Welded part quality determination device and welded part quality determination method

Abstract

To provide a welded part quality determination device and a welded part quality determination method which can accurately detect a welding failure without needing much labor.SOLUTION: This welded part quality determination device comprises: an input unit that acquires, as determination target data, data relating to measurement values of a plurality of types of welding parameters containing at least welding current, a welding speed, and an electrode force excluding a welding temperature during a welding operation of the determination target; a deviation calculation unit that calculates, as deviation of the determination target data, a ratio of an average value among minimum values of distances between data contained in a multidimensional normal data distribution which is a distribution of data relating to difference values between measurement values of the welding parameters acquired during the normal welding operation and set values or data relating to difference values between the standardized measurement values and the set values to a minimum value of distances between data relating a difference value between a measurement value of the determination target data and a set value and data contained in the multidimensional normal data distribution; and a determination unit that determines a welded part quality in the welding operation of the determination target on the basis of the deviation of the determination target data.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a weld quality determination device and a weld quality determination method for determining the quality of a weld when the widthwise ends of a leading plate and a trailing plate are welded together using a welding machine installed in a continuous steel plate processing line. [Background technology]

[0002] In a continuous steel processing line, where a welding machine is used to weld the widthwise ends of a leading sheet and a trailing sheet together and then the leading sheet and the trailing sheet are continuously processed, overlooking a welding defect can lead to problems such as sheet breakage. For this reason, a method for determining the quality of a weld based on the welding temperature has been proposed. Specifically, Patent Document 1 describes a method for determining the quality of a weld by calculating the temperature distribution of the weld using a heat conduction model and comparing the calculated temperature distribution with a set temperature. Patent Document 2 also describes a method for determining the quality of a weld by comparing the maximum temperature in the width direction of the weld with a reference temperature. Furthermore, Patent Document 3 describes a method for determining the quality of a weld by calculating the deviation of the welding temperature to be determined from a typical temperature distribution generated from actual temperature measurements of the weld using principal component analysis. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 7-185835 [Patent Document 2] Japanese Patent Application Publication No. 7-195179 [Patent Document 3] Japanese Patent Publication No. 2021-178346 Summary of the Invention [Problem to be solved by the invention]

[0004] However, welding defects can occur even when the welding temperature is within the normal range. This is because welding can sometimes be performed normally and sometimes not, even at the same welding temperature. Specifically, the welding temperature varies depending on welding parameters such as the welding current, welding speed, and electrode pressure. Specifically, the welding temperature increases as the welding current increases, and decreases as the welding speed and electrode pressure increase. Furthermore, if the electrode pressure is too large, the steel sheet is crushed, shortening the overlap between the leading and trailing sheets, resulting in welding defects. On the other hand, if the electrode pressure is too small, the contact area between the steel sheet and the electrode wheel decreases, causing the welding current to flow through a narrow area, resulting in welding defects due to increased temperature at the weld and sparks caused by poor contact. Therefore, if an increase in welding temperature due to an increase in welding current and a decrease in welding temperature due to an increase in electrode pressure occur simultaneously, the change in welding temperature is relatively small, but the shortened overlap between the leading and trailing sheets can result in welding defects. However, in this case, methods that determine the quality of a weld based on welding temperature cannot detect welding defects. To solve this problem, a method of setting thresholds to monitor welding parameters is conceivable. However, this method requires setting thresholds for each of the more than 100 welding conditions, which are combinations of plate thickness and steel type, and requires a great deal of effort.

[0005] The present invention has been made in consideration of the above-mentioned problems, and its object is to provide a weld quality determination device and a weld quality determination method that can accurately detect weld defects without requiring much effort. [Means for solving the problem]

[0006] The weld quality determination device of the present invention is a weld quality determination device that determines the quality of a weld when the widthwise ends of a leading plate and a trailing plate are welded together using a welding machine installed on a continuous steel plate processing line, and includes: an input unit that acquires, as data to be determined, measurement value data of multiple types of welding parameters including at least the welding current, welding speed, and electrode pressure, excluding the welding temperature during the welding operation to be determined; a deviation calculation unit that calculates, as the deviation of the data to be determined, the ratio between the average value of the minimum values of the distances between data included in a multidimensional normal data distribution, which is a distribution of data of difference values between the measurement values and set values of multiple types of welding parameters acquired during normal welding operation or data of difference values between the measurement values and set values that have been standardized, and the minimum value of the distance between the data of difference values between the measurement values and set values of the data to be determined and the data included in the multidimensional normal data distribution; and a determination unit that determines the quality of the weld in the welding operation to be determined based on the deviation of the data to be determined.

[0007] The determination unit may determine the degree of abnormality of the welding operation based on the degree of deviation of the determination target data, and determine an abnormality in the equipment that does not reach the level of a welding abnormality during the welding operation to be determined.

[0008] The method for determining the quality of a weld according to the present invention is a method for determining the quality of a weld when widthwise ends of a leading sheet and a trailing sheet are welded together using a welding machine installed in a continuous steel sheet processing line, and includes the following steps: an input step of acquiring, as data to be determined, measurement value data of multiple types of welding parameters including at least the welding current, welding speed, and electrode pressure, excluding the welding temperature, during the welding operation to be determined; a deviation calculation step of calculating, as the deviation of the data to be determined, the ratio between the average value of the minimum values of distances between data included in a multidimensional normal data distribution, which is a distribution of data of difference values between measurement values and set values of multiple types of welding parameters acquired during normal welding operation or data of difference values between the measurement values and set values that have been standardized, and the minimum value of the distance between the data of difference values between the measurement values and set values of the data to be determined and the data included in the multidimensional normal data distribution; and a determination step of determining the quality of the weld in the welding operation to be determined based on the deviation of the data to be determined.

[0009] The determining step may include a step of determining the degree of abnormality of the welding operation based on the degree of deviation of the data to be determined, and determining an abnormality in the equipment that does not reach the level of a welding abnormality during the welding operation to be determined. [Effects of the Invention]

[0010] According to the weld quality determination device and the weld quality determination method of the present invention, welding defects can be detected with high accuracy without requiring much effort. [Brief explanation of the drawings]

[0011] [Figure 1] FIG. 1 is a block diagram showing the configuration of a weld quality determination device according to one embodiment of the present invention. [Figure 2] FIG. 2 is a flowchart showing the flow of the determination process according to one embodiment of the present invention. [Figure 3] FIG. 3 is a diagram showing the results of a welding test in the examples. [Figure 4] FIG. 4 is a diagram showing the results of a welding test in the examples. DETAILED DESCRIPTION OF THE INVENTION

[0012] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS A weld quality determination device and a weld quality determination method according to an embodiment of the present invention will be described below with reference to the drawings.

[0013] Fig. 1 is a block diagram showing the configuration of a weld quality determination device according to one embodiment of the present invention. As shown in Fig. 1, the weld quality determination device 1 according to one embodiment of the present invention determines the quality of a weld between a leading sheet P1 and a trailing sheet P2 in a continuous steel sheet processing line based on measurements of multiple types of welding parameters obtained from a control device 3 that controls the operation of a welding machine 2. Examples of welding parameters include, excluding welding temperature, welding current, welding speed, electrode pressure, overlap between the leading sheet P1 and the trailing sheet P2, and positional deviation of the electrode wheels.

[0014] The welding machine 2 of this embodiment is equipped with an entry-side clamping device and an exit-side clamping device (not shown), an electrode wheel 4, a radiation thermometer 5, a swaging roll 6, and a carriage 7. The entry-side clamping device and the exit-side clamping device clamp and fix the leading plate P1 and the trailing plate P2 from above and below with their widthwise ends slightly overlapping. The electrode wheel 4 applies pressure to the overlapping portion of the leading plate P1 and the trailing plate P2 from above and below while passing current through it, thereby welding the widthwise ends of the leading plate P1 and the trailing plate P2 together.

[0015] A radiation thermometer 5 measures the temperature of the weld immediately after welding (welding temperature) and inputs an electrical signal indicating the measured temperature to the control device 3. A swaging roll 6 smooths the weld by applying pressure to the weld from above and below. A carriage 7 moves the electrode wheel 4 and swaging roll 6 in the width direction of the leading sheet P1 and the trailing sheet P2, which is the welding direction, while keeping the electrode wheel 4 and the swaging roll 6 fixed.

[0016] Furthermore, in the welding machine 2 of this embodiment, sensors (not shown) are used to measure the current passed through the overlapping portion of the leading sheet P1 and the trailing sheet P2 via the electrode wheel 4 as the welding current, the moving speed of the carriage 7 as the welding speed, and the force applied by the electrode wheel 4 in the vertical direction as the electrode pressurizing force. Other welding parameters are also measured in the same manner. Each measured value is input to the control device 3 as an electrical signal.

[0017] The weld quality determination device 1, which is one embodiment of the present invention, is configured by an information processing device such as a computer, and includes an input unit 10, a pre-processing calculation unit 11, a storage unit 12, a deviation calculation unit 13, and a determination unit 14. Each unit is a functional block realized by the information processing device executing a computer program. The function of each unit will be described later.

[0018] The weld quality determination device 1 having such a configuration determines the quality of the welds of the leading sheet P1 and the trailing sheet P2 by executing the determination process shown below. Below, with reference to the flowchart shown in Figure 2, the operation of the weld quality determination device 1 when executing the determination process (weld quality determination method) will be described.

[0019] [Determination process] Fig. 2 is a flowchart showing the flow of the determination process according to one embodiment of the present invention. The flowchart shown in Fig. 2 starts when the welding operation for welding the widthwise ends of the leading sheet P1 and the trailing sheet P2 together is completed, and the determination process proceeds to step ST1.

[0020] In the processing of step ST1, input unit 10 acquires data on the measured values and set values of a plurality of types of welding parameters from control device 3 and inputs the acquired data to pre-processing calculation unit 11. This completes the processing of step ST1, and the determination processing proceeds to the processing of step ST2.

[0021] In the processing of step ST2, preprocessing calculation unit 11 calculates the difference between the measured value and the set value for each type of welding parameter and inputs the calculated difference value data to storage unit 12. Preprocessing calculation unit 11 also inputs the difference value data calculated from the measured values of the welding parameters obtained during the welding operation to be judged to deviation calculation unit 13 as the data to be judged. By calculating the difference between the measured value and the set value, the welding parameter value is converted to a value based on zero, and the quality of the weld can be judged uniformly for any welding parameter setting, even if there are many combinations of welding parameter types depending on the plate thickness and steel type. Here, if the ranges of the values of each welding parameter differ greatly, the average value and standard deviation of each welding parameter may be used to standardize the data. Specifically, if a certain welding parameter is set to x i Then, the welding parameter x collected as normal data i The average value of all data is μ, the standard deviation is σ, and the welding parameter x i Standardized data x si x si =(x i The difference is calculated as (μ) / σ. Each welding parameter is similarly standardized using the average value and standard deviation of the respective normal data. The data used for determining whether the welding is good or bad, as described below, is also standardized in the same way. The number of data points for the measurement values used to calculate the difference value should be approximately 1 to 3,000. This completes the processing of step ST2, and the determination processing proceeds to the processing of step ST3.

[0022] In the processing of step ST3, storage unit 12 generates a distribution of data of difference values during normal operation (normal data distribution) for each type of welding parameter using data of difference values during multiple past welding operations that were determined to have been performed normally. Then, storage unit 12 inputs the generated normal data distribution data for each type of welding parameter to deviation calculation unit 13 as a multidimensional normal data distribution (normal data group). For example, if welding current, welding speed, and electrode pressure are included in the welding parameters, storage unit 12 inputs each normal data distribution data to deviation calculation unit 13 as a three-dimensional normal data distribution with welding current as the x-coordinate, welding speed as the y-coordinate, and electrode pressure as the z-coordinate. This completes the processing of step ST3, and the determination processing proceeds to the processing of step ST4.

[0023] In the process of step ST4, the deviation calculation unit 13 calculates the minimum value d of the distance between data in the normal data distribution space for n data included in the normal data group. i For example, when the welding parameters include the welding current, the welding speed, and the electrode pressure, the deviation calculation unit 13 calculates the minimum value d of the distance between data in the three-dimensional normal data distribution space using the following formulas (1) and (2): i The average value of x is calculated as the first distance d. 1i ,y 1i ,z 1i is the coordinate value of the i-th data in the normal data set, x 1k ,y 1k ,z 1k indicates the coordinate value of the data in the normal data group that is closest to the i-th data (the position with the shortest distance). This completes the process of step ST4, and the determination process proceeds to the process of step ST5.

[0024]

number

[0025]

number

[0026] In the process of step ST5, the deviation calculation unit 13 calculates the minimum distance between the n pieces of data included in the normal data group and the data to be determined as the second distance D using the following formula (3): In formula (3), x2, y2, and z2 are the coordinate values of the data to be determined, 1j ,y 1j ,z 1j indicates the coordinate values of the data in the normal data group that is closest to the data to be determined. This completes the process of step ST5, and the determination process proceeds to step S6.

[0027]

number

[0028] In the process of step ST6, the deviation calculation unit 13 uses the following formula (4) to calculate the ratio of the first distance d to the second distance D as the deviation K. This completes the process of step ST6, and the determination process proceeds to the process of step S7.

[0029]

number

[0030] In the processing of step ST7, the determination unit 14 determines the quality of the weld in the welding operation being determined based on the deviation K. Specifically, if the deviation K is equal to or greater than a first threshold value having a magnitude of 1 or greater, the determination unit 14 determines that there is a sign that an abnormality will occur in the equipment. Furthermore, if the deviation K is equal to or greater than a second threshold value that is greater than the first threshold value, the determination unit 14 determines that poor welding has occurred in the welding operation being determined. This completes the processing of step ST7, and the series of determination processes ends.

[0031] In addition, when the data of each welding parameter is standardized in the calculation of the degree of peeling K, it may be possible to identify the welding parameter that contributes significantly to the value of the degree of peeling K. In such cases, attention can be focused on the welding parameter that contributes most to the value of the degree of peeling K (the welding parameter that has calculated the largest difference among the differences between the welding parameters in the calculation of the degree of peeling), and the equipment corresponding to that welding parameter can be identified as a candidate for an equipment abnormality that does not result in a welding abnormality.

[0032] As is clear from the above description, in the judgment process according to one embodiment of the present invention, deviation calculation unit 13 calculates the deviation of the judgment target data as the ratio between the average of the minimum distances between data included in a multidimensional normal data distribution, which is a distribution of data on difference values between measured values and set values of multiple types of welding parameters acquired during normal welding operations, and the minimum distance between the judgment target data and data included in the multidimensional normal data distribution. Then, judgment unit 14 judges the quality of the weld in the welding operation being judged based on the deviation of the judgment target data. This allows for accurate detection of poor welding without requiring much effort. [Example]

[0033] In this example, three types of welding parameters were acquired during the welding operation to be evaluated, and the quality of the weld was evaluated based on the degree of deviation of the welding parameters from the three-dimensional data distribution. Specifically, in the welding test, a cut piece of steel plate was sandwiched between two steel plates to increase the plate thickness, and data to be evaluated was collected. Specifically, the plate thickness of the normal weld was set to 1.3 mm, and the plate thickness of the portion sandwiched between the cut piece was set to 3.9 mm. By welding under the welding conditions for the 1.3 mm plate thickness, data different from the set value that should normally be obtained for the 3.9 mm plate thickness portion was obtained.

[0034] The normal data used for pass / fail judgment was data from 900 welding operations over a three-month period from February to May 2023. The normal data distribution calculated from the difference between the measured and set values of this normal data was: welding current -0.4 to +0.2 kA, welding speed -0.1 to +0.1 m / min, and electrode pressure -0.5 to +1.2 kN. If the data calculated as the difference between the measured and set values of the data to be judged is within the range of the normal data distribution, and there is a point where the data within the normal data distribution completely matches the data to be judged, the degree of deviation K will be 0.

[0035] The results of the welding test are shown in Figure 3. As shown in Figure 3(a), in the 1.3 mm thick section where normal welding was performed, the welding temperature and the condition of the weld were both normal, and the deviation K was 0. In contrast, as shown in Figure 3(b), in the 3.9 mm thick section, the welding temperature rose to 1179°C, which was within the normal range of 930 to 1250°C, but the weld showed surface roughness and a reduction in the weld area.

[0036] According to the method of the present invention, the first distance d is 0.001 and the second distance D i was calculated to be 15.67, and the deviation K was calculated to be 15,670. In addition, another welding test was conducted using a steel plate with a thickness of 1.3 mm, and the welding conditions of welding current and electrode pressure were changed from their normal set values. The results are shown in Figure 4. Under the conditions shown in Figure 4(d), the welding temperature (912°C) fell outside the normal range (930 to 1,250°C). Therefore, by using the deviation K (= 538) under the conditions shown in Figure 4(c) as the threshold, it was confirmed that welding abnormalities can be detected from the deviation, which indicates the degree of abnormality in equipment operation.

[0037] Although the present invention has been described above as an embodiment, the present invention is not limited to the descriptions and drawings that form part of the disclosure of the present invention. In other words, other embodiments, examples, and operational techniques that can be made by those skilled in the art based on the present invention are all included in the scope of the present invention. [Explanation of symbols]

[0038] 1. Weld quality judgment device 2. Welding machine 3. Control device 4 electrode ring 5 Radiation thermometer 6 Swaging roll 7 Carriage 10 Input section 11 Pre-processing calculation section 12 Preservation Department 13 Deviation calculation section 14 Judgment section P1 Leading Board P2 trailing plate

Claims

1. A weld quality determination device that determines the quality of a weld when width direction ends of a leading plate and a trailing plate are welded together using a welding machine installed in a continuous steel plate processing line, an input unit that acquires, as data to be determined, measurement values of a plurality of welding parameters including at least a welding current, a welding speed, and an electrode pressure, excluding a welding temperature during a welding operation to be determined; a deviation calculation unit that calculates, as a deviation of the data to be determined, a ratio between an average value of minimum values of distances between data included in a multidimensional normal data distribution, which is a distribution of data of difference values between measurement values and set values of a plurality of types of welding parameters acquired during a normal welding operation or data of difference values between the measurement values and the set values that have been standardized, and a minimum value of distances between data of difference values between measurement values and set values of the data to be determined and data included in the multidimensional normal data distribution; a determination unit that determines whether a weld in a welding operation to be determined is good or bad based on the degree of deviation of the determination target data; A welding quality determination device comprising:

2. 2. The weld quality determination device according to claim 1, wherein the determination unit determines the degree of abnormality of the welding operation based on the degree of deviation of the data to be determined, and determines an abnormality in the equipment that does not amount to a welding abnormality during the welding operation to be determined.

3. A method for determining the quality of a weld when width direction ends of a leading plate and a trailing plate are welded together using a welding machine installed in a continuous steel plate processing line, comprising: an input step of acquiring, as data to be determined, measurement values of a plurality of types of welding parameters including at least a welding current, a welding speed, and an electrode pressure, excluding a welding temperature during a welding operation to be determined; a deviation calculation step of calculating, as a deviation of the data to be determined, a ratio between an average value of minimum values of distances between data included in a multidimensional normal data distribution, which is a distribution of data of difference values between measured values and set values of a plurality of types of welding parameters acquired during a normal welding operation or data of difference values between the measured values and set values that have been standardized, and a minimum value of distances between data of difference values between the measured values and set values of the data to be determined and data included in the multidimensional normal data distribution; a determination step of determining whether a weld in a welding operation to be determined is good or bad based on the degree of deviation of the determination target data; A method for determining whether a weld is good or bad, including:

4. 4. The method for determining whether a weld is good or bad according to claim 3, wherein the determination step includes a step of determining the degree of abnormality of the welding operation based on the degree of deviation of the data to be determined, and determining an abnormality in the equipment that does not amount to a welding abnormality during the welding operation to be determined.

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