KR20210036522A - Welding defect inspecting method and apparatus and automatic welding apparatus - Google Patents

Abstract

Disclosed are a welding defect inspection method and apparatus, and an automatic welding machine including the same. An automatic welding machine according to an embodiment of the present invention is an automatic welding machine that performs welding by traveling to a welding part, comprising: a welding part for generating a weld bead by performing welding on the welding part; an image photographing unit for photographing the welding bead; and an image reading unit for detecting an actual weld bead shape by reading an image, and determining the presence or absence of a weld defect by comparing the same with a design weld bead shape. If there is a weld defect, welding is stopped and the data about the weld defect is reported so that the present invention can have a welding defect inspection function that performs inspection together with welding.

Description

Welding defect inspection method and apparatus, and automatic welding machine including the same

The present invention relates to a welding defect inspection method and apparatus, and an automatic welding machine including the same.

In shipbuilding and offshore structures, a lot of time and manpower are consumed to check for defects in welding after performing automatic welding.

In the process of inspection for welding defects, it is necessary in a short time to determine whether or not the recommended welding length is observed, as well as defects on the welding bead that occur during welding.

However, in the past, welding construction proceeds to the construction stand, and inspection work proceeds at a later stage. There was a problem to proceed.

Korean Patent Registration No. 10-1891415 (Registered on August 21, 2018)-A system and method for detecting defects in welding parts

An object of the present invention is to provide a welding defect inspection method and apparatus and an automatic welding machine including the same, which can significantly reduce the time and manpower for the welding inspection by completing the inspection at the same time as the welding.

The present invention eliminates reading errors on welding defects through big data analysis, checks the data of each tree and each chapter through an around view function for the welding part, generates defect information, and inspects welding defects that can be reflected in the result data. It is to provide a method and apparatus and an automatic welding machine including the same.

Objects other than the present invention will be easily understood through the following description.

According to an aspect of the present invention, there is provided an automatic welding machine for performing welding by traveling to a welding portion, comprising: a welding portion for generating a welding bead by performing welding on the welding portion; An image photographing unit for photographing the welding bead; And an image reader that reads the image to detect the actual weld bead shape, and compares it with the design weld bead shape to determine the presence or absence of a welding defect, but if a welding defect exists, the welding is stopped and the data on the welding defect is reported. Thus, an automatic welding machine with a welding defect inspection function that performs inspection along with welding is provided.

It may further include an image projection unit for modeling a virtual welding bead volume by analyzing the design welding bead shape, and projecting the modeled virtual welding bead volume onto the welding portion with a plurality of laser lines.

The plurality of laser lines may be projected in different colors.

The image capturing unit photographs the virtual welding bead volume projected by the plurality of laser lines together, and the image reading unit detects the welding defect by matching the actual welding bead shape and the virtual welding bead volume one-to-one. have.

In the process of modeling the virtual weld bead volume, an error range is set and coded from the information on the design weld bead shape, and the information on the design weld bead shape includes a rate of change of the depth of the weld tip, a rate of change of the area in the direction of the angle, and a deflection At least one of the rates is included, and the image reading unit may determine whether the welding defect exists through mapping of the violation of the error range and the welding defect big data.

The image capturing unit photographs the welding bead in three directions including a long line direction and a square neck direction, and may set a deviation for the square neck direction to be wider than a deviation for the square line direction.

Other aspects, features, and advantages other than those described above will become apparent from the following drawings, claims, and detailed description of the invention.

According to an embodiment of the present invention, since the inspection can be completed at the same time as the welding, there is an effect of significantly reducing the time and manpower for the welding inspection.

In addition, there is an effect of removing reading errors about welding defects through big data analysis, checking the data of each item and each chapter through the around view function for the welding part, generating defect information, and reflecting it in the result data.

1 is a view showing an automatic welding machine including a welding defect inspection apparatus according to an embodiment of the present invention,
2 is a view showing a welding bead in a welded joint,
3 is a view showing a welding bead photographing using an image photographing unit
4 is a flowchart of a welding defect inspection method performed in an automatic welding machine according to an embodiment of the present invention;
5 is a view showing various information related to the shape of a welding bead;
6 is a view showing a state to which a welding defect inspection method according to an embodiment of the present invention is applied.

In the present invention, various modifications may be made and various embodiments may be provided, and specific embodiments will be illustrated in the drawings and described in detail in the detailed description. However, this is not intended to limit the present invention to a specific embodiment, it should be understood to include all changes, equivalents, or substitutes included in the spirit and scope of the present invention.

1 is a view showing an automatic welding machine including a welding defect inspection apparatus according to an embodiment of the present invention, FIG. 2 is a view showing a welding bead at a weld joint, and FIG. 3 is a welding bead photographing using an image photographing unit It is a diagram showing the appearance.

1, an automatic welding machine 100, an autonomous driving unit 110, a driving wheel 115, a welding unit 120, an image capturing unit 130, an image reading unit 140, and an image projection unit 150 are shown. have.

The automatic welding machine 100 according to an embodiment of the present invention is an apparatus that performs welding while autonomously driving to a point requiring welding in a structure such as a ship.

The automatic welding machine 100 may include an autonomous driving unit 110 and a driving wheel 115 for autonomous driving. The autonomous driving unit 110 may autonomously perform operations such as driving or stopping according to an input of a worker or a control signal from a remote server. During the driving process, coordinates can be recognized through CAD data on the work site and can be moved while guiding the surrounding structural members. Such autonomous driving technology is a matter that is obvious to a person skilled in the art to which the present invention pertains, and a detailed description thereof will be omitted.

The automatic welding machine 100 includes a welding part 120. The welding part 120 may include a feed for supplying a welding wire.

As a welding method by the welding part 120, arc welding, gas welding, resistance welding, and the like may be used. Arc welding is a welding made by the heat of an arc, and there is usually shielded arc welding while blocking air using an arc and an impregnated metal as a protective medium, and a solvent, inert gas, carbon dioxide gas, etc. are used as the protective medium. Gas welding is a welding made by the heat of gas, and usually uses oxygen and acetylene, and uses heat generated by combustion of acetylene. Resistance welding is a welding in which a current flows through a contact portion of a member to be joined, and is heated by resistance heat generated therein to apply pressure.

Of course, other welding methods such as electromagnetic welding, laser welding, and ultrasonic welding may be used.

A state in which penetration through the welding part 120 is completed is shown in FIGS. 2 and 3.

Referring to FIG. 2, a state in which the welding material 20 is welded on the plate 10 is shown. Welding beads 30 are made at both sides of the point where the plate 10 and the welding material 20 meet. A welding line is formed on the surface of the welding bead 30.

The welding bead 30 has a long triangular bar shape, and its cross section has an elliptical shape during the welding lamination process. The joint formed by the meeting of the two objects to be welded (plate 10 and welding material 20) becomes the root of the joint, and the weld bead width h1 (that is, the weld toe) at the first object Distance) and the width of the weld bead (h2) at the second object become the leg length, and the distance (a) from the root of the joint to the inclined surface of the weld bead becomes the throat thickness. These geometrical features are utilized in discriminating welding defects with information on the shape of the weld bead.

When penetration through the welding part 120 is completed (in a state of being welded after welding), the image capturing unit 130 photographs a point where welding is performed by the welding part 120 (see FIG. 3). The image capturing unit 130 may be, for example, a camera.

A plurality of image capturing units 130 may be provided, and image data related to each item and each chapter may be checked in an around view format. The image capturing unit 130 may photograph two leg length lines (welding edge ends) and three directions for each tree with respect to the weld bead.

When the position of the welding edge is confirmed within the camera lens, the image photographing unit 130 may basically set a direction of 45 degrees (°), which is a root crack occurrence portion. A crack crack refers to a crack that occurs at the start end of a weld, and the crack advances to the center of the timber. In the case of the T joint, the angle between the plate and the welding material is 90 degrees (˚), and the root crack advances in the direction of each tree, and the ideal angle is 45 degrees (˚). In the direction of 45 degrees, a wide area can be observed by adding +/- 15 degrees (˚) of left and right deviation. In addition, the welding tip region can be observed as a +/- 10 degree (˚) region.

Welding is completed with one welding bead by stacking several layers of layers. The place where the degree of overlap of each layer is severe is the 45 degree (˚) direction for each tree, and the 15 degree deviation from the left and right is the area where welding defects mainly occur. The reason that the deviation in the direction of the angle is wider than that in the direction of the angle line (the welding end) is to observe a wider area because the probability of occurrence of welding defects is higher.

Two image capture units 130 may be applied to one welding bead. In case the reading of the image captured by the first image capturing unit 130 fails, an extra image capturing unit 130 may be installed at a distance from each other.

When there is a reinforcing material on the plate so that when welding on both sides, two welding beads are formed, so a total of four image capturing units 130 may be provided.

The image captured by the image capturing unit 130 is transmitted to the image reading unit 140, and the image reading unit 140 analyzes the captured image to estimate an actual weld bead shape.

The image reading unit 140 may access big data about various welding defects stored in a storage means such as a memory or stored in a database of a remote server, and read the defect types detected in the actual welding bead shape. have.

In addition to general photographic data, the welding defect big data may include tomography data.

The image projection unit 150 is provided with information about the design angle, design angle, and design welding bead shape reflecting the workability of the site for the site to be welded, and models a virtual welding bead volume. . Virtual welding bead volume modeling may be performed by a combination of a plurality of lines.

Then, the virtual weld bead volume is projected onto the joint to be welded. The image projection unit 150 may be, for example, a laser irradiation device, and may project a predicted weld bead shape by irradiating a laser line.

The projected virtual welding bead volume may be formed of a combination of a plurality of projected lines, and may be used as a sketch in a welding process using the welding part 120. Through the plurality of laser lines, the welding angle long distance, the shape of the welding bead, and the height of each tree can be visually confirmed.

In order to increase the recognition rate, different colors may be projected onto the laser line.

The image capturing unit 130 may also capture an image of a virtual welding bead volume projected by the image projection unit 150 when capturing an image of an actual welding bead shape.

The image reader 140 may detect a difference between the virtual welding bead volume and the actual welding bead shape by mapping the image analysis result. In addition, it is possible to determine whether there is a final defect, whether or not to resume work, etc. through a secondary mapping comparing the detected difference with the welding defect big data.

The automatic welding machine 100 according to the present embodiment is a device capable of completing both welding and inspection at the same time, and can significantly reduce time and manpower for welding inspection. Since data related to welding defects is stored in the memory provided in the automatic welding machine 100, the welding defect location, type, and similar photo of the welding defect can be reflected in the welding result data for parts determined as welding defects during inspection. . As a result, it may be possible to correct the welding defect immediately.

The automatic welding machine 100 according to the present embodiment may record an image of the welding progress from multiple angles in a three-dimensional virtual space by using the image photographing unit 130. If a case similar to welding defect big data occurs during work, welding can be stopped and alarms and related matters can be reported. The reporting may be automatically transmitted to an administrator terminal or a remote server wirelessly, or may be output to a separate data logger. Professional managers or inspectors can re-read and decide whether to proceed with welding work. If you need to increase work efficiency, you can ignore the alarm and continue welding, and then check the location of the welding defect and the type of defect based on the reporting result, and take action.

4 is a flowchart of a method for inspecting welding defects performed in an automatic welding machine according to an embodiment of the present invention, and FIG. 5 is a view showing various types of information on a shape of a weld bead.

Referring to FIG. 4, a method of inspecting a welding defect performed in an automatic welding machine according to the present embodiment is as follows.

First, a pre-predicted weld bead shape is assumed according to a work site situation in which welding is required, and an error range out of this is pre-set and coded (step S300). It can be seen as normal welding up to the preset error range, and if it is out of this, it can be seen that a welding defect has occurred.

Information on the shape of the weld bead for setting the error range may include a rate of change of the weld toe depth, a rate of change of the area in the direction of the angle, and a rate of deflection of the bend (see FIG. 5).

When the automatic welding machine 100 is manually driven or autonomously driven to arrive at the welding start site and sets the welding part 120 to the welding start site, the image projection unit 150 reads the design welding bead shape and sets the virtual welding bead volume. Acknowledge it (step S305).

The image projection unit 150 projects the virtual welding bead volume onto the joint to be welded (step S310).

The automatic welding machine 100 performs welding by using the virtual welding bead volume as a sketch when welding through the welding part 120 (step S315). The welding part 120 follows and welds volume information made up of a combination of virtual projected lines.

For example, when a laser transmission line is projected onto a welding area, the welding angle long distance, the shape of the welding bead, and the height of each tree can be visually displayed. The automatic welding machine 100 may perform welding based on the visualized line information. To this end, the image capturing unit 130 may be used as a means for obtaining visualized line information. The welding part 120 performs a one-to-one matching operation with the corresponding volume.

In the past, only welding length information was transmitted to the site, so workers had no choice but to empirically conduct welding to satisfy the minimum welding length or more. In contrast, according to the present embodiment, since there is a comparison object, it is possible to accurately finish the welding operation within a shorter time.

The image projection unit 150 may improve the recognition rate by projecting colors onto the laser line.

When welding is in progress, the image photographing unit 130 acquires an image of an actual welding bead shape (step S320). Then, the design welding bead shape and the image-acquired actual welding bead shape are compared (step S325).

In this case, the image photographing unit 130 may store the difference between the virtual welding bead volume and the actual welded bead volume as an image result and perform mapping processing.

In addition, the image reading unit 140 may finally determine the presence or absence of defects through secondary mapping between matters that violate a predetermined error range and existing big data (site error, welding error, defect data, etc.) (step S330. ). In addition, it is possible to determine whether to stop or resume the welding operation.

6 is a view showing a state to which a welding defect inspection method according to an embodiment of the present invention is applied.

If the welds that have been inspected are normal, they are marked in yellow, and the bad welds identified by the laser band are marked in red.

It is natural that the welding defect inspection method according to the present embodiment may be performed as an automated procedure according to a time-series sequence by a program built in or installed in a digital processing device. Codes and code segments constituting the program can be easily inferred by a computer programmer in the art. In addition, the program is stored in a computer readable media that can be read by a digital processing device, and is read and executed by the digital processing device to implement the method. The information storage medium includes a magnetic recording medium, an optical recording medium, and a carrier wave medium.

10: plate 20: welding material
30: welding bead 100: automatic welding machine
110: autonomous driving unit 115: driving wheel
120: welding part 130: image photographing part
140: image reading unit 150: image projection unit

Claims (5)

As an automatic welding machine that performs welding by driving to the welding area,
A welding part for generating a welding bead by performing welding on a welding part;
An image photographing unit for photographing the welding bead; And
Including an image reading unit that reads the image to detect the actual welding bead shape, and compares it with the design welding bead shape to determine whether or not there is a welding defect,
An automatic welding machine having a welding defect inspection function that stops welding when there is a welding defect, reports data on the welding defect, and performs inspection together with welding. The method of claim 1,
An automatic welding machine having a welding defect inspection function further comprising an image projection unit for modeling a virtual welding bead volume by analyzing the design welding bead shape, and projecting the modeled virtual welding bead volume onto the welding area with a plurality of laser lines . The method of claim 2,
An automatic welding machine having a weld joint inspection function in which the plurality of laser lines are projected in distinct colors. The method of claim 2,
The image photographing unit photographs the virtual welding bead volume projected by the plurality of laser lines together,
The image reading unit is an automatic welding machine having a welding defect inspection function for detecting the welding defect by matching the actual welding bead shape and the virtual welding bead volume on a one-to-one basis. The method of claim 2,
In the process of modeling the virtual welding bead volume, an error range is set and coded from information about the design welding bead shape,
The information on the shape of the design weld bead includes at least one of a rate of change of the depth of the weld toe, a rate of change of the area in the direction of the angle, and a rate of deflection of the bending,
The image reading unit is an automatic welding machine having a welding defect inspection function to determine whether the welding defect is determined through the mapping of the violation of the error range and welding defect big data.

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