A welding head trajectory optimization method for ultrasonic welding equipment

Abstract

The present invention relates to the field of ultrasonic welding technology, and more particularly to a method for optimizing the welding head trajectory of an ultrasonic welding device. The method comprises: identifying a workpiece to be welded, obtaining initial parameters of the workpiece to be welded, and determining an initial welding trajectory based on the initial parameters; identifying a trajectory surface image corresponding to the initial welding trajectory, analyzing the trajectory surface image to obtain surface features; adjusting the initial welding trajectory based on the surface features to obtain an adjusted welding trajectory; real-time monitoring of welding features during a welding process according to the adjusted welding trajectory, calibrating the adjusted welding trajectory in real time based on the welding features to obtain a target welding trajectory; analyzing the welding performance of the welded workpiece after welding according to the target welding trajectory, and adjusting the target welding trajectory based on the analysis results of the welding performance to optimize it in the next welding cycle. The present invention improves the accuracy of the welding trajectory.

Description

Technical Field

[0001] The present invention relates to the technical field of ultrasonic welding, and in particular to a method for optimizing the welding head trajectory of ultrasonic welding equipment. Background Art

[0002] Ultrasonic welding, as an efficient and environmentally friendly joining technology, is widely used in various fields, including automotive, electronics, and medical. Traditional ultrasonic welding equipment typically relies on preset welding paths when performing welding tasks. These paths are often based on experience or simple geometric shapes, and lack detailed consideration of the actual surface characteristics of the welded parts.

[0003] The patent document with Chinese patent application number CN118438446A discloses a method for planning the trajectory of a welding robot, which includes the following steps: first, using visual sensors, laser scanning and force feedback sensors to collect data on the welding joint, and applying a data fusion algorithm including a Kalman filter or a deep learning model to integrate multi-sensor information to achieve an accurate description of the weld geometry and spatial position; second, based on the acquired weld information, introducing an adaptive path planning algorithm that combines graph search including the A* algorithm and machine learning such as reinforcement learning to adapt to weld changes caused by material deformation or thermal diffusion in real time and adjust the welding path; finally, establishing a simulation model of the welding process to predict the impact of different welding parameters on the weld quality, and using machine learning methods such as support vector machines or neural networks to dynamically adjust the welding speed, power and pressure parameters based on real-time data to optimize the parameter settings during the welding process.

[0004] The existing technology uses simulation models and machine learning algorithms to predict and adjust welding parameters, which relies on a large amount of historical data and prior knowledge. When problems are encountered during the actual welding process, real-time adjustments cannot be made, resulting in inaccurate welding trajectories. Summary of the Invention

[0005] To this end, the present invention provides a welding head trajectory optimization method for ultrasonic welding equipment, which solves the problem of inaccurate welding trajectory by identifying and analyzing the trajectory surface image corresponding to the welding trajectory, obtaining surface features in real time, and adjusting the initial welding trajectory accordingly.

[0006] To achieve the above object, the present invention provides a method for optimizing the welding head trajectory of an ultrasonic welding device, comprising: identifying a workpiece to be welded, obtaining initial parameters of the workpiece to be welded, and determining an initial welding trajectory based on the initial parameters;

[0007] Identifying a track surface image corresponding to the initial welding track, and analyzing the track surface image to obtain surface features;

[0008] Adjusting the initial welding trajectory based on the surface features to obtain an adjusted welding trajectory;

[0009] Real-time monitoring of welding characteristics of the welding process according to the adjusted welding trajectory, real-time calibration of the adjusted welding trajectory according to the welding characteristics, and obtaining a target welding trajectory;

[0010] The welding performance of the welded part after welding according to the target welding trajectory is analyzed, and the target welding trajectory is adjusted according to the analysis result of the welding performance to optimize it in the next welding cycle.

[0011] Furthermore, the step of determining the initial welding trajectory based on the initial parameters includes:

[0012] Acquiring an image of the workpiece to be welded;

[0013] Analyzing the image to be welded to determine the contour features of the area to be welded;

[0014] Dividing the area to be welded into a linear welding area and a non-linear welding area based on the contour features of the area to be welded;

[0015] Calculate the proportions of the linear welding area and the non-linear welding area respectively, and obtain the linear proportion and the non-linear proportion;

[0016] The straight line ratio and the non-straight line ratio are compared, and an initial welding trajectory is determined based on the comparison result.

[0017] Furthermore, the step of dividing the area to be welded into a linear welding area and a non-linear welding area based on the contour features of the area to be welded comprises:

[0018] Identifying a plurality of inflection points in the contour feature of the area to be welded, dividing the contour feature of the area to be welded based on the plurality of inflection points to obtain a plurality of sub-contours;

[0019] The curvature values ​​of the plurality of sub-contours are calculated, the curvature values ​​are compared with preset curvature values, and the linear welding area and the non-linear welding area are determined based on the comparison result.

[0020] Furthermore, the step of determining the initial welding trajectory based on the comparison result includes:

[0021] When the straight line ratio is greater than or equal to the non-straight line ratio, the straight line welding area is welded, and when the straight line welding area is welded, the non-straight line welding area is welded to obtain an initial welding trajectory;

[0022] When the proportion of the straight lines is smaller than the proportion of the non-straight lines, the shortest welding path of the area to be welded is determined according to the shortest path algorithm and is used as the initial welding trajectory.

[0023] Furthermore, the step of analyzing the trajectory surface image to obtain surface features includes:

[0024] identifying a plurality of edge contours in the track surface image by an edge detection algorithm;

[0025] Identifying brightness values ​​of edge contour areas included in a plurality of edge contours;

[0026] The crack area and the convex area in the surface image are determined based on the brightness value recognition result.

[0027] Furthermore, the step of adjusting the initial welding trajectory based on the surface features includes:

[0028] Identifying the crack direction and crack length of the crack area, and determining a repair welding path based on the crack direction and crack length to adjust the initial welding trajectory;

[0029] The raised area corresponding to the raised region is calculated, and when the raised area is greater than or equal to a preset area, a new welding trajectory is set according to the edge shape of the raised region to adjust the initial welding trajectory.

[0030] Furthermore, the step of real-time monitoring of welding characteristics of the welding process according to the adjustment of the welding trajectory includes:

[0031] Get real-time images during welding;

[0032] The contact position between the welding head and the workpiece to be welded during the welding process is obtained based on real-time images.

[0033] Furthermore, the step of adjusting the welding trajectory for real-time calibration according to the welding characteristics includes:

[0034] Calculating a deviation distance between the contact position and a position corresponding to the adjusted welding trajectory;

[0035] The welding head is adjusted in real time based on the deviation distance to calibrate the adjusted welding trajectory and obtain the target welding trajectory.

[0036] Furthermore, the step of analyzing the welding performance of the welded part after welding according to the target welding trajectory includes:

[0037] Collecting images at the welding inflection point to obtain an inflection point image;

[0038] Analyzing the inflection point image to identify welding porosity and welding uniformity;

[0039] The welded parts are analyzed based on the welding porosity and welding uniformity, and the welding performance is identified according to the identification result.

[0040] Furthermore, the step of adjusting the target welding trajectory according to the analysis result of the welding performance includes:

[0041] When the welding performance is poor, welding points are added at preset intervals at the inflection point to adjust the target welding trajectory;

[0042] When the welding performance is not bad, the target welding trajectory is not adjusted.

[0043] Compared with the prior art, the beneficial effect of the present invention is that, by identifying the initial parameters of the workpiece to be welded and determining the initial welding trajectory, the actual situation in the welding process can be grasped more accurately, the initial welding trajectory can be adjusted based on the surface features, welding defects can be significantly reduced, and the overall quality of the welded workpiece can be improved. By real-time monitoring of the welding characteristics during the welding process and real-time calibration of the adjusted welding trajectory based on these characteristics, the welding process is made more stable and controllable, and the welding parameters and trajectory are adjusted in time to ensure the consistency of welding quality. By continuously optimizing the welding trajectory, unnecessary welding paths and repetitive work are reduced, thereby reducing welding time and cost, improving resource utilization efficiency, improving welding quality and efficiency, analyzing welding performance and adjusting the target welding trajectory according to the results, forming a closed-loop optimization process, providing a more accurate and efficient basis for subsequent welding, and improving welding efficiency and accuracy.

[0044] In particular, by analyzing the welding image, the contour features of the area to be welded can be accurately identified, which improves the accuracy of the welding trajectory. The welding area is subdivided into linear welding areas and non-linear welding areas, and their proportions are calculated separately, which helps to formulate more appropriate welding trajectories and strategies for different types of welding areas. By comparing the linear proportion and non-linear proportion, the direction and sequence of the initial welding trajectory are determined, and unnecessary movement of the welding head during the welding process is reduced, thereby reducing energy consumption and wear and improving welding efficiency. Different welding path strategies are formulated for different types of welding areas to achieve customized welding and improve welding quality.

[0045] In particular, by identifying the direction and length of the cracks in the crack area, the repair welding path is accurately determined, which improves the pertinence and efficiency of the repair welding. When encountering a raised area, the raised area is calculated and compared with the preset area to provide a basis for subsequent path optimization. If the raised area is large, a new welding trajectory is set according to the edge shape of the raised area to ensure that the welding head can fit closely to the welding surface and improve the welding quality. By adjusting the welding trajectory to adapt to the raised area, the quality of welding is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 A schematic flow chart of a method for optimizing the trajectory of a welding head of an ultrasonic welding device according to an embodiment of the present invention;

[0047] Figure 2 A schematic diagram of a flow chart of determining an initial welding trajectory of a welding head trajectory optimization method for an ultrasonic welding device provided in an embodiment of the present invention;

[0048] Figure 3 A schematic diagram of a process for obtaining surface features of a welding head trajectory optimization method for an ultrasonic welding device provided in an embodiment of the present invention;

[0049] Figure 4 A schematic flow chart of monitoring welding characteristics of a welding head trajectory optimization method for ultrasonic welding equipment provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0050] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are merely used to explain the present invention and are not intended to limit the present invention.

[0051] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0052] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it should not be understood as a limitation on the present invention.

[0053] Furthermore, it should be noted that, in the description of the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; they may refer to mechanical connections or electrical connections; they may refer to direct connections or indirect connections through an intermediate medium; and they may refer to internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0054] See also Figure 1 As shown, an embodiment of the present invention provides a method for optimizing the welding head trajectory of an ultrasonic welding device, the method comprising:

[0055] Step S100, identifying the parts to be welded, obtaining initial parameters of the parts to be welded, and determining an initial welding trajectory based on the initial parameters;

[0056] Step S200, identifying a track surface image corresponding to the initial welding track, and analyzing the track surface image to obtain surface features;

[0057] Step S300, adjusting the initial welding trajectory based on the surface features to obtain an adjusted welding trajectory;

[0058] Step S400, real-time monitoring of welding characteristics of the welding process according to the adjusted welding trajectory, real-time calibration of the adjusted welding trajectory according to the welding characteristics, and obtaining a target welding trajectory;

[0059] Step S500: analyzing the welding performance of the welded part after welding according to the target welding trajectory, and adjusting the target welding trajectory according to the analysis result of the welding performance to optimize it in the next welding cycle.

[0060] Specifically, the embodiment of the present invention can more accurately grasp the actual situation in the welding process by identifying the initial parameters of the workpiece to be welded and determining the initial welding trajectory, adjust the initial welding trajectory based on surface features, significantly reduce welding defects, and thus improve the overall quality of the welded workpiece. By real-time monitoring of welding characteristics during the welding process and real-time calibration of the adjusted welding trajectory based on these characteristics, the welding process is made more stable and controllable, and the welding parameters and trajectory are adjusted in time to ensure the consistency of welding quality. By continuously optimizing the welding trajectory, unnecessary welding paths and repetitive work are reduced, thereby reducing welding time and cost, improving resource utilization efficiency, and improving welding quality and efficiency. The welding performance is analyzed and the target welding trajectory is adjusted according to the results, forming a closed-loop optimization process, providing a more accurate and efficient basis for subsequent welding, and improving welding efficiency and accuracy.

[0061] See also Figure 2 As shown, the step of determining the initial welding trajectory based on the initial parameters includes:

[0062] Step S110, obtaining a welding image of the workpiece to be welded;

[0063] Step S120, analyzing the image to be welded to determine the contour features of the area to be welded;

[0064] Step S130, dividing the area to be welded into a linear welding area and a non-linear welding area based on the contour features of the area to be welded;

[0065] Step S140, respectively calculating the proportions of the linear welding area and the non-linear welding area to obtain a linear proportion and a non-linear proportion;

[0066] Step S150 , comparing the straight line proportion and the non-straight line proportion, and determining an initial welding trajectory based on the comparison result.

[0067] Specifically, the step of determining the contour features of the area to be welded in the embodiment of the present invention includes:

[0068] Processing the image to be welded by an edge detection algorithm to obtain boundary features;

[0069] The boundary features are extracted by a contour extraction algorithm to obtain the contour features of the area to be welded.

[0070] Specifically, the edge detection algorithm described in the embodiment of the present invention includes Canny edge detection, Sobel edge detection, etc., and the contour extraction algorithm includes threshold-based segmentation, region-based segmentation, or edge-based segmentation. In the embodiment of the present invention, algorithms such as Hough Transform or Chain Code Tracking can be used to accurately extract the contour of the area to be welded.

[0071] Specifically, the embodiment of the present invention can accurately identify the contour features of the area to be welded by analyzing the welding image, thereby improving the accuracy of the welding trajectory, subdividing the welding area into linear welding areas and non-linear welding areas, and calculating their proportions respectively, which helps to formulate more appropriate welding trajectories and strategies for different types of welding areas. By comparing the linear proportion and non-linear proportion, the direction and sequence of the initial welding trajectory are determined, and unnecessary movement of the welding head during the welding process is reduced, thereby reducing energy consumption and wear and improving welding efficiency. Different welding path strategies are formulated for different types of welding areas, thereby achieving customized welding and improving welding quality.

[0072] Specifically, the step of dividing the area to be welded into a linear welding area and a non-linear welding area based on the contour features of the area to be welded comprises:

[0073] Identifying a plurality of inflection points in the contour feature of the area to be welded, dividing the contour feature of the area to be welded based on the plurality of inflection points to obtain a plurality of sub-contours;

[0074] The curvature values ​​of the plurality of sub-contours are calculated, the curvature values ​​are compared with preset curvature values, and the linear welding area and the non-linear welding area are determined based on the comparison result.

[0075] Specifically, the embodiment of the present invention can identify inflection points on the contour of the area to be welded by using an image processing algorithm, such as corner detection (such as the Sh i-Tomas i algorithm or Harris corner detection).

[0076] Specifically, the embodiment of the present invention calculates the curvature value of each sub-contour, and the curvature value can be calculated using the following formula: Where k is the curvature value, dy / dx is the slope of the point on the subcontour, and d 2 y / dx 2 is the derivative of the slope.

[0077] Specifically, the step of determining the initial welding trajectory based on the comparison result includes:

[0078] When the straight line ratio is greater than or equal to the non-straight line ratio, the straight line welding area is welded, and when the straight line welding area is welded, the non-straight line welding area is welded to obtain an initial welding trajectory;

[0079] When the proportion of the straight lines is smaller than the proportion of the non-straight lines, the shortest welding path of the area to be welded is determined according to the shortest path algorithm and is used as the initial welding trajectory.

[0080] Specifically, the steps of calculating the proportions of the linear welding area and the non-linear welding area respectively in the embodiment of the present invention include:

[0081] Calculate the straight length value of the edge contour of the straight welding area and the non-straight length value of the edge contour of the non-straight welding area;

[0082] Divide the straight line length value by the sum of the straight line length value and the non-straight line length value to obtain the straight line ratio;

[0083] Divide the non-straight line length value by the sum of the straight line length value and the non-straight line length value to obtain the non-straight line ratio.

[0084] Specifically, in an embodiment of the present invention, when the straight line proportion is greater than or equal to the non-straight line proportion, the initial welding trajectory can be obtained by welding the straight line welding areas in sequence according to the same direction, and after welding is completed, welding the straight line welding areas according to the edge contour features in the same direction.

[0085] Specifically, the shortest path algorithm described in the embodiment of the present invention includes Dijkstra algorithm, A* algorithm, etc.

[0086] See also Figure 3 As shown, the step of analyzing the trajectory surface image to obtain surface features includes:

[0087] Step S210, identifying a plurality of edge contours in the track surface image using an edge detection algorithm;

[0088] Step S220, identifying brightness values ​​of edge contour areas included in the plurality of edge contours;

[0089] Step S230 : determining crack areas and convex areas in the surface image based on the brightness value recognition result.

[0090] Specifically, the step of determining the crack area and the convex area in the surface image based on the brightness value recognition result in the embodiment of the present invention includes:

[0091] Comparing the brightness values ​​with the brightness value range to obtain a comparison result;

[0092] If the brightness value is lower than the brightness value range, the area is determined to be a crack area;

[0093] If the brightness value is higher than the brightness value range, the area is determined to be a convex area.

[0094] Specifically, the brightness range described in the embodiment of the present invention is [50, 150], which is obtained based on a large amount of actual image data analysis and experimental verification.

[0095] Specifically, the embodiment of the present invention accurately identifies the edge contours in the trajectory surface image through an edge detection algorithm, providing an accurate basis for subsequent path optimization. By analyzing the surface features obtained from the trajectory surface image, it can depict in detail the various surface defects encountered in the welding process, thereby providing strong support for subsequent welding quality control. By monitoring the surface condition of the welding track in real time, potential problems can be discovered in a timely manner and preventive maintenance can be performed, thereby avoiding equipment failures and increased downtime, thereby improving the efficiency of the welding process.

[0096] Specifically, the step of adjusting the initial welding trajectory based on the surface features includes:

[0097] Identifying the crack direction and crack length of the crack area, and determining a repair welding path based on the crack direction and crack length to adjust the initial welding trajectory;

[0098] The raised area corresponding to the raised region is calculated, and when the raised area is greater than or equal to a preset area, a new welding trajectory is set according to the edge shape of the raised region to adjust the initial welding trajectory.

[0099] Specifically, when identifying the crack direction and length of a crack area, the embodiment of the present invention may use a line detection algorithm in image processing technology, such as Hough transform line detection, to accurately obtain the extension direction and specific length of the crack.

[0100] Specifically, the step of determining the repair welding path based on the crack direction and crack length in the embodiment of the present invention includes:

[0101] Determine the starting point and end point of the crack, and based on the extension direction of the crack, generate a certain width of the repair welding area on both sides of the crack, and generate the repair welding path based on the repair welding area;

[0102] The repair welding path is merged with the initial welding trajectory to form an adjusted welding trajectory.

[0103] Specifically, in an embodiment of the present invention, when the area of ​​the protrusion is greater than or equal to a preset area, the protrusion boundary is obtained through a contour fitting algorithm, and the welding path is replanned based on the shape.

[0104] Specifically, the preset area described in the embodiment of the present invention is determined based on experimental data and actual application scenarios. For example, if the protrusion area exceeds 1.5 times the weld width, it is considered to have an impact on the welding quality and a new welding path needs to be planned.

[0105] Specifically, an embodiment of the present invention also includes not adjusting the initial welding trajectory when the protrusion area is smaller than a preset area.

[0106] Specifically, the embodiment of the present invention accurately determines the repair welding path by identifying the crack direction and length in the crack area, thereby improving the targetedness and efficiency of the repair welding. When encountering a raised area, the raised area is calculated and compared with the preset area to provide a basis for subsequent path optimization. If the raised area is large, a new welding trajectory is set according to the edge shape of the raised area to ensure that the welding head can fit closely to the welding surface and improve the welding quality. By adjusting the welding trajectory to adapt to the raised area, the welding quality is improved.

[0107] See also Figure 4 As shown, the step of real-time monitoring of the welding characteristics of the welding process according to the adjustment of the welding trajectory includes:

[0108] Step S410, obtaining a real-time image during the welding process;

[0109] Step S420: Acquire the contact position between the welding head and the workpiece to be welded during the welding process based on the real-time image.

[0110] Specifically, the step of adjusting the welding trajectory in real time according to the welding characteristics includes:

[0111] Calculating a deviation distance between the contact position and a position corresponding to the adjusted welding trajectory;

[0112] The welding head is adjusted in real time based on the deviation distance to calibrate the adjusted welding trajectory and obtain the target welding trajectory.

[0113] Specifically, the step of analyzing the welding performance of the welded part after welding according to the target welding trajectory includes:

[0114] Collecting images at the welding inflection point to obtain an inflection point image;

[0115] Analyzing the inflection point image to identify welding porosity and welding uniformity;

[0116] The welded parts are analyzed based on the welding porosity and welding uniformity, and the welding performance is identified according to the identification result.

[0117] Specifically, the steps of identifying welding porosity and welding uniformity in the embodiment of the present invention include:

[0118] Extract several contour features from the inflection point image based on edge detection algorithm;

[0119] Analyzing the areas containing the plurality of contour features by analyzing the grayscale distribution and texture features in the image to identify the welding pore areas and determine the pore distribution;

[0120] Gray values ​​in the welding profile are statistically identified based on the gray histogram, so as to determine the welding uniformity according to the difference between the maximum value and the minimum value among a plurality of gray values.

[0121] Specifically, the steps of analyzing the welded parts based on the welding porosity and welding uniformity in the embodiment of the present invention include:

[0122] Determine the porosity distribution based on the ratio of the porosity area to the total weld area;

[0123] When the porosity distribution is greater than the preset distribution and the welding uniformity is greater than the preset uniformity, the welding performance is poor;

[0124] When the porosity distribution is smaller than the preset distribution and the welding uniformity is smaller than the preset uniformity, the welding performance is excellent;

[0125] When the porosity distribution is less than the preset distribution or the welding uniformity is less than the preset uniformity, the welding performance is medium.

[0126] Specifically, the step of adjusting the target welding trajectory according to the analysis results of the welding performance includes:

[0127] When the welding performance is poor, welding points are added at preset intervals at the inflection point to adjust the target welding trajectory;

[0128] When the welding performance is not bad, the target welding trajectory is not adjusted.

[0129] Specifically, the preset interval in the embodiment of the present invention is 1 / 5 of the curvature radius at the inflection point.

[0130] Thus far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present invention.

[0131] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that the present invention is susceptible to various modifications and variations. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A method for optimizing the welding head trajectory of an ultrasonic welding device, characterized in that: include: Identify the parts to be welded, obtain initial parameters of the parts to be welded, and determine an initial welding trajectory based on the initial parameters; Identifying a track surface image corresponding to the initial welding track, and analyzing the track surface image to obtain surface features; Adjusting the initial welding trajectory based on the surface features to obtain an adjusted welding trajectory; Real-time monitoring of welding characteristics of the welding process according to the adjusted welding trajectory, real-time calibration of the adjusted welding trajectory according to the welding characteristics, and obtaining a target welding trajectory; Analyzing the welding performance of the welded part after welding according to the target welding trajectory, and adjusting the target welding trajectory according to the analysis results of the welding performance to optimize it in the next welding cycle; The step of determining the initial welding trajectory based on the initial parameters includes: Acquiring an image of the workpiece to be welded; Analyzing the image to be welded to determine the contour features of the area to be welded; Dividing the area to be welded into a linear welding area and a non-linear welding area based on the contour features of the area to be welded; Calculate the proportions of the linear welding area and the non-linear welding area respectively, and obtain the linear proportion and the non-linear proportion; comparing the straight line ratio and the non-straight line ratio, and determining an initial welding trajectory based on the comparison result; The step of dividing the area to be welded into linear welding areas and non-linear welding areas based on the contour features of the area to be welded comprises: Identifying a plurality of inflection points in the contour feature of the area to be welded, dividing the contour feature of the area to be welded based on the plurality of inflection points to obtain a plurality of sub-contours; The curvature values ​​of the plurality of sub-contours are calculated, the curvature values ​​are compared with preset curvature values, and the linear welding area and the non-linear welding area are determined based on the comparison result.

2. The welding head trajectory optimization method of ultrasonic welding equipment according to claim 1, characterized in that: The step of determining the initial welding trajectory based on the comparison result includes: When the straight line ratio is greater than or equal to the non-straight line ratio, the straight line welding area is welded, and when the straight line welding area is welded, the non-straight line welding area is welded to obtain an initial welding trajectory; When the proportion of the straight lines is smaller than the proportion of the non-straight lines, the shortest welding path of the area to be welded is determined according to the shortest path algorithm and is used as the initial welding trajectory.

3. The welding head trajectory optimization method of ultrasonic welding equipment according to claim 2, characterized in that: The step of analyzing the trajectory surface image to obtain surface features comprises: identifying a plurality of edge contours in the track surface image by an edge detection algorithm; Identifying brightness values ​​of edge contour areas included in a plurality of edge contours; The crack area and the convex area in the surface image are determined based on the brightness value recognition result.

4. The welding head trajectory optimization method of ultrasonic welding equipment according to claim 3, characterized in that: The step of adjusting the initial welding trajectory based on the surface features comprises: Identifying the crack direction and crack length of the crack area, and determining a repair welding path based on the crack direction and crack length to adjust the initial welding trajectory; The raised area corresponding to the raised region is calculated, and when the raised area is greater than or equal to a preset area, a new welding trajectory is set according to the edge shape of the raised region to adjust the initial welding trajectory.

5. The welding head trajectory optimization method of ultrasonic welding equipment according to claim 4, characterized in that: The step of real-time monitoring of welding characteristics of the welding process according to the adjustment of the welding trajectory comprises: Get real-time images during welding; The contact position between the welding head and the workpiece to be welded during the welding process is obtained based on real-time images.

6. The welding head trajectory optimization method of ultrasonic welding equipment according to claim 5, characterized in that: The step of adjusting the welding trajectory for real-time calibration according to the welding characteristics comprises: Calculating a deviation distance between the contact position and a position corresponding to the adjusted welding trajectory; The welding head is adjusted in real time based on the deviation distance to calibrate the adjusted welding trajectory and obtain the target welding trajectory.

7. The welding head trajectory optimization method of ultrasonic welding equipment according to claim 6, characterized in that: The step of analyzing the welding performance of the welded part after welding according to the target welding trajectory includes: Collecting images at the welding inflection point to obtain an inflection point image; Analyzing the inflection point image to identify welding porosity and welding uniformity; The welded parts are analyzed based on the welding porosity and welding uniformity, and the welding performance is identified according to the identification result.

8. The welding head trajectory optimization method of ultrasonic welding equipment according to claim 7, characterized in that: The step of adjusting the target welding trajectory according to the analysis result of the welding performance includes: When the welding performance is poor, welding points are added at preset intervals at the inflection point to adjust the target welding trajectory; When the welding performance is not bad, the target welding trajectory is not adjusted.

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