Pipe all-position submerged arc welding optimization method, device and equipment based on temperature field monitoring and weld tracking and storage medium

Abstract

The application discloses a pipeline all-position submerged arc welding optimization method and device based on temperature field monitoring and weld tracking, and equipment and a storage medium, relates to the technical field of submerged arc welding, and the method comprises the steps of obtaining a three-dimensional pipeline model, and extracting the width, depth and curvature information of a target weld area in the three-dimensional pipeline model; planning a welding gun path according to the width, depth and curvature information, and controlling the welding gun to move along the welding gun path; monitoring the temperature field of the target weld area in the case of welding gun movement, and calculating the target welding current, target welding voltage and offset of the welding gun position according to the temperature field; adjusting the welding current, welding voltage and position of the welding gun based on the target welding current, target welding voltage and offset, and completing welding optimization. The application accurately tracks the weld position and real-time monitors the temperature field change, improves the welding quality and heat input uniformity of the pipeline all-position submerged arc welding, and ensures the stability and efficiency of the welding process.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of submerged arc welding, in particular to a pipe all-position submerged arc welding optimization method, device, equipment and storage medium based on temperature field monitoring and weld tracking. BACKGROUND

[0002] In modern industrial manufacturing, pipe all-position submerged arc welding technology is widely used in energy transportation pipelines, chemical equipment and other fields. The stability of welding quality and the uniformity of heat input are key factors to ensure the safety and reliability of welded structures. Especially in the case where the pipe cannot be rotated, the complexity of the welding process increases significantly, and the welding gun needs to be accurately aligned with the weld center in different positions (such as vertical welding, overhead welding and elbow). This high-precision welding requirement is particularly important in modern industrial manufacturing.

[0003] Currently, in the pipe all-position submerged arc welding technology, a flux pocket device is usually used to stabilize the flux delivery, and a visual sensor or a laser sensor is used for weld tracking. In addition, temperature field monitoring technology is also applied to the welding process, mainly through infrared temperature sensors or infrared thermal imaging cameras to obtain temperature data of the welding area.

[0004] However, the existing methods still have many shortcomings. First, the flowability problem of the flux leads to uneven temperature distribution in the welding area, which further affects the stability of heat input. Even if a flux pocket device is used, the flowability of the flux in the pocket device is still difficult to completely control, leading to unstable molten pool shape and easy occurrence of welding defects. Second, the existing weld tracking technology has low precision in complex welding positions (such as pipe elbows, vertical welding and overhead welding, etc.), making it difficult to ensure that the welding gun is always aligned with the weld center. In addition, although the existing temperature field monitoring technology can obtain temperature data, it cannot realize real-time dynamic adjustment of welding parameters (such as current, voltage and welding speed), making it difficult to effectively cope with temperature unevenness in the welding process. Therefore, how to accurately track the weld position and monitor the temperature field changes in real time to improve the welding quality and heat input uniformity of pipe all-position submerged arc welding has become a problem to be solved.

[0005] The above content is only used to assist in understanding the technical solutions of the present application, and does not represent the acknowledgement of the above content as prior art. SUMMARY

[0006] The present application aims to provide a pipe all-position submerged arc welding optimization method, device, equipment and storage medium based on temperature field monitoring and weld tracking, which aims to solve the technical problem of how to accurately track the weld position and monitor the temperature field changes in real time to improve the welding quality and heat input uniformity of pipe all-position submerged arc welding.

[0007] To achieve the above object, the application provides a pipe all-position submerged arc welding optimization method based on temperature field monitoring and weld tracking, which comprises the following steps:

[0008] acquiring a three-dimensional pipe model and extracting width, depth and curvature information of a target weld area in the three-dimensional pipe model;

[0009] planning a welding gun path according to the width, depth and curvature information and controlling the welding gun to move along the welding gun path;

[0010] monitoring the temperature field of the target weld area in the case that the welding gun moves and calculating a target welding current, a target welding voltage and an offset amount of the welding gun position according to the temperature field;

[0011] adjusting the welding current, the welding voltage and the position of the welding gun based on the target welding current, the target welding voltage and the offset amount to complete welding optimization.

[0012] In an embodiment, the step of acquiring a three-dimensional pipe model and extracting width, depth and curvature information of a target weld area in the three-dimensional pipe model comprises the following steps: performing multi-angle scanning on a pipe weld area to obtain three-dimensional point cloud data; performing denoising and registration processing on the three-dimensional point cloud data to obtain a three-dimensional pipe model; segmenting a target weld area from the three-dimensional pipe model based on a region growing algorithm; and extracting width, depth and curvature information of the target weld area.

[0013] In an embodiment, the step of segmenting a target weld area from the three-dimensional pipe model based on a region growing algorithm comprises the following steps: selecting at least one seed point on a weld surface of the three-dimensional pipe model and calculating a normal direction of the seed point; searching for neighborhood points of the seed point and calculating a normal angle and a curvature difference between the neighborhood points and the seed point according to the normal direction; when the normal angle is less than a preset angle threshold and the curvature difference is less than a preset curvature threshold, adding the neighborhood points to an initial weld area; returning to the step of searching for neighborhood points of the seed point and calculating a normal angle and a curvature difference between the neighborhood points and the seed point according to the normal direction until the radius of the initial weld area is greater than a preset expansion threshold or the number of points in the initial weld area reaches a preset point number threshold to obtain a target weld area.

[0014] In an embodiment, the step of extracting the width, depth and curvature information of the target weld region comprises: fitting two side edge points of the target weld region by least square method; taking the maximum width of the two side edge points as the width of the target weld region; calculating the depth based on the normal distance of the point cloud of the target weld region and the inner wall of the three-dimensional pipeline model; extracting the curvature information of the surface of the target weld region by principal component analysis method.

[0015] In an embodiment, the step of denoising and registering the three-dimensional point cloud data to obtain a three-dimensional pipeline model comprises: calculating the distance distribution of each point and its neighborhood points by neighborhood distance calculation on each point in the three-dimensional point cloud data; removing outliers beyond a preset noise threshold based on the mean and standard deviation of the distance distribution to obtain denoised point cloud data; taking the denoised point cloud data scanned from a first angle as a reference point cloud and the other denoised point cloud data as initial point clouds; matching the nearest point between each point in the initial point cloud and the reference point cloud to obtain a matching point pair; calculating a rotation matrix and a translation vector by least square method according to the matching point pair; transforming the initial point cloud according to the rotation matrix and the translation vector, and returning to the step of matching the nearest point between each point in the initial point cloud and the reference point cloud to obtain a matching point pair until the alignment error of the initial point cloud and the reference point cloud is less than a preset convergence threshold or the iteration number reaches a preset iteration number threshold to obtain a target point cloud; merging the target point cloud and the reference point cloud to obtain a three-dimensional pipeline model.

[0016] In an embodiment, the step of planning a welding gun path according to the width, depth and curvature information, and controlling the welding gun to move along the welding gun path comprises: calculating an initial motion trajectory of the welding gun along the center line of the weld based on the width and the curvature information; smoothing the initial motion trajectory by B-spline curve algorithm and Bezier algorithm to obtain a target welding gun path; calculating a target inclination angle of the welding gun according to the curvature information, the normal direction of the welding gun and the normal direction of the center line of the weld; calculating the motion parameters of each joint of the welding gun by inverse kinematics algorithm according to the target welding gun path and the target inclination angle, and generating welding gun control instructions according to the motion parameters; sending the welding gun control instructions to the welding gun driving device to control the welding gun driving device to control the welding gun to maintain the target inclination angle and move along the target welding gun path.

[0017] In an embodiment, the step of monitoring the temperature field of the target weld area while the welding torch is moving and calculating the target welding current, the target welding voltage and the offset of the welding torch position according to the temperature field comprises: monitoring the temperature field of the target weld area while the welding torch is moving, the temperature field being obtained by continuously scanning the target weld area by an infrared thermal imaging camera; extracting the left temperature value and the right temperature value of the welding torch from the temperature field and calculating the absolute value of the temperature difference between the left temperature value and the right temperature value; calculating the target welding current and the target welding voltage according to the absolute value of the temperature difference, a preset current adjustment coefficient, a preset voltage adjustment coefficient, an initial welding current and an initial welding voltage; determining the offset direction of the welding torch according to the size relationship between the left temperature value and the right temperature value when the absolute value of the temperature difference exceeds a preset temperature difference threshold; and calculating the offset of the welding torch position by a preset path correction coefficient based on the offset direction of the welding torch and the absolute value of the temperature difference.

[0018] In addition, to achieve the above object, the present application further provides a pipeline all-position submerged arc welding optimization device based on temperature field monitoring and weld tracking, which comprises:

[0019] a model acquisition module, configured to acquire a three-dimensional pipeline model and extract the width, depth and curvature information of a target weld area in the three-dimensional pipeline model;

[0020] a path planning module, configured to plan a welding torch path according to the width, depth and curvature information and control the welding torch to move along the welding torch path;

[0021] a temperature monitoring module, configured to monitor the temperature field of the target weld area while the welding torch is moving and calculate the target welding current, the target welding voltage and the offset of the welding torch position according to the temperature field;

[0022] a dynamic adjustment module, configured to adjust the welding current, the welding voltage and the position of the welding torch based on the target welding current, the target welding voltage and the offset, so as to complete the welding optimization.

[0023] In addition, to achieve the above object, the present application further provides a pipeline all-position submerged arc welding optimization device based on temperature field monitoring and weld tracking, which comprises: a memory, a processor and a computer program stored in the memory and capable of running on the processor, the computer program being configured to implement the steps of the pipeline all-position submerged arc welding optimization method based on temperature field monitoring and weld tracking as described above.

[0024] In addition, in order to achieve the above-mentioned purpose, the present application also provides a storage medium, which is a computer readable storage medium, and a computer program is stored on the storage medium, and the computer program is executed by a processor to implement the steps of the pipe all-position submerged arc welding optimization method based on temperature field monitoring and weld tracking as described above.

[0025] In addition, in order to achieve the above-mentioned purpose, the present application also provides a computer program product, which comprises a computer program, and the computer program is executed by a processor to implement the steps of the pipe all-position submerged arc welding optimization method based on temperature field monitoring and weld tracking as described above.

[0026] The one or more technical solutions provided by the present application have at least the following technical effects:

[0027] Firstly, the welding control system obtains three-dimensional point cloud data, generates a three-dimensional pipe model, and then extracts the width, depth and curvature information of the target weld area. This process provides accurate geometric data for the welding torch path planning, ensuring that the welding torch can accurately align with the weld, reducing the welding deviation. Then, the welding control system plans the welding torch path based on the extracted weld geometric information and controls the welding torch to move along the path. Through accurate path planning, the welding torch can dynamically adjust according to the actual shape and size of the weld, ensuring the uniformity and consistency of the welding process. During the movement of the welding torch, the temperature field of the target weld area is monitored in real time, and the target welding current, target welding voltage and offset of the welding torch position are calculated according to the temperature field data. By monitoring the temperature field in real time, the system can timely find the problem of uneven heat input and dynamically adjust the welding parameters and welding torch position accordingly, ensuring the stability and uniformity of heat input in the welding process. Finally, the welding control system adjusts the welding current, welding voltage and position of the welding torch according to the calculated target welding current, target welding voltage and offset, completing the welding optimization. By accurately tracking the weld position and monitoring the temperature field changes in real time, the welding quality and heat input uniformity of the pipe all-position submerged arc welding are improved, ensuring the stability and efficiency of the welding process. BRIEF DESCRIPTION OF DRAWINGS

[0028] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and serve to explain the principles of the present application together with the specification.

[0029] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the accompanying drawings needed to be used in the embodiments or prior art description will be briefly introduced as follows. Obviously, for those skilled in the art, other drawings can also be obtained without creative labor based on these drawings.

[0030] Figure 1A flowchart provided by the pipeline all-position submerged arc welding optimization method based on temperature field monitoring and weld tracking in Embodiment 1 of the present application;

[0031] Figure 2 A pipeline all-position submerged arc welding system structure diagram provided by the pipeline all-position submerged arc welding optimization method based on temperature field monitoring and weld tracking in Embodiment 1 of the present application;

[0032] Figure 3 A flowchart provided by the pipeline all-position submerged arc welding optimization method based on temperature field monitoring and weld tracking in Embodiment 2 of the present application;

[0033] Figure 4 A module structure diagram of the pipeline all-position submerged arc welding optimization device based on temperature field monitoring and weld tracking in the embodiment of the present application;

[0034] Figure 5 A device structure diagram of the hardware operating environment involved in the pipeline all-position submerged arc welding optimization method based on temperature field monitoring and weld tracking in the embodiment of the present application.

[0035] Explanation of reference numerals:

[0036] 1, pipeline; 2, flux box moving device; 3, line laser profile sensor; 4, infrared thermal imaging camera; 5, welding torch; 6, welding torch adjusting mechanism; 7, welding trolley; 8, welding wire reel; 9, ring rail; 10, cover plate driving motor; 11, flux box; 12, material conveying pipe.

[0037] The purpose implementation, functional features and advantages of the present application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0038] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application, and are not used to limit the present application.

[0039] In order to better understand the technical solutions of the present application, the specific embodiments will be described in detail below with reference to the drawings and the specific embodiments.

[0040] In modern industry, pipeline all-position submerged arc welding is widely used in energy and chemical industries, and the welding quality and heat input uniformity are the key to ensure the safety of the structure. However, in the existing method, although the flux feeding device, visual or laser sensor is used for weld tracking, and the temperature field is monitored by infrared sensor, there are still many problems: the temperature distribution is uneven due to the flowability of the flux, the weld tracking accuracy is low, and the welding parameters cannot be adjusted in real time to cope with the temperature unevenness.

[0041] The main solution of the embodiment of the application is: firstly, three-dimensional point cloud data is acquired to generate a pipe model, the width, depth and curvature information of the weld are extracted, accurate data is provided for the welding torch path planning, and the welding torch is accurately aligned with the weld. Then, the welding torch path is planned and controlled based on the geometric information, the welding torch is dynamically adjusted according to the shape of the weld, and the uniformity of welding is ensured. During the welding process, the temperature field is monitored in real time, the target welding parameters and the welding torch offset are calculated, the welding current, voltage and welding torch position are dynamically adjusted, the welding optimization is finally completed, and the welding quality and heat input uniformity are improved.

[0042] It should be noted that the execution subject of the embodiment of the application can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone and the like, or an electronic device, a welding control system and the like capable of realizing the above functions. The embodiment and the following embodiments will be described below by taking the welding control system as an example.

[0043] Based on this, the embodiment of the application provides a pipe all-position submerged arc welding optimization method based on temperature field monitoring and weld tracking, which refers to Figure 1 , Figure 1 The flowchart of the first embodiment of the pipe all-position submerged arc welding optimization method based on temperature field monitoring and weld tracking of the application is shown in the figure.

[0044] In the embodiment, the pipe all-position submerged arc welding optimization method based on temperature field monitoring and weld tracking includes steps S10-S40:

[0045] Step S10, a three-dimensional pipe model is acquired, and the width, depth and curvature information of a target weld area in the three-dimensional pipe model are extracted.

[0046] It should be noted that please refer to Figure 2 , Figure 2A schematic diagram of a pipe all-position submerged arc welding system structure is provided for the first embodiment of the pipe all-position submerged arc welding optimization method based on temperature field monitoring and weld tracking of the present application. The diagram shows the structure of a pipe all-position submerged arc welding system, which includes several key components. The pipe 1 is the object of welding, placed in the center of the welding system. The flux box moving device 2 is used to control the movement of the flux box 11 along the pipe, ensuring that the flux can uniformly cover the welding area. The line laser profile sensor 3 and the infrared thermal imaging camera 4 are installed on the welding torch 5, used to monitor the geometry and temperature field of the weld area in real time. The welding torch adjusting mechanism 6 can accurately adjust the position and angle of the welding torch to meet the needs of different welding positions. The welding trolley 7 carries the welding torch and related sensors, moves along the ring rail 9, and realizes the accurate positioning of the welding torch. The welding wire reel 8 provides the welding wire required for welding, which is delivered to the welding torch through the feed pipe 12. The cover plate driving motor 10 controls the movement of the cover plate, which is used to protect or support the pipe. The whole system realizes accurate welding of the pipe weld area by coordinating the actions of each component, ensuring the quality and efficiency of welding.

[0047] The three-dimensional pipe model refers to the three-dimensional geometric model of the pipe reconstructed by three-dimensional point cloud data, which can accurately reflect the shape, size and spatial position of the weld of the pipe, providing a basis for subsequent weld geometry information extraction and welding path planning. The target weld area refers to the area where the weld is located in the three-dimensional pipe model, which is segmented from the entire point cloud data. It is the part that needs to be focused on and processed in the welding process, and contains the geometric characteristics of the weld, such as width, depth and curvature information.

[0048] The width refers to the transverse dimension of the weld area in the three-dimensional pipe model along the weld direction, which is one of the important parameters of the weld geometry, directly affecting the movement path of the welding torch and the setting of the welding parameters, and is crucial for ensuring the quality of welding and the uniformity of heat input. The depth refers to the vertical distance from the surface of the pipe to the bottom of the weld in the three-dimensional pipe model. Depth information is very important for heat input control and welding torch angle adjustment in the welding process, which can help the welding system better adapt to the welding needs of different groove shapes. The curvature information refers to the bending degree of the weld surface in the three-dimensional pipe model, including Gaussian curvature and average curvature, reflecting the shape change of the weld surface. Especially in pipe welding, the shape of the weld may be affected by the bending or groove angle of the pipe. Accurate curvature information is crucial for the welding control system to conduct accurate path planning and welding torch angle adjustment, ensuring that the welding torch always maintains the best contact angle with the weld surface during the welding process, thereby improving the welding quality and stability.

[0049] It can be understood that first, the welding control system obtains the three-dimensional point cloud data of the pipeline, and forms a complete three-dimensional pipeline model according to the data. Second, the system segments the target weld area from the three-dimensional pipeline model to ensure that the extracted area accurately reflects the actual position and shape of the weld. Finally, the system calculates the width, depth, Gaussian curvature and average curvature information of the weld based on the segmented weld area point cloud data through a fitting algorithm, providing accurate geometric data support for subsequent welding path planning and parameter optimization.

[0050] In step S20, a welding gun path is planned according to the width, depth and curvature information, and the welding gun is controlled to move along the welding gun path.

[0051] It should be noted that the welding gun path refers to the movement trajectory of the welding gun in the welding process calculated and planned by the welding control system according to the geometric characteristics of the weld, including width, depth and curvature information. It is a path that ensures the welding gun can accurately align with the center line of the weld and dynamically adjust according to the actual shape and size of the weld. By accurately planning the welding gun path, the welding control system can achieve stable tracking of the welding gun under complex weld shapes, ensuring uniformity and high quality in the welding process.

[0052] As an example, the step of planning a welding gun path according to the width, depth and curvature information, and controlling the welding gun to move along the welding gun path includes: based on the width and the curvature information, calculating an initial movement trajectory of the welding gun along the center line of the weld; using B-spline curve algorithm and Bezier algorithm to smooth the initial movement trajectory to obtain a target welding gun path; according to the curvature information, the normal direction of the welding gun and the normal direction of the center line of the weld, calculating the target inclination angle of the welding gun; according to the target welding gun path and the target inclination angle, calculating the movement parameters of each joint of the welding gun through inverse kinematics algorithm, and generating welding gun control instructions according to the movement parameters; sending the welding gun control instructions to the welding gun driving device to make the welding gun driving device control the welding gun to maintain the target inclination angle and move along the target welding gun path.

[0053] The center line of the weld refers to the geometric center line of the target weld area in the three-dimensional pipeline model, which is the central axis in the width direction of the weld, used to define the path that the welding gun needs to accurately track in the welding process.

[0054] B-spline curve algorithm is a mathematical method for generating smooth curves, used to smooth the initial movement trajectory of the welding gun. By defining a set of control points and corresponding weights, B-spline curve can generate a continuous and smooth curve, avoiding sudden changes or discontinuous points in the path, which helps to optimize the movement trajectory of the welding gun, making it smoothly follow the weld in the welding process and reduce welding defects.

[0055] Bezier algorithm is a control point-based parametric curve generation method used to further optimize the motion trajectory of the welding torch, ensuring its smoothness. Bezier curve is defined by control points and parametric equations, which can generate a smooth curve from the starting point to the ending point. It is used in combination with B-spline curve algorithm to further optimize the welding torch path, making it more suitable for complex weld shape and welding requirements.

[0056] The initial motion trajectory refers to the preliminary welding torch path calculated based on the weld centerline and weld width. It is the first step of welding torch path planning, reflecting the direction and position of the welding torch in ideal conditions. The initial motion trajectory is usually a simple geometric path that may contain some unsmooth points or segments. Subsequently, it is smoothed by B-spline curve algorithm and Bezier algorithm to generate the final target welding torch path. The target welding torch path refers to the final motion trajectory of the welding torch after optimization and smoothing, which is obtained by processing the initial motion trajectory with B-spline curve algorithm and Bezier algorithm, ensuring the smooth and continuous movement of the welding torch during welding.

[0057] The normal direction of the welding torch refers to the direction perpendicular to the weld surface at the nozzle end of the welding torch during welding, used to describe the posture of the welding torch relative to the weld surface. By adjusting the normal direction of the welding torch, the optimal contact angle between the welding torch and the weld surface can be ensured, thereby optimizing the welding heat input and molten pool stability, and improving the welding quality. The normal direction of the weld centerline refers to the direction perpendicular to the weld centerline at a certain point on the weld centerline, reflecting the bending degree and direction of the weld centerline at that point. It helps the welding system dynamically adjust the motion trajectory and inclination angle of the welding torch according to the actual shape of the weld, ensuring that the welding torch always follows the weld centerline and maintains the optimal contact angle with the weld surface.

[0058] The target inclination angle refers to the optimal inclination angle that the welding torch needs to maintain during the welding process, which ensures that the welding torch can dynamically adjust according to the actual shape and curvature of the weld during the welding process, thereby ensuring the stability of the welding process and the uniformity of heat input. The inverse kinematics algorithm is a mathematical method for calculating the joint motion parameters of a robot, which is used to calculate the motion parameters of each joint of the welding torch according to the target welding torch path and the target inclination angle. Through the inverse kinematics algorithm, the joint angles and positions of the welding torch at each moment can be determined, thereby generating precise welding torch control instructions to ensure that the welding torch can weld according to the planned path and angle. Motion parameters refer to parameters that describe the motion state of each joint of the welding torch, including joint angles, velocities, accelerations, etc., which are used to define the specific motion mode of the welding torch during the welding process. These parameters determine the motion trajectory, velocity change, and posture adjustment of the welding torch, and are the basis for welding torch control instructions. Welding torch control instructions refer to instructions generated by the welding control system to control the motion of the welding torch, which contain the motion information of each joint of the welding torch, such as joint angles, velocities, and accelerations. The welding torch control instructions are sent to the welding torch through the welding torch driving device to ensure that the welding torch welds according to the planned path and angle.

[0059] The welding torch driving device refers to a hardware device used to control the motion of the welding torch, which usually includes motors, drivers, and other mechanical components. The welding torch driving device drives the motion of each joint of the welding torch according to the welding torch control instructions, thereby achieving precise control of the welding torch.

[0060] First, the welding control system converts the point cloud data P local =(x,y,z) of the target weld area from the local coordinate system of the line laser profile sensor to the global coordinate system P global =(X,Y,Z) of the welding control system, which is transformed by the known rotation matrix R and translation vector T, to ensure that the point cloud data is in the same coordinate frame as the welding control system, thereby providing accurate reference for subsequent path planning. The conversion formula is:

[0061] P global =R·P local +T

[0062] where P local is the point cloud data in the local coordinate system of the line laser profile sensor, P global is the point cloud data in the global coordinate system, R is the rotation matrix, and T is the translation vector.

[0063] Next, based on the width and curvature information of the weld, the system calculates a preliminary motion trajectory along the weld centerline, which provides a basic path for the motion of the welding torch by extracting key points on the weld centerline and connecting these points. Then, the initial motion trajectory is smoothed using the B-spline curve algorithm, which defines control points and weights to generate a continuous and smooth curve to eliminate abrupt changes and discontinuous points in the path; at the same time, the Bezier algorithm is used to further optimize the curve to ensure the smoothness of the welding torch path, and finally the target welding torch path is obtained. B-spline curve formula:

[0064]

[0065] where P smooth is the smoothed path, N i (t) is the B-spline basis function, P i is the control point, n is the number of control points, and t is the path parameter.

[0066] Bezier curve formula:

[0067] P smooth (t)=(1-t) 3 P0+3(1-t) 2 tP1+3(1-t)t 2 P2+t 3 P3

[0068] where P0, P1, P2, P3 are control points, and t is the path parameter.

[0069] Subsequently, based on the curvature information of the weld and the normal direction of the welding torch and the weld centerline, the system calculates the target inclination angle of the welding torch at different positions, and by comparing the normal direction of the welding torch at the current position with the normal direction of the weld centerline, the angle of the welding torch is adjusted to maintain the optimal contact angle with the weld surface. Target inclination angle calculation formula:

[0070]

[0071] where N i is the normal direction of the welding torch at the current position, N weld is the normal direction of the weld centerline, and θ gun is the inclination angle of the welding torch.

[0072] Next, using inverse kinematics algorithm, the motion parameters of each joint of the welding torch are calculated based on the target welding torch path and the target inclination angle, including joint angle, speed and acceleration, etc., which are derived through mathematical models and algorithms to ensure that the welding torch can move according to the planned path and angle. Ideal position calculation formula of welding torch:

[0073] Pgun (x, y, z) = f(C weld , N weld , θ gun )

[0074] where P gun (x, y, z) is the position of the welding torch, C weld is the coordinate of the centerline of the weld, N weld is the normal direction of the weld, and θ gun is the angle of the welding torch.

[0075] Finally, the welding torch control commands are generated according to the calculated motion parameters and sent to the welding torch driving device, which controls the welding torch to maintain the target tilt angle and move along the target welding torch path, thereby achieving precise welding operation.

[0076] Step S30, while the welding torch is moving, the temperature field of the target weld area is monitored, and the target welding current, target welding voltage, and offset of the welding torch position are calculated according to the temperature field.

[0077] It should be noted that the temperature field refers to the temperature distribution of the target weld area during welding, which is monitored in real time by an infrared thermal imaging camera installed on the welding torch, and can reflect the temperature changes of the welding area and the surrounding area. The temperature field data is presented in the form of temperature values, which is used to analyze whether the heat input during welding is uniform and whether there are local temperature abnormalities caused by welding torch offset or flux flowability. The target welding current refers to the welding current value adjusted dynamically according to the real-time monitored temperature field data. If the temperature field shows that the temperature of some areas is too high or too low, the system will calculate the welding current value that needs to be adjusted according to the preset adjustment strategy to optimize the heat input and ensure the welding quality. The target welding voltage refers to the welding voltage value adjusted dynamically according to the real-time monitored temperature field data. If the temperature field shows that the temperature of some areas is too high or too low, the system will calculate the welding voltage value that needs to be adjusted according to the preset adjustment strategy to optimize the heat input and ensure the welding quality. The offset of the welding torch position refers to the deviation between the actual position of the welding torch during welding and the planned path.

[0078] As an example, the step of monitoring the temperature field of the target weld area while the welding torch is moving and calculating the target welding current, the target welding voltage and the offset amount of the welding torch position according to the temperature field comprises: monitoring the temperature field of the target weld area while the welding torch is moving, the temperature field being obtained by continuously scanning the target weld area by an infrared thermal imaging camera; extracting the left temperature value and the right temperature value of the welding torch from the temperature field and calculating the absolute value of the temperature difference between the left temperature value and the right temperature value; calculating the target welding current and the target welding voltage according to the absolute value of the temperature difference, a preset current adjustment coefficient, a preset voltage adjustment coefficient, an initial welding current and an initial welding voltage; determining the offset direction of the welding torch according to the size relationship between the left temperature value and the right temperature value when the absolute value of the temperature difference exceeds a preset temperature difference threshold; and calculating the offset amount of the welding torch position by a preset path correction coefficient based on the offset direction of the welding torch and the absolute value of the temperature difference.

[0079] The absolute value of the temperature difference refers to the absolute value of the difference between the left temperature value and the right temperature value of the welding torch, which is used to determine whether the welding torch deviates from the center line of the weld and the degree of deviation, and is an important basis for dynamically adjusting the welding current, the voltage and the position of the welding torch.

[0080] The preset current adjustment coefficient is a fixed parameter used to calculate the target welding current, which is calibrated based on the actual welding process and experience. This coefficient is used to convert the absolute value of the temperature difference into the adjustment amount of the welding current to optimize the heat input and ensure the uniformity of the welding process, and reflects the influence degree of the temperature difference on the adjustment of the welding current, which is one of the key parameters in the welding control system for dynamically adjusting the welding parameters.

[0081] The preset voltage adjustment coefficient is a fixed parameter used to calculate the target welding voltage, which is also calibrated based on the actual welding process and experience. This coefficient is used to convert the absolute value of the temperature difference into the adjustment amount of the welding voltage to optimize the heat input and ensure the uniformity of the welding process, and reflects the influence degree of the temperature difference on the adjustment of the welding voltage, which is one of the key parameters in the welding control system for dynamically adjusting the welding parameters.

[0082] The initial welding current refers to the welding current value set at the beginning of the welding process, which is pre-set according to the welding process requirements and the material characteristics of the pipeline. It is the reference value for the welding control system to dynamically adjust the welding current, and the subsequent target welding current is adjusted based on the initial welding current and the absolute value of the temperature difference.

[0083] The initial welding voltage refers to the welding voltage value set at the beginning of the welding process, which is pre-set according to the welding process requirements and the material characteristics of the pipeline. It is the reference value for the welding control system to dynamically adjust the welding voltage, and the subsequent target welding voltage is adjusted based on the initial welding voltage and the absolute value of the temperature difference.

[0084] The target welding current refers to the welding current value calculated based on the absolute value of the temperature difference and the preset current adjustment coefficient, which is the dynamically adjusted welding current, used to compensate for uneven heat input caused by the welding torch deviation or uneven temperature field. The target welding voltage refers to the welding voltage value calculated based on the absolute value of the temperature difference and the preset voltage adjustment coefficient, which is the dynamically adjusted welding voltage, used to compensate for uneven heat input caused by the welding torch deviation or uneven temperature field. The preset temperature difference threshold is a pre-set temperature difference value used to determine whether the welding torch deviates from the weld centerline. When the absolute value of the temperature difference exceeds the preset temperature difference threshold, it indicates that the welding torch position deviates significantly, and path correction is needed.

[0085] The welding torch deviation direction refers to the direction in which the welding torch deviates from the weld centerline during welding. By comparing the temperature values on the left and right sides of the welding torch, it is determined whether the welding torch deviates to the left or right. If the left temperature value is higher than the right temperature value, the welding torch deviates to the right; otherwise, if the right temperature value is higher than the left temperature value, the welding torch deviates to the left. The preset path correction coefficient is a fixed parameter used to calculate the welding torch position deviation, which is calibrated based on actual welding process and experience. This coefficient is used to convert the absolute value of the temperature difference into the correction amount of the welding torch position to adjust the position of the welding torch so that it re-aligns with the weld centerline.

[0086] First, the welding control system continuously scans the target weld area through the infrared thermal imaging camera installed on the welding torch, and real-time acquires the temperature field data of the welding area, which includes the temperature information on both sides of the welding torch, for subsequent analysis and adjustment. Second, the system extracts the temperature values on the left and right sides of the welding torch from the temperature field data, and calculates the absolute value of the temperature difference between the two temperature values, to determine whether the welding torch deviates from the weld centerline and the degree of deviation by comparing the temperature difference on both sides. The temperature difference value ΔT calculation formula is:

[0087] ΔT = |T left -T right |

[0088] where T left and T right are the temperature values on the left and right sides of the welding torch, respectively.

[0089] Then, the system calculates the target welding current and target welding voltage through the formula based on the absolute value of the temperature difference, the preset current adjustment coefficient, the voltage adjustment coefficient, and the initially set welding current and voltage, dynamically adjusts the welding parameters to optimize the heat input and ensure the uniformity of the welding process. The target welding current and target welding voltage calculation formula is:

[0090] I adjusted = I initial +k I ·ΔT

[0091] U adjusted = U initial + k U · ΔT

[0092] where I adjusted and U adjusted are the target welding current and voltage; I initial and U initial are the initial set welding current and voltage; k I and k U are the current and voltage adjustment coefficients (calibrated by actual welding process).

[0093] When the absolute value of the temperature difference exceeds the preset temperature difference threshold, the system determines the offset direction of the welding torch according to the size relationship of the left and right temperature values, that is, whether the welding torch is deviated to the left or right. Finally, based on the offset direction of the welding torch and the absolute value of the temperature difference, the offset amount of the welding torch position is calculated through the preset path correction coefficient, and the position of the welding torch is adjusted accordingly to re-align it with the weld centerline, thereby ensuring the stability of the welding process and the welding quality. The offset amount of the welding torch position calculation formula:

[0094] ΔP gun = k path · ΔT

[0095] where ΔP gun is the path correction amount of the welding torch, representing the distance the welding torch should move. k path is the path correction coefficient, calibrated based on actual welding process parameters (such as welding speed, pipe curvature, etc.).

[0096] Step S40, adjusting the welding current, voltage and position of the welding torch based on the target welding current, target welding voltage and offset amount, completing the welding optimization.

[0097] It can be understood that first, the welding control system dynamically adjusts the output parameters of the welding power source according to the calculated target welding current and target welding voltage, so that the welding current and voltage smoothly transition from the initial or current value to the target value, to optimize the welding heat input and ensure the uniformity of the welding process. Then, the system adjusts the transverse position of the welding torch through the welding torch driving device according to the calculated welding torch position offset amount, so that it re-aligns with the weld centerline and corrects the welding torch offset caused by the temperature difference.

[0098] Finally, the welding control system synchronizes the adjusted welding current, welding voltage and welding torch position to the welding process, ensuring that the welding torch follows the optimized path and parameters in subsequent welding, thereby completing the welding optimization and improving the welding quality and stability. Position adjustment formula:

[0099]

[0100] wherein is the adjusted welding torch position, P gun is the current position of the welding torch, ΔP gun is the corrected path deviation.

[0101] The embodiment provides a pipeline all-position submerged arc welding optimization method based on temperature field monitoring and weld tracking. First, a welding control system acquires three-dimensional point cloud data, generates a three-dimensional pipeline model, and then extracts the width, depth and curvature information of the target weld area. This process provides accurate geometric data for welding torch path planning, ensuring that the welding torch can accurately align with the weld, reducing welding deviation. Next, the welding control system plans the welding torch path based on the extracted weld geometry information and controls the welding torch to move along the path. Through accurate path planning, the welding torch can dynamically adjust according to the actual shape and size of the weld, ensuring the uniformity and consistency of the welding process. During the movement of the welding torch, the temperature field of the target weld area is monitored in real time, and the target welding current, target welding voltage and offset of the welding torch position are calculated based on the temperature field data. By monitoring the temperature field in real time, the system can timely detect the problem of uneven heat input and dynamically adjust the welding parameters and welding torch position accordingly, ensuring the stability and uniformity of heat input during the welding process. Finally, the welding control system adjusts the welding current, welding voltage and position of the welding torch based on the calculated target welding current, target welding voltage and offset, completing the welding optimization. By accurately tracking the weld position and monitoring the temperature field changes in real time, the welding quality and heat input uniformity of the pipeline all-position submerged arc welding are improved, ensuring the stability and efficiency of the welding process.

[0102] Based on the first embodiment of the present application, the same or similar contents as the above-mentioned embodiment one can be referred to the above introduction, and will not be described in detail hereinafter. On this basis, please refer to Figure 3 , Figure 3 is a flowchart of the second embodiment of the pipeline all-position submerged arc welding optimization method based on temperature field monitoring and weld tracking, and the steps S10 of the pipeline all-position submerged arc welding optimization method based on temperature field monitoring and weld tracking include steps S11-S14:

[0103] Step S11, multi-angle scanning is performed on the pipeline weld area to obtain three-dimensional point cloud data.

[0104] It should be noted that the three-dimensional point cloud data refers to a set of points containing spatial three-dimensional coordinates obtained by multi-angle scanning of the pipeline weld area by a line laser profile sensor. Each point represents a specific position on the surface of the weld area, containing X, Y, Z coordinate information of the position, and possible reflection intensity or other attributes.

[0105] It can be understood that firstly, the welding control system controls the ring rail driving device to make the line laser profile sensor perform multi-angle rotary scanning around the pipeline weld area, to ensure comprehensive coverage of the weld area. Secondly, the sensor collects point cloud data of the weld surface at each preset angle position, which reflects the three-dimensional geometric features of the weld area. Finally, the welding control system integrates and processes the collected multi-angle point cloud data to generate a complete three-dimensional point cloud model, providing accurate data support for subsequent weld detection and welding path planning.

[0106] In step S12, the three-dimensional point cloud data is denoised and registered to obtain a three-dimensional pipeline model.

[0107] It should be noted that the registration process refers to the process of aligning three-dimensional point cloud data obtained from different angles or positions to the same coordinate system. Since the line laser profile sensor may have positional and directional deviations when scanning the pipeline weld area at multiple angles, registration is needed to align these scattered point cloud data to form a complete and accurate three-dimensional model.

[0108] As an example, the step of denoising and registering the three-dimensional point cloud data to obtain a three-dimensional pipeline model includes: calculating the neighborhood distance of each point in the three-dimensional point cloud data to obtain the distance distribution of each point and its neighborhood points; based on the mean and standard deviation of the distance distribution, removing outliers beyond the preset noise threshold to obtain denoised point cloud data; taking the denoised point cloud data scanned from the first angle as the reference point cloud, and the other denoised point cloud data as the initial point cloud; matching the nearest point between each point in the initial point cloud and the reference point cloud to obtain a matching point pair; calculating the rotation matrix and translation vector by least squares method according to the matching point pair; transforming the initial point cloud according to the rotation matrix and translation vector, and returning to the step of matching the nearest point between each point in the initial point cloud and the reference point cloud to obtain a matching point pair, until the alignment error of the initial point cloud and the reference point cloud is less than a preset convergence threshold or the number of iterations reaches a preset iteration threshold, to obtain a target point cloud; merging the target point cloud and the reference point cloud to obtain a three-dimensional pipeline model.

[0109] Neighborhood points refer to points in the three-dimensional point cloud data that are close in space to a particular point. In the denoising process, by calculating the distance between a point and its neighborhood points, it can be analyzed whether the point is an abnormal point.

[0110] Distance distribution refers to the statistical properties of the distances between a point and its neighbors, including the mean and standard deviation of the distances. By calculating these statistics, we can identify which points have distances from their neighbors that are significantly different from the normal range.

[0111] The preset noise threshold is a set value used to determine whether a point is a noise point. If the distance between a point and its neighbors exceeds this threshold, the point will be identified as a noise point and removed.

[0112] Outliers are points in the point cloud data that have distances from their neighbors that are significantly different from the normal range. These points may be due to scanning errors, reflection interference, or other abnormal situations.

[0113] Denoised point cloud data refers to point cloud data that has been processed to remove outliers. This data is cleaner and can more accurately reflect the true geometric characteristics of the weld area.

[0114] The first angle refers to the angular position of the line laser profile sensor when it first collects data during the scanning process. The point cloud data obtained from this angle is used as the reference point cloud.

[0115] The reference point cloud refers to the denoised point cloud data obtained from the first angle, which remains unchanged during the point cloud registration process and serves as a reference for aligning other point cloud data.

[0116] The initial point cloud refers to the denoised point cloud data obtained from other angles, which needs to be aligned with the reference point cloud.

[0117] The matching point pair refers to the closest point pair found in the initial point cloud and the reference point cloud. By calculating the distance between these point pairs, we can determine the best alignment between the initial point cloud and the reference point cloud.

[0118] The rotation matrix is a mathematical tool used to describe the rotational relationship between the initial point cloud and the reference point cloud. By calculating the rotation matrix using the least squares method, we can rotate the initial point cloud to align with the reference point cloud.

[0119] The translation vector is a mathematical tool used to describe the translational relationship between the initial point cloud and the reference point cloud. By calculating the translation vector using the least squares method, we can translate the initial point cloud to align with the reference point cloud.

[0120] The alignment error refers to the distance difference between the initial point cloud and the reference point cloud during the point cloud registration process. Through iterative optimization, the alignment error will gradually decrease until it meets the preset convergence condition.

[0121] The preset convergence threshold is a set value used to determine whether the point cloud registration process is accurate enough. When the alignment error is less than this threshold, the registration process can be stopped.

[0122] The preset iteration threshold is a set value for limiting the maximum number of iterations of the point cloud registration process. If the convergence condition is not met after reaching the number of iterations, the registration process will stop.

[0123] The target point cloud refers to the point cloud data aligned with the reference point cloud after multiple iterations of registration.

[0124] First, the welding control system calculates the distance between each point in the point cloud data and its surrounding neighborhood points one by one, and the calculation formula is as follows:

[0125]

[0126] Where P i and P j are neighborhood points, and d(P i , P j ) is the distance between the two points.

[0127] By counting these distance values, the distance distribution of each point is obtained, including the mean μ and standard deviation σ, so that it can be identified which points are significantly deviating from the normal range of distance from the surrounding points. These points may be noise points, and the calculation formula is as follows:

[0128]

[0129] Where n is the number of points in the neighborhood, μ is the mean distance, and σ is the distance standard deviation.

[0130] Second, the system removes those outliers whose distance mean exceeds the threshold (d(P i , P j ) > μ + α·σ) according to the preset noise threshold α, obtaining the denoised point cloud data. This process effectively reduces the impact of scanning errors and environmental interference on the data, providing a more accurate point cloud basis for subsequent processing. Next, the system takes the denoised point cloud data obtained from the first angle scanning as the reference point cloud, and the denoised point cloud data obtained from other angle scanning as the initial point cloud, providing a reference and a set of data to be aligned for point cloud registration. Then, the system calculates the Euclidean distance between each point in the initial point cloud and all points in the reference point cloud, finds the closest matching point, and forms a matching point pair. This process ensures that each point in the initial point cloud can find the closest corresponding point in the reference point cloud.

[0131] Subsequently, according to these matching point pairs, the best rotation matrix and translation vector are calculated by the least squares method. These two matrices describe the precise spatial transformation relationship of the initial point cloud relative to the reference point cloud, providing a mathematical basis for the alignment of the point cloud, and the calculation formula is as follows:

[0132]

[0133] where, and are the i-th matched points of the target point cloud and the reference point cloud respectively, R is the rotation matrix, and T is the translation vector.

[0134] Next, the system utilizes the computed rotation matrix and translation vector to transform the initial point cloud, i.e., adjusting each point in the initial point cloud according to the rotation and translation relationship to align with the reference point cloud. This transformation process is achieved through matrix operations, ensuring accurate spatial alignment of point cloud data. Then, the system performs nearest point matching again between each point in the transformed initial point cloud and the reference point cloud, calculating a new alignment error, i.e., the distance difference between the reference point cloud and the transformed initial point cloud. This process is used to evaluate the alignment effect of the current transformation. Finally, the system determines whether the alignment error is less than the preset convergence threshold or the number of iterations reaches the preset iteration threshold. If the conditions are met, the final aligned initial point cloud and the reference point cloud are merged to form a complete three-dimensional pipeline model, completing the registration of point cloud data and model construction. If the conditions are not met, return to the nearest point matching step and continue iterative optimization until the conditions are met.

[0135] Step S13, based on the region growing algorithm, the target weld region is segmented from the three-dimensional pipeline model.

[0136] It should be noted that the region growing algorithm is a segmentation method based on the geometric features of point cloud, which is used to extract specific regions from the three-dimensional pipeline model. It starts from one or more seed points and gradually aggregates neighboring points with similar features (such as normal direction, curvature, etc.) to the same region. The algorithm sets similarity criteria (such as the angle threshold of the normal direction, curvature similarity, etc.) to determine whether the neighborhood points belong to the target region, and continuously expands until the stop condition is met (such as reaching the set neighborhood radius or the number of points in the region reaches the upper limit). This method can effectively identify and separate regions with similar geometric features, and is suitable for complex shape weld segmentation.

[0137] As an example, the step of segmenting the target weld region from the three-dimensional pipe model based on the region growing algorithm includes: selecting at least one seed point on the weld surface of the three-dimensional pipe model, and calculating the normal direction of the seed point; searching for a neighborhood point of the seed point, and calculating the normal angle and curvature difference between the neighborhood point and the seed point according to the normal direction; when the normal angle is less than a preset angle threshold and the curvature difference is less than a preset curvature threshold, the neighborhood point is added to an initial weld region; returning to the step of searching for a neighborhood point of the seed point, and calculating the normal angle and curvature difference between the neighborhood point and the seed point according to the normal direction, until the radius of the initial weld region is greater than a preset expansion threshold or the number of points in the initial weld region reaches a preset point number threshold, to obtain a target weld region.

[0138] The weld surface refers to the actual physical surface of the weld in the three-dimensional pipe model, that is, the area that needs to be welded in the welding process. It is the external manifestation of the geometric characteristics of the weld, including the shape, width, depth, etc. of the weld, and is the starting point and basis for the region growing algorithm to segment the weld.

[0139] The seed point refers to one or more starting points selected on the weld surface, which is used to start the region growing algorithm. These points are usually located at the center position of the weld and have representative geometric characteristics such as normal direction and curvature. The selection of the seed point directly affects the starting direction and range of region growing.

[0140] The normal direction of the seed point refers to the direction perpendicular to the weld surface where the seed point is located in the three-dimensional space. It is obtained by calculating the geometric characteristics of the points in the neighborhood of the seed point, and reflects the local orientation of the weld surface at that point. The normal direction is one of the important bases for judging whether the neighborhood point belongs to the weld region in the region growing algorithm.

[0141] The normal angle refers to the angle between the normal direction of the neighborhood point and the normal direction of the seed point. By calculating this angle, the similarity of the neighborhood point and the seed point in geometric characteristics can be judged. If the angle is small, it means that the normal directions of the neighborhood point and the seed point are close, and it is more likely to belong to the same weld region.

[0142] The curvature difference refers to the difference between the curvature of the neighborhood point and the curvature of the seed point. Curvature reflects the bending degree of the weld surface at a certain point. By calculating the curvature difference, the similarity of the neighborhood point and the seed point in curvature characteristics can be judged. If the curvature difference is small, it means that the curvatures of the neighborhood point and the seed point are close, and it is more likely to belong to the same weld region.

[0143] The preset angle threshold θ thresholdis a preset value used to determine whether the angle between the normal direction of the neighborhood point and the normal direction of the seed point is small enough. If the normal angle is smaller than the threshold value, the neighborhood point is considered to be similar to the seed point in the geometric feature and can be added to the weld region.

[0144] The preset curvature threshold value is a preset value used to determine whether the difference between the curvature of the neighborhood point and the curvature of the seed point is small enough. If the curvature difference is smaller than the threshold value, the neighborhood point is considered to be similar to the seed point in the curvature feature and can be added to the weld region.

[0145] The initial weld region refers to the initial part of the weld region formed by gradually expanding from the seed point through the region growing algorithm, which includes the seed point and the neighborhood points that meet the similarity criteria.

[0146] The preset expansion threshold value is a preset value used to limit the expansion range of the initial weld region, which is usually represented in the form of radius. When the radius of the initial weld region is greater than the threshold value, the region growing algorithm will stop expanding.

[0147] The point number refers to the number of points included in the initial weld region or the target weld region.

[0148] The preset point number threshold value is a preset value used to limit the maximum number of points included in the initial weld region, which is used to control the size of the weld region and prevent overgrowth.

[0149] First, the welding control system selects at least one seed point on the weld surface of the three-dimensional pipeline model, and determines the normal direction of the seed point by calculating the geometric features of the points in the neighborhood of the seed point, providing a directional reference for subsequent region growing. Second, the system searches for neighborhood points within a preset radius range centered on the seed point, and calculates the normal angle and curvature difference between these neighborhood points and the seed point, respectively. By comparing whether the normal angle is smaller than the preset angle threshold θ threshold and whether the curvature difference is smaller than the preset curvature threshold, it is determined whether the neighborhood points have similar geometric features to the seed point. If the conditions are met, these neighborhood points are added to the initial weld region, and the weld region range is gradually expanded. The normal angle calculation formula is:

[0150]

[0151] where N i and N j are the normal vectors of the seed point and the neighborhood point in the point cloud, θ is the angle between them, and if θ ≤ θ threshold , the neighborhood point is considered to belong to the weld region.

[0152] Finally, the system repeatedly searches for neighborhood points and calculates the feature difference, continuously including neighborhood points that meet the conditions into the initial weld region until the radius of the initial weld region exceeds the preset expansion threshold r threshold , or the number of points in the region reaches the preset point threshold (such as 5000 points), stops region growing, and finally obtains the target weld region, thereby accurately segmenting the part where the weld is located and providing accurate positioning and range for subsequent welding operations. Condition judgment formula:

[0153]

[0154] where d(P i , P seed ) is the distance between each point and the seed point, and N max is the maximum number of points set.

[0155] Step S14, extract the width, depth, and curvature information of the target weld region.

[0156] As an example, the step of extracting the width, depth, and curvature information of the target weld region includes: fitting the two side edge points of the target weld region by least squares method; taking the maximum width of the two side edge points as the width of the target weld region; calculating the depth based on the normal distance of the point cloud of the target weld region to the inner wall of the three-dimensional pipeline model; and extracting the curvature information of the surface of the target weld region by principal component analysis method.

[0157] The two side edge points refer to the points on the two boundaries of the target weld region in the width direction, which are obtained by least squares fitting and used to define the two side boundaries of the weld.

[0158] The maximum width refers to the maximum distance between the two side edge points of the target weld region. By calculating the distance between the two side edge points and taking the maximum value, the width of the weld can be obtained.

[0159] The normal distance of the inner wall of the three-dimensional pipeline model refers to the perpendicular distance from a point in the target weld region to the inner wall of the three-dimensional pipeline model. This distance is determined by calculating the distance between the point and the inner wall in the normal direction. The normal direction is the direction from the weld surface to the inner wall of the pipeline, which is perpendicular to the weld surface.

[0160] Firstly, the welding control system processes the point cloud data of the target weld area, and fits the edge points on both sides of the weld through the least squares method. Specifically, the system substitutes the coordinate data of the edge points into the mathematical model of the least squares method, and obtains two best fitting straight lines by solving the optimization problem of minimizing the sum of squared errors. These two straight lines represent the boundaries of the two sides of the weld. Then, the system calculates the distance of each point between the two fitting straight lines, and selects the maximum value as the width of the target weld area. This width value is used for subsequent welding torch path planning and welding parameter adjustment to ensure that the welding torch can accurately align with the center of the weld. The width calculation formula is as follows:

[0161] W = max(d(P left ,P right ))

[0162] where P left and P right are the left and right edge points of the weld area, d(P left ,P right ) is the Euclidean distance between the two points, and W is the width of the target weld area.

[0163] Next, the system calculates the normal distance of each point in the point cloud data of the target weld area to the inner wall of the three-dimensional pipe model. Specifically, for each point, the system calculates the vector between the point and the reference point on the inner wall of the pipe, and calculates the projection length of the vector in the normal direction of the inner wall of the pipe. The maximum value of these projection lengths is the depth of the weld, which is used to optimize the settings of welding current and voltage to adapt to different weld depth requirements. The depth is mainly affected by the groove shape of the pipe (such as deep V-shaped groove). By fitting the V-shaped groove of the weld area from the point cloud, the groove angle a is calculated. If the groove of the welded pipe is a standard deep V-shaped groove, the angle a can be determined by fitting the points on the inner and outer surfaces of the pipe. The groove angle calculation formula is as follows:

[0164] a = atan2(y2-y1, x2-x1)

[0165] where (x1, y1) and (x2, y2) are points on both sides of the weld groove, and a is the groove angle.

[0166] The depth calculation formula is as follows:

[0167]

[0168] where (x i ,y i ,z i ) is a point in the point cloud, (x w ,y w ,z w ) is a reference point on the inner wall of the pipe, and N iis the normal vector of point P i , D i is the depth of the point.

[0169] Finally, the curvature information of the target weld area surface is extracted by principal component analysis. The system first calculates the covariance matrix of the neighborhood points of each point, then solves the eigenvalues and eigenvectors of the matrix, the size of the eigenvalues reflects the distribution of the neighborhood points in different directions, and the eigenvectors indicate the principal component direction. For each point P i =(x i ,y i ,z i ), the normal direction of the point is calculated by the PCA method:

[0170] N i =(N x ,N y ,N z )

[0171] N i =PCA(P neighborhood (i))

[0172] Where P neighborhood (i) represents the domain set of point P i , and the PCA method is used to calculate the normal vector N i .

[0173] By analyzing these eigenvalues and eigenvectors, the system can calculate the Gaussian curvature and the mean curvature of each point, which are used to optimize the pose adjustment of the welding gun, ensuring that the welding gun maintains the optimal contact angle with the weld surface during the welding process, thereby improving the welding quality and stability. Gaussian curvature calculation formula:

[0174] Mean curvature calculation formula:

[0175] Where L, M, N are parameters of the second derivative matrix, E, F, G are coefficients of the first fundamental form, representing the bending degree of the surface in different directions.

[0176] The embodiment first performs multi-angle scanning on the pipe weld area by a line laser profile sensor to obtain three-dimensional point cloud data of the weld area. This process can comprehensively cover the weld area, ensuring the integrity and accuracy of the data. Then, the obtained three-dimensional point cloud data is denoised and registered to remove abnormal points and integrate multi-angle data, generating a complete three-dimensional pipe model. Denoising improves data quality, while registration ensures model accuracy. Then, the target weld area is segmented from the three-dimensional pipe model based on a region growing algorithm. By selecting a seed point and gradually expanding, the weld area is accurately identified, providing clear positioning for subsequent welding operations. Finally, the width, depth, and curvature information of the target weld area are extracted. The extraction of these geometric features provides key data support for welding parameter optimization and welding torch path planning, thereby improving welding quality and efficiency.

[0177] The application also provides a pipe all-position submerged arc welding optimization device based on temperature field monitoring and weld tracking. Please refer to Figure 4 The pipe all-position submerged arc welding optimization device based on temperature field monitoring and weld tracking comprises:

[0178] A model acquisition module 10 is configured to acquire a three-dimensional pipe model and extract the width, depth, and curvature information of a target weld area in the three-dimensional pipe model.

[0179] A path planning module 20 is configured to plan a welding torch path according to the width, depth, and curvature information and control the welding torch to move along the welding torch path.

[0180] A temperature monitoring module 30 is configured to monitor the temperature field of the target weld area when the welding torch moves and calculate a target welding current, a target welding voltage, and an offset amount of the welding torch position according to the temperature field.

[0181] A dynamic adjustment module 40 is configured to adjust the welding current, welding voltage, and position of the welding torch based on the target welding current, target welding voltage, and offset amount to complete welding optimization.

[0182] The pipe all-position submerged arc welding optimization device based on temperature field monitoring and weld tracking provided in the application adopts the pipe all-position submerged arc welding optimization method based on temperature field monitoring and weld tracking in the above embodiment, and can solve the technical problem of how to improve the welding quality and heat input uniformity of pipe all-position submerged arc welding by accurately tracking the weld position and monitoring the temperature field change in real time. Compared with the prior art, the pipe all-position submerged arc welding optimization device based on temperature field monitoring and weld tracking provided in the application has the same beneficial effects as the pipe all-position submerged arc welding optimization method based on temperature field monitoring and weld tracking provided in the above embodiment, and other technical features in the pipe all-position submerged arc welding optimization device based on temperature field monitoring and weld tracking are the same as the features disclosed in the above embodiment method, which will not be described here.

[0183] The application provides a pipe all-position submerged arc welding optimization device based on temperature field monitoring and weld tracking. The pipe all-position submerged arc welding optimization device based on temperature field monitoring and weld tracking comprises at least one processor and a memory in communication connection with the at least one processor. The memory stores instructions executable by the at least one processor. The instructions are executed by the at least one processor to enable the at least one processor to execute the pipe all-position submerged arc welding optimization method based on temperature field monitoring and weld tracking in the above embodiment one.

[0184] Reference will be made to the following Figure 5 The pipe all-position submerged arc welding optimization device based on temperature field monitoring and weld tracking shown in the drawing is suitable for implementing the pipe all-position submerged arc welding optimization device based on temperature field monitoring and weld tracking in the embodiments of the application. The pipe all-position submerged arc welding optimization device based on temperature field monitoring and weld tracking in the embodiments of the application can include but is not limited to mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), and vehicle terminal (for example, vehicle navigation terminal) and fixed terminals such as digital TVs and desktop computers. Figure 5 The pipe all-position submerged arc welding optimization device based on temperature field monitoring and weld tracking shown in the drawing is only an example and should not bring any limitation to the functions and use range of the embodiments of the application.

[0185] As Figure 5As shown, the pipe all-position submerged arc welding optimization apparatus based on temperature field monitoring and weld tracking can include a processing device 1001 (e.g., a central processing unit, a graphics processing unit, etc.) that can perform various appropriate actions and processes according to programs stored in a ROM (Read Only Memory) 1002 or programs loaded from a storage device 1003 into a RAM (Random Access Memory) 1004. In the RAM 1004, various programs and data required for the pipe all-position submerged arc welding optimization apparatus based on temperature field monitoring and weld tracking to operate are also stored. The processing device 1001, the ROM 1002, and the RAM 1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, an LCD (Liquid Crystal Display), a speaker, a vibrator, etc.; the storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the pipe all-position submerged arc welding optimization apparatus based on temperature field monitoring and weld tracking to communicate wirelessly or wired with other devices to exchange data. Although the pipe all-position submerged arc welding optimization apparatus based on temperature field monitoring and weld tracking with various systems is shown in the figure, it should be understood that all the systems shown are not required to be implemented or possessed. More or less systems can be alternatively implemented or possessed.

[0186] In particular, according to embodiments of the present disclosure, the processes described above with reference to the flowcharts can be implemented as a computer software program. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a computer readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network by a communication device, or installed from the storage device 1003, or installed from the ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the methods of the embodiments of the present disclosure are performed.

[0187] The pipe all-position submerged arc welding optimization device based on temperature field monitoring and weld tracking provided in the application adopts the pipe all-position submerged arc welding optimization method based on temperature field monitoring and weld tracking in the above embodiment, and can solve the technical problem of how to improve the welding quality and heat input uniformity of pipe all-position submerged arc welding by accurately tracking the weld position and monitoring the temperature field change in real time. Compared with the prior art, the pipe all-position submerged arc welding optimization device based on temperature field monitoring and weld tracking provided in the application has the same beneficial effects as the pipe all-position submerged arc welding optimization method based on temperature field monitoring and weld tracking provided in the above embodiment, and other technical features in the pipe all-position submerged arc welding optimization device based on temperature field monitoring and weld tracking are the same as the features disclosed in the previous embodiment method, which will not be repeated here.

[0188] The application provides a computer readable storage medium having computer readable program instructions (i.e. computer programs) stored thereon for executing the pipe all-position submerged arc welding optimization method based on temperature field monitoring and weld tracking in the above embodiment.

[0189] The computer readable storage medium provided in the application may, for example, be a U disk, but is not limited to an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, system or device, or any combination of the above. More specific examples of computer readable storage media can include, but are not limited to, an electrical connection with one or more conductive wires, a portable computer diskette, a hard disk, a RAM (Random Access Memory), a ROM (Read Only Memory), an EPROM (Erasable Programmable Read Only Memory or flash memory), an optical fiber, a CD-ROM (CD-Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present embodiment, the computer readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system or device. The program code contained on the computer readable storage medium can be transmitted in any suitable medium, including but not limited to electrical wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0190] The above computer readable storage medium can be included in the pipe all-position submerged arc welding optimization device based on temperature field monitoring and weld tracking; or can exist separately and not be assembled into the pipe all-position submerged arc welding optimization device based on temperature field monitoring and weld tracking.

[0191] The computer readable storage medium described above carries one or more programs, when the one or more programs are executed by the pipe all-position submerged arc welding optimization device based on temperature field monitoring and weld tracking, the pipe all-position submerged arc welding optimization device based on temperature field monitoring and weld tracking is caused to: acquire a three-dimensional pipe model, and extract width, depth and curvature information of a target weld area in the three-dimensional pipe model; plan a welding gun path according to the width, the depth and the curvature information, and control the welding gun to move along the welding gun path; monitor a temperature field of the target weld area in the case that the welding gun moves, and calculate a target welding current, a target welding voltage and an offset amount of the welding gun position according to the temperature field; adjust the welding current, the welding voltage and the position of the welding gun based on the target welding current, the target welding voltage and the offset amount, and complete welding optimization.

[0192] Computer program code for carrying out operations of the present application can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0193] The computer program product can solve the technical problem of how to improve the welding quality and heat input uniformity of the pipeline all-position submerged arc welding by accurately tracking the welding position and monitoring the temperature field change in real time. Compared with the prior art, the computer program product provided in the present application has the same beneficial effects as the pipeline all-position submerged arc welding optimization method based on temperature field monitoring and welding tracking provided in the above embodiments, and details are not repeated here.

[0194] The readable storage medium provided in the present application is a computer readable storage medium, which stores computer readable program instructions (i.e., a computer program) for executing the above-mentioned pipeline all-position submerged arc welding optimization method based on temperature field monitoring and welding tracking, and can solve the technical problem of how to improve the welding quality and heat input uniformity of the pipeline all-position submerged arc welding by accurately tracking the welding position and monitoring the temperature field change in real time. Compared with the prior art, the computer readable storage medium provided in the present application has the same beneficial effects as the pipeline all-position submerged arc welding optimization method based on temperature field monitoring and welding tracking provided in the above embodiments, and details are not repeated here.

[0195] The present application also provides a computer program product comprising a computer program, which, when executed by a processor, implements the steps of the pipeline all-position submerged arc welding optimization method based on temperature field monitoring and welding tracking as described above.

[0196] The computer program product provided in the present application can solve the technical problem of how to improve the welding quality and heat input uniformity of the pipeline all-position submerged arc welding by accurately tracking the welding position and monitoring the temperature field change in real time. Compared with the prior art, the computer program product provided in the present application has the same beneficial effects as the pipeline all-position submerged arc welding optimization method based on temperature field monitoring and welding tracking provided in the above embodiments, and details are not repeated here.

[0197] The above only describes some embodiments of the present application, and does not limit the patent scope of the present application, and any equivalent structural transformation made according to the technical concept of the present application, or direct / indirect application in other related technical fields is included in the patent protection scope of the present application.

Claims

1. A method for optimizing pipe all-position submerged arc welding based on temperature field monitoring and weld tracking, characterized in that, The method comprises: acquiring a three-dimensional pipeline model and extracting width, depth and curvature information of a target weld area in the three-dimensional pipeline model; planning a welding gun path according to the width, depth and curvature information and controlling the welding gun to move along the welding gun path, which comprises: calculating an initial motion trajectory of the welding gun along a weld center line based on the width and the curvature information; smoothing the initial motion trajectory using a B-spline curve algorithm and a Bezier algorithm to obtain a target welding gun path; calculating a target inclination angle of the welding gun according to the curvature information, a normal direction of the welding gun and a normal direction of the weld center line; calculating motion parameters of each joint of the welding gun through an inverse kinematics algorithm according to the target welding gun path and the target inclination angle, and generating a welding gun control instruction according to the motion parameters; sending the welding gun control instruction to a welding gun driving device to control the welding gun driving device to control the welding gun to maintain the target inclination angle and move along the target welding gun path; monitoring a temperature field of the target weld area in the case that the welding gun moves, and calculating a target welding current, a target welding voltage and an offset amount of the welding gun position according to the temperature field, which comprises: monitoring the temperature field of the target weld area in the case that the welding gun moves, the temperature field being obtained by continuously scanning the target weld area through an infrared thermal imaging camera; extracting a left temperature value and a right temperature value of the welding gun from the temperature field and calculating an absolute value of a temperature difference between the left temperature value and the right temperature value; calculating the target welding current and the target welding voltage according to the absolute value of the temperature difference, a preset current adjustment coefficient, a preset voltage adjustment coefficient, an initial welding current and an initial welding voltage; determining a welding gun offset direction according to a size relationship between the left temperature value and the right temperature value in the case that the absolute value of the temperature difference exceeds a preset temperature difference threshold; calculating the offset amount of the welding gun position through a preset path correction coefficient based on the welding gun offset direction and the absolute value of the temperature difference; adjusting the welding current, the welding voltage and the position of the welding gun based on the target welding current, the target welding voltage and the offset amount to complete welding optimization.

2. The method of claim 1, wherein, The step of acquiring the three-dimensional pipeline model and extracting the width, depth and curvature information of the target weld area in the three-dimensional pipeline model comprises: performing multi-angle scanning on a pipeline weld area to obtain three-dimensional point cloud data; performing denoising and registration processing on the three-dimensional point cloud data to obtain a three-dimensional pipeline model; segmenting a target weld area from the three-dimensional pipeline model based on a region growing algorithm; extracting the width, depth and curvature information of the target weld area.

3. The method of claim 2, wherein, The step of segmenting the target weld area from the three-dimensional pipeline model based on the region growing algorithm comprises: selecting at least one seed point on a weld surface of the three-dimensional pipeline model and calculating a normal direction of the seed point; searching for neighborhood points of the seed point and calculating a normal angle and a curvature difference between the neighborhood points and the seed point according to the normal direction; add the neighborhood point to an initial weld region when the normal angle is less than a preset angle threshold and the curvature difference is less than a preset curvature threshold; return to the steps of searching for the neighborhood point of the seed point and calculating the normal angle and the curvature difference between the neighborhood point and the seed point according to the normal direction until the radius of the initial weld region is greater than a preset expansion threshold or the number of points in the initial weld region reaches a preset point number threshold, to obtain a target weld region.

4. The method of claim 2, wherein, the step of extracting the width, depth and curvature information of the target weld region comprises: fitting two side edge points of the target weld region by a least square method; taking the maximum width of the two side edge points as the width of the target weld region; calculating the depth based on the normal distance between the point cloud of the target weld region and the inner wall of the three-dimensional pipeline model; extracting the curvature information of the surface of the target weld region by a principal component analysis method.

5. The method of claim 2, wherein, the step of denoising and registering the three-dimensional point cloud data to obtain a three-dimensional pipeline model comprises: calculating the neighborhood distance of each point in the three-dimensional point cloud data to obtain the distance distribution of each point and neighborhood points; based on the mean and standard deviation of the distance distribution, removing outliers beyond a preset noise threshold to obtain denoised point cloud data; taking the denoised point cloud data scanned from a first angle as a reference point cloud and other denoised point cloud data as initial point cloud data; matching the nearest point between each point in the initial point cloud and the reference point cloud to obtain a matching point pair; calculating a rotation matrix and a translation vector by a least square method according to the matching point pair; transforming the initial point cloud according to the rotation matrix and the translation vector, and returning to the step of matching the nearest point between each point in the initial point cloud and the reference point cloud to obtain a matching point pair until the alignment error of the initial point cloud and the reference point cloud is less than a preset convergence threshold or the iteration number reaches a preset iteration number threshold to obtain a target point cloud; merging the target point cloud and the reference point cloud to obtain a three-dimensional pipeline model.

6. A device for optimizing pipe all-position submerged arc welding based on temperature field monitoring and weld tracking, characterized in that, the device comprises: a model acquisition module configured to acquire a three-dimensional pipeline model and extract the width, depth and curvature information of a target weld region in the three-dimensional pipeline model; a path planning module configured to plan a welding gun path according to the width, depth and curvature information and control the welding gun to move along the welding gun path, wherein the path planning module comprises: calculating an initial motion trajectory of the welding gun along a weld center line based on the width and the curvature information; smoothing the initial motion trajectory by a B-spline curve algorithm and a Bezier algorithm to obtain a target welding gun path; calculating a target inclination angle of the welding gun according to the curvature information, the normal direction of the welding gun and the normal direction of the weld center line; calculating motion parameters of each joint of the welding gun by an inverse kinematics algorithm according to the target welding gun path and the target inclination angle, and generating a welding gun control instruction according to the motion parameters; and a welding gun control module configured to control the welding gun to move according to the welding gun control instruction. sending the welding gun control instruction to a welding gun driving device, so that the welding gun driving device controls the welding gun to keep the target inclination angle and move along the target welding gun path; a temperature monitoring module configured to monitor a temperature field of the target weld area when the welding gun moves, and calculate a target welding current, a target welding voltage and an offset of the welding gun position according to the temperature field, wherein the temperature field is obtained by continuously scanning the target weld area by an infrared thermal imaging camera; extracting a left temperature value and a right temperature value of the welding gun from the temperature field, and calculating an absolute value of a temperature difference between the left temperature value and the right temperature value; calculating the target welding current and the target welding voltage according to the absolute value of the temperature difference, a preset current adjustment coefficient, a preset voltage adjustment coefficient, an initial welding current and an initial welding voltage; determining a welding gun offset direction according to a size relationship between the left temperature value and the right temperature value when the absolute value of the temperature difference exceeds a preset temperature difference threshold value; calculating the offset of the welding gun position by a preset path correction coefficient based on the welding gun offset direction and the absolute value of the temperature difference; a dynamic adjustment module configured to adjust a welding current, a welding voltage and a position of the welding gun based on the target welding current, the target welding voltage and the offset, and complete welding optimization.

7. A pipe all-position submerged arc welding optimization apparatus based on temperature field monitoring and weld tracking, characterized by, The device comprises a memory, a processor and a computer program stored on the memory and executable on the processor, and the computer program is configured to implement the steps of the pipe all-position submerged arc welding optimization method based on temperature field monitoring and weld tracking according to any one of claims 1 to 5.

8. A storage medium, characterized by The storage medium is a computer readable storage medium, and the storage medium stores a computer program, and the computer program is executed by the processor to implement the steps of the pipe all-position submerged arc welding optimization method based on temperature field monitoring and weld tracking according to any one of claims 1 to 5.

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