Welding seam tracking and self-adaptive adjusting device and adjusting method thereof

Abstract

The invention discloses a welding seam tracking and self-adaptive adjusting device and an adjusting method thereof, and relates to the technical field of welding seam adjustment, and the adjusting method comprises the steps of capturing a welding seam heat distribution diagram, obtaining the highest temperature in a welding seam contour to calculate the highest temperature fluctuation rate of a welding seam, and obtaining the lowest temperature in the welding seam contour to calculate the welding seam cooling rate. According to the welding seam cooling rate and the highest temperature fluctuation rate, the welding seam temperature abnormal coefficient is calculated; capturing a weld shape picture, identifying a newly-added weld area contour, extracting a newly-added weld length and a newly-added weld width, calculating a newly-added weld length-width ratio, and further calculating a weld size abnormal coefficient; and a welding seam temperature abnormal coefficient and a welding seam size abnormal coefficient are obtained, a welding seam abnormal coefficient is calculated, and a friction rotating speed adjusting value is calculated through a PID algorithm. Welding stability is comprehensively evaluated, friction rotating speed is adjusted in real time, and welding stability and welding seam quality are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of weld seam adjustment, in particular to a weld seam tracking and adaptive adjustment device and an adjustment method thereof. Background Art

[0002] In the field of welding automation, weld seam tracking and adaptive adjustment technology are the core links to achieve high-quality welding. As industrial manufacturing develops towards high precision and high efficiency, especially in the fields of aerospace, nuclear power equipment, new energy vehicles, etc., the demand for welding complex structural parts has increased sharply, and the problem of insufficient adaptability of traditional welding processes in dynamic environments has become increasingly prominent. Traditional welding robots mostly rely on fixed trajectories programmed offline and cannot respond to dynamic changes in the welding process (such as weld offset caused by thermal deformation) in real time. In addition, most systems only implement position tracking and lack real-time evaluation of welding quality (such as depth and porosity), resulting in a disconnect between parameter adjustment and quality goals. The optimization of process parameters (current, speed) relies on trial and error based on engineers' experience, which is inefficient and difficult to ensure consistency.

[0003] The principle of friction stir welding uses a high-speed rotating stirring needle to contact the workpiece and generate frictional heat, causing local plasticization of the material, and then forming a dense weld under the stirring and extrusion action of the stirring needle. It includes key steps such as inserting the stirring needle into the workpiece, frictional heat generation, plastic deformation of the material, stirring and extrusion to form a weld.

[0004] In a Chinese invention application with publication number CN118123307A, a vision-based adaptive weld seam adjustment method and system are disclosed, comprising an electronic device capturing an image of an object to be welded; the electronic device determining a region of the object to be welded from the image and dividing the region into M sub-regions to be welded, where M is an integer greater than 1; and the electronic device dynamically determining the weld seam width of each of the M sub-regions to be welded based on their respective morphologies. Using the method of the present invention, each sub-region to be welded can be welded to a weld seam width that is appropriate for the region's morphology, ensuring that the weld seam width of each sub-region after welding meets the requirements of the sub-region to be welded, thereby ensuring the reliability and stability of automated welding.

[0005] In the above invention application, each sub-area to be welded is welded with a weld width suitable for the shape of the area. However, for pre-estimation analysis, in the actual welding process, if all sub-areas are preset with a fixed weld width without reserving space for real-time adjustment, when the material thickness fluctuates, the gap error or the heat-affected zone changes, the fixed parameters are likely to lead to defects such as incomplete penetration and undercutting, reducing the structural strength. Sudden problems (such as positioning deviation) require work to be stopped and reworked, and the lack of dynamic adjustment interrupts the welding rhythm and extends the overall construction period. Long-term operation with non-optimal parameters accelerates the wear of the gun tip, and the reduction in current / voltage matching further affects the stability of the weld, forming a vicious cycle. Although this type of pre-planning solution is convenient for initial planning, it sacrifices process flexibility and is difficult to meet the dynamic precision requirements of complex workpieces.

[0006] To this end, the present invention provides a weld tracking and adaptive adjustment device and an adjustment method thereof. Summary of the Invention

[0007] (1) Technical problems solved In view of the shortcomings of the prior art, the present invention provides a weld tracking and adaptive adjustment device and its adjustment method. The present invention obtains the weld temperature anomaly coefficient Wd and the weld size anomaly coefficient , calculate the welding seam abnormality coefficient Yc, and use the PID algorithm to calculate the friction speed adjustment value , comprehensively evaluate welding stability, adjust friction speed in real time, ensure welding stability and weld quality, and improve welding quality and efficiency by comprehensively monitoring and optimizing the welding process, thereby solving the technical problems recorded in the background technology.

[0008] (2) Technical solution To achieve the above objectives, the present invention is implemented through the following technical solutions: a weld seam tracking and adaptive adjustment method, comprising the following steps: Capture weld heat distribution map and obtain the maximum temperature within the weld contour Calculate the maximum temperature fluctuation rate Gb of the weld and obtain the lowest temperature within the weld contour Calculate the weld cooling rate Lq, and calculate the weld temperature anomaly coefficient Wd based on the weld cooling rate Lq and the maximum temperature fluctuation rate Gb; Capture weld shape images, identify the contours of newly added weld areas, and extract the length of newly added welds and new weld width , calculate the new weld aspect ratio , and further calculate the weld size abnormality coefficient ; Obtain weld temperature anomaly coefficient Wd and weld size anomaly coefficient , calculate the welding seam abnormality coefficient Yc, and use the PID algorithm to calculate the friction speed adjustment value .

[0009] Furthermore, an infrared thermal imager is used to capture the weld heat distribution map, and the weld contour in the weld heat distribution map is extracted by combining image processing algorithms (such as edge detection and morphological analysis), and the maximum temperature within the weld contour is recorded. and minimum temperature .

[0010] Furthermore, the maximum temperature within the weld contour is obtained , calculate the maximum temperature fluctuation rate Gb of the weld:

[0011] in, i Indicates the time sequence number of the weld temperature data. i =1, 2, ..., n , n is the total number of weld temperature data.

[0012] Furthermore, the lowest temperature within the weld contour is obtained , calculate the weld cooling rate Lq: .

[0013] Furthermore, the weld cooling rate Lq and the maximum temperature fluctuation rate Gb are obtained, and the weld temperature anomaly coefficient Wd is calculated:

[0014] in, Indicates the standard cooling rate of the weld, Indicates the standard maximum temperature fluctuation rate of the weld.

[0015] Furthermore, a high-speed camera is used to capture weld shape images, and the weld contours in each weld shape image are extracted by combining image processing algorithms. By comparing and analyzing the differences in weld contours before and after, the contours of the newly added weld areas are identified, and the length of the newly added welds is extracted. and new weld width .

[0016] Further, get the length of the newly added weld and new weld width , calculate the new weld aspect ratio :

[0017] Among them, j represents the time sequence number of each weld shape picture, j=2, 3, ..., m , m The total number of weld shape images.

[0018] Furthermore, the aspect ratio of the newly added weld is obtained , calculate the weld size anomaly coefficient :

[0019] in, Indicates the standard weld aspect ratio.

[0020] Furthermore, the weld temperature anomaly coefficient Wd and weld size anomaly coefficient are obtained. , calculate the welding seam abnormality coefficient Yc:

[0021] According to the welding seam abnormal coefficient Yc, the abnormal friction speed V is calculated:

[0022] in, Indicates the minimum friction speed of welding, Indicates the maximum friction speed of welding, which is determined by the performance of the specific welding equipment. Indicates the abnormal coefficient threshold of welding seam.

[0023] Furthermore, the friction speed adjustment value is calculated using the PID algorithm :

[0024] in, is the proportional gain, is the integral gain, is the differential gain.

[0025] A weld tracking and adaptive adjustment device, comprising: Weld temperature analysis module captures weld heat distribution and obtains the maximum temperature within the weld contour Calculate the maximum temperature fluctuation rate Gb of the weld and obtain the lowest temperature within the weld contour Calculate the weld cooling rate Lq, and calculate the weld temperature anomaly coefficient Wd based on the weld cooling rate Lq and the maximum temperature fluctuation rate Gb; Weld shape analysis module captures weld shape images, identifies the contours of newly added weld areas, and extracts the length of newly added welds and new weld width , calculate the new weld aspect ratio , and further calculate the weld size abnormality coefficient ; Adaptive adjustment module to obtain weld temperature anomaly coefficient Wd and weld size anomaly coefficient , calculate the welding seam abnormality coefficient Yc, and use the PID algorithm to calculate the friction speed adjustment value .

[0026] (3) Beneficial effects The present invention provides a weld tracking and adaptive adjustment device and an adjustment method thereof, which have the following beneficial effects: 1. Capture the weld heat distribution map and obtain the highest temperature within the weld contour Calculate the maximum temperature fluctuation rate Gb of the weld and obtain the lowest temperature within the weld contour The weld cooling rate Lq is calculated, and based on the weld cooling rate Lq and the maximum temperature fluctuation rate Gb, the weld temperature anomaly coefficient Wd is calculated to quantify the temperature anomaly in the welding process and provide a basis for adjusting the process parameters. By monitoring these parameters in real time, the welding process can be finely controlled, balancing temperature uniformity and cooling efficiency, and ultimately reducing the welding defect rate.

[0027] 2. Capture the weld shape image, identify the contour of the newly added weld area, and extract the length of the newly added weld and new weld width , calculate the new weld aspect ratio , and further calculate the weld size abnormality coefficient , quantify dimensional deviations, judge weld shape and penetration, avoid welding defects, and provide a basis for parameter adjustment.

[0028] 3. Obtain the weld temperature anomaly coefficient Wd and weld size anomaly coefficient , calculate the welding seam abnormality coefficient Yc, and use the PID algorithm to calculate the friction speed adjustment value , comprehensively evaluate welding stability, adjust friction speed in real time to ensure welding stability and weld quality, and improve welding quality and efficiency by comprehensively monitoring and optimizing the welding process. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 A schematic flow chart of a weld seam tracking and adaptive adjustment method according to the present invention; Figure 2 This is a structural schematic diagram of a weld seam tracking and adaptive adjustment device of the present invention. DETAILED DESCRIPTION

[0030] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0031] See also Figure 1 The present invention provides a weld tracking and adaptive adjustment method, comprising the following steps: Step 1: Capture the weld heat distribution map and obtain the highest temperature within the weld contour Calculate the maximum temperature fluctuation rate Gb of the weld and obtain the lowest temperature within the weld contour Calculate the weld cooling rate Lq, and calculate the weld temperature anomaly coefficient Wd based on the weld cooling rate Lq and the maximum temperature fluctuation rate Gb.

[0032] The step 1 includes the following: Step 101: Use an infrared thermal imager to capture the weld heat distribution map, combine image processing algorithms (such as edge detection and morphological analysis) to extract the weld contour in the weld heat distribution map, and record the highest temperature within the weld contour. and minimum temperature .

[0033] Step 102: Obtain the maximum temperature within the weld contour , calculate the maximum temperature fluctuation rate Gb of the weld:

[0034] in, i Indicates the time sequence number of the weld temperature data. i =1, 2, ..., n , n is the total number of weld temperature data.

[0035] Step 103: Obtain the lowest temperature within the weld contour , calculate the weld cooling rate Lq:

[0036] Step 104: Obtain the weld cooling rate Lq and the maximum temperature fluctuation rate Gb, and calculate the weld temperature anomaly coefficient Wd:

[0037] in, Indicates the standard cooling rate of the weld, Indicates the standard maximum temperature fluctuation rate of the weld.

[0038] When using, combine the contents in steps 101 to 104: Capture weld heat distribution map and obtain the maximum temperature within the weld contour Calculate the maximum temperature fluctuation rate Gb of the weld and obtain the lowest temperature within the weld contour The weld cooling rate Lq is calculated, and based on the weld cooling rate Lq and the maximum temperature fluctuation rate Gb, the weld temperature anomaly coefficient Wd is calculated to quantify the temperature anomaly in the welding process and provide a basis for adjusting the process parameters. By monitoring these parameters in real time, the welding process can be finely controlled, balancing temperature uniformity and cooling efficiency, and ultimately reducing the welding defect rate.

[0039] Step 2: Capture the weld shape image, identify the contour of the newly added weld area, and extract the length of the newly added weld and new weld width , calculate the new weld aspect ratio , and further calculate the weld size abnormality coefficient .

[0040] The second step includes the following: Step 201: Use a high-speed camera to capture weld shape images, combine image processing algorithms (such as edge detection and morphological analysis) to extract the weld contour in each weld shape image, and compare and analyze the difference between the weld contours before and after to identify the contour of the newly added weld area and extract the length of the newly added weld. and new weld width .

[0041] Step 202: Get the length of the newly added weld and new weld width , calculate the new weld aspect ratio :

[0042] Among them, j represents the time sequence number of each weld shape picture, j=2, 3, ..., m , m The total number of weld shape images.

[0043] Step 203: Obtain the aspect ratio of the newly added weld , calculate the weld size anomaly coefficient :

[0044] in, Indicates the standard weld aspect ratio.

[0045] When using, combine the contents in steps 201 to 203: Capture weld shape images, identify the contours of newly added weld areas, and extract the length of newly added welds and new weld width , calculate the new weld aspect ratio , and further calculate the weld size abnormality coefficient , quantify dimensional deviations, judge weld shape and penetration, avoid welding defects, and provide a basis for parameter adjustment.

[0046] Step 3: Obtain the weld temperature anomaly coefficient Wd and weld size anomaly coefficient , calculate the welding seam abnormality coefficient Yc, and use the PID algorithm to calculate the friction speed adjustment value .

[0047] The step three includes the following: Step 301: Obtain the weld temperature anomaly coefficient Wd and the weld size anomaly coefficient , calculate the welding seam abnormality coefficient Yc:

[0048] Step 302: Calculate the abnormal friction speed V based on the weld abnormality coefficient Yc:

[0049] in, Indicates the minimum friction speed of welding, Indicates the maximum friction speed of welding, which is determined by the performance of the specific welding equipment. Indicates the abnormal coefficient threshold of welding seam.

[0050] Step 303: Calculate the friction speed adjustment value using the PID algorithm :

[0051] in, is the proportional gain, is the integral gain, is the differential gain.

[0052] When using, combine the contents in steps 301 to 303: Obtain weld temperature anomaly coefficient Wd and weld size anomaly coefficient , calculate the welding seam abnormality coefficient Yc, and use the PID algorithm to calculate the friction speed adjustment value , comprehensively evaluate welding stability, adjust friction speed in real time to ensure welding stability and weld quality, and improve welding quality and efficiency by comprehensively monitoring and optimizing the welding process.

[0053] See also Figure 2 The present invention provides a weld tracking and adaptive adjustment device, comprising: Weld temperature analysis module captures weld heat distribution and obtains the maximum temperature within the weld contour Calculate the maximum temperature fluctuation rate Gb of the weld and obtain the lowest temperature within the weld contour Calculate the weld cooling rate Lq, and calculate the weld temperature anomaly coefficient Wd based on the weld cooling rate Lq and the maximum temperature fluctuation rate Gb.

[0054] Weld shape analysis module captures weld shape images, identifies the contours of newly added weld areas, and extracts the length of newly added welds and new weld width , calculate the new weld aspect ratio , and further calculate the weld size abnormality coefficient .

[0055] Adaptive adjustment module to obtain weld temperature anomaly coefficient Wd and weld size anomaly coefficient , calculate the welding seam abnormality coefficient Yc, and use the PID algorithm to calculate the friction speed adjustment value .

[0056] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. Those skilled in the art will appreciate that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution.

[0057] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0058] The above is only a specific implementation method of the present application, but the scope of protection of the present application is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed in this application, which should be covered by the scope of protection of the present application.

Claims

1. A weld seam tracking and adaptive adjustment method, characterized by: The steps include: Capture weld heat distribution map and obtain the maximum temperature within the weld contour Calculate the maximum temperature fluctuation rate Gb of the weld and obtain the lowest temperature within the weld contour Calculate the weld cooling rate Lq, and calculate the weld temperature anomaly coefficient Wd based on the weld cooling rate Lq and the maximum temperature fluctuation rate Gb; Capture weld shape images, identify the contours of newly added weld areas, and extract the length of newly added welds and new weld width , calculate the new weld aspect ratio , and further calculate the weld size abnormality coefficient ; Obtain weld temperature anomaly coefficient Wd and weld size anomaly coefficient , calculate the welding seam abnormality coefficient Yc, and use the PID algorithm to calculate the friction speed adjustment value .

2. The weld seam tracking and adaptive adjustment method according to claim 1, characterized in that: Get the maximum temperature within the weld contour , calculate the maximum temperature fluctuation rate Gb of the weld: in, i Indicates the time sequence number of the weld temperature data. i =1, 2, ..., n , n is the total number of weld temperature data.

3. The weld seam tracking and adaptive adjustment method according to claim 1, characterized in that: Get the minimum temperature within the weld contour , calculate the weld cooling rate Lq: 。 4. The weld seam tracking and adaptive adjustment method according to claim 1, characterized in that: Obtain the weld cooling rate Lq and the maximum temperature fluctuation rate Gb, and calculate the weld temperature anomaly coefficient Wd: in, Indicates the standard cooling rate of the weld, Indicates the standard maximum temperature fluctuation rate of the weld.

5. The weld seam tracking and adaptive adjustment method according to claim 1, characterized in that: A high-speed camera is used to capture weld shape images. The weld contours in each weld shape image are extracted using an image processing algorithm. The differences in weld contours before and after are compared and analyzed to identify the contours of the newly added weld area and extract the length of the newly added weld. and new weld width .

6. The weld seam tracking and adaptive adjustment method according to claim 1, characterized in that: Get the length of the newly added weld , Add weld width , calculate the new weld aspect ratio : Among them, j represents the time sequence number of each weld shape picture, j=2, 3, ..., m , m The total number of weld shape images.

7. The weld seam tracking and adaptive adjustment method according to claim 1, characterized in that: Get the aspect ratio of the newly added weld , calculate the weld size anomaly coefficient : in, Indicates the standard weld aspect ratio.

8. The weld seam tracking and adaptive adjustment method according to claim 1, characterized in that: Obtain weld temperature anomaly coefficient Wd and weld size anomaly coefficient , calculate the welding seam abnormality coefficient Yc: According to the welding seam abnormal coefficient Yc, the abnormal friction speed V is calculated: in, Indicates the minimum friction speed of welding, Indicates the maximum friction speed of welding, which is determined by the performance of the specific welding equipment. Indicates the abnormal coefficient threshold of welding seam.

9. The weld seam tracking and adaptive adjustment method according to claim 1, characterized in that: Calculate the friction speed adjustment value using PID algorithm : in, is the proportional gain, is the integral gain, is the differential gain.

10. A weld seam tracking and adaptive adjustment device, characterized in that: include: Weld temperature analysis module captures weld heat distribution and obtains the maximum temperature within the weld contour Calculate the maximum temperature fluctuation rate Gb of the weld and obtain the lowest temperature within the weld contour Calculate the weld cooling rate Lq, and calculate the weld temperature anomaly coefficient Wd based on the weld cooling rate Lq and the maximum temperature fluctuation rate Gb; Weld shape analysis module captures weld shape images, identifies the contours of newly added weld areas, and extracts the length of newly added welds and new weld width , calculate the new weld aspect ratio , and further calculate the weld size abnormality coefficient ; Adaptive adjustment module to obtain weld temperature anomaly coefficient Wd and weld size anomaly coefficient , calculate the welding seam abnormality coefficient Yc, and use the PID algorithm to calculate the friction speed adjustment value .

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