JPH0890250A - Method and equipment for resistance welding - Google Patents

Abstract

PURPOSE: To control the welding temperature during the resistance welding within the target temperature range. CONSTITUTION: A preceding material 21 and a succeeding material 22 are pressed from the top and the bottom by an upper electrode 24a and a lower electrode 24b. The surface temperature in achieving the seam welding is detected by a radiation thermometer 25. The initial value of the welding current is set by a welding current setting device 29 according to the welding conditions, and corrected based on the difference between the target temperature and the welding temperature measured by the radiation thermometer 25. A thyristor stack 27 is phase controlled according to the corrected welding current, and the signal corresponding to the welding current is feedback from a current detector 28 to a feedback device 35. The learning function is provided in a processing unit 30 to set the connection based on the temperature difference, and the leaning results are stored to enable the control with high precision except when an equipment abnormality detecting device 33 detects the abnormality or when the related data are inputted from a welding abnormality inputting device 39 after welding.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a resistance welding method and apparatus for superposing and welding strips of metal plates or strips containing stainless steel, high alloy iron or the like.

[0002]

2. Description of the Related Art Conventionally, for example, Japanese Patent Laid-Open No. 5-1159.
Japanese Patent Publication No. 03, etc. discloses a configuration in which a preceding material and a following material are joined by a resistance welding method in a continuous metal strip processing line. In this prior art, while performing overlap welding of metal strips by a seam welder, the strip surface temperature is detected and the rate of temperature change per unit time is calculated.

FIG. 7 shows the appearance of a typical seam welder, and FIG. 8 shows the internal structure of the carriage of the seam welder shown in FIG. Such a seam welding machine is provided, for example, on the entrance side of a continuous strip running line for metal strips, and the metal strips that are rewound from a plurality of payoff reels and sequentially supplied to the tail strip of the preceding material 1. And the leading end of the trailing member 2 are sequentially overlapped and used for welding. During welding, the tail end of the preceding material 1 is held by the exit side clamp 3 and the tip end of the following material 2 is held by the entrance side clamp 4. The preceding material 1 and the following material 2 are inserted into the carriage 5, and the carriage 5 performs lap resistance welding while moving the preceding material 1 and the following material 2 in the plate width direction. An operation panel 6 is provided adjacent to the carriage 5 and inputs for operating the seam welder.

The carriage 5 can be moved in the plate width direction of the preceding material 1 and the following material 2 by a driving device 7 such as a hydraulic cylinder. A double cut shear 8 is provided in the carriage 5 and cuts the tail end of the preceding material 1 and the leading end of the following material 2 before starting resistance welding. When the output side clamp 3 and the input side clamp 4 are displaced so as to be close to each other, they are cut in advance so that the overlap margin between the tail end of the preceding material 1 and the tip of the following material 2 becomes constant. This is to keep it. The pair of upper and lower roller-shaped electrodes 9 apply a welding current from above and below where the preceding material 1 and the following material 2 are superposed, and the Joule heat generated partially melts the preceding material 1 and the following material 2, The tail end of the material 1 and the tip of the following material 2 are joined. A welding current having a large current value is supplied to the electrode 9 from the secondary conductor 10. Double cut shear 8, electrode 9
The secondary conductor 10 is installed in the carriage frame 11. A welding power source 12 for supplying a current to the secondary conductor 10 is attached to the outside of the carriage frame 11 and can be moved together with the movement of the carriage 5.

The welding current to be applied between the electrodes is the data such as the plate thickness, the plate width, the material of each of the leading material 1 and the trailing material 2, the mutual overlapping margin, the feeding speed of the electrode 9 and the pressing force. Is initialized from the outside beforehand. In order to apply a constant welding current between the electrodes 9 while pressing the electrodes 9 up and down, the welding current is detected and feedback control is performed. A switching element such as a thyristor is used for controlling the welding current, and its gate is ignited at an ignition angle corresponding to the welding current and controlled to a constant value.

The welding current required for welding is given by the following first equation according to Joule's law.

Q = 0.24 × I ² × R × t (1) In this first equation, Q is the heat input (kcal), I is the welding current (A), and R is the resistance value between the electrodes (Ω). ), T is the welding time (s
ec) is represented. t is the time for which the welding current of I per unit area flows, and is determined by the feed speed of the electrode 9. R is determined by the material of the metal, the stacking margin, and the electrode pressing force. The weldability is determined by the heat input Q, the welding current I, and the welding time t.
Then, if the resistance value R is controlled, welding should always be possible under constant conditions. In the conventional seam welder, these conditions are controlled to be constant.

[0008]

In the seam welding machine as shown in FIG. 7, the resistance value R changes due to the change in the overlap margin due to mechanical backlash, and the welding time t changes due to the change in the feed speed of the electrode 9. The resistance value R changes due to the change in the hydraulic system, the electrode pressing force changes, and the resistance value R also changes depending on the shape and surface condition of the contact portion of the preceding material 1 or the following material 2. Various factors such as the degree of adhesion of rolling oil, deviation of plate thickness tolerance, presence or absence of scale as an oxide film, and surface roughness can be considered for changes in the shape and surface condition of metal contact parts. . Fluctuations of these factors may cause the welded part to break during welding, or weld cracking during rolling of the welded part due to defective welding, which adversely affects the quality of the threading line and products.

In the prior art of Japanese Patent Laid-Open No. 5-115903, the surface temperature of the welded portion is detected to judge the quality of the welded portion, but the surface temperature of the welded portion falls within a certain range. However, good welding cannot be performed.

An object of the present invention is to provide a resistance welding method and apparatus capable of performing stable resistance welding by controlling the temperature of the welded portion within a fixed target range.

[0011]

SUMMARY OF THE INVENTION The present invention is a method of resistance welding by laminating metal strips, in which the welding current is detected, the surface temperature during welding is measured, and the measured surface temperature is within a target range. The resistance welding method is characterized in that the welding current is corrected as described above. The correction of the welding current according to the present invention is characterized in that the relationship between the welding conditions and the measured value of the surface temperature is learned and the correction is performed according to the learning result. Further, according to the present invention, the ratio α is set within a range of 0 ≦ α ≦ 1, the correction amount corresponding to the welding condition is multiplied by the ratio α, and the correction amount based on the learning result is multiplied by the ratio (1−α). The welding current is corrected by the sum of these multiplication results. Further, the present invention is characterized in that it is judged whether or not there is an abnormality in the welding conditions during welding, and when it is judged that there is an abnormality, the learning is not performed. In addition, the present invention determines whether or not there is an abnormality in the welding result of the metal strip, and the relationship between the welding condition and the measured value of the surface temperature when the welding result is determined to be abnormal is excluded from the learning result. Characterize. Furthermore, the present invention is, in an apparatus for resistance welding by stacking metal strips, condition detecting means for detecting welding conditions, temperature measuring means for measuring a surface temperature during welding, and output from the condition detecting means and the temperature measuring means. A learning unit that responds and stores the relationship between the welding condition and the surface temperature; and a current correction unit that responds to the outputs from the temperature measuring unit and the learning unit and that corrects the welding current so that the surface temperature falls within the target range. It is a resistance welding device characterized by including.

[0012]

According to the present invention, the welding current is detected, and the welding current is corrected so that the measured surface temperature of the welding machine is within the target range. Whether or not the welding is performed well depends on how much the temperature of the welded portion rises due to the Joule heat generated by the welding current. If the temperature is too high, it may cause breakage or cracks in the welded portion, and if the temperature is too low, the welding strength tends to be insufficient. Although the amount of heat generated by the welding current changes depending on the resistance and the welding time, the welding current greatly affects the temperature as its squared value. If the welding current is controlled with respect to the temperature rise of the welded portion, fluctuations due to other factors can be easily canceled and the temperature can be corrected quickly.

According to the present invention, the relationship between the welding condition and the measured surface temperature is learned in advance, and the welding current is corrected according to the learning result. Welding conditions include various factors and affect the surface temperature in various ways. By learning in advance, it is possible to improve the method of correcting the welding current with respect to the variation of each factor of the welding condition to a more accurate method.

According to the invention, the ratio α is set to
By adjusting the relationship between the welding conditions and learning, it is possible to correct the welding current with respect to the surface temperature with higher accuracy.

Further, according to the present invention, when it is judged that the welding condition during welding is abnormal, the condition is not subject to learning, so that the accuracy is obtained by using the learning result only when the welding condition is good. It is possible to correct high welding current.

Further, according to the present invention, when the welding result is judged to be abnormal, the relationship between the welding condition and the surface temperature at that time is excluded from the object of learning, so only the relationship with a good welding result is learned. As a result, it is possible to perform correction so as to obtain a stable welding result.

Further, according to the present invention, the learning means stores the relationship between the welding condition detected by the condition detecting means and the surface temperature detected by the temperature measuring means, and the welding current is corrected based on the learning result. Done. Under constant welding conditions, the change in surface temperature due to the change in welding current is learned, so that the welding current during welding can be corrected and adjusted to the optimum welding temperature.

According to the invention, the correction of the welding current is
The correction amount corresponding to the welding condition is multiplied by the ratio α, the correction amount based on the learning result is multiplied by the ratio (1−α), and the sum of these multiplication results is used. Therefore, the welding condition and the learning result are appropriately adjusted. It is possible to easily control the welding temperature to the optimum value by correcting the welding current by reflecting the above.

Further, according to the present invention, when it is determined that the welding condition during welding is abnormal, the relationship between the welding condition and the measured surface temperature is not learned. Since the learning result has a relationship with the measured value of the surface current when there is no abnormality in the welding conditions, the welding current can be accurately corrected.

Further, according to the present invention, the relationship between the welding condition when the welding result is judged to be abnormal and the measured value of the surface temperature is excluded from the learning result. Use only proven conditions for which As a result, it is possible to increase the possibility that the welding result by the corrected welding current is good.

Further, according to the invention, the learning means stores the relationship between the welding condition detected by the condition detecting means and the surface temperature at the time of welding measured by the temperature measuring means,
The current correction means corrects the welding current according to the learning result so that the surface temperature falls within the target range. By means of learning
The actual results of the relationship between the welding condition and the measured value of the surface temperature can be used, and the welding temperature can be controlled with high accuracy by correcting the welding current.

[0022]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS FIG. 1 shows a schematic electrical construction of an embodiment of the present invention, FIG. 2 shows an electrical construction related to the processing apparatus of FIG. 1, and FIG. 3 shows an operation of the embodiment of FIG. FIG. 4 shows a mechanical configuration for seam welding, FIG. 5 shows an electrical configuration of another embodiment of the present invention, and FIG. 6 shows an electrical configuration of yet another embodiment of the present invention. Show.

As shown in FIG. 1, a welding current supplied from the secondary conductor 20 flows through the preceding material 21 and the following material 22, and the Joule heat at that time causes seam welding. To the secondary conductor 20, a welding transformer 23 supplies a welding current, which has been stepped down from the commercial AC power source and has a large current, and is guided to the electrode 24. The electrode 24 is composed of an upper electrode 24a that presses the leading material 21 and the trailing material 22 from above and below, and a lower electrode 24b. Upper electrode 24a and lower electrode 2
The surface temperature of the portion sandwiched by 4b is measured by the radiation thermometer 25. The output of the radiation thermometer 25 is
It is converted into a current value in the range of 4 to 20 mA by the converter 26. Electric power is supplied to the primary side of the welding transformer 23 from a commercial AC power source through the thyristor stack 27. The current on the primary side is detected by the current detector 28. The current on the primary side is increased in inverse proportion to the step-down ratio of the welding transformer 23, and becomes the welding current on the secondary side.

The welding current is obtained by adding a welding current correction amount given by a processing device 30 realized by a microcomputer to a welding current set value set by an external welding current setting device 29 by a host process computer or the like, Further, feedback control is performed and it is determined. The processing device 30 includes the preceding material data setting device 3
1, signals from the trailing material data setting device 32 and the equipment abnormality detecting device 33 are given, and calculation for calculating the welding current correction amount is performed according to a predetermined program. The set value of the welding current from the welding current setting device 29 and the processing device 3
The correction amount of the welding current from 0 is added by the correction device 34, and the output is given to the feedback device 35. The output of the feedback device 35 is the output amplifier 36.
Is given as a gate signal to the thyristor stack 27 via. The thyristor stack 27 includes a plurality of thyristors as switching elements, controls the phase of the primary current of the welding transformer 23 according to a gate signal, and controls the secondary conductor 2
Adjust the welding current flowing to zero. A primary current corresponding to the welding current flows through the primary side of the welding transformer 23, and the current is returned from the current detector 28 to the feedback device 35 via the input amplifier 37.

The processing device 30 is the preceding material data setting device 3
1 and the following material data setting device 32 has the target welding temperature preset according to the material such as the steel type of the preceding material and the following material, the plate thickness and the plate width. This data is compared with the detected temperature given by the output from the converter 26, and when a deviation larger than the check value of the upper limit or the lower limit is generated, a large deviation signal is output and a large deviation alarm 38 issues an alarm. generate. Further, if the result of welding the preceding material 21 and the following material 22 is abnormal, the welding abnormality input device 39 is subsequently detected.
Is input to the processing device 30.

FIG. 2 shows the configuration related to the processing device 30 of FIG. 1 in more detail. The preceding material data setting device 31 and the following material data setting device 32 are made of materials 31a, 32a,
Data such as plate thicknesses 31b and 32b and plate widths 31c and 32c are provided to the processing device 30, respectively. In the processing device 30, a learning control means 40, a learning memory 41, a data memory 42, an average temperature calculation means 43, a calculation means 44, which are realized by software processing based on a memory such as a ROM or a RAM and a CPU, etc. 45, dead zone setting means 4
6, an upper / lower limit checking means 47, a limiter means 48 and the like are included. The equipment abnormality detection device 33 constantly monitors the operation state of the welding machine for the items shown in Table 1 below, and when it is determined that there is a welding abnormality, inputs the determination result to the learning control means 40. When it is determined that the welded part of the metal strip is abnormal in the subsequent process, the data related to the learning control means 40 is input via the welding abnormality input device 39.

[0027]

[Table 1]

FIG. 3 shows the operation of the embodiment of FIGS. 1 and 2. From step a1, preparation for welding is started between a pair of the leading material and the trailing material. In step a2,
Welding conditions such as plate thickness, plate width, steel type, feed rate, overlap margin, electrode pressure, etc. are entered. In step a3, step a
According to the welding condition input in 2, the current value preset by the technical standard or the like is set as the welding current. At step a4, the preceding material data setting device 3 of FIG.
From 1, the data such as the material 31a, the plate thickness 31b, and the plate width 31c of the preceding material is given to the processing device 30. In step a5, the trailing material data setting device 3 of FIG.
From 2, the data such as the material 32a, the plate thickness 32b, and the plate width 32c of the succeeding material are given to the processing device 30. At step a6, the target temperature and the upper and lower limit ranges are read from the data memory 42 according to the supplied data. At step a7, the learning memory 4 of FIG.
From 1, the temperature correction amount for correcting the target temperature is read based on the target temperature from the data memory 42 and the average temperature from the average temperature calculation means 43. Computing means 44 of FIG.
Then, the target temperature from the data memory 42 is corrected by the temperature correction amount from the learning memory 41, and the correction result is calculated by the calculating means 4
Give 5 The calculating means 45 responds to the welding temperature 26a and the output from the calculating means 44, and executes step a8 in FIG.
Temperature comparison.

In step a9, the result of the temperature comparison in the calculation means 45 is given to the dead zone setting means 46 in FIG. 2, and when the temperature deviation exceeds the predetermined dead zone range, the output corresponding to the deviation is checked for upper and lower limits. Given to the means 47. The upper / lower limit check means 47 performs the upper / lower limit check process of step a10 of FIG. 3, and when the deviation exceeds the upper / lower limit, the process proceeds from step a11 to step a12, and the large deviation alarm 38 issues an alarm. However, since the temperature of the welded portion has not risen sufficiently within a preset time range from the start of welding current application, at least the upper limit check function of the processing of the upper and lower limit check means 47 is performed. Set to the stopped state. Next, step a13
Then, the limiter means 48 shown in FIG.
The correction amount is limited based on the upper limit and the lower limit read from No. 2, and is derived as the welding current correction amount 30a.

At step a14, the welding current correction amount 30a derived from the limiter means 48 of FIG. 2 is given to the correction device 34 of FIG. 1 to correct the welding current set value from the welding current setting device 29. In step a15 of FIG. 3, the phase angle control of the thyristor stack 27 is performed based on the corrected welding current, and the welding current is supplied between the upper electrode 24a and the lower electrode 24b. At step a16, the surface temperature near the weld is measured by the radiation thermometer 25 shown in FIG. At step a17, it is judged if the seam welding is completed. When it is determined that the processing has not ended, the processing returns to step a8. When it is determined that the welding is completed, in step a18, the equipment abnormality detection device 3
It is determined whether or not 3 has detected an equipment abnormality as shown in Table 1. When no equipment abnormality is detected, the average temperature from the average temperature calculation means 43 is stored in the learning memory 41 by the learning control means 40 of FIG. 2 in step a19.
The learning function of storing 1/2 of the difference from the target temperature from the data memory 42 as the temperature correction amount is activated. In this way, the welding of the metal strip is repeated one after another.

At step a20, it is judged whether or not a welding abnormality has occurred in the subsequent process. When a welding abnormality has occurred, data is given from the welding abnormality input device 39 of FIG. 2 to the learning control means 40, and in step a21, the related learning result is removed from the learning memory 41. Step a2
At 2, finally, the process for one welding point is completed.

FIG. 4 shows the mechanical construction of a seam welder preferably used in the embodiment of FIGS. 1 and 2. FIG.
4A is a front sectional view, and FIG. 4B is a simplified perspective view. A carriage 50 that is movable in the plate width direction perpendicular to the sheet passing direction of the preceding material 21 and the following material 22.
A roller-shaped upper electrode 24a and a lower electrode 24b are attached to the. Wheels 51 are provided on the bottom surface of the carriage 50 so that the preceding material 21 and the following material 22 can move vertically in the sheet passing direction. When the carriage 50 moves, the upper electrode 24a and the lower electrode 24b press the overlapping portion 52 of the preceding material 21 and the following material 22 from above and below to perform seam welding. At the time of welding, FIG. 4 (a)
As shown in, the leading material 21 and the trailing material 22 are held by the output side clamp 53 and the input side clamp 54, respectively. The surface temperature of the welded portion is monitored using a radiation thermometer 25.

FIG. 5 shows a configuration related to the processing apparatus 60 according to another embodiment of the present invention. The present embodiment is similar to the configuration shown in FIG. 2, the processing device 60 is replaced by the processing device 30 of FIG. 2, and the portions corresponding to the configuration of FIG. In this embodiment, it should be noted that the ratio α (0 ≦ α ≦ 1) set by the α setting device 61 can be externally set, and the α calculation means 62 uses the set value of α for learning memory. 41 and the data stored in the data memory 42 are used to calculate the correction amount of the welding current. Further, the learning control means 63 compares the target temperature from the data memory 42 with the welding temperature 26a,
When this difference is larger than the preset reference value,
It is determined that the welding is abnormal and is excluded from the learning target in the learning memory 41. The α calculation means 62 performs the calculation shown in the following second equation.

C = αA + (1-α) B (2) Here, A and B represent the correction amount data read from the data memory 42 and the learning memory 41, respectively, and C represents the calculation. The results are shown. According to the present embodiment, it is possible to adjust the ratio of using the learning result according to the value of the ratio α. For example, when welding is repeatedly performed under similar conditions, the value of the ratio α is reduced, that is, the ratio (1-
The value of α) is increased to make full use of the learning function, and when the fluctuation of the welding conditions is large, the value of the ratio α is set to a small value and welding is performed with the learning function almost stopped. Further, when the deviation between the welding temperature 26a and the target temperature from the data memory 42 is large, the learning is stopped, so that the reliability of the data learned in the learning memory 41 can be improved.

FIG. 6 shows a configuration related to the processing apparatus 70 according to still another embodiment of the present invention. The present embodiment is also similar to the configuration of FIG. 2, and corresponding parts are designated by the same reference numerals.
The processing device 70 of this embodiment is the processing device 30 having the configuration of FIG.
Is replaced by It should be noted that the first learning memory 7
The learning means 74 is configured to include the first and second learning memories 72 and the data analysis means 73, and the data analysis means 73 is controlled by the learning control means 75. First,
The correction amount based on the difference between the target temperature and the average temperature is learned in the first learning memory 71, as in the embodiment shown in FIGS. 1 and 2. The data analysis unit 73 performs statistical analysis such as the average value of past data and stores the analysis result in the second learning memory 72. Since the data for the temperature correction amount is learned in the second learning memory 72 after the data analysis means 73 analyzes the data, it is possible to perform highly reliable learning without being affected by instantaneous noise or the like. it can.

In each of the above-mentioned embodiments, the case where seam welding is continuously performed on the metal strip has been described, but the present invention is also applicable to mash seam welding in which the overlap margin of the welded portion is crushed. Can be applied. Rather, in mash seam welding where the welding conditions are more severe, the present invention is preferably implemented and reliable welding can be performed. Further, not only continuous seam welding but also spot welding may be performed at a plurality of positions, and the same can be applied not only to welding of coil-shaped metal bands but also to welding of metal plates. .

Further, in each of the embodiments, the radiation thermometer is used to detect the surface temperature in the vicinity of the welded portion, but a temperature measuring sensor such as a thermocouple may be directly contacted with the surface of the welded portion to measure the temperature. You may

[0038]

As described above, according to the present invention, paying attention to the welding temperature which affects the weldability, the surface temperature of the welded portion is constantly measured so that the weldability is stable even if there are various fluctuation factors. The welding current can be controlled and the welding current can be controlled to make the weldability constant. As a result, in the metal strip line or the like, even if various fluctuation factors occur, the quality of the product is not adversely affected, and reliable and stable resistance welding can be performed.

Further, according to the present invention, the relationship between the welding condition and the surface temperature can be learned, the welding current can be corrected based on the learning result, and the welding temperature can be controlled to fall within a certain range. The relationship between various welding conditions and welding temperature is
Although not necessarily simple, learning can be performed to improve the accuracy of the welding current correction and approach the optimum conditions.

Further, according to the present invention, by setting the ratio α,
By adjusting the correction amount based on the welding condition and the correction amount based on the learning result, the welding current can be corrected to perform control to bring the welding temperature close to the optimum welding temperature.

Further, according to the present invention, since the relationship with the measured value of the surface temperature when the welding condition is abnormal is not learned, the learning result for correcting the welding current corresponds to the case where the welding condition is good. However, the welding current can be corrected with high accuracy.

Further, according to the present invention, since the relationship between the welding condition and the measured value of the surface temperature when the welding result is judged to be abnormal is excluded from the learning result, the welding result is abnormal from the correction result of the welding current. The possibility of becoming welded is reduced, and reliable welding can be performed.

Further, according to the present invention, the temperature measuring means monitors the surface temperature closely related to the welding temperature of the welded portion, and the welding condition detected by the condition detecting means,
The relationship with the temperature change is learned by the learning means, and the current correction means corrects the welding current so that the surface temperature falls within the target range based on the learning result. Since resistance welding is performed so that the welding temperature is within a certain range by controlling the welding current while correcting the temperature based on the learning result, stable welding quality can be easily obtained.

[Brief description of drawings]

FIG. 1 is a block diagram showing a schematic electrical configuration of an embodiment of the present invention.

FIG. 2 is a block diagram showing an electrical configuration related to the processing apparatus 30 of the embodiment of FIG.

FIG. 3 is a flowchart showing the operation of the embodiment shown in FIGS. 1 and 2.

FIG. 4 is a front sectional view and a perspective view showing a schematic configuration of a welding machine used in the embodiment of FIG.

FIG. 5 is a block diagram showing an electrical configuration related to a processing apparatus of another embodiment of the present invention.

FIG. 6 is a block diagram showing an electrical configuration related to a processing apparatus of still another embodiment of the present invention.

FIG. 7 is a simplified perspective view showing the overall configuration of a conventional seam welder.

8 is a simplified perspective view showing a configuration related to the carriage of the seam welding machine of FIG. 7. FIG.

[Explanation of symbols]

 21 Leading Material 22 Trailing Material 23 Welding Transformer 24 Electrode 24a Upper Electrode 24b Lower Electrode 25 Radiation Thermometer 26a Welding Temperature 27 Thyristor Stack 28 Current Detector 29 Welding Current Setting Device 30, 60, 70 Processing Device 30a Welding Current Correction Amount 31 Leading material data setting device 32 Subsequent material data setting device 33 Equipment abnormality detection device 34 Correction device 35 Feedback device 38 Large deviation alarm 39 Welding abnormality input device 40, 63, 75 Learning control means 41, 71, 72 Learning memory 42 data Memory 43 Average temperature calculation means 44, 45 Calculation means 47 Upper / lower limit check means 50 Carriage 52 Overlap margin 61 α setting device 62 α Calculation device

Continuation of front page (51) Int.Cl. ⁶ Identification number Office reference number FI technical display location G05B 13/02 L 9131-3H

Claims (6)

[Claims] 1. A method of resistance welding by stacking metal strips, comprising detecting a welding current, measuring a surface temperature during welding, and correcting the welding current so that the measured surface temperature falls within a target range. Resistance welding method characterized by. 2. The resistance welding method according to claim 1, wherein the correction of the welding current is performed in advance by learning the relationship between the welding condition and the measured value of the surface temperature and according to the learning result. 3. A ratio α is set within a range of 0 ≦ α ≦ 1, a correction amount corresponding to a welding condition is multiplied by a ratio α, and a correction amount based on the learning result is multiplied by a ratio (1-α). The resistance welding method according to claim 2, wherein the welding current is corrected by the sum of these multiplication results. 4. The resistance according to claim 2, wherein it is judged whether or not there is an abnormality in welding conditions during welding, and when it is judged that there is an abnormality, the learning is not performed. Welding method. 5. It is determined whether or not there is an abnormality in the welding result of the metal strip, and the relationship between the welding condition and the measured value of the surface temperature when the welding result is determined to be abnormal is excluded from the learning result. The resistance welding method according to any one of claims 2 to 4, which is characterized in that. 6. In a device for resistance welding by stacking metal strips, condition detecting means for detecting welding conditions, temperature measuring means for measuring a surface temperature during welding, and output from the condition detecting means and the temperature measuring means. Respond,
Includes learning means that stores the relationship between welding conditions and surface temperature, and current correction means that responds to the outputs from the temperature measurement means and the learning means and that corrects the welding current so that the surface temperature falls within the target range. Resistance welding equipment.