Weld quality determination device and weld 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 welding quality determination device and a welding 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 plate processing line where the widthwise ends of a leading plate and a trailing plate are welded together using a welding machine, and the leading and trailing plates are processed continuously, overlooking welding defects can lead to problems such as plate breakage. For this reason, methods have been proposed to determine the quality of a weld based on the welding temperature. 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 the set temperature. Patent Document 2 describes a method for determining the quality of a weld by comparing the highest temperature in the widthwise 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 degree of deviation of the welding temperature to be judged from a typical temperature distribution shape generated from actual temperature measurement values ​​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 [Overview of the project] [Problems that the invention aims to solve]

[0004] However, welding defects can occur even when the welding temperature is within the normal range. This is because welding may or may not be performed correctly at the same welding temperature. Specifically, the welding temperature changes depending on welding parameters such as welding current, welding speed, and electrode pressure. In particular, the welding temperature rises as the welding current increases, and the welding temperature decreases as the welding speed and electrode pressure increase. Also, if the electrode pressure is too high, the steel plate is crushed, shortening the overlap between the leading and trailing plates, resulting in welding defects. On the other hand, if the electrode pressure is too low, the contact area between the steel plate and the electrode ring decreases, causing the welding current to flow over a narrow area, resulting in welding defects due to temperature rise in the weld area and spark generation due to 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 welding defects may occur because the overlap between the leading and trailing plates shortens. However, in this case, welding defects cannot be detected by methods that judge the quality of the weld based on the welding temperature. To address these challenges, one approach is to set thresholds and monitor welding parameters. However, this method requires setting thresholds for each of the more than 100 different welding conditions based on plate thickness and steel type combinations, which is a very laborious process.

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

[0006] The welding quality determination device according to the present invention is a welding 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 comprises: an input unit that acquires data of measured values ​​of a plurality of types of welding parameters, including at least welding current, welding speed, and electrode pressure, excluding the welding temperature during the welding operation to be determined, as data to be determined; a deviation degree calculation unit that calculates the deviation degree of the data to be determined as the ratio of the average of the minimum distances between data included in a multidimensional normal data distribution, which is a distribution of data of the difference between measured values ​​and set values ​​of a plurality of types of welding parameters acquired during a normal welding operation or data of the difference between measured values ​​and set values ​​that has undergone standardization processing, to the minimum distance between the data of the difference between measured 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 degree 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 data to be determined, and may determine that there is an abnormality in the equipment during the welding operation to be determined that does not result in a welding abnormality.

[0008] The present invention relates to a method for determining the quality of a weld, which 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. The method includes: an input step of acquiring data of measured values ​​of multiple types of welding parameters, including at least welding current, welding speed, and electrode pressure, excluding the welding temperature during the welding operation to be determined, as data to be determined; a deviation degree calculation step of calculating the deviation degree of the data to be determined as the ratio of the average of the minimum distances between data included in a multidimensional normal data distribution, which is a distribution of data of the difference between measured values ​​and set values ​​of multiple types of welding parameters acquired during a normal welding operation or data of the difference between measured values ​​and set values ​​that has undergone standardization processing, to the minimum distance between the data of the difference between measured 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 a weld in the welding operation to be determined based on the deviation degree of the data to be determined.

[0009] The determination 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 the equipment abnormality during the welding operation to be determined to the extent that it does not result in a welding abnormality. [Effects of the Invention]

[0010] According to the welding quality determination device and welding quality determination method of the present invention, welding defects can be detected accurately without requiring much effort. [Brief explanation of the drawing]

[0011] [Figure 1] Figure 1 is a block diagram showing the configuration of a welding quality determination device, which is one embodiment of the present invention. [Figure 2] Figure 2 is a flowchart showing the flow of a determination process, which is one embodiment of the present invention. [Figure 3] Figure 3 shows the results of the welding test in the example. [Figure 4] Figure 4 shows the results of the welding test in the example.

Best Mode for Carrying Out the Invention

[0012] Hereinafter, referring to the drawings, a welding part quality determination device and a welding part quality determination method according to an embodiment of the present invention will be described.

[0013] FIG. 1 is a block diagram showing the configuration of a welding part quality determination device according to an embodiment of the present invention. As shown in FIG. 1, a welding part quality determination device 1 according to an embodiment of the present invention determines the quality of the welded part between the preceding plate P1 and the succeeding plate P2 in a continuous steel plate processing line based on measurement values of a plurality of types of welding parameters acquired from a control device 3 that controls the operation of a welding machine 2. Examples of welding parameters include welding current, welding speed, electrode pressing force, overlap of the preceding plate P1 and the succeeding plate P2, and position deviation of the electrode wheel, etc., excluding the welding temperature.

[0014] Note that the welding machine 2 of the present embodiment includes an inlet side clamping device and an outlet side clamping device (not shown), an electrode wheel 4, a radiation thermometer 5, a swaging roll 6, and a carriage 7. The inlet side clamping device and the outlet side clamping device sandwich and fix the preceding plate P1 and the succeeding plate P2 from above and below in a state where the width direction ends slightly overlap. The electrode wheel 4 energizes while pressing the overlapping portion of the preceding plate P1 and the succeeding plate P2 from above and below to weld the width direction ends of the preceding plate P1 and the succeeding plate P2 to each other.

[0015] The radiation thermometer 5 measures the temperature of the welded part immediately after welding (welding temperature) and inputs an electrical signal indicating the measured temperature to the control device 3. The swaging roll 6 smooths the welded part by pressing it from above and below. The carriage 7 moves in the width direction of the preceding plate P1 and the succeeding plate P2, which is the welding direction, while fixing the electrode wheel 4 and the swaging roll 6 in place.

[0016] Furthermore, in the welding machine 2 of this embodiment, a sensor (not shown) is used to measure the current supplied to the overlapping portion of the leading plate P1 and the trailing plate P2 via the electrode wheel 4 as the welding current, the movement 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 pressure. Other welding parameters are also measured in the same manner. Each measured value is then input to the control device 3 as an electrical signal.

[0017] One embodiment of the weld quality determination device 1 is composed of 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 degree 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 functions of each unit will be described later.

[0018] The welding quality determination device 1, having the above configuration, determines the quality of the weld between the leading plate P1 and the trailing plate P2 by performing the determination process shown below. The operation of the welding quality determination device 1 (welding quality determination method) when performing the determination process will be explained below with reference to the flowchart shown in Figure 2.

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

[0020] In step ST1, the input unit 10 acquires data on measured and set values ​​of multiple types of welding parameters from the control device 3, and inputs the acquired data to the pre-processing calculation unit 11. With this, the process of step ST1 is completed, and the judgment process proceeds to step ST2.

[0021] In step ST2, the 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 data into the storage unit 12. The preprocessing calculation unit 11 also inputs the difference data calculated from the measured values ​​of the welding parameters obtained during the welding operation to be judged into the 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 values ​​are converted to zero-based values, allowing for a uniform determination of the quality of the weld in any welding parameter setting, where there are numerous combinations of welding parameter types depending on the plate thickness and steel type. Here, if the ranges of the values ​​for each welding parameter differ significantly, data standardization processing may be performed using the mean and standard deviation of each welding parameter. Specifically, a certain welding parameter can be x i Therefore, the welding parameters x collected as normal data i Let μ be the mean of all data and σ be the standard deviation, and the welding parameter x i Standardized data x si to x si =(x i The calculation is performed as -μ) / σ. Each welding parameter is similarly standardized using the mean and standard deviation of its respective normal data. The data used for welding quality judgment, described later, is also standardized in the same way. The number of data points for the measured values ​​used to calculate the difference should be around 1 to 3000. With this, the processing in step ST2 is completed, and the judgment process proceeds to step ST3.

[0022] In the process of step ST3, the storage unit 12 generates the distribution of the difference value data (normal data distribution) during normal operation for each type of welding parameter by using the data of the difference values during a plurality of past welding operations determined to have been normally performed. Then, the storage unit 12 inputs the data of the normal data distribution for each type of generated welding parameter as a multi-dimensional normal data distribution (normal data group) to the divergence degree calculation unit 13. For example, when welding current, welding speed, and electrode pressing force are included in the welding parameters, the storage unit 12 inputs the data of each normal data distribution as a three-dimensional normal data distribution with the welding current as the x coordinate, the welding speed as the y coordinate, and the electrode pressing force as the z coordinate to the divergence degree calculation unit 13. Thereby, the process of step ST3 is completed, and the determination process proceeds to the process of step ST4.

[0023] In the process of step ST4, the divergence degree calculation unit 13 calculates the average value of the minimum value d i (i = 1 to n) of the distances between the n pieces of data included in the normal data group in the normal data distribution space as the first distance d. For example, when welding current, welding speed, and electrode pressing force are included in the welding parameters, the divergence degree calculation unit 13 uses the following mathematical formulas (1) and (2) to calculate the average value of the minimum value d i of the distances between the data in the three-dimensional normal data distribution space as the first distance d. In the mathematical formula (1), x 1i , y 1i , z 1i are the coordinate values of the i-th data in the normal data group, and x 1k , y 1k , z 1k are the coordinate values of the data in the normal data group that is the nearest neighbor (the position with the shortest distance) of the i-th data. Thereby, the process of step ST4 is completed, and the determination process proceeds to the process of step ST5.

[0024]

Number

[0025]

Number

[0026] In step ST5, the deviation calculation unit 13 calculates the minimum distance between the n data points included in the normal data group and the data to be judged as the second distance D using the following formula (3). In formula (3), x2, y2, z2 are the coordinate values ​​of the data to be judged, x 1j ,y 1j ,z 1j This indicates the coordinate value of the data in the group of normal data that is closest to the data to be judged. With this, the processing in step ST5 is completed, and the judgment process proceeds to the processing in step S6.

[0027]

number

[0028] In step ST6, the deviation calculation unit 13 calculates the deviation K as the ratio of the first distance d to the second distance D using the following formula (4). With this, step ST6 is completed, and the judgment process proceeds to step S7.

[0029]

number

[0030] In step ST7, the determination unit 14 determines the quality of the weld in the welding operation being judged based on the deviation degree K. Specifically, if the deviation degree K is greater than or equal to a first threshold of 1 or more, the determination unit 14 determines that there is a sign of an impending malfunction in the equipment. Furthermore, if the deviation degree K is greater than or equal to a second threshold which is greater than the first threshold, the determination unit 14 determines that a welding defect has occurred in the welding operation being judged. With this, the process in step ST7 is completed, and the series of determination processes is finished.

[0031] Furthermore, in the calculation of the degree of peeling K, if the data for each welding parameter has been standardized, it may be possible to identify a welding parameter that significantly contributes to the value of the degree of peeling K. In such cases, by focusing on the welding parameter that contributes most to the value of the degree of peeling K (the welding parameter for which the largest difference is calculated among the differences of each welding parameter in the degree of peeling calculation), the equipment corresponding to that welding parameter can be considered a candidate for equipment abnormality that does not reach the level of a welding abnormality.

[0032] As is clear from the above explanation, in the judgment process which is one embodiment of the present invention, the deviation degree calculation unit 13 calculates the deviation degree of the data to be judged as the ratio of the average of the minimum distances between data included in a multidimensional normal data distribution, which is a distribution of data of the difference between measured values ​​and set values ​​of multiple types of welding parameters acquired during normal welding operation, to the minimum distance between the data to be judged and the data included in the multidimensional normal data distribution. Then, the judgment unit 14 determines the quality of the weld in the welding operation to be judged based on the deviation degree of the data to be judged. This makes it possible to accurately detect welding defects without requiring much effort. [Examples]

[0033] In this example, three types of welding parameters were acquired during the welding operation to be judged, and the quality of the weld was determined from the degree of deviation of the welding parameters from the three-dimensional data distribution. Specifically, in the welding test, the plate thickness was increased by inserting a cut piece of steel plate between two steel plates, and data to be judged was collected. Specifically, the plate thickness of the normal weld was set to 1.3 mm, and the plate thickness of the part with the cut piece inserted was set to 3.9 mm. By welding under the welding conditions for a plate thickness of 1.3 mm, data different from the normally expected set value was obtained in the part with a plate thickness of 3.9 mm.

[0034] For the quality determination, data from 900 welding operations over a three-month period from February to May 2023 was used as normal data. The normal data distribution, calculated from the difference between the measured and set values ​​of this normal data, was -0.4 to +0.2 kA for welding current, -0.1 to +0.1 m / min for welding speed, and -0.5 to +1.2 kN for electrode pressure. The deviation degree K is considered to be 0 if the data obtained by calculating the difference between the measured and set values ​​of the data to be judged falls within the range of the normal data distribution, and there is a point where the data within the normal data distribution and the data to be judged perfectly match.

[0035] Figure 3 shows the results of the welding test. As shown in Figure 3(a), in the section with a plate thickness of 1.3 mm where normal welding was performed, both the welding temperature and the condition of the weld were normal, and the degree of deviation K was 0. In contrast, as shown in Figure 3(b), in the section with a plate thickness of 3.9 mm, although the welding temperature rose to 1179°C, which was within the normal range of 930-1250°C, surface roughness was observed in the weld, and a reduction in the welded area was also observed.

[0036] According to the method of the present invention, the first distance d is 0.001 and the second distance D is 0.001 from the welding data of the portion with a plate thickness of 3.9 mm. i The value was calculated to be 15.67, and the deviation K was calculated to be 15670. In addition, as another welding test, the steel plate thickness was set to 1.3 mm, and the welding conditions, specifically the welding current and electrode pressure, were changed from the 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 (930~1250°C). Therefore, by using the deviation K (=538) under the conditions shown in Figure 4(c) as a threshold, it was confirmed that welding abnormalities can be detected from the deviation, which represents the degree of abnormality in equipment operation.

[0037] Although embodiments applying the invention made by the present inventors have been described above, the present invention is not limited by the descriptions and drawings that constitute part of the disclosure of the present invention in this embodiment. That is, all other embodiments, examples, and operational techniques made by those skilled in the art based on this embodiment are included in the scope of the present invention. [Explanation of Symbols]

[0038] 1. Weld quality determination device 2 Welding machine 3. Control device 4 electrode ring 5 Radiation thermometer 6 Swaging Rolls 7 Carriage 10 Input section 11 Preprocessing Calculation Unit 12 Storage section 13. Deviation Calculation Unit 14 Judgment section P1 Pre-release board P2 trailing plate

Claims

1. A welding quality determination device 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, An input unit that acquires data of measured values ​​of multiple types of welding parameters, including at least welding current, welding speed, and electrode pressure, excluding the welding temperature during the welding operation to be judged, as data to be judged. A deviation degree calculation unit calculates the deviation degree of the data to be judged by taking the ratio of the minimum distance between data included in a multidimensional normal data distribution, which is a distribution of data of the difference between measured values ​​and set values ​​of multiple types of welding parameters acquired during normal welding operation, or data of the difference between measured values ​​and set values ​​that has undergone standardization processing, to the minimum distance between the data of the difference between measured values ​​and set values ​​of the data to be judged and the data included in the multidimensional normal data distribution, as the deviation degree of the data to be judged. A determination unit that determines the quality of the weld in the welding operation to be determined based on the degree of deviation of the data to be determined, A welding quality determination device equipped with the following features.

2. The welding 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 during the welding operation to be determined that does not result in a welding abnormality.

3. A 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 on a continuous steel plate processing line, An input step of acquiring data of measured values ​​of multiple types of welding parameters, including at least welding current, welding speed, and electrode pressure, excluding the welding temperature during the welding operation to be judged, as data to be judged. A deviation degree calculation step in which the deviation degree of the data to be judged is calculated as the ratio of the minimum distance between data included in a multidimensional normal data distribution, which is a distribution of data of the difference between measured values ​​and set values ​​of multiple types of welding parameters obtained during normal welding operation, or data of the difference between measured values ​​and set values ​​that has undergone standardization processing, to the minimum distance between the data of the difference between measured values ​​and set values ​​of the data to be judged and the data included in the multidimensional normal data distribution, A determination step in which the quality of the weld in the welding operation to be judged is determined based on the degree of deviation of the data to be judged, A method for determining the quality of a welded joint, including the method described above.

4. The welding quality determination method according to claim 3, wherein the determination step includes 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 result in a welding abnormality during the welding operation to be determined.

Images