Method and device for corner groove welding planning

Abstract

The invention relates to a corner groove welding planning method and device, and belongs to the technical field of robot welding, and the method comprises the steps that a plurality of pieces of point cloud data of a target corner groove are obtained; registering the plurality of point cloud data to obtain the shape of the cross section of the target corner groove; determining a welding strategy based on the shape of the cross section, and determining initial welding parameters based on the welding strategy; constructing a welding thermal process model of the target corner groove; the initial welding parameters of the welding thermal process model are optimized, and optimized welding parameters are obtained; based on the optimized welding parameters and welding strategies, the welding track of the target corner groove is determined; the welding gun swing speed corresponding to the welding track is planned, and the welding speed is determined; and the target corner groove is welded based on the welding track and the welding speed. The automatic welding effect of the corner groove of the steel structure is improved.

Description

Technical Field

[0001] The invention relates to the technical field of robot welding, and in particular to a method and device for corner groove welding planning. Background Art

[0002] With the rapid development of railway transportation, shipping and large-scale engineering machinery industries, large steel structures are increasingly widely used due to their light weight, excellent plasticity and toughness, outstanding seismic performance and high strength. In the construction industry, steel components are generally assembled by welding medium and thick plates. Compared with thin plate welding, the structure of medium and thick plates is larger and the groove is wider, which makes the welding process more difficult and requires multi-layer and multi-pass welding. In this process, exhaust gas, strong light, dust and noise will be generated, which are harmful to the health of workers. As a major manufacturing country, the improvement of welding technology is crucial for my country to become a manufacturing power. Therefore, promoting the application of robots in multi-layer and multi-pass automated welding of medium and thick plates can not only liberate workers from harsh environments, but also improve labor efficiency and promote industrial development. It can be seen that the automation of medium and thick plate welding is an important direction for the future development of engineering machinery.

[0003] At present, the automated welding of medium and thick plates by robots often involves straight groove welding. Compared with straight grooves, corner grooves may be restricted in position during welding because the welding position is at the corner. The welding operation is more difficult, the stress of corner welds is more complex, and stress concentration is easily generated around the welds. Special attention should be paid to avoid welding defects and cracks caused by stress concentration. Therefore, it is possible to consider using the welding mutation point from the straight groove to the corner groove as the starting point for splicing welding to reduce the local heat source input at the corner part, thereby reducing deformation. In order to ensure the quality of corner groove welding, it is necessary not only to correct welding parameters such as welding voltage and current, wire feeding speed, and welding speed, but also to combine the welding robot posture control weld bead arrangement planning, etc., to reasonably plan the welding trajectory.

[0004] However, the existing method of steel structure corner groove welding planning has problems such as inaccurate groove image recognition, uneven heat source input for splicing welding, and complex robot welding trajectory planning, resulting in poor automated welding effect of steel structure corner groove. Summary of the invention

[0005] In view of this, it is necessary to provide a method and device for corner groove welding planning to solve the problem of poor automated welding effect of steel structure corner grooves.

[0006] In order to solve the above problems, the present invention provides a method for corner groove welding planning, comprising: Obtain several point cloud data of the target corner groove; Registering the plurality of point cloud data to obtain the cross-sectional shape of the target corner groove; determining a welding strategy based on the shape of the cross section, and determining initial welding parameters based on the welding strategy; Construct the welding thermal process model of the target corner groove; Optimizing the initial welding parameters of the welding thermal process model to obtain optimized welding parameters; Determine the welding trajectory of the target corner groove based on the optimized welding parameters and welding strategy; Plan the welding gun swing speed corresponding to the welding trajectory and determine the welding speed; The target corner groove is welded based on the welding trajectory and welding speed.

[0007] In a possible implementation, the initial welding parameters include: welding current, welding voltage and welding speed.

[0008] In a possible implementation, registering the plurality of point cloud data to obtain the cross-sectional shape of the target corner groove includes: Register several point cloud data to obtain the weld contour of the target corner groove; The shape of the cross section is derived based on the weld contour.

[0009] In a possible implementation, the welding strategy includes: The number of welded layers, the number of weld passes, and the cross-sectional area of ​​each weld.

[0010] In a possible implementation, constructing a welding thermal process model of a target corner groove includes: The welding thermal process model of the target corner groove is constructed based on finite element software.

[0011] In a possible implementation, the welding thermal process model is expressed as:

[0012] In the formula, Represents the welding thermal process model; Represents the surface Gaussian welding thermal process model; Represents the double ellipsoid welding thermal process model; The welding thermal process model representing the front hemisphere; The welding thermal process model representing the rear hemisphere; Represents the weight coefficient of the surface Gaussian welding thermal process model; Represents the weight coefficient of the double ellipsoid welding thermal process model; where:

[0013] Where Q is the heat input per unit time. , unit is W; is the radius of heat source action, in mm; r is the diameter from any point in the heat source area to the center of the heat source, in mm; μ is the welding efficiency; U is the welding voltage, in V; I is the welding current, in A;

[0014]

[0015] Where q is the heat generation rate, in W / m 3 ; a f , a r , b , c are the shape parameters of the double ellipsoid heat source, in m; μ is the welding efficiency; U is the welding voltage, in V; I is the welding current, in A; f f is the energy distribution coefficient of the heat source model in the front part; f r is the energy distribution coefficient of the rear partial heat source model; x Direction is the welding forward direction; y The direction is the normal direction of welding forward; z The direction is the weld thickness direction.

[0016] In a possible implementation, the planning of the welding gun swing speed corresponding to the welding trajectory and determining the welding speed include: Based on the S-type acceleration and deceleration planning algorithm, the welding gun swing speed corresponding to the welding trajectory is planned to obtain the acceleration; The welding speed is determined based on the jerk.

[0017] In a possible implementation, the expression of the jerk is:

[0018] in, ; , , , , , , The time for the 7 exercise stages respectively; , , , , , , They are the jerk of the 7 motion stages, Indicates the maximum acceleration allowed by the welding gun; is the starting speed; is the terminal velocity.

[0019] In a possible implementation, after determining the welding trajectory of the target corner groove based on the optimized welding parameters and welding strategy, the method further includes: The welding trajectory is interpolated and optimized based on a non-uniform B-spline curve to obtain an optimized welding trajectory.

[0020] On the other hand, the present invention also provides a device for corner groove welding planning, comprising: A point cloud data acquisition module is used to acquire a number of point cloud data of the target corner groove; A shape acquisition module, used to register the plurality of point cloud data to obtain the cross-sectional shape of the target corner groove; A welding strategy acquisition module, used to determine a welding strategy based on the shape of the cross section, and to determine initial welding parameters based on the welding strategy; A welding thermal process model building module is used to build a welding thermal process model of the target corner groove; An optimized welding parameter acquisition module is used to optimize the initial welding parameters of the welding thermal process model to obtain optimized welding parameters; A welding trajectory determination module, used to determine the welding trajectory of the target corner groove based on the optimized welding parameters and welding strategy; The welding speed determination module is used to plan the welding gun swing speed corresponding to the welding trajectory and determine the welding speed; The welding module is used to weld the target corner groove based on the welding trajectory and welding speed.

[0021] The beneficial effects of the present invention are as follows: a method for corner groove welding planning provided by the present invention first obtains a plurality of point cloud data of a target corner groove, then aligns the plurality of point cloud data, obtains the shape of the cross section of the target corner groove, aligns a plurality of point cloud data to ensure the accuracy and integrity of the cross section shape of the groove, further determines the welding strategy and initial welding parameters based on the shape of the cross section, further constructs a welding thermal process model of the target corner groove, thereby accurately describing the welding thermal process in the welding process, further optimizes the initial welding parameters of the welding thermal process model, obtains the optimized welding parameters, further determines the welding trajectory of the target corner groove based on the optimized welding parameters and welding strategy, and finally plans the welding gun swing speed corresponding to the welding trajectory, determines the welding speed, thereby ensuring the uniformity and stability of welding, and welds the target corner groove based on the welding trajectory and welding speed. The present invention ensures the accuracy of the shape of the cross section of the corner groove through multiple sets of point cloud data, accurately describes the welding thermal process in the welding process through the welding thermal process model, and improves the stability of welding through the planning of the welding speed, thereby improving the effect of automated welding of the corner groove of the steel structure. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 A flowchart of an embodiment of a method for corner groove welding planning provided by the present invention; Figure 2 A flowchart of a specific embodiment of a method for corner groove welding planning provided by the present invention; Figure 3 A specific embodiment of a method for corner groove welding planning provided in the present invention is a flow chart of point cloud precise registration based on GICP iterative algorithm; Figure 4 A schematic diagram of a thermal process model of corner groove welding is a specific embodiment of a method for corner groove welding planning provided in the present invention; Figure 5 A schematic diagram of a corner groove weld filling strategy is a specific embodiment of a method for corner groove welding planning provided in the present invention; Figure 6 It is a schematic diagram of a welding method for a spliced ​​weld seam in accordance with a specific embodiment of a method for planning corner groove welding provided in the present invention; Figure 7 It is a schematic diagram of S-shaped acceleration and deceleration planning with continuous acceleration in a specific embodiment of a method for corner groove welding planning provided in the present invention; Figure 8 A schematic flow chart of an embodiment of a device for corner groove welding planning provided by the present invention; Fig. 9A schematic structural diagram of an embodiment of an electronic device provided by the present invention. DETAILED DESCRIPTION

[0023] The preferred embodiments of the present invention are described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not used to limit the scope of the present invention.

[0024] The present invention provides a method and device for corner groove welding planning, which are respectively described below.

[0025] Figure 1 A schematic flow chart of an embodiment of a method for corner groove welding planning provided by the present invention is as follows: Figure 1 As shown, the method for corner groove welding planning includes: S101, obtaining a plurality of point cloud data of a target corner groove; S102, registering the plurality of point cloud data to obtain a cross-sectional shape of a target corner groove; S103, determining a welding strategy based on the shape of the cross section, and determining initial welding parameters based on the welding strategy; S104, constructing a welding thermal process model of the target corner groove; S105, optimizing the initial welding parameters of the welding thermal process model to obtain optimized welding parameters; S106, determining a welding trajectory of a target corner groove based on the optimized welding parameters and welding strategy; S107, planning the welding gun swing speed corresponding to the welding trajectory, and determining the welding speed; S108, welding the target corner groove based on the welding trajectory and welding speed.

[0026] Compared with the prior art, the present embodiment provides a method for corner groove welding planning, firstly obtains a plurality of point cloud data of the target corner groove, then aligns the plurality of point cloud data, obtains the shape of the cross section of the target corner groove, aligns the plurality of point cloud data to ensure the accuracy and integrity of the cross section shape of the groove, further determines the welding strategy and initial welding parameters based on the shape of the cross section, further constructs the welding thermal process model of the target corner groove, thereby accurately describing the welding thermal process in the welding process, further optimizes the initial welding parameters of the welding thermal process model, obtains the optimized welding parameters, further determines the welding trajectory of the target corner groove based on the optimized welding parameters and welding strategy, finally plans the welding gun swing speed corresponding to the welding trajectory, determines the welding speed, thereby ensuring the uniformity and stability of the welding, and welds the target corner groove based on the welding trajectory and the welding speed. The present invention ensures the accuracy of the shape of the cross section of the corner groove through multiple sets of point cloud data, accurately describes the welding thermal process in the welding process through the welding thermal process model, improves the stability of welding through the planning of the welding speed, thereby improving the effect of the automated welding of the corner groove of the steel structure.

[0027] It should be noted that the method for corner groove welding planning of the present invention is applied to welding equipment, and the welding equipment includes a robot motion control module, a detection module and a welding module. The robot motion control module is used to control the robot motion, the detection module is used to capture the groove image for feature extraction, and the welding module is used to control the welding voltage and current.

[0028] It should be noted that the corner groove of the present embodiment is a steel structure, and it can be understood that the corner groove may also be a corner groove of other material structures.

[0029] In a specific embodiment of the present invention, Figure 2 As shown, the specific steps are as follows: Step 1: Use a dual-view camera to shoot the steel structure corner groove, and analyze the obtained data to obtain the point cloud data at the corner groove; Step 2: Using a multi-scale alignment strategy, first roughly align the point cloud data obtained from the dual-view camera, then perform detailed point cloud data registration based on the GICP iterative algorithm, extract the geometric features of the corner groove, and determine the shape and size of its cross section; Step 3: Establish a combined welding thermal process model at the corner groove of the steel structure, predict the welding heat distribution and molten pool shape during the corner groove splicing welding process, formulate a weld filling strategy using the weld bead equal height filling method, and determine the position and welding process parameters of the steel structure corner groove weld splicing welding; Step 4: Based on the S-type acceleration and deceleration planning algorithm with continuous jerk, the speed of the welding trajectory of the splicing welding is planned to ensure the continuous change of the robot joint jerk and reduce the impact of robot vibration on welding; Step 5: Use non-uniform B-spline curves to interpolate and optimize the complex trajectory at the corner groove to achieve smooth transition of the welding robot's splicing welding trajectory at the corner.

[0030] In a specific embodiment of the present invention, in step S101, a plurality of point cloud data of the target corner groove are obtained. Specifically, a camera under dual viewing angles is used to shoot the corner groove of the steel structure, and the obtained data is analyzed to obtain the point cloud data at the corner groove. The camera under dual viewing angles is used to detect the corner groove to ensure the integrity and accuracy of the point cloud data at the corner groove. It is understandable that other multi-view cameras can be used.

[0031] The camera and robot body are calibrated through the hand-eye calibration method to ensure that the robot can accurately identify the position information and respond accurately.

[0032] Further, more specifically, obtaining a plurality of point cloud data of the target corner groove includes the following steps: S1011: photographing the target corner groove with a dual-view camera, recording the actual scanning speed of the camera, and storing the point cloud data of the target corner groove in a table; S1012: Find the actual distance between adjacent rows in the table: row spacing = scanning speed Working time / number of rows, the actual distance between adjacent columns is the data spacing between the X axes; S1013: multiply the row spacing by the number of rows to obtain the X coordinate value of the corresponding row, multiply the column spacing by the number of columns to obtain the Y coordinate value of the corresponding column, and the depth value in the original data table is the Z coordinate value; S1014: Convert (X, Y, Z) data into three-dimensional coordinate point set data in .ply format through the ply_write function.

[0033] In some embodiments of the present invention, the initial welding parameters include: welding current, welding voltage and welding speed.

[0034] In some embodiments of the present invention, registering the plurality of point cloud data to obtain the cross-sectional shape of the target corner groove includes: Register several point cloud data to obtain the weld contour of the target corner groove; The shape of the cross section is derived based on the weld contour.

[0035] In some embodiments of the present invention, in step S102, as Figure 3The figure shows a flow chart of point cloud precise registration based on the GICP iterative algorithm, which performs registration on the plurality of point cloud data to obtain the cross-sectional shape of the target corner groove, specifically including: S1021. Use manual alignment to roughly align the point cloud data at the corners under two viewing angles. Specifically, denoise the point cloud data of the corner groove taken from two viewing angles, use feature representation to complete point feature correspondence, and estimate the initial transformation matrix based on the correspondence results; then apply this transformation matrix to one of the point cloud data to perform preliminary alignment operations, as shown in the following formula:

[0036] Among them, R is a 3x3 rotation matrix, T is a 3x1 translation vector, , , and , , They represent different sets of coordinate points in three-dimensional space. Manual alignment of point cloud data means calculating the values ​​of R and T to roughly align the point cloud data under view 1 and view 2.

[0037] S1022, further align the point cloud data after S21 processing based on the GICP iterative algorithm. The basic principle of the GICP iterative algorithm is as follows:

[0038] Among them, F(R,T) is the objective function about the rotation matrix R and the translation vector T, n is the number of points in the source three-dimensional coordinate point set, is a point in the source point cloud data, is the target point cloud data The closest point, Yes The covariance matrix of and the geometric characteristics of its neighborhood. is the covariance matrix Initialize the target point cloud data and source point cloud data, as well as the preliminary transformation matrix. Then perform alignment iterations: For each iteration, Figure 3 As shown, the following steps are performed: a. Use KD-Tree to perform nearest neighbor search, establish point pairing, and calculate the covariance matrix of each point in the source three-dimensional coordinate point set; b. Calculate the weighted offset vector, taking into account the covariance information of the source and target points; c. Estimate the transformation matrix by minimizing the sum of squares of the weighted offset vectors; d. If the error of the transformation matrix is ​​less than the threshold, stop the iteration; otherwise, update the position and covariance matrix of the source three-dimensional coordinate point set and repeat step b; e. Output the final transformation matrix to achieve the registration of the source point cloud data to the target point cloud data.

[0039] S1023, contouring the weld, identifying the characteristic points of the corner groove, and accurately reconstructing the shape of the cross section of the corner groove. Specifically, the process of contouring the weld is as follows: Set the threshold T and calculate the normal vector of a point n i and the normal vector of each point in its k domain { n i1 , n i2 ,…, n ik} The inner product mean is as follows:

[0040] in, Represents the normal vector of the current point, Indicates the number of j The normal vector of a point, < , > indicates the first j Normal vector of a point The normal vector of the current point The inner product of .

[0041] Then take the normal vector eigenvalue of the point fi Is it the normal vector characteristic value of each point in the neighborhood of this point? {f i1 , f i2 ,…, f ik} is used as the condition, and a subset is selected as the final feature point set. The corner groove contour points are reconstructed based on the B-spline function, as shown in the following formula:

[0042] in, P i is the control point, F(t) is the i The k-th order B-spline basis function of the control points.

[0043] The basis functions are defined recursively as: When k=1;

[0044] When k>1;

[0045] Through the above steps, a fitting curve is obtained. , the curve depicts the actual contour shape of the corner groove within the range of t through basis functions and control points.

[0046] In some embodiments of the present invention, the welding strategy includes: The number of welded layers, the number of weld passes, and the cross-sectional area of ​​each weld.

[0047] In a specific embodiment of the present invention, in step S103, the welding strategy is determined based on the shape of the cross section. Specifically, the basic types of welding grooves include I-shaped grooves, V-shaped grooves, U-shaped grooves, J-shaped grooves, etc. In this embodiment, the corner groove is a single-sided V-shaped groove. Therefore, multi-layer and multi-pass welding is selected to effectively control heat input and weld cooling rate by superimposing welds layer by layer, thereby reducing welding defects and improving the mechanical properties and appearance quality of the weld.

[0048] Further, more specifically, the equal height weld filling strategy is used. The height of each layer of weld is consistent. The number of weld layers is determined according to the height of the cross-sectional shape of the groove. Specifically, Figure 5 As shown, the height h of each layer of weld is:

[0049] Where H represents the height of the groove cross-section shape; n represents n layers of weld; According to the geometric relationship, the width of the i-th layer can be obtained , the width of the i-1th for:

[0050] The cross-sectional area of ​​the single-sided V-shaped groove is equal, and the diamond side length of the weld in each layer is A:

[0051] The entire cross-section of each weld can be approximated as a trapezoid, and the area of ​​the trapezoid is It can be expressed as:

[0052] The number of welds per layer is:

[0053] Calculate the length BT of the lower base of each layer welded to the small and medium trapezoids:

[0054] Spatial position coordinates of the jth weld bead in the i-th layer x i,j , y i,j , z i,j for:

[0055] Among them, the jth weld position coordinates x, i, j of the i-th layer need to be limited to the range as follows:

[0056] in, Indicates the welding angle.

[0057] The first layer is the base welding. Due to the narrow welding section, only one weld pass is selected for the base welding. Two weld passes are selected for the second layer. After that, one weld pass is added for each additional layer. The number of weld passes is consistent with the number of layers. When the number of welding layers is given, the weld area of ​​each layer is also determined accordingly.

[0058] In some embodiments of the present invention, the step of constructing a welding thermal process model of a target corner groove includes: The welding thermal process model of the target corner groove is constructed based on finite element software.

[0059] In a specific embodiment of the present invention, a welding thermal process model is established in a simulation software. The software used in this embodiment is ABAQUS. It can be understood that other simulation software with similar functions can also be used. Figure 4 As shown, the expression of the welding thermal process model is:

[0060] In the formula, Represents the welding thermal process model; Represents the surface Gaussian welding thermal process model; Represents the double ellipsoid welding thermal process model; The welding thermal process model representing the front hemisphere; The welding thermal process model representing the rear hemisphere; Represents the weight coefficient of the surface Gaussian welding thermal process model; Represents the weight coefficient of the double ellipsoid welding thermal process model; where:

[0061] Where Q is the heat input per unit time. , unit is W; is the radius of heat source action, in mm; r is the diameter from any point in the heat source area to the center of the heat source, in mm; μ is the welding efficiency; U is the welding voltage, in V; I is the welding current, in A;

[0062]

[0063] Where q is the heat generation rate, in W / m 3 ; a f , a r , b , c are the shape parameters of the double ellipsoid heat source, in m; μ is the welding efficiency; U is the welding voltage, in V; I is the welding current, in A; f f is the energy distribution coefficient of the heat source model in the front part; f r is the energy distribution coefficient of the rear heat source model; the x direction is the welding forward direction; the y direction is the welding forward normal direction; and the z direction is the weld thickness direction.

[0064] like Figure 6 As shown, this embodiment uses the welding mutation point from the straight groove to the corner groove as the starting point of the splice welding. After the welding robot completes the straight segment welding task, it moves to the splice welding starting point, adjusts the welding process parameters, and performs welding operations to meet the welding heat input requirements at the corner groove and improve the welding quality of the corner groove.

[0065] Specifically, the simulation software is used to run the simulation, analyze the temperature distribution, molten pool shape, cooling rate, and heat-affected zone size during welding, and adjust the heat source model parameters to obtain the appropriate molten pool size. The welding parameters of welding current, voltage, and speed are optimized to control the heat input, reduce the heat-affected zone, and avoid the degradation of material properties caused by overheating.

[0066] It should be noted that in order to ensure the uniformity and consistency of the weld, the welding speed needs to be kept stable. Therefore, before speed planning, various parameters of the trajectory need to be set, including: welding trajectory length, maximum speed, maximum acceleration, maximum deceleration, jerk, each period of time, etc., and then the speed of the welding gun swing is planned based on the S-type acceleration and deceleration planning algorithm interpolation algorithm with continuous jerk. In some embodiments of the present invention, the welding gun swing speed planning corresponding to the welding trajectory determines the welding speed, including: Based on the S-type acceleration and deceleration planning algorithm, the welding gun swing speed corresponding to the welding trajectory is planned to obtain the acceleration; The welding speed is determined based on the jerk.

[0067] like Figure 7 As shown, the acceleration process includes acceleration, uniform acceleration and deceleration, and the deceleration process includes acceleration and deceleration, uniform deceleration and deceleration. The acceleration and deceleration are connected by a uniform speed, and the whole process includes 7 stages. In some embodiments of the present invention, the expression of the welding speed is:

[0068] in, ; , , , , , , The time for the 7 exercise stages respectively; , , , , , , They are the jerk of the 7 motion stages, Indicates the maximum acceleration allowed by the welding gun; is the starting speed; is the terminal velocity. The change of acceleration is achieved by combining the cosine function and the straight line segment, while the change of jerk follows the law of the sine function. This design makes the acceleration curve smoothly connected at the starting point and the end point. Such a curve not only utilizes the smooth and differentiable characteristics of trigonometric functions, but also enhances the controllability of the entire trajectory through the connection of straight line segments. This not only makes full use of the acceleration capability of the robot, but also optimizes the speed change of the welding gun during the welding process, thereby ensuring the stability of the welding process and the quality of the weld.

[0069] In a specific embodiment of the present invention, the welding speed is determined based on the jerk. Specifically, the acceleration is obtained by integrating the jerk, and the welding speed is obtained by integrating the acceleration.

[0070] In some embodiments of the present invention, after determining the welding trajectory of the target corner groove based on the optimized welding parameters and welding strategy, the method further includes: The welding trajectory is interpolated and optimized based on a non-uniform B-spline curve to obtain an optimized welding trajectory, and the non-uniform B-spline curve is used to improve the stability and uniformity of welding.

[0071] In an embodiment of the present invention, the expression of the non-uniform B-spline curve is:

[0072] in is the weight factor that adjusts the influence of the control point on the curve, is the set of control points, is the k-th non-uniform B-spline basis function.

[0073] First, the welding path model is constructed according to the shape characteristics of the corner groove, and the non-uniform B-spline curve is used to simulate the complex curve path to ensure the accurate depiction of the welding path. The shape characteristics of the corner groove are converted into parameter form, and the control points, weights and node vectors are set to create a non-uniform B-spline curve, and ensure that this curve can accurately match the actual shape of the corner groove. By fine-tuning the position, weight and node vector of the control points, we strive to make the curve smoother and more accurate, ensuring the smooth path and stable operation of the robot during welding.

[0074] In order to better implement a method for corner groove welding planning in an embodiment of the present invention, based on a method for corner groove welding planning, correspondingly, as Figure 8 As shown, an embodiment of the present invention further provides a device for corner groove welding planning, and a device 800 for corner groove welding planning includes: The point cloud data acquisition module 801 is used to acquire a plurality of point cloud data of the target corner groove; The shape acquisition module 802 is used to register the plurality of point cloud data to obtain the cross-sectional shape of the target corner groove; A welding strategy acquisition module 803, used to determine a welding strategy based on the shape of the cross section, and to determine initial welding parameters based on the welding strategy; A welding thermal process model building module 804 is used to build a welding thermal process model of a target corner groove; An optimized welding parameter acquisition module 805 is used to optimize the initial welding parameters of the welding thermal process model to obtain optimized welding parameters; A welding trajectory determination module 806 is used to determine the welding trajectory of the target corner groove based on the optimized welding parameters and welding strategy; The welding speed determination module 807 is used to plan the welding gun swing speed corresponding to the welding trajectory and determine the welding speed; The welding module 808 is used to weld the target corner groove based on the welding trajectory and welding speed.

[0075] The device 800 for corner groove welding planning provided in the above embodiment can implement the technical solution described in the above embodiment of a method for corner groove welding planning. The specific implementation principles of the above modules or units can refer to the corresponding contents in the above embodiment of a method for corner groove welding planning, which will not be repeated here.

[0076] like Fig. 9As shown, the present invention also provides an electronic device 900. The electronic device 900 includes a processor 901, a memory 902 and a display 903. Fig. 9 Only some components of the electronic device 900 are shown, but it should be understood that it is not required to implement all of the components shown, and more or fewer components may be implemented instead.

[0077] In some embodiments, the processor 901 may be a central processing unit (CPU), a microprocessor or other data processing chip, which is used to run program codes or process data stored in the memory 902, such as a method for corner groove welding planning in the present invention.

[0078] In some embodiments, the processor 901 may be a single server or a server group. The server group may be centralized or distributed. In some embodiments, the processor 901 may be local or remote. In some embodiments, the processor 901 may be implemented in a cloud platform. In some embodiments, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an internal cloud, a multi-cloud, etc., or any combination thereof.

[0079] In some embodiments, the memory 902 may be an internal storage unit of the electronic device 900, such as a hard disk or memory of the electronic device 900. In other embodiments, the memory 902 may also be an external storage device of the electronic device 900, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc., equipped on the electronic device 900.

[0080] Furthermore, the memory 902 may include both an internal storage unit of the electronic device 900 and an external storage device. The memory 902 is used to store application software installed in the electronic device 900 and various data.

[0081] In some embodiments, the display 903 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, etc. The display 903 is used to display information on the electronic device 900 and to display a visual user interface. The components 901-903 of the electronic device 900 communicate with each other via a system bus.

[0082] In one embodiment, when the processor 901 executes a corner groove welding planning program in the memory 902, the following steps may be implemented: Obtain several point cloud data of the target corner groove; Registering the plurality of point cloud data to obtain the cross-sectional shape of the target corner groove; determining a welding strategy based on the shape of the cross section, and determining initial welding parameters based on the welding strategy; Construct the welding thermal process model of the target corner groove; Optimizing the initial welding parameters of the welding thermal process model to obtain optimized welding parameters; Determine the welding trajectory of the target corner groove based on the optimized welding parameters and welding strategy; Plan the welding gun swing speed corresponding to the welding trajectory and determine the welding speed; The target corner groove is welded based on the welding trajectory and welding speed.

[0083] It should be understood that: when the processor 901 executes a corner groove welding planning program in the memory 902, in addition to the above functions, other functions can also be implemented. For details, please refer to the description of the corresponding method embodiment above.

[0084] Furthermore, the embodiment of the present invention does not specifically limit the type of the electronic device 900 mentioned, and the electronic device 900 may be a portable electronic device such as a mobile phone, a tablet computer, a personal digital assistant (PDA), a wearable device, a laptop computer, etc. Exemplary embodiments of portable electronic devices include but are not limited to portable electronic devices equipped with IOS, Android, Microsoft or other operating systems. The above-mentioned portable electronic devices may also be other portable electronic devices, such as a laptop computer with a touch-sensitive surface (e.g., a touch panel). It should also be understood that in some other embodiments of the present invention, the electronic device 900 may not be a portable electronic device, but a desktop computer with a touch-sensitive surface (e.g., a touch panel).

[0085] Those skilled in the art will appreciate that all or part of the processes of the above-mentioned embodiments can be implemented by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium, wherein the computer-readable storage medium is a disk, an optical disk, a read-only storage memory, or a random access memory, etc.

[0086] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. A method for corner groove welding planning, characterized in that: include: Obtain several point cloud data of the target corner groove; Registering the plurality of point cloud data to obtain the cross-sectional shape of the target corner groove; determining a welding strategy based on the shape of the cross section, and determining initial welding parameters based on the welding strategy; Construct the welding thermal process model of the target corner groove; Optimizing the initial welding parameters of the welding thermal process model to obtain optimized welding parameters; Determine the welding trajectory of the target corner groove based on the optimized welding parameters and welding strategy; Plan the welding gun swing speed corresponding to the welding trajectory and determine the welding speed; The target corner groove is welded based on the welding trajectory and welding speed.

2. The method for corner groove welding planning according to claim 1, characterized in that: The initial welding parameters include: welding current, welding voltage and welding speed.

3. The method for corner groove welding planning according to claim 1, characterized in that: The registering of the plurality of point cloud data to obtain the cross-sectional shape of the target corner groove includes: Register several point cloud data to obtain the weld contour of the target corner groove; The shape of the cross section is derived based on the weld contour.

4. The method for corner groove welding planning according to claim 1, characterized in that: The welding strategy includes: The number of welded layers, the number of weld passes, and the cross-sectional area of ​​each weld.

5. The method for corner groove welding planning according to claim 1, characterized in that: The method of constructing a welding thermal process model of a target corner groove comprises: The welding thermal process model of the target corner groove is constructed based on finite element software.

6. The method for corner groove welding planning according to claim 1, characterized in that: The expression of the welding thermal process model is: In the formula, Represents the welding thermal process model; Represents the surface Gaussian welding thermal process model; Represents the double ellipsoid welding thermal process model; The welding thermal process model representing the front hemisphere; Represents the welding thermal process model of the rear hemisphere; Represents the weight coefficient of the surface Gaussian welding thermal process model; Represents the weight coefficient of the double ellipsoid welding thermal process model; where: Where Q is the heat input per unit time. , unit is W; is the radius of heat source action, in mm; r is the diameter from any point in the heat source area to the center of the heat source, in mm; μ is the welding efficiency; U is the welding voltage, in V; I is the welding current, in A; Where q is the heat generation rate, in W / m 3 ; a f , a r , b , c are the shape parameters of the double ellipsoid heat source, in m; μ is the welding efficiency; U is the welding voltage, in V; I is the welding current, in A; f f is the energy distribution coefficient of the heat source model in the front part; f r is the energy distribution coefficient of the rear partial heat source model; x Direction is the welding forward direction; y The direction is the normal direction of welding forward; z The direction is the weld thickness direction.

7. The method for corner groove welding planning according to claim 1, characterized in that: The welding torch swing speed planning corresponding to the welding trajectory and determining the welding speed include: Based on the S-type acceleration and deceleration planning algorithm, the welding gun swing speed corresponding to the welding trajectory is planned to obtain the acceleration; The welding speed is determined based on the jerk.

8. The method for corner groove welding planning according to claim 7, characterized in that: The expression of the acceleration is: in, ; , , , , , , The time for the 7 exercise stages respectively; , , , , , , They are the jerk of the 7 motion stages, Indicates the maximum acceleration allowed by the welding gun; is the starting speed; is the terminal velocity.

9. The method for corner groove welding planning according to claim 1, characterized in that: After determining the welding trajectory of the target corner groove based on the optimized welding parameters and welding strategy, the method further includes: The welding trajectory is interpolated and optimized based on a non-uniform B-spline curve to obtain an optimized welding trajectory.

10. A device for corner groove welding planning, characterized in that: include: A point cloud data acquisition module is used to acquire a number of point cloud data of the target corner groove; A shape acquisition module, used to register the plurality of point cloud data to obtain the cross-sectional shape of the target corner groove; A welding strategy acquisition module, used to determine a welding strategy based on the shape of the cross section, and to determine initial welding parameters based on the welding strategy; A welding thermal process model building module is used to build a welding thermal process model of the target corner groove; An optimized welding parameter acquisition module is used to optimize the initial welding parameters of the welding thermal process model to obtain optimized welding parameters; A welding trajectory determination module, used to determine the welding trajectory of the target corner groove based on the optimized welding parameters and welding strategy; The welding speed determination module is used to plan the welding gun swing speed corresponding to the welding trajectory and determine the welding speed; The welding module is used to weld the target corner groove based on the welding trajectory and welding speed.

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