clear from implementation of this disclosure. Furthermore, the objectives of this disclosure will be achieved through the configurations and combinations thereof described in the claims.

[0008] The spot welding method and apparatus for achieving the purposes of this disclosure include the following configuration.

[0009] According to one aspect of this disclosure, a method for spot welding includes the following steps: applying a preset welding heat input amount to a welding device by a controller; applying the preset welding heat input amount to a welding position by moving the welding device by the controller; measuring the height change of the welding position to which the preset welding heat input amount has been applied by an encoder; calculating an optimal target heat input amount by the controller by comparing the slope of the real-time height change of the welding position measured by the encoder with a slope set in the controller; and determining the welding quality by comparing the calculated optimal target heat input amount with the actual welding heat input amount.

[0010] The controller can apply a preset welding heat input corresponding to the welding substrate positioned at the welding device.

[0011] The controller can calculate the optimal target heat input by compensating for the current applied to the welding position.

[0012] As another aspect, the spot welding method includes: applying a preset welding heat input corresponding to the welding substrate positioned in the welding device to the welding device by a controller; applying the preset welding heat input to the welding position by the controller moving the welding device; measuring the height change of the welding position to which the preset welding heat input has been applied by an encoder; and compensating the current value applied to the welding position by comparing the real-time height change slope of the welding position measured by the encoder with a slope set in the controller to provide an optimal target heat input.

[0013] Furthermore, in the step of applying a preset welding heat input amount corresponding to the welding substrate positioned at the welding device by the controller to the welding device, the preset welding heat input amount can be calculated based on existing data stored according to the completed welding.

[0014] Furthermore, in the step of compensating the current value applied to the welding position to provide an optimal target heat input by comparing the real-time height change slope of the welding position measured via an encoder with a slope set in the controller, the method may include: determining whether the height change slope of the welding position is greater than a set slope that does not produce spatter; when the height change slope of the welding position is greater than the set slope that does not produce spatter, increasing the current value applied to the welding apparatus; determining whether the height change slope of the welding position is a set slope that produces spatter based on the increased current value; and when the height change slope of the weld joint is below the set slope that produces spatter, setting an optimal target welding heat input by including a first margin value in the increased current value.

[0015] Furthermore, when compensating for the current applied to the welding position to provide an optimal target heat input by comparing the real-time height change slope of the welding position measured via an encoder with a slope set in the controller, the method may include: determining whether the height change slope of the welding position is below a set slope that produces spatter; when the height change slope of the welding position is below a set slope that produces spatter, reducing the current applied to the welding apparatus; determining whether the height change slope of the welding position is greater than a set slope that does not produce spatter based on the reduced current value; and when the height change slope of the welding position is greater than a set slope that does not produce spatter, setting the optimal target heat input by adding a second margin value to the reduced current value.

[0016] Furthermore, in the step of compensating for the current value applied to the welding position by comparing the slope of the height change of the welding position measured by the encoder with the slope set in the controller, the method may also include: the controller evaluating the welding quality status for which the compensated current value has been applied.

[0017] Furthermore, in the step of evaluating the welding quality status with the applied compensation current value by the controller, the method may include: measuring the height change of the welding position by an encoder during welding; measuring the weld nugget formation completion time at the location where the measured height change of the welding position is the largest; and calculating the actual applied heat input based on the measured weld nugget formation completion time.

[0018] Furthermore, in the step of calculating the actual applied heat input based on the measured weld nugget formation completion time, the method may include: calculating the actual heat input applied to the welding position based on the welding dynamic resistance calculated according to the voltage drop detected during the welding process, the current applied to the welding apparatus, and the weld nugget formation completion time; determining whether the actual applied heat input is within the normal range; and determining a quality defect when the actual applied heat input is outside the normal range.

[0019] Furthermore, in the step of calculating the actual welding heat input based on the measured weld nugget formation completion time, the method may include having the controller calculate the actual welding heat input applied to the welding apparatus by performing a definite integral on the applied current and the calculated dynamic resistance based on the weld nugget formation completion time.

[0020] Furthermore, in the step of compensating the current value applied to the welding position to provide the optimal target heat input by comparing the slope of the height change of the welding position measured by the encoder with the slope set in the controller, the set slope can be set by the machine learning algorithm of the analysis processor.

[0021] Furthermore, in the step of compensating the current value applied to the welding position to provide an optimal target heat input by comparing the slope of the height change of the welding position measured via the encoder with the slope set in the controller, the method may include storing the calculated β peak of the dynamic resistance and the calculated optimal target heat input in the controller.

[0022] According to another aspect of this disclosure, an apparatus for spot welding includes: a welding device; a controller configured to apply a preset welding heat input to the welding device and to apply the preset welding heat input to a welding position by moving the welding device; and an encoder configured to measure the height change of the welding position to which the preset welding heat input has been applied; wherein the controller is configured to calculate an optimal target heat input by comparing the slope of the real-time height change of the welding position measured by the encoder with a slope set in the controller; and wherein the controller is configured to determine the welding quality by comparing the calculated optimal target heat input with the actual welding heat input.

[0023] In this device, the controller can apply a preset welding heat input corresponding to the welding substrate positioned at the welding device.

[0024] In this device, the controller can calculate the optimal target heat input by compensating for the current value applied to the welding position.

[0025] According to this disclosure, the following effects can be achieved from the configurations, combinations, and operational relationships described below.

[0026] This disclosure has the following effect: it provides an efficient method for spot welding by calculating the optimal heat input based on the real-time distance change between the two electrodes of the welding apparatus according to the initial heat input applied to the welding apparatus.

[0027] Furthermore, this disclosure has the effect of providing an effective method for spot welding that can minimize the defect rate because the quality of the weld after welding can be determined by comparing the actual applied heat input with the target heat input calculated based on the weld nugget formation completion time at the end of the welding process. Attached Figure Description

[0028] Figure 1 A configuration diagram of a welding apparatus as an embodiment of this disclosure is shown;

[0029] Figure 2 A flowchart of a spot welding method according to an embodiment of the present disclosure is shown;

[0030] Figure 3 A flowchart of the optimal welding condition algorithm for a spot welding method as an embodiment of this disclosure is shown.

[0031] Figure 4A Height-time data are shown during normal welding performed according to embodiments of this disclosure;

[0032] Figure 4B Height-time data are shown when abnormal welding is performed according to an embodiment of this disclosure;

[0033] Figure 5 The data on heat input during normal welding performed according to embodiments of this disclosure are shown; and

[0034] Figure 6 The data used to calculate the amount of heat input is shown, which is then applied in practice to determine the quality of the weld. Detailed Implementation

[0035] It is to be understood that the term “vehicle” or “of a vehicle” or other similar terms as used herein include motor vehicles (generally such as passenger cars including sport utility vehicles (SUVs), buses, trucks, and various commercial vehicles), boats (including various ships and vessels), aircraft, etc., and include hybrid vehicles, electric vehicles, plug-in hybrid electric vehicles, hydrogen-powered vehicles, and other vehicles with alternative fuels (e.g., fuels obtained from resources other than petroleum). As mentioned herein, a hybrid vehicle is a vehicle with two or more power sources, such as a gasoline-powered and an electric-powered vehicle.

[0036] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. As used herein, unless the context clearly indicates otherwise, the singular forms “a,” “an,” and “the” are intended to also include the plural forms. It should also be understood that when the terms “comprising” and / or “including” are used in this specification, they specify the presence of the stated features, integrals, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or combinations thereof. As used herein, the term “and / or” includes any and all combinations of one or more of the associated listed items. Throughout the specification, unless explicitly stated otherwise, the word “comprising” and variations such as “including” or “having” will be understood to imply inclusion of the stated elements, but do not exclude any other elements. Furthermore, the terms “unit,” “component,” “part,” and “module” described in the specification mean a unit for performing at least one function and operation, and can be implemented by hardware components or software components and combinations thereof.

[0037] Furthermore, the control logic of this disclosure can be embodied in a non-volatile computer-readable medium containing executable program instructions that can be executed by a processor, controller, etc. Examples of computer-readable media include, but are not limited to, ROM, RAM, optical disc (CD)-ROM, magnetic tape, floppy disk, flash drive, smart card, and optical data storage device. The computer-readable medium can also be distributed across a network-connected computer system, enabling it to be stored and executed in a distributed manner, for example, via a telematics server or a controller area network (CAN).

[0038] In the following, embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. Embodiments of the present disclosure may be modified in various ways, and the scope of the present disclosure should not be construed as limited to the embodiments described below. These embodiments are provided to provide a more complete explanation of the present disclosure to those skilled in the art.

[0039] The terminology used in this disclosure is for describing specific exemplary embodiments only and is not intended to limit the embodiments. Unless the context clearly indicates otherwise, the singular form is intended to include the plural form.

[0040] Some components are given the terms “first,” “second,” etc., to distinguish them throughout the specification because they have the same name, but they are not necessarily limited to the order in the following description.

[0041] Furthermore, in this specification, various embodiments can be implemented as software (e.g., a program) including commands stored in a machine-readable storage medium (e.g., a computer). A machine is an apparatus that can invoke stored commands from a storage medium and operate according to the invoked commands; the machine may include electronic devices (e.g., servers) according to the embodiments described herein. Commands may include code created or executed by a compiler or interpreter. Machine-readable storage media can be provided in non-transitory storage medium types. The term "non-transitory" means that the storage medium does not include signals and is tangible, regardless of whether data is stored semi-permanently or temporarily in the storage medium.

[0042] Furthermore, according to embodiments of this disclosure, the methods according to the various embodiments disclosed herein can be included in a computer program product. The computer program product can be traded as an item between a seller and a buyer. The computer program product can be distributed on a device-readable storage medium (e.g., a compact disc read-only memory (CD-ROM)) or via an application store on a network (e.g., the Play Store). TMWhen computer program products are distributed on the web, at least a portion of the computer program products may be temporarily stored or created in a storage medium, such as the memory of a manufacturer's server, an application store's server, or a relay server.

[0043] In the following description, embodiments will be described in detail with reference to the accompanying drawings, and in the following description of the drawings, the same reference numerals are given to the same parts and repeated descriptions are omitted.

[0044] Figure 1 A configuration diagram for performing spot welding as an embodiment of this disclosure is shown.

[0045] This disclosure relates to a method for spot welding, the method including a welding apparatus 10 for performing welding and a welding target substrate placed on the welding apparatus 10, and including a controller 200 that can calculate and store dynamic resistance generated during the welding process and current applied to the welding apparatus 10, optimal target heat input, actual welding heat input applied to the welding apparatus in real time, weld nugget generation completion time, etc.

[0046] The controller 200 includes: a servo motor control processor 210, which can control the servo motors of the robot arm constituting the welding device 10; a data file storage server 220, which can store the current and voltage applied through the welding device 10, as well as the distance data between the two electrodes of the welding device obtained by the encoder 100 located in the welding device 10, the weld nugget formation completion time, etc.; and an analysis processor 230, which can calculate the optimal target heat input applied to the welding device 10 based on the distance change measured by the encoder 100.

[0047] The analysis processor 230 includes data such as the distance slope between electrodes measured by encoder 100, the amount of heat input applied in real time based on the weld nugget formation completion time, and the target amount of heat input to perform machine learning algorithms.

[0048] In this disclosure, the resistance changes dynamically through the correlation between two phenomena: an increase in resistance due to the rise in substrate temperature caused by the resistive heat generated when the welding current passes through the material; and a decrease in resistance due to the increase in the conductive cross-sectional area. This resistance is referred to as the dynamic resistance. Furthermore, the dynamic resistance is calculated by continuously measuring the current I and voltage during welding.

[0049] In the dynamic resistance setting, the maximum resistance value after the set soldering time has elapsed is set as the reference dynamic resistance peak value Bref. The set soldering time can be set from 20ms to 40ms, and the reference dynamic resistance peak value Bref can be set to 220μΩ.

[0050] Furthermore, as an embodiment of this disclosure, the weld nugget formation completion time can be measured by the encoder 100, the dynamic resistance at each time point per unit time according to the weld nugget formation completion time can be calculated, and the actual welding heat input applied to the welding apparatus 10 can be calculated by performing a definite integral over time based on these dynamic resistances.

[0051] An electric motor unit includes a servo motor for operating a robot. The servo motor is the robot's actuator and is driven based on control signals for robot operation of a welding apparatus output from a controller 200.

[0052] In addition, the motor unit may also include a proportional-integral-derivative (PID) filter unit and a pulse generator. The PID filter unit may have the following functions: calculating compensation information based on the actual rotational position information detected by the digital encoder 100 and the robot operation control signal output from the controller 200. The pulse generator may have the function of generating pulse signals based on the output of the PID filter unit.

[0053] The encoder 100 is configured for the servo motors of each specific axis of the robot and includes the functionality to link the motor unit and the robot operation controller 200. The encoder 100 can detect digital encoder values ​​from an output signal representing the actual position information of the servo motor during operation; these digital encoder values ​​are the pulse values ​​for each rotation. Furthermore, the encoder 100 can be used to transmit the digital encoder values ​​to the controller 200 using a ZigBee wireless communication method. Additionally, the encoder 100 also has the function of receiving robot operation control signals from the controller 200 via a ZigBee wireless communication method.

[0054] At least one encoder 100 of this disclosure may be located at a first electrode on the upper part of the robot arm of the welding apparatus performing welding, or at a second electrode on the lower part of the robot arm. Furthermore, the encoder 100 can measure the distance between the first and second electrodes, and in embodiments of this disclosure, the encoder 100 can measure thickness change data at the welding position in real time and transmit this thickness change data to the controller 200.

[0055] Furthermore, the encoder 100 can measure the height change at the welding position in real time, and the measured height may be reduced due to spatter generated at the welding position. That is, due to the generation of spatter, the distance between the first electrode and the second electrode decreases, and the displacement slope calculated by the controller 200 may be negative.

[0056] The welding position may include a preset area located between the first electrode and the second electrode, and welding can be performed by controlling the motor unit to make contact between the first electrode and the second side of the substrate opposite to the first side that contacts the second electrode.

[0057] The heat input applied by the welding device 10 may include a heat input preset in the controller 200 based on the substrate being initially welded. This preset heat input is output by the analysis processor 230 through machine learning based on existing data after welding the same substrate, and the output data can be stored in the data file storage server 220 of the controller 200. Therefore, the controller 200 is configured to apply the pre-stored heat input to the welding device 10 when the welding device 10 applies input to the same substrate.

[0058] Furthermore, during welding, the analysis processor 230 of the controller 200 can calculate the optimal target heat input based on the applied heat input. The optimal target heat input can be set as the boundary between the high heat input stage and the medium heat input stage based on the actual welding "Lobe" curve.

[0059] The controller 200 may include a servo motor processor 210 and a data file storage server 220. The servo motor processor controls the robotic arm of the welding apparatus 10, and the data file storage server 220 stores data measured during welding. The data file storage server 220 may store data such as current, voltage, heat input, dynamic resistance, and weld nugget formation completion time during the operation of the welding apparatus 10, and this data stored on the server is transmitted to an analysis processor 230 for welding quality analysis. The analysis processor 230 of the controller 200 can collect data for determining the optimal heat input by performing machine learning, and can calculate correction values ​​for providing the optimal heat input based on the measurement slope of the current-time graph. That is, the analysis processor 230 determines the real-time optimal heat input for welding and reflects the correction value corresponding to the determined heat input to the heat input applied to the welding apparatus 10.

[0060] Furthermore, the controller 200 includes a step of comparing the actual applied heat input with the target heat input to determine the quality of the welding apparatus 10 to which the target heat input was applied. The controller 200 can calculate the real-time heat input by integrating the dynamic resistance and current based on the weld nugget formation completion time, and can determine the welding quality by comparing the calculated real-time heat input with the target heat input.

[0061] The controller 200 can be linked to the encoder 100 using wireless or wired communication methods. The controller 200 has a central processing unit and can generate robot operation control signals to drive servo motors of specific axes, thereby causing movement of multiple axes of the robot. The robot operation control signals generated by the controller 200 are transmitted via wired or wireless communication to the encoder 100 of each motor unit set for each robot axis, thereby driving the servo motor of a specific axis according to the robot operation control signals.

[0062] As for the encoder 100 that drives the servo motor in conjunction with the controller 200, the encoder 100 detects digital encoder values ​​from the output signal representing the actual position information during the operation of the servo motor. These digital encoder values ​​are the pulse values ​​for each rotation. In this case, the encoder 100 can use the ZigBee wireless communication method to transmit the digital encoder values ​​detected from the servo motor of a specific axis of the robot to the controller 200.

[0063] Subsequently, the controller 200, having received these digital encoder values, generates robot operation control signals based on these values ​​to control the robot's operation. The controller 200, which generates the robot operation control signals, transmits the robot operation control signals wirelessly to the encoder 100 attached to the servo motor of a specific axis.

[0064] Furthermore, the encoder 100, which receives the robot operation control signal, can use the robot operation control signal to actively drive the servo motor of a specific axis of the robot through a processor arranged in the wireless communication module.

[0065] In this disclosure, encoder 100 can control robot operations and can measure the distance between the first and second electrodes in real time and transmit this distance to controller 200. In embodiments of this disclosure, encoder 100 can be configured to have a transmission speed of 2 ms. Furthermore, the distance between the first and second electrodes measured by encoder 100 can be transmitted to analysis processor 230 via Ethernet communication. Analysis processor 230 is configured to calculate the optimal welding heat input based on the height change received by encoder 100, according to the displacement slope, and is configured to compensate for the actual heat input applied during welding.

[0066] Figure 2 A flowchart of a spot welding method according to an embodiment of the present disclosure is shown.

[0067] First, the controller 200 applies a preset welding heat input amount corresponding to the welding substrate positioned at the welding device 10 to the welding device 10. In this case, the welding substrate can be set according to input from the user, and the preset welding heat input amount applied to the welding device 10 can be the heat input amount stored in the data file storage server 220 of the controller 200 according to the existing welding steps (step S10).

[0068] In addition, the controller 200 is configured to apply a preset welding heat input amount by moving the first electrode or the second electrode of the welding device 10 (step S20).

[0069] Subsequently, the method includes the step of the controller 200 measuring the height change of the welding position in real time via the encoder 100 (step S30). In this process, the encoder 100 measures the displacement (height) of the weld point, and the analysis processor 230 can determine the slope based on the displacement using a machine learning algorithm (step S30).

[0070] In addition, the controller 200 can receive the current, dynamic resistance and actual welding heat input at the weld joint during welding, and can store the data in the data file storage server 220.

[0071] Subsequently, the controller 200 provides the target heat input by comparing the real-time height change of the welding position measured by the encoder 100 with the slope set in the controller 200 to compensate for the current value applied to the welding position (step S40).

[0072] Subsequently, as a welding quality assessment step, a step is included to determine whether the actual applied heat input is 90% to 110% of the target heat input (step S50), and when the actual welding heat input meets this condition, the corresponding weld is determined to be normal. Simultaneously with the actual welding, the weld nugget formation completion time is measured by the encoder 100, and the actual welding heat input can be calculated by definite integral of the dynamic resistance measured per unit time and the applied current value based on the weld nugget formation completion time.

[0073] Furthermore, it is determined whether the actual welding heat input applied to the welding apparatus is within 90% to 110% of the optimal target heat input (S50). Additionally, when the actual welding heat input falls outside this range, the controller issues a faulty welding alarm and compensates for the current value, thus maintaining the actual welding heat input within the optimal target heat input range. This ensures the normal quality of the weld is maintained.

[0074] By comparing the calculated target heat input with the actual welding heat input in this way, the quality of the weld can be determined, and the controller 200 can issue an alarm that the welding device 10 has a problem or that the weld is defective.

[0075] Figure 3 The process of determining the optimal welding conditions algorithm for calculating the target heat input (step S40) as an embodiment of this disclosure is shown.

[0076] The process of determining the optimal welding conditions algorithm includes calculating the target heat input amount via controller 200. That is, this is a step of providing the target heat input amount by compensating for the current value applied to the welding apparatus, wherein the height change amount (slope) measured by encoder 100 is determined.

[0077] The determination process includes the following steps: determining whether the slope of the height change of the welding position measured in real time by the encoder 100 is greater than the preset slope in the controller 200 that does not produce spatter (step S100).

[0078] When the height change slope of the welding position is greater than the set slope that does not produce spatter, the current value applied to the welding device 10 is increased, and the actual amount of heat input applied is measured (step S110). The determination process includes determining whether the height change slope of the weld point corresponding to the increased current value measured by the encoder 100 is below the set slope that produces spatter (step S120).

[0079] The determination process includes the following steps: when the slope of the weld height change is below the set slope for generating spatter, an optimal target heat input is set by adding a first margin value to the increased current value (step S130). As an embodiment of this disclosure, the set slope for generating spatter can be calculated as zero because the height change of the substrate becomes zero when spatter begins to occur. Furthermore, the first margin value can be set to 0.98, and this is to prevent the risk of spatter from occurring from the substrate when the current value corresponding to the set slope for generating spatter is calculated as the actual welding heat input.

[0080] In other words, when the welding apparatus 10 has the first displacement slope that does not produce spatter, the welding apparatus 10 performs the following steps: by increasing the applied current by 2% at a time, a target heat input that is close to the slope that produces spatter is calculated, and the target heat input is compensated using the actual welding heat input.

[0081] Conversely, the controller 200 determines whether the slope of the height change at the welding position is below a set slope that produces spatter (step S200). This means that the initially applied preset heat input is the condition for the substrate to produce spatter.

[0082] When the slope of the height change at the welding position is below the set slope that generates spatter, the determination process includes the following steps: the controller 200 reduces the current applied to the welding apparatus 10 and calculates the heat input (step S210). This determination process includes the following steps: determining whether the height change at the welding position is greater than the set slope that does not generate spatter based on the reduced current value (step S220). In this case, the set slope that generates spatter can be set to zero and can be determined based on an inflection point where the height change slope initially calculated by the encoder 100 changes to zero in the case of initial spatter generation. Therefore, the calculated heat input is determined without generating spatter.

[0083] When the slope of the height change at the welding position is greater than the set slope, the determination process includes the following steps: setting the target heat input by adding a second margin value to the reduced current value (step S230). In this case, the second margin value can be set to 1.02, and the reduced current value can be a current that is 2% lower than the currently applied current for each determination.

[0084] The applied current value can be analyzed as the same concept as the heat input.

[0085] Figure 4A The data shows the height variation when a current with optimal heat input is applied. Figure 4B Data on height variations based on splashing is shown. Furthermore, Figure 5 The boundary values ​​for the high heat input region and the medium heat input region, which are considered normal welding zones, are shown.

[0086] As shown in the figure Figure 4A The changes in height over time as a normal welding condition are shown, as well as the data when applying the boundary heat input ranges of high and medium heat input ranges.

[0087] In other words, it includes data on the increase of displacement intervals measured by encoder 100 as a function of welding time, and includes data on three consecutive cases where the time-height slope is greater than 0.1. This means Figure 5 The boundary heat input between the high heat input range and the medium heat input range shown is applied to the state of the welding apparatus 10.

[0088] Therefore, this is data on performing a welding process with normal quality under the application of optimal welding heat input, and can include an algorithm that satisfies the condition of a time-height slope greater than 0.1 three times consecutively.

[0089] In comparison, Figure 4BThe data shows that, in the case of splashing, the height decreases continuously over time.

[0090] As shown in the figure, when the controller 200 measures the time-height slope to be below -0.5 three times consecutively, it performs current compensation to provide optimal heat input. In other words, when the welding displacement slope is less than zero, the controller 200 determines that spatter has occurred.

[0091] When the displacement slope is measured to be less than zero after a number of measurements set in controller 200, spatter is determined to have occurred, and the current applied to the welding apparatus 10 is reduced. This refers to... Figure 4B The situation within the block diagram shown.

[0092] Subsequently, based on the compensated current value, the displacement slope of the welding position is greater than zero, which indicates that no spatter is generated, and the displacement slope has a value greater than zero after 55 horizontal axis time (index time).

[0093] As mentioned above, such as Figure 3 As shown, this disclosure can perform downward compensation of the current value corresponding to the spatter generation situation, and can provide the welding apparatus with a target heat input with a displacement slope greater than 0. This compensation can improve weld quality.

[0094] Figure 6 The steps shown are to determine the weld quality by comparing the optimal target heat input with the actual welding heat input applied to the welding apparatus after applying the optimal target heat input.

[0095] This is through comparison Figure 2 The steps shown are for determining the welding quality by calculating the optimal target heat input and the actual welding heat input applied to the welding apparatus 10.

[0096] In embodiments of this disclosure, the encoder 100 can determine the height change between electrodes in real time during welding. Therefore, the completion time of weld nugget formation can be determined. More preferably, the controller 200 can determine the weld nugget formation time as the point in time when the height change measured by the encoder 100 approaches zero, and can measure the change in dynamic resistance during the weld nugget formation time. Therefore, the actual welding heat input actually manifested by the welding apparatus 10 can be calculated using the dynamic resistance before the weld nugget formation completion time and the applied current value.

[0097] Furthermore, in embodiments of this disclosure, the controller 200 can measure the height change between electrodes over a time range using the encoder 100. The controller 200 can calculate the actual welding heat input applied to the welding apparatus 10 by performing a definite integral on the applied current and the calculated dynamic resistance based on the weld nugget formation completion time.

[0098] In other words, the dynamic resistance and the applied current value are calculated based on the time the weld nugget formed by welding is in a liquid state, and the actual welding heat input applied to the welding device 10 is calculated by performing a definite integral on the calculated dynamic resistance and current value based on the corresponding time period.

[0099] The controller 200 compares the actual welding heat input calculated as described above with a preset range of the target heat input. More preferably, the controller 200 determines whether the actual welding heat input corresponds to 90% to 110% of the target heat input, and determines that the welding quality is met when the actual welding heat input corresponds to 90% to 110% of the target heat input.

[0100] On the other hand, when the actual welding heat input is outside the range of 90% to 110% of the target heat input, the controller 200 additionally compensates for the current value applied through the welding device 10. Furthermore, when the actual welding heat input is outside the range of 90% to 110% of the target heat input, the controller 200 can determine that a welding defect has occurred and can issue an alarm to the user.

[0101] This specification provides examples of this disclosure. Furthermore, the specification provides embodiments of this disclosure, and this disclosure can be used in various other combinations, modifications, and environments. That is, this disclosure can be changed or modified within the scope of this disclosure described herein, equivalent to the scope described, and / or within the knowledge or technology of related art. This embodiment illustrates the optimal state for implementing the spirit of this disclosure and can be changed in various ways for specific areas of application and uses of this disclosure. Therefore, the detailed description of this disclosure is not intended to limit this disclosure to the embodiments. Furthermore, the claims should be construed as including other embodiments.

Claims

1. A method for spot welding, the method comprising: The controller applies a preset welding heat input to the welding device; The controller applies the preset welding heat input to the welding position by moving the welding device; The encoder measures the height change at the welding position where the preset welding heat input is applied; The controller calculates the optimal target heat input by comparing the real-time height change slope of the welding position, measured via the encoder, with a slope set in the controller; and The controller determines the welding quality by comparing the calculated optimal target heat input with the actual welding heat input.

2. The method according to claim 1, wherein, The controller applies a preset welding heat input corresponding to the welding substrate positioned at the welding device.

3. The method according to claim 1, wherein, The controller calculates the optimal target heat input by compensating for the current value applied to the welding position.

4. The method according to claim 1, wherein, The preset welding heat input is calculated based on existing data stored from completed welding operations.

5. The method according to claim 1, further comprising: In the step of calculating the optimal target heat input... Determine whether the slope of the height change at the welding position is greater than the set slope that will not produce spatter; When the slope of the height change at the welding position is greater than the set slope that prevents spatter, the current applied to the welding device is increased; Based on the increased current value, determine whether the slope of the height change at the welding position is the set slope that produces spatter; and When the slope of the height change at the welding position is below the set slope that produces spatter, the optimal target heat input is set by adding a first margin value to the increased current value.

6. The method according to claim 1, further comprising: In the step of calculating the optimal target heat input... Determine whether the slope of the height change at the welding position is below the set slope that will produce spatter; When the slope of the height change at the welding position is below the set slope that produces spatter, the current applied to the welding device is reduced; Based on the reduced current value, determine whether the slope of the height change at the welding position is greater than the set slope that prevents spatter; and When the slope of the height change at the welding position is greater than the set slope for no spatter, the optimal target heat input is set by adding a second margin value to the reduced current value.

7. The method according to claim 1, further comprising: In the step of determining the welding quality The controller compares the range set based on the optimal target heat input with the actual welding heat input. as well as When the actual welding heat input is outside the set range, the current value applied to the welding device is compensated.

8. The method according to claim 7, further comprising: The encoder measures the height change of the welding position during welding; The time for weld nugget formation to complete is measured at the location where the height change at the measured welding position is greatest. as well as The actual amount of heat input applied is calculated based on the measured weld nugget formation completion time.

9. The method of claim 8, comprising: In the step of calculating the actual applied heat input based on the measured weld nugget formation completion time, The actual heat input applied to the welding position is calculated based on the welding dynamic resistance calculated from the voltage drop detected during the welding process, the current applied to the welding device, and the time for the weld nugget to form. Determine whether the actual applied heat input is within the normal range; as well as When the actual applied heat input is outside the normal range, the quality is determined to be poor.

10. The method of claim 8, comprising: In the step of calculating the actual welding heat input... The controller calculates the actual welding heat input of the welding device by performing a definite integral on the applied current and the calculated dynamic resistance based on the weld nugget formation completion time.

11. The method according to claim 1, wherein, In the step of calculating the optimal target heat input by the controller by comparing the slope of the height change of the welding position, measured via the encoder, with a slope set in the controller, The slope is set by analyzing the processor's machine learning algorithm.

12. The method according to claim 1, further comprising: In the step of calculating the optimal target heat input... The calculated peak value of the dynamic resistance (β) and the calculated optimal target heat input are stored in the controller.

13. An apparatus for spot welding, the apparatus comprising: Welding equipment; The controller is configured to apply a preset welding heat input to the welding device and to apply the preset welding heat input to the welding position by moving the welding device; as well as An encoder is configured to measure the height change of the welding position where the preset welding heat input has been applied; The controller is configured to calculate the optimal target heat input by comparing the real-time height change slope of the welding position, measured via the encoder, with a slope set in the controller. The controller is configured to determine the welding quality by comparing the calculated optimal target heat input with the actual welding heat input.

14. The apparatus according to claim 13, wherein, The controller applies a preset welding heat input corresponding to the welding substrate positioned at the welding device.

15. The apparatus according to claim 13, wherein, The controller calculates the optimal target heat input by compensating for the current value applied to the welding position.

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