Welding control method, welding system, welding control program, and multi-layer welding method

Abstract

In automated welding of multi-layer welds, the time required for setting conditions can be reduced, and appropriate welding conditions can be automatically set. [Solution] A welding control method for multi-layer welding using a welding system, wherein the welding system comprises a welding robot, a robot control device, a camera, and a data processing device that processes image data obtained from the camera, and includes the steps of: determining welding conditions at an arbitrary position on the welding start side of the workpiece using the welding robot before welding; starting the welding of the first layer based on the welding conditions, and during the welding of the first layer, the data processing device inputs image data obtained from the camera, outputs feature quantities of the image data to the robot control device, and the robot control device controls at least one of the welding conditions based on the feature quantities; and after welding the first layer, determining teaching point information for the second and subsequent layers before welding the second layer based on the construction information obtained by the control in the welding of the first layer.

Description

Technical Field

[0001] The present invention relates to a welding control method, a welding system, a welding control program, and a multi-layer welding method.

Background Art

[0002] In recent years, in each manufacturing field such as shipbuilding, bridges, and construction, as an automatic welding technology for obtaining high welding quality, there is a technology that uses a vision sensor (hereinafter also referred to as a "camera") and controls welding based on a welding image. For example, in Patent Document 1, even if there are variations in luminance for each image, variations in the arc or molten pool, or variations in the presence or appearance position of spatter, the problem is to enable accurate image recognition. An image obtained by a camera is input to a machine learning model, state-related information output from the machine learning model is acquired, and based on the acquired state-related information, a welding mechanism that performs arc welding is controlled, so that accurate image recognition is possible even if there are variations in luminance for each image. A welding control technology is disclosed.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In this way, welding can be performed automatically and with high precision using a camera. However, in order to perform automatic welding with high precision, it is necessary to set the reference welding conditions to appropriate values ​​automatically. In particular, in multi-layer welding, multiple layers are formed by multiple welding passes, so it is necessary to set the welding conditions automatically for each welding pass. Furthermore, when setting conditions automatically, conventional methods involve teaching or sensing the welding position, but as the workpiece (hereinafter also referred to as "work") becomes larger, the welding length increases, and the number of locations to teach or sense also increases, thus increasing the time required for teaching or sensing. In other words, in automatic welding of multi-layer welds, there is a need for a function that can reduce the time required to set conditions and automatically set appropriate welding conditions. This function is especially important as the workpiece becomes larger. Patent Document 1 discloses a welding control method after the conditions have been set, but it does not consider the above function at all.

[0005] The present invention has been made in view of the above-mentioned problems, and its purpose is to provide a welding control method, welding system, welding control program, and multi-layer welding method that can reduce the time required for setting conditions and automatically set appropriate welding conditions in automatic multi-layer welding. [Means for solving the problem]

[0006] The present invention consists of the following configuration.

[0007] (1) A welding control method for multi-layer welding performed using a welding system, The welding system comprises at least a welding robot, a robot control device for controlling the welding robot, a camera, and a data processing device for processing image data obtained from the camera. Before welding, the welding conditions are determined using the welding robot at an arbitrary position on the workpiece on the welding start side. The steps include: starting the first layer of welding based on the welding conditions; during the welding of the first layer, the data processing device inputs image data obtained from the camera, outputs the feature quantities of the image data to the robot control device, and the robot control device controls at least one of the welding conditions based on the feature quantities; After welding the first layer, the following steps are taken: Before welding the second layer, based on the construction information obtained through the control during welding the first layer, the teaching point information for the second and subsequent layers is determined. A welding control method for multilayer welding, characterized by having the following features.

[0008] (2) A welding control method for multi-layer welding performed using a welding system, The welding system comprises at least a welding robot, a robot control device for controlling the welding robot, a camera, and a data processing device for processing image data obtained from the camera. Before welding, the welding conditions are determined using the welding robot at an arbitrary position on the workpiece on the welding start side. The steps include: starting the first layer of welding based on the welding conditions; during the welding of the first layer, the data processing device inputs image data obtained from the camera, outputs the feature quantities of the image data to the robot control device, and the robot control device controls at least one of the welding conditions based on the feature quantities; After welding the first layer, the step of determining the teaching point information for the second layer before welding the second layer, based on the construction information obtained by the control during welding the first layer, For the second layer and beyond, based on the construction information obtained by the control during welding of the nth layer (where n is a natural number greater than or equal to 2), the step of determining at least one of the following before welding the (n+1)th layer: teaching point information for the (n+1)th layer, welding conditions for the teaching point information, and the layering pattern of the teaching point information. A welding control method for multilayer welding, characterized by having the following features.

[0009] (3) A welding system for performing multi-layer welding, The system comprises at least a welding robot, a robot control device for controlling the welding robot, a camera, and a data processing device for processing image data obtained from the camera. The welding robot determines the welding conditions at an arbitrary position on the workpiece on the welding start side before welding. Based on the aforementioned welding conditions, the welding of the first layer is started. The data processing device inputs image data obtained from the camera during the welding of the first layer, and outputs the feature quantities of the image data to the robot control device. The robot control device controls at least one of the welding conditions based on the feature quantity. After welding the first layer, the robot control device determines the teaching point information for the second and subsequent layers before welding the second layer, based on the construction information obtained through the control of the first layer welding. Welding system.

[0010] (4) A welding control program for multi-layer welding, A robot control device for controlling a welding robot, A function to cause the welding robot to perform the first layer of welding based on welding conditions determined at an arbitrary position on the workpiece on the welding start side before welding, During the welding of the first layer, the image data includes the molten pool, welding wire, and arc, and has a function to control at least one of the welding conditions based on the feature quantities of the image data obtained based on the image data obtained from the camera. After welding the first layer, and based on the construction information obtained through the control during welding the first layer, a function is provided to determine the teaching point information for the second and subsequent layers before welding the second layer. A welding control program that makes this possible.

[0011] (5) A multilayer welding method using a welding system, The welding system comprises at least a welding robot, a robot control device for controlling the welding robot, a camera, and a data processing device for processing image data obtained from the camera. Before welding, determining welding conditions at an arbitrary position on the welding start side of the workpiece to be welded; Starting the first layer of welding based on the welding conditions, and during the first layer of welding, controlling at least one of the welding conditions based on the feature amount of the image data obtained based on the image data in which the molten pool, the welding wire, and the arc are included in the image and obtained from the camera; After the first layer of welding, determining the teaching point information for the second layer and subsequent layers before the second layer of welding based on the construction information obtained by the control in the first layer of welding; A multi-layer bead welding method, characterized by comprising the above steps.

Effect of the Invention

[0012] According to the present invention, in the automatic welding of multi-layer bead welding, the time for condition setting can be reduced, and appropriate welding conditions can be automatically set.

Brief Description of the Drawings

[0013] [Figure 1] FIG. 1 is a schematic diagram showing a configuration example of a welding system according to the present embodiment. [Figure 2] FIG. 2 is a flowchart showing an example of a welding control process according to the present embodiment. [Figure 3] FIG. 3 is a perspective view for explaining the arrangement position of an imaging device according to the present embodiment. [Figure 4] FIG. 4 is a diagram illustrating a welding image captured by an imaging device in the case of welding in a horizontal posture. [Figure 5] FIG. 33 is a block diagram showing a configuration example of a data processing device according to the present embodiment. [Figure 6] FIG. 6 is an explanatory diagram showing an example of a screen used for teaching work. [Figure 7] FIG. 7 is an explanatory diagram showing a specific example of a welding image obtained by welding in a horizontal posture and an example of welding information in the welding image. [Figure 8] FIG. 8 is a conceptual diagram illustrating the amount of deviation from a welding line according to the present embodiment. [Figure 9] Figure 9 is a conceptual diagram illustrating how teaching points are added and updated according to this embodiment. [Modes for carrying out the invention]

[0014] Hereinafter, a welding system according to one embodiment of the present invention will be described with reference to the drawings. In each drawing, the same components are given the same reference numeral to indicate their correspondence. The welding system according to the present invention is suitable for a portable welding robot, but is not limited to the configuration of this embodiment. For example, it may be a 6-axis welding robot or an automatic welding device having a drive unit such as a trolley. In this embodiment, as an example, single-sided welding in a horizontal position is selected, but is not limited to this, and the construction method and welding position are not particularly limited.

[0015] Furthermore, in this embodiment, as will be described later, at least the molten pool during welding is captured in the image data, and feature points related to the molten pool, welding wire, and arc are extracted. The method for extracting these feature points is not particularly limited, but in this embodiment, feature points are extracted using a data processing device described later.

[0016] Figure 1 is a schematic diagram showing an example of the configuration of a welding system according to this embodiment. The welding system 50 includes a portable welding robot 100, a feed device 300, a welding power supply 400, a shielding gas supply source 500, a robot control device 600, an imaging device 700, and a data processing device 800. As described above, when applying the features of this embodiment to an automatic welding device having a drive unit such as a 6-axis welding robot or a trolley, further configurations may be included to match those configurations. In addition, each part constituting the welding system 50 is connected in a communicative manner by various wired or wireless communication methods. The communication method here is not limited to one, and multiple communication methods may be combined for connection.

[0017] (Robot control device) The robot control device 600 is connected to the portable welding robot 100 by a robot control cable 610 and to the welding power supply 400 by a power supply control cable 620. The robot control device 600 has a data holding unit 601 that holds teaching data that defines in advance the operation pattern of the portable welding robot 100, welding start position, welding end position, construction conditions, welding conditions, parameter table (hereinafter also referred to as "condition DB"), etc. Based on this teaching data, it sends command information as commands to the portable welding robot 100 and the welding power supply 400 to control the operation of the portable welding robot 100 and the welding conditions.

[0018] Furthermore, the robot control device 600 may include a groove shape information calculation unit 602 that calculates groove shape information from detection data obtained by performing sensing such as touch sensing before welding, and a welding condition acquisition unit 603 that performs stack design based on at least one of the groove shape information and the condition DB, and sets or corrects the welding conditions of the teaching data for each pass. The groove shape information calculation unit 602 and the welding condition acquisition unit 603 constitute the control unit 604. The control unit 604 is configured using, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), a DSP (Digital Signal Processor), or an FPGA (Field Programmable Gate Array). In this embodiment, welding condition setting using sensing, which is most preferable from the viewpoint of efficiency, is applied, but it is not limited to this, and for example, welding condition setting may be performed by direct teaching. Furthermore, in the present invention, the sensing position or teaching position (hereinafter also referred to as the "teaching position" or "teaching point") of the first layer (hereinafter also referred to as the "first layer") is any position on the welding start side, as will be described later. Note that any position on the welding start side refers to the welding start position or the vicinity of the welding start position. In this embodiment, the welding start position is used from the viewpoint of accuracy of groove shape information, but the welding conditions at the welding start position may be set based on groove shape information in the vicinity of the welding start position. The layer design and welding condition setting for the second pass and subsequent passes according to the present invention will also be described later.

[0019] Lamination design refers to determining the appropriate number of layers and passes for a given groove. A layer refers to the number of times the weld bead is layered in the thickness direction of the plate. In lamination design for multi-layer welding, it is generally assumed that the layer height per layer is kept constant. Therefore, it is preferable to perform lamination design based on groove shape information and set or correct the welding conditions based on the calculated lamination design information. Here, lamination design information includes the number of layers, the number of passes, and the layer height (≒ height of one pass), but the welding conditions are determined based on at least the calculated layer height value. For example, if sensing reveals that the gap is larger at the end of welding than at the start of welding, the gap width will widen as welding progresses, so it is necessary to increase the amount of weld material to keep the layer height constant. In this case, welding conditions related to the amount of weld material include wire feeding speed and welding speed, and these welding conditions should be set or corrected based on the groove shape information and lamination design information.

[0020] Figure 2 is a flowchart illustrating an example of welding control processing according to this embodiment. In this embodiment, the robot control device 600 starts welding with welding conditions set or corrected based on sensing. The imaging device 700 captures images of the molten pool during welding, including the molten pool in the image data. The data processing device 800, which acquires the captured image data, extracts feature points. The robot control device 600 then receives correction signals for various processes as command information (hereinafter also referred to as "commands") from the information of each feature point (S1). The robot control device 600 sequentially executes controls such as gap processing (S2), rod movement processing (S3), tracing and amplitude processing (S4), and speed processing (S5), which will be described later. The robot control device 600 performs each control process according to the correction signals received during welding, and then outputs information on the status update of various control conditions to the data processing device 800 (S6). The above processes (S1 to S6) are repeated until the target welding is completed (S7).

[0021] The welding power supply 400, under the command of the robot control device 600, supplies power to the welding wire 211 and the workpiece Wo, which are consumable electrodes, thereby generating an arc between the welding wire 211 and the workpiece Wo. Power from the welding power supply 400 is sent to the feeder 300 via the power cable 410, and from the feeder 300 to the welding torch (hereinafter referred to as "torch") 200 via the conduit tube 420. Power from the welding power supply 400 is then supplied to the welding wire 211 via the contact tip at the tip of the torch 200. The current during welding may be DC or AC, and its waveform is not particularly specified. Therefore, the current may be a pulse such as a square wave or a triangular wave.

[0022] Furthermore, the welding power supply 400 is configured such that, for example, power cable 410 is connected to the torch 200 as the positive electrode, and power cable 430 is connected to the workpiece Wo as the negative electrode. Note that this is the case when welding with reverse polarity; when welding with positive polarity, the power cable for the positive electrode should be connected to the workpiece Wo, and the power cable for the negative electrode should be connected to the torch 200.

[0023] (Shielding gas supply source) The shielding gas supply source 500 consists of a container filled with shielding gas, ancillary components such as valves, etc. Shielding gas is supplied from the shielding gas supply source 500 to the supply device 300 via a gas tube 510. The shielding gas supplied to the supply device 300 is then supplied to the torch 200 via a conduit tube 420. The shielding gas supplied to the torch 200 flows through the torch 200, is guided to the nozzle 210, and is ejected from the tip of the torch 200. Examples of shielding gases used in this embodiment include argon (Ar), carbon dioxide (CO2), or a mixture thereof.

[0024] In this embodiment, the conduit tube 420 has a conductive path formed on the outer sheath side of the tube for functioning as a power cable, a protective tube for protecting the welding wire 211 is arranged inside the tube, and a flow path for shielding gas is formed. However, the conduit tube 420 is not limited to this, and for example, a bundle of power supply cables and shielding gas supply hoses can be used with a protective tube for supplying the welding wire 211 to the torch 200 at its center. Alternatively, for example, the tube for supplying the welding wire 211 and shielding gas and the power cable can be installed separately.

[0025] (Feeding device) The feeding device 300 feeds the welding wire 211 to the torch 200. The welding wire 211 fed by the feeding device 300 is not particularly limited and is selected according to the properties of the workpiece Wo and the welding method, for example, solid wire or flux-cored wire can be used. The wire diameter of the welding wire is not particularly limited, but in this embodiment, the preferred wire diameter is 1.6 mm at the upper limit and 0.9 mm at the lower limit.

[0026] Furthermore, in this embodiment, a voltage is applied between the workpiece Wo and the welding wire 211, and a touch sensor is used as the detection means to sense the surface of the groove 10 shown in Figure 3 by utilizing the voltage drop phenomenon that occurs when the welding wire 211 comes into contact with the workpiece Wo. The detection means is not limited to the touch sensor of this embodiment, and an image sensor, laser sensor, or a combination of these detection means may be used, but it is preferable to use the touch sensor of this embodiment due to the simplicity of the device configuration.

[0027] (Imaging device) The imaging device 700 (hereinafter also referred to as the "visual sensor" or "camera") is composed of, for example, a camera equipped with a CMOS (Complementary Metal-Oxide-Semiconductor) as a visual sensor. The placement of the imaging device 700 is not particularly limited; it may be directly attached to the portable welding robot 100, or it may be fixed in a specific location in the surrounding area as a surveillance camera. When the imaging device 700 is directly attached to the portable welding robot 100, the imaging device 700 moves in accordance with the operation of the portable welding robot 100 to image the area around the tip of the torch 200. The imaging device 700 may consist of multiple cameras. For example, the imaging device 700 may be composed of multiple cameras with different functions and installation locations.

[0028] Furthermore, the direction in which the imaging device 700 captures images is not particularly limited. For example, if the direction in which welding progresses is forward, the device may be positioned to capture images from the front, or it may be positioned to capture images from the side or rear. Therefore, the imaging range of the imaging device 700 can be determined as appropriate. In order to suppress interference from the torch 200, it is preferable to capture images from the front, and in this embodiment, imaging is performed from the front. The captured image information is transmitted to the data processing device 800 and used by the data processing device 800. At this time, the data processing device 800 may, for example, select arbitrary images from the captured image information at predetermined intervals and use them for processing described later. The method of selection and selection settings here may be switched according to, for example, the configuration and function of the imaging device 700 and the performance of the data processing device 800.

[0029] In this embodiment, an imaging device 700 is directly attached to and fixed to a portable welding robot 100, and a moving image is captured as a welding image, such that the imaging range includes at least the workpiece Wo, the welding wire 211, and the arc as objects (targets) to be included in the image data. Various imaging settings related to the welding image may be predetermined or switched according to the operating conditions of the welding system 50. Examples of imaging settings include the frame rate, the number of pixels in the image, the resolution, and the shutter speed.

[0030] Figure 3 is a perspective view illustrating the arrangement of the imaging device 700 according to this embodiment. Note that the orientation of the torch 200 and the groove differs depending on the welding position, so the orientation shown in Figure 3 is just one example. In this embodiment, the workpiece Wo is a butt joint. The workpiece Wo consists of two metal plates that are butted together with a groove in between. In this embodiment, a horizontal orientation is given as an example, in which case the upper plate workpiece will be referred to as W1 (hereinafter referred to as "upper plate W1") and the lower plate workpiece as W2 (hereinafter referred to as "lower plate W2"). ​​A ceramic backing material 14 is attached to the back side of the two butted workpieces W1 and W2. Note that a metal backing material may be used as the backing material 14, or a configuration without a backing material may be used. Therefore, the material of the backing material is not particularly limited and may differ depending on the material of the workpiece Wo, etc. In a butt joint, arc welding is performed in one direction along the groove. In the following, the direction in which welding progresses is referred to as the "weld line direction." In Figure 3, the direction in which welding progresses is indicated by an arrow. For this reason, the torch 200 is located behind the imaging device 700.

[0031] Figure 4 illustrates a welding image captured by the imaging device 700 in the case of welding in a horizontal position. The image data in Figure 4 has coordinates on a coordinate plane consisting of two axes, the X axis and the Y axis. In this embodiment of the horizontal position, the X axis indicates the direction of the welding line, and the Y axis indicates the direction perpendicular to the X axis. The imaging device 700 captures an image of the range including the welding position of the workpiece Wo during arc welding. This captured image includes the molten pool, welding wire 211, and arc.

[0032] The visual sensor of the imaging device 700 in this embodiment can continuously capture still images of, for example, 1024 × 768 pixels. In other words, the imaging device 700 can capture welding images as moving images. The resolution of still images that can be captured by the imaging device 700 is not particularly limited. For example, if the imaging device 700 is composed of multiple cameras, each of the multiple cameras may acquire welding images of different resolutions. Furthermore, before inputting into the trained model described later, preprocessing such as extracting an arbitrary feature region from the captured welding image may be performed for the purpose of reducing processing time. The arbitrary feature region may be a fixed-size range arranged so that a predetermined area is located in the center. Also, the size of the arbitrary feature region may be changed according to the welding conditions.

[0033] (Data processing device) Figure 5 is a block diagram showing an example configuration of the data processing device 800 according to this embodiment. The data processing device 800 is composed of, for example, a computer. The computer is composed of a main unit 810, an input unit 820, and a display unit 830. The main unit 810 is composed of a CPU 811, a GPU (Graphical Processing Unit) 812, a ROM 813, a RAM 814, a non-volatile storage device 815, an input / output interface 816, a communication interface 817, a video output interface 818, and a calculation unit 819. The CPU 811, GPU 812, ROM 813, RAM 814, non-volatile storage device 815, input / output interface 816, communication interface 817, video output interface 818, and calculation unit 819 are connected to each other so as to be able to communicate with each other by buses or signal lines.

[0034] The non-volatile storage device 815 stores a learning program 815A that performs deep learning using predetermined training data, a trained model 815B generated through the execution of the learning program 815A, an information generation program 815C that generates welding information related to welding using the trained model 815B, and image data 815D. In addition to these, the non-volatile storage device 815 also has an operating system and application programs installed.

[0035] The data processing unit 800 implements various functions through the execution of programs by the CPU 811 and GPU 812. In this embodiment, the data processing unit 800 implements the function of generating a trained model by machine learning and the function of performing various processes during actual welding using the trained model. The details of these functions will be described later. Alternatively, the data processing unit 800 may be divided into two parts: one for generating a trained model and another for performing control processing based on information output from the trained model during actual welding. From the standpoint of versatility, it is more preferable to divide the data processing unit 800 according to each function. The GPU 812 is used as the arithmetic unit when executing the learning program 815A and the information generation program 815C. The ROM 813 stores the BIOS (Basic Input Output System) and other programs executed by the CPU 811. The RAM 814 is used as the working area for programs read from the non-volatile storage device 815.

[0036] The input / output interface 816 is connected to the input unit 820, which consists of a keyboard, mouse, etc. An imaging device 700, which is a visual sensor, is also connected to the input / output interface 816. Image data output from the imaging device 700 is provided to the CPU 811 via the input / output interface 816. The communication interface 817 is a communication module for wired or wireless communication. The video output interface 818 is connected to a display unit 830, which consists of, for example, a liquid crystal display or an organic EL (Electro-Luminescence) display, and outputs a video signal to the display unit 830 according to the video data provided by the CPU 811. The calculation unit 819 works in cooperation with the CPU 811 and GPU 812 to perform various processes, such as calculating geometric quantities used to control the welding speed according to this embodiment. These geometric quantities will be described later.

[0037] (Generating a pre-trained model) The following describes the feature points extracted from image data and the trained model used to extract these feature points in this embodiment. The trained model 815B in this embodiment is composed of a convolutional neural network and includes multiple convolutional layers and multiple pooling layers. However, the configuration of the convolutional neural network is not limited to the above, and the number of layers and configuration may be different.

[0038] The trained model 815B takes the welding image output from the imaging device 700 as input data and outputs feature information for calculating at least the gap width and molten pool information related to the welding direction. In this embodiment, the captured image input to the trained model 815B includes at least the molten pool, welding wire, and arc as objects, i.e., targets. By inputting the captured image to the trained model 815B, feature points obtained from each of these objects, or from between multiple objects, are extracted. Based on the extracted feature points, the data processing device 800 acquires information such as the gap width and molten pool information, described later, as geometric quantities in real time. Examples of geometric quantities of molten pool information include the distance between the welding wire and the tip of the molten pool in the welding direction, the width of the molten pool, or the area of ​​the molten pool. For example, the molten pool information includes at least one of the distance between a predetermined position in the welding image and the tip of the molten pool, and the area of ​​the molten pool. The predetermined position may be the wire tip position or the arc center point.

[0039] In this embodiment, the feature points related to welding information are the tip of the welding wire 211 (hereinafter also referred to as the "wire tip"), the center point of the arc (hereinafter also referred to as the "arc center"), the positions of the left and right (however, up and down in the case of a sideways orientation) ends of the molten pool relative to the welding direction, and the positions of the left and right (however, up and down in the case of a sideways orientation) ends of the molten pool relative to the welding direction. The input of feature points to be used as training data is performed by the operator specifying a specific position on the welding image according to the instructions on the operation screen that supports the teaching work. Therefore, the training data is composed of pairs of welding images and feature points that are coordinate information as welding information specified by the operator. In the learning process, the welding information output from the learning model is compared with the welding information included in the training data, and the parameters are adjusted by feeding back the error. By repeating this process, machine learning progresses, and a trained model 815B is generated.

[0040] Figure 6 is an explanatory diagram showing an example of a screen used for teaching. The welding image shown in Figure 6 includes the molten pool 15, welding wire 211, and arc 16. In Figure 6, the molten pool 15 is shown with shading. Figure 7 is an explanatory diagram showing a specific example of a welding image obtained by welding in a horizontal position, and an example of welding information within that welding image. Here, for the sake of ease of explanation, positions corresponding to the coordinates indicated by feature points are drawn on the welding image. As mentioned above, the image has coordinates and is a coordinate plane consisting of two axes, the X axis and the Y axis. In the explanation of Figures 6 and 7, "upper end" and "lower end" merely indicate the top and bottom of the image, and may be replaced with "right end," "left end," etc., depending on the welding position and the orientation of the image.

[0041] In this embodiment, the imaging device 700 is installed so that the welding line direction and the X-axis direction are parallel. Therefore, in this embodiment, the X-axis direction may be referred to as the welding line direction. Also, the Y-axis direction is perpendicular to the X-axis, or in other words, it is the groove width direction which is perpendicular to the welding line. Therefore, the Y-axis direction may be referred to as the groove width direction. Furthermore, since the X-axis on which the portable robot moves in this embodiment is the welding line direction, the X-axis on which the portable robot moves and the X-axis on the welding image have the same direction. Similarly, the Y-axis direction on which the portable robot moves and the Y-axis direction on the welding image are also the same.

[0042] In this embodiment, as shown in Figure 6, the operator is taught the following feature points: the coordinate position PA (ArcX, ArcY) of the arc center, the coordinate position PW (WireX, WireY) of the wire tip, the coordinate position PLD (Pool_Lead_Dx, Pool_Lead_Dy) of the area below the molten pool tip, the coordinate position PLU (Pool_Lead_Ux, Pool_Lead_Uy) of the area above the molten pool tip, the coordinate position PD (Pool_Dy) of the lower end of the molten pool, and the coordinate position PU (Pool_Uy) of the upper end of the molten pool. Feature point input is performed by the operator indicating a specific position on the screen. The coordinates that define the boundary between the welding wire 211 and the arc are an example of the wire tip position coordinates. Also, the area below the molten pool tip, the area above the molten pool tip, the lower end of the molten pool, and the upper end of the molten pool are examples of feature points related to the behavior of the molten pool 15. For example, if the feature points of the lower end and upper end of the molten pool are known, the width of the molten pool 15 can be calculated.

[0043] (Geometric quantity data) In this embodiment, the robot control device 600 or the data processing device 800 calculates at least two values: the difference in the X direction between a predetermined position on the molten pool tip and the position of the wire tip (hereinafter referred to as "LeadX"), and the difference between the position above the molten pool tip and the position below the molten pool tip (hereinafter referred to as "LeadW"). In this embodiment, the numerical data calculated based on the feature points in this way is also referred to as "geometric quantity data". The data processing device 800 calculates this geometric quantity data and transmits it to the robot control device 600 at predetermined time intervals, and the robot control device 600 performs welding control. The molten pool tip position may be either above the molten pool tip or below the molten pool tip, depending on the application, regardless of the difference between the position above and below the molten pool tip. The robot control device 600 and the data processing device 800 may be integrated. Within the bounds of avoiding inconsistencies, the data processing device 800 may perform the processing that the robot control device 600 is supposed to perform, and the robot control device 600 may perform the processing that the data processing device 800 is supposed to perform.

[0044] <Welding control method for multi-layer welding> The groove on a workpiece typically has varying weld line deviations and widths depending on the location. Conventionally, this required sensing at multiple locations before welding, and the larger the workpiece and the longer the weld length, the longer the sensing time. In the present invention, pre-welding sensing is limited to the welding start point only. Layer design is performed based on the groove shape at the start point, and welding conditions are set based on the layer design. Welding is started with the set welding conditions, and during welding, the imaging device 700 and data processing device 800 are used to control welding conditions, trace the weld line, and trace the width, completing the first layer of welding. This reduces the sensing time, even for larger workpieces, and improves welding efficiency. Furthermore, for the second layer, layer design is performed at each position on the weld line based on the construction information obtained from the first layer of welding, and welding conditions are set. Since the conditions at each position on the weld line can be set using the construction information obtained from the first layer of welding, this process is time-efficient. In the present invention, the position on the weld line where welding conditions are set is referred to as the teaching position. Furthermore, the optimal conditions for the second layer can be set according to the workpiece affected by the first layer of welding. In other words, the conditions for the second layer can be set for a workpiece that takes into account the deformation caused by thermal distortion due to the first layer of welding, without requiring any extra time.

[0045] Furthermore, for the second layer and beyond, welding may be performed using welding conditions based on the lamination design performed in the second layer, as in this embodiment. This is because, by designing the lamination using construction information such as gap width and profile obtained from the welding of the first layer, it becomes possible to produce welded joints with stable quality. Therefore, the lamination design may be performed in the second layer, and the set conditions may be applied directly to the third layer and beyond. Alternatively, processing may also be performed using the imaging device 700 and data processing device 800 for the second layer, and in the third layer, the teaching position may be determined again and the welding conditions may be set. In this way, workpiece information may be acquired for each layer or each pass, and the lamination design may be redesigned for the next layer or next pass, and the welding conditions may be reset. The details of the welding control method for multi-layer welding will be described step by step below.

[0046] [Before welding] (STEP 1: Sensing) The sensing step before welding begins allows the groove shape, plate thickness, starting point, etc., to be identified by touch sensing using the touch sensor described above. In this embodiment, at least the welding start position is identified by touch sensing of the groove shape and plate thickness. A groove shape information calculation step is performed to calculate groove shape information from the detection data of the groove cross-sectional shape obtained from sensing the welding start position. Examples of groove shape information include the groove angle, plate thickness, groove depth, estimated weld metal height, and gap. After this groove shape information calculation step, the calculated data is input as set values ​​to the data holding unit 601. In this embodiment, in the groove shape information calculation step, at least one of the plate thickness, groove depth, and estimated weld metal height, along with the gap, is calculated as groove shape information and input as set values ​​to the data holding unit 601. In the groove shape information calculation step, if the gap is smaller than the wire diameter of the welding wire, the gap amount may be calculated as 0.

[0047] (STEP 2: Setting welding conditions for the starting point) Next, based on the groove shape information data and condition DB input as set values ​​to the data holding unit 601, the setting conditions on the teaching program data are set for each layer and each pass corresponding to the layer design. In other words, a program is initially set to weld the entire length of the weld using the welding conditions at the starting point. In this embodiment, for example, the welding current, arc voltage, welding speed, and weaving conditions are set as welding conditions. In this embodiment, although it is called setting, it may also be correcting. That is, if the set value has not yet been set, it is set, and if the set value has already been set, the set value is corrected.

[0048] [Welding the first layer] (STEP 3: Welding control for the first layer) The welding of the first layer is started with the welding conditions set at the starting point. In this embodiment, the first layer is formed in one pass, so the first layer = 1 pass. As soon as welding starts, as described above, the imaging device 700 starts capturing images, inputs the welding images to the data processing device 800, calculates geometric quantity data from the welding image data, and outputs the geometric quantity data to the robot control device 600. In this embodiment, the geometric quantity data output to the robot control device 600 is LeadX and LeadW as described above. The robot control device 600, having received the geometric quantity data, performs welding control based on the flow in Figure 2. In this embodiment, the first layer = 1 pass example is used, but the number of passes for each layer is irrelevant, and the present invention is applicable even if the welding of the first layer takes two or more passes.

[0049] As shown in Figure 2, the robot control device 600 receives information including the aforementioned geometric quantity data from the data processing device 800 at predetermined time intervals. This reception is also referred to as command reception. When the robot control device 600 receives a command, in gap processing S2, it changes the welding conditions set at the starting point position according to the received geometric quantity data of LeadW. By changing the welding conditions based on LeadW in this way, welding of the first layer becomes possible with only starting point sensing. In this embodiment, the geometric quantity data of LeadW is treated as the gap value in gap processing S2. In this embodiment, the unit of the gap value is mm, and the geometric quantity data of the first layer LeadW is referred to as the "root gap". There is no particular method for changing the welding conditions according to the geometric quantity data of LeadW, but in this embodiment, a database (hereinafter also referred to as the "rod DB") is prepared in advance for each welding mode, which contains welding conditions corresponding to the gap value, and the welding conditions can be changed based on the rod DB and the received geometric quantity data of LeadW. The welding mode referred to here refers to fixed conditions such as wire type, shielding gas type, inclination angle, and pitch. These fixed conditions are also called "standard items." The rod movement DB can be stored in a memory area such as the data holding unit 601 of the robot control device 600.

[0050] In the rod movement process S3 shown in Figure 2, the robot control device 600 determines the rod movement method based on the information received from the command or the information from the pre-processing, such as the gap processing S2. Rod movement is also called weaving. In this embodiment, the robot control device 600 determines the weaving method based on conditions such as the offset amount, weaving amplitude, end stop time (lower end), and end stop time (upper end) determined in the gap processing S2. If weaving is not specified, the rod movement process S3 is skipped, but in this embodiment, it is preferable to use weaving for the first layer of welding. This is because using weaving for the first layer improves the welding quality of the first layer and allows for the acquisition of a flat bead, thus making the welding of the second layer and beyond more stable. This effect is particularly noticeable in welding in difficult positions such as a lateral position. Furthermore, it is even more preferable to change the welding conditions at each position during weaving. Specifically, it is preferable to change the welding conditions during weaving when (a) moving from one end to the other end, (b) when positioned at one end, and (c) when positioned at the other end. Taking the sideways orientation as an example, it is advisable to change conditions such as current and voltage during periods of upper end stoppage, lower end stoppage, movement from upper end to lower end, and movement from lower end to upper end, as well as upper end stoppage time and lower end stoppage time.

[0051] Regarding tracing and amplitude processing, in this embodiment, it is performed by tracing and amplitude processing S4 shown in Figure 2. In tracing and amplitude processing S4, the robot control device 600 performs welding line tracing and width tracing based on the information received from the command or the information from the pre-processing. The tracing method is not limited, but in this embodiment, the center position of LeadW is set as the welding center position, and welding line tracing control is performed according to the direction and amount of deviation from the welding center position (hereinafter also referred to as "amount of deviation from the welding line") calculated based on the welding center position and the coordinate position PW of the wire tip. Taking the lateral orientation in this embodiment as an example, it is good to determine whether there is a deviation in the downward direction or in the upward direction. In addition, width tracing control is performed by calculating the amplitude correction amount according to the value of LeadW. Figure 8 is a conceptual diagram illustrating the amount of deviation from the welding line in this embodiment.

[0052] In the present invention, further corrections are made to the conditions set according to the gap. This correction process further improves the accuracy of the control, and stable welding quality can be maintained even when various conditions such as welding conditions, weaving method, welding position, root gap, backing gap, and misalignment are combined. The condition to be corrected can be any one of the following: welding speed, welding current, arc voltage, or overhang length, but from the viewpoint of ease of control and accuracy, it is preferable to correct at least the welding speed. In this embodiment, speed processing S5 is performed in Figure 2 to correct the welding speed. Speed ​​processing S5 shown in Figure 2 calculates the amount of correction for the welding speed using the gap width value obtained by receiving a command and LeadX, which is one of the molten pool information related to the welding direction. In speed processing S5 of this embodiment, LeadW is used as the gap width value. In addition, although LeadX is used as the molten pool information related to the welding direction in this embodiment, other geometric quantity data such as molten pool area may be used.

[0053] In accordance with the welding conditions modified by the above process, the robot control device 600 transmits command values ​​to the portable welding robot 100 and the welding power supply 400. The process described above, from steps S1 to S6 in Figure 2, is repeated until the welding of the first layer is completed.

[0054] [After welding the first layer ~ Before welding the second layer] (STEP 4: Determining the teaching point information for the second layer) After the first layer of welding, teaching point information on the weld area is determined based on the construction information obtained during the first layer of welding. Teaching point information includes, for example, the teaching position (which may simply be called the "teaching point") and information on the groove cross-sectional shape at the teaching position. Determining teaching point information refers to adding or updating the teaching position and the groove cross-sectional shape information at the teaching position.

[0055] In this embodiment, the construction information obtained during the welding of the first layer refers to the gap width value (LeadW value) of the entire length of the welded section or the amount of deviation from the weld line. The teaching point information is determined based on the gap width value, the amount of deviation from the weld line, or both.

[0056] For example, the determination of teaching point information, such as teaching positions and groove cross-sectional shapes at teaching positions, is performed by adding or updating them at positions where the welding start position, welding end position, gap width, or deviation from the weld line changes by predetermined lengths. For example, in the case of welding where the gap width changes, teaching positions and groove cross-sectional shapes at teaching positions are added or updated at positions where the gap width changes by predetermined lengths from the gap width at the starting position. Figure 9 is a conceptual diagram illustrating how teaching positions are added or updated according to this embodiment. In Figure 9, for example, when the gap width changes every 2 mm, teaching positions and groove cross-sectional shapes at teaching positions are added or updated, with positions at 4 mm, 6 mm, 8 mm, and 10 mm being added or updated as teaching positions, and groove cross-sectional shapes at each teaching position being added or updated.

[0057] A preferred method for determining teaching point information is to determine it based on both the gap width value and the amount of deviation from the weld line for each half-cycle of weaving or each robot control cycle.

[0058] (STEP 5: Setting conditions for the second layer) Based on the groove shape information for each teaching position of the second layer obtained in STEP 4, the layer design is performed by referring to the condition database. Alternatively, the layer design for each teaching point can be performed using the gap width at each teaching position obtained during welding of the first layer and the groove shape information other than the gap width obtained during start point sensing, and the conditions can be set based on that layer design.

[0059] In this embodiment, standard gap width stacking design information (hereinafter also referred to as "standard stacking design information") is stored in the condition DB in advance. Based on the standard stacking design information, the robot control device 600 simply calculates the cross-sectional area per pass at each teaching position and determines the welding conditions from that cross-sectional area. For example, if it is foreseeable in advance that the gap width will vary from 4 to 10 mm due to the nature of the workpiece to be welded, a stacking design with a median gap width of 7 mm is prepared in advance, and the cross-sectional area per pass at each teaching position obtained from the stacking design (number of layers - number of passes) with a gap width of 7 mm is calculated and the welding conditions are set. At this time, the cross-sectional area per pass at a teaching position can be simply calculated by multiplying the cross-sectional area of ​​each pass in the standard stacking design information by (10 mm / 7 mm) if the gap width is 10 mm, or by multiplying by (4 mm / 7 mm) if the gap width is 4 mm, and so on. This allows welding conditions for multiple teaching positions to be easily set using a single piece of predefined standard layered design information, significantly reducing the workload associated with calculation processing.

[0060] (STEP 6: Welding of the second layer and beyond) In this embodiment, the passes from the second layer onwards are welded using welding conditions based on the layer design generated at each teaching point. Alternatively, the passes from the second layer onwards may also be processed using the imaging device 700 and data processing device 800 to determine the teaching position again for the next layer and set the conditions. Workpiece information may be acquired for each layer or pass, and the layer design may be redesigned and the welding conditions reset for the next layer or pass. Specifically, for the second layer onwards, based on the construction information obtained through control during the welding of the nth layer (where n is a natural number greater than or equal to 2), at least one of the following may be determined before welding the (n+1)th layer: the teaching point information for the (n+1)th layer, the welding conditions for the teaching point information, and the layering pattern of the teaching point information.

[0061] By controlling multi-layer welding through the steps described above, welding time can be significantly reduced, and welding can be performed under optimal conditions for the second and subsequent layers, resulting in excellent weld quality.

[0062] (Selection of welding materials) In the present invention, all layers may be welded using the same welding material, or the welding material may be changed for each layer. The welding material to be applied is selected from at least slag-type flux-cored wire, metal-type flux-cored wire, and solid wire. When all layers are welded using the same welding material, it is preferable to use one of slag-type flux-cored wire, metal-type flux-cored wire, or solid wire from the viewpoint of weldability. When the welding material is changed for each layer, it is preferable to weld the first layer or the nth layer (where n is a natural number selected from 2 or more) with the same welding material, and then use a different welding material for the n+1th layer and beyond. Specifically, by using slag-type flux-cored wire or metal-type flux-cored wire for the first or second layer, which are difficult to weld, a good bead shape can be obtained. On the other hand, by switching to solid wire for the third layer and beyond, good penetration can be obtained.

[0063] The present invention is not limited to the embodiments described above. It is also intended and within the scope of protection to be provided for the combination of each configuration of the embodiments, as well as for modifications and applications by those skilled in the art based on the description in the specification and well-known art.

[0064] As described above, the following matters are disclosed in this specification:

[0065] (1) A welding control method for multi-layer welding performed using a welding system, The welding system comprises at least a welding robot, a robot control device for controlling the welding robot, a camera, and a data processing device for processing image data obtained from the camera. Before welding, the welding conditions are determined using the welding robot at an arbitrary position on the workpiece on the welding start side. The steps include: starting the first layer of welding based on the welding conditions; during the welding of the first layer, the data processing device inputs image data obtained from the camera, outputs the feature quantities of the image data to the robot control device, and the robot control device controls at least one of the welding conditions based on the feature quantities; After welding the first layer, the following steps are taken: Before welding the second layer, based on the construction information obtained through the control during welding the first layer, the teaching point information for the second and subsequent layers is determined. A welding control method for multilayer welding, characterized by having the following features.

[0066] (2) Weaving is performed during the welding of the first layer, At a minimum, the welding conditions during weaving are varied when moving from one end to the other, when positioned at one end, and when positioned at the other end. The welding control method according to (1), characterized by having the following.

[0067] (3) The welding control method according to (2), characterized in that the welding conditions in the weaving are determined from a pre-set DB based on geometric quantity data or construction information acquired during welding.

[0068] (4) The welding control method according to (1), characterized in that the construction information is at least one of the gap and the amount of deviation from the weld line.

[0069] (5) The welding material shall be selected from at least one of the following: solid wire, slag-type flux-cored wire, and metal-type flux-cored wire. When n is a natural number selected from 2 or greater, The first or nth layer of welding is performed using the same welding material. From the (n+1)th layer onward, a different welding material will be used than the first n layers. A welding control method characterized by any one of (1) to (4).

[0070] (6) The welding material shall be selected from at least one of the following: solid wire, slag-type flux-cored wire, and metal-type flux-cored wire. Perform welding of all layers using the same welding material. A welding control method described in any one of (1) to (4), characterized by the above.

[0071] (7) A welding control method for multi-layer welding performed using a welding system, The welding system comprises at least a welding robot, a robot control device for controlling the welding robot, a camera, and a data processing device for processing image data obtained from the camera. Before welding, the welding conditions are determined using the welding robot at an arbitrary position on the workpiece on the welding start side. The steps include: starting the first layer of welding based on the welding conditions; during the welding of the first layer, the data processing device inputs image data obtained from the camera, outputs the feature quantities of the image data to the robot control device, and the robot control device controls at least one of the welding conditions based on the feature quantities; After welding the first layer, the step of determining the teaching point information for the second layer before welding the second layer, based on the construction information obtained by the control during welding the first layer, For the second layer and beyond, based on the construction information obtained by the control during welding of the nth layer (where n is a natural number greater than or equal to 2), the step of determining at least one of the following before welding the (n+1)th layer: teaching point information for the (n+1)th layer, welding conditions for the teaching point information, and the layering pattern of the teaching point information. A welding control method for multilayer welding, characterized by having the following features.

[0072] (8) A welding system for performing multi-layer welding, The system comprises at least a welding robot, a robot control device for controlling the welding robot, a camera, and a data processing device for processing image data obtained from the camera. The welding robot determines the welding conditions at an arbitrary position on the workpiece on the welding start side before welding. Based on the aforementioned welding conditions, the welding of the first layer is started. The data processing device inputs image data obtained from the camera during the welding of the first layer, and outputs the feature quantities of the image data to the robot control device. The robot control device controls at least one of the welding conditions based on the feature quantity. After welding the first layer, the robot control device determines the teaching point information for the second and subsequent layers before welding the second layer, based on the construction information obtained through the control of the first layer welding. Welding system.

[0073] (9) A welding control program for multilayer welding, A robot control device for controlling a welding robot, A function to cause the welding robot to perform the first layer of welding based on welding conditions determined at an arbitrary position on the workpiece on the welding start side before welding, During the welding of the first layer, the image data includes the molten pool, welding wire, and arc, and has a function to control at least one of the welding conditions based on the feature quantities of the image data obtained based on the image data obtained from the camera. After welding the first layer, and based on the construction information obtained through the control during welding the first layer, a function is provided to determine the teaching point information for the second and subsequent layers before welding the second layer. A welding control program that makes this possible.

[0074] (10) A multilayer welding method using a welding system, The welding system comprises at least a welding robot, a robot control device for controlling the welding robot, a camera, and a data processing device for processing image data obtained from the camera. The steps include determining the welding conditions at an arbitrary position on the workpiece on the welding start side before welding, The steps include: starting the welding of the first layer based on the welding conditions, and controlling at least one of the welding conditions during the welding of the first layer based on image data that includes the molten pool, welding wire, and arc, and is obtained based on the feature quantities of the image data obtained from the image data obtained from the camera; After welding the first layer, the following steps are taken: Before welding the second layer, based on the construction information obtained through the control during welding the first layer, the teaching point information for the second and subsequent layers is determined. A multilayer welding method characterized by having the following features. [Explanation of Symbols]

[0075] 50 Welding Systems 100 Portable Welding Robots 200 Torches 210 nozzles 211 Welding wire 300 Feeding device 400 Welding Power Supply 410 Power Cable 420 Conduit Tube 430 Power Cable 500 Shielding gas supply source 510 Gas Tube 600 Robot Control Device 601 Data storage unit 602 Bevel shape information calculation unit 603 Welding Condition Acquisition Section 604 Control Unit 610 Robot Control Cable 620 Power control cable 700 Imaging device 800 Data Processing Devices 810 Main Unit 815 Non-volatile memory 816 Input / Output Interfaces 817 Communication Interface 818 Video output interface 819 Calculation Department 820 Input Section 830 Display section

Claims

1. A welding control method for multi-layer welding performed using a welding system, The welding system comprises at least a welding robot, a robot control device for controlling the welding robot, a camera, and a data processing device for processing image data obtained from the camera. Before welding, the welding conditions are determined using the welding robot at an arbitrary position on the workpiece on the welding start side. The first welding is started based on the welding conditions, and during the welding of the first layer, the data processing device inputs image data obtained from the camera, outputs the feature quantities of the image data to the robot control device, and the robot control device controls at least one of the welding conditions based on the feature quantities. After welding the first layer, and based on the construction information obtained through the control during welding the first layer, the step of determining the teaching point information for the second layer and beyond before welding the second layer is performed. A welding control method for multilayer welding, characterized by having the following features.

2. During the welding of the first layer, weaving is performed. At a minimum, the welding conditions during weaving are varied when moving from one end to the other, when positioned at one end, and when positioned at the other end. The welding control method according to claim 1, characterized by having the following:

3. The welding control method according to claim 2, characterized in that the welding conditions in the weaving are determined from a preset DB based on geometric quantity data or construction information acquired during welding.

4. The welding control method according to claim 1, characterized in that the aforementioned construction information is at least one of the gap and the amount of deviation from the weld line.

5. The welding material is selected from at least one of the following: solid wire, slag-type flux-cored wire, and metal-type flux-cored wire. When n is a natural number selected from 2 or greater, The first or nth layer of welding is performed using the same welding material. From the (n+1)th layer onward, a different welding material will be used than the first n layers. A welding control method according to any one of claims 1 to 4, characterized by the above.

6. The welding material is selected from at least one of the following: solid wire, slag-type flux-cored wire, and metal-type flux-cored wire. Perform welding of all layers using the same welding material. A welding control method according to any one of claims 1 to 4, characterized by the above.

7. A welding control method for multi-layer welding performed using a welding system, The welding system comprises at least a welding robot, a robot control device for controlling the welding robot, a camera, and a data processing device for processing image data obtained from the camera. Before welding, the welding conditions are determined using the welding robot at an arbitrary position on the workpiece on the welding start side. The first welding is started based on the welding conditions, and during the welding of the first layer, the data processing device inputs image data obtained from the camera, outputs the feature quantities of the image data to the robot control device, and the robot control device controls at least one of the welding conditions based on the feature quantities. After welding the first layer, the following steps are taken: Before welding the second layer, the teaching point information for the second layer is determined based on the construction information obtained through the control during welding the first layer. For the second layer and beyond, based on the construction information obtained by the control during welding of the nth layer (where n is a natural number greater than or equal to 2), the step of determining at least one of the following before welding the (n+1)th layer: teaching point information for the (n+1)th layer, welding conditions for the teaching point information, and the layering pattern of the teaching point information. A welding control method for multilayer welding, characterized by having the following features.

8. A welding system for performing multi-layer welding, The system comprises at least a welding robot, a robot control device for controlling the welding robot, a camera, and a data processing device for processing image data obtained from the camera. The welding robot determines the welding conditions at an arbitrary position on the workpiece on the welding start side before welding. Based on the aforementioned welding conditions, the welding of the first layer is started. The data processing device inputs image data obtained from the camera during the welding of the first layer, and outputs the feature quantities of the image data to the robot control device. The robot control device controls at least one of the welding conditions based on the feature quantity. After welding the first layer, the robot control device determines the teaching point information for the second and subsequent layers before welding the second layer, based on the construction information obtained through the control of the first layer welding. Welding system.

9. A welding control program for multi-layer welding, A robot control device for controlling a welding robot, A function to cause the welding robot to perform the first layer of welding based on welding conditions determined at an arbitrary position on the workpiece on the welding start side before welding, During the welding of the first layer, the image data includes the molten pool, welding wire, and arc, and has a function to control at least one of the welding conditions based on the feature quantities of the image data obtained from the image data obtained from the camera. After welding the first layer, and based on the construction information obtained through the control during welding the first layer, a function is provided to determine the teaching point information for the second and subsequent layers before welding the second layer. A welding control program that makes this possible.

10. A multi-layer welding method performed using a welding system, The welding system comprises at least a welding robot, a robot control device for controlling the welding robot, a camera, and a data processing device for processing image data obtained from the camera. The steps include determining the welding conditions at an arbitrary position on the workpiece on the welding start side before welding, The steps include: starting the welding of the first layer based on the welding conditions, and controlling at least one of the welding conditions during the welding of the first layer based on image data in which the molten pool, welding wire, and arc are included in the image, and based on the feature quantities of the image data obtained from the image data obtained from the camera; After welding the first layer, and based on the construction information obtained through the control during welding the first layer, the step of determining the teaching point information for the second layer and beyond before welding the second layer is performed. A multilayer welding method characterized by having the following features.

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