Stainless steel laser welding parameter optimization method based on dynamic ring-shaped scanning path

Abstract

The application discloses a kind of based on dynamic annular scanning path's stainless steel laser welding parameter optimization method, S1.Initialization welding parameter setting is suitable for controlling welding heat distribution;S2.before welding, the material thickness of the welding area of stainless steel workpiece is measured;S3.determine scanning path layer and progressive speed according to welding parameter;S4.welding control system adjusts welding parameter according to temperature monitoring data;S5.laser welding control system carries out real-time adjustment to the layer of dynamic annular scanning path, progressive speed and scanning path radius;S6.optimize scanning amplitude, scanning frequency and welding speed in real time;S7.after welding, weld quality is detected, and detection data is compared with preset welding quality standard.The application realizes the accurate control of welding heat input, the significant improvement of weld quality and the overall optimization of welding efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of stainless steel laser welding, and in particular to a stainless steel laser welding parameter optimization method based on a dynamic annular scanning path. Background Art

[0002] With the development of laser welding technology, stainless steel materials are widely used in industrial manufacturing fields, including aerospace, automobile manufacturing and construction engineering, due to their excellent corrosion resistance and mechanical properties. As an efficient and precise processing technology, stainless steel laser welding has a process quality that directly affects the structural strength and service life of the material. However, the existing stainless steel laser welding process still faces many technical challenges in practical applications, especially in the control of heat-affected zones and the prevention and control of weld defects in high-quality welding.

[0003] Currently, traditional laser welding processes typically utilize fixed scanning paths or simple linear paths. These methods can easily lead to concentrated heat in the weld area when processing heat-sensitive stainless steel, resulting in an excessively large heat-affected zone and significant thermal deformation. Furthermore, due to the lack of dynamic adjustment capabilities for laser power, scanning speed, and focal position parameters, weld defects such as porosity and cracks often occur during stainless steel welding, impacting weld quality consistency and the material's mechanical properties.

[0004] In recent years, although some improved methods have attempted to improve welding effects by optimizing laser parameters and scanning paths, such as adopting a constant circular path or a layered scanning strategy, the existing methods still have obvious shortcomings. On the one hand, the fixed path design cannot adapt to the dynamic changes in the temperature distribution in the welding area in real time, resulting in uneven heat input; on the other hand, the existing methods lack the ability to accurately respond to changes in the thickness of the welding area, which can easily cause insufficient weld strength or local overheating at the junction of thick and thin materials. In addition, traditional processes have weak temperature monitoring and real-time feedback adjustment capabilities during the welding process, and parameter adjustment has a lag, making it difficult to meet the needs of high-quality welding.

[0005] In summary, the existing technology has significant defects in heat control, parameter adjustment, path planning and quality consistency, and cannot fully meet the technical requirements of stainless steel welding for high precision, high efficiency and low defects. There is an urgent need for an optimization method that can dynamically adapt to the characteristics of the welding area to solve the above problems. Summary of the Invention

[0006] One object of the present invention is to propose a stainless steel laser welding parameter optimization method based on a dynamic annular scanning path, which achieves precise control of welding heat input, significant improvement of weld quality and comprehensive optimization of welding efficiency.

[0007] According to the stainless steel laser welding parameter optimization method based on the dynamic ring-shaped scanning path, the following steps are included:

[0008] S1. According to the thickness characteristics of the stainless steel material, set the welding parameters in the laser welding control system, and initialize the welding parameter setting to be suitable for controlling the welding heat distribution;

[0009] S2. Measure the material thickness of the welding area of the stainless steel workpiece before welding, and input the detected material thickness data into the laser welding control system;

[0010] S3. According to the welding parameters, the laser welding control system generates a dynamic ring-shaped scanning path suitable for different thickness areas of the stainless steel according to the detected material thickness data, and determines the scanning path layer number and the progressive speed;

[0011] S4. In the welding process, the temperature distribution of the welding area is monitored in real time, and the temperature monitoring data of the welding area is fed back to the laser welding control system, and the welding control system adjusts the welding parameters according to the temperature monitoring data;

[0012] S5. Based on the real-time temperature monitoring data and thickness detection data, the laser welding control system adjusts the layer number, progressive speed and scanning path radius of the dynamic ring-shaped scanning path in real time;

[0013] S6. On the basis of dynamic adjustment of the path level, the laser welding control system further adjusts the laser power and focal point position according to the temperature distribution of the welding area, and optimizes the scanning amplitude, scanning frequency and welding speed in real time;

[0014] S7. After the welding is completed, the quality of the weld is detected, including the evaluation of the smoothness of the weld, the size of the heat affected zone and the welding strength, and the detection data is compared with the preset welding quality standard.

[0015] Optionally, the S1 specifically includes the following contents:

[0016] S11, according to the thickness characteristics of the stainless steel material, calculate the initial laser power P0:

[0017] P0=k1·t+P min ;

[0018] Wherein, k1 is the power coefficient, which is related to the thermal conductivity and reflectivity of the stainless steel material, t is the measured thickness of the stainless steel material, P min is the minimum initial power value;

[0019] S12, according to the thickness t of the stainless steel material and the laser energy distribution requirement, the initial radius r0 of the dynamic ring-shaped scanning path;

[0020] S13. According to the surface flatness and thickness distribution of the stainless steel material, the focus position f is related to the welding depth h and the path radius r0, and the following relationship is satisfied:

[0021] f=β·h+γ·r0;

[0022] Among them, β is the focus adjustment coefficient, which represents the influence weight of laser focus with welding depth, γ is the influence coefficient of path radius, and h is the target welding depth, which is determined by the material thickness t;

[0023] S14, welding speed v is set according to the initial laser power P0 and focus position f:

[0024]

[0025] Among them, η is the laser energy utilization efficiency coefficient, ρ is the thermal conductivity of the material, which indicates the material's conduction rate of thermal energy;

[0026] S15. Input the calculated initial laser power, scanning path radius, laser focus position and welding speed v into the laser welding control system as welding parameter initialization settings.

[0027] Optionally, S2 specifically includes the following contents:

[0028] S21, measuring the material thickness t(x, y) of the welding area of ​​the stainless steel workpiece in real time using a non-contact measuring device, where x, y are the two-dimensional coordinates of the welding area;

[0029] S22. Smoothly interpolate the obtained material thickness t(x, y) in the welding area D, convert the discrete measurement value into a continuous distribution value t'(x, y) by double integration, and generate a thickness distribution map:

[0030]

[0031] Among them, λ2 is the interpolation smoothing parameter, which is used to smooth the thickness data according to the welding requirements of stainless steel materials, and t(u,v) is the thickness value at the coordinate point (u,v);

[0032] S23, inputting the data of the thickness distribution map into the laser welding control system to generate a thickness matrix T = {t′(x, y)}, where each element of the matrix corresponds to the thickness of a point in the welding area;

[0033] S24, perform partition calculation on the thickness matrix T to determine the thickness-thin zone boundary threshold t c , the threshold value of the thick and thin areas t c Dynamic adjustment to changes in thickness distribution and local inhomogeneities:

[0034]

[0035] in, is the average thickness value of the thickness matrix T, t′ i is the thickness value of the i-th thickness point after interpolation, w i is the weight, n is the total number of points after interpolation;

[0036] Θ i is the thickness distribution complexity factor, which is calculated by the local change of the thickness distribution graph t'(x,y):

[0037]

[0038] in, and At thickness point t′ i The partial derivative of the thickness distribution diagram t'(x,y) with respect to x and y at the location, λ is the thickness change sensitivity coefficient;

[0039] S25, based on the calculated thickness-thinness threshold t c , t′(x,y)>t c The area is defined as the thick area, and t′(x,y)≤t c The area is defined as the thin area.

[0040] Optionally, S3 specifically includes the following contents:

[0041] S31, define the number of layers N of the dynamic annular scanning path at each coordinate point (x, y) L (x,y) and the progressive speed v r (x, y), the number of layers indicates the number of times the circular scanning path is superimposed at that point, and the progressive speed indicates the speed at which the circular path radius expands between layers. For thick stainless steel areas, the number of layers is increased to encrypt the path, while for thin material areas, the number of layers is reduced and the progressive speed is increased;

[0042] S33, define the number of layers N of the dynamic annular scanning path L (x, y) and the functional relationship of the thickness distribution t'(x, y), when t'(x, y)>t c hour:

[0043] N L (x,y)=N0+α·[t′(x,y)-t c ];

[0044] When t′(x,y)≤t c hour:

[0045] N L (x,y)=max{N min ,N0-α′·[tc -t′(x,y)]};

[0046] Among them, N0 is the reference layer number, which is related to the setting value of the initial laser power P0 and the initial radius r0 of the scanning path. min is the minimum layer value, which is used to avoid insufficient energy due to excessive reduction of the number of layers. α and α′ are the layer adjustment coefficients, which represent the rate of increase and decrease of the number of layers with thickness difference.

[0047] S34, defining the progressive speed v of the dynamic annular scanning path r The functional relationship between (x, y) and thickness distribution t'(x, y), with the initial welding speed v as the reference value, when t'(x, y)>t c hour:

[0048]

[0049] When t′(x,y)≤t c hour:

[0050]

[0051] Among them, μ and μ′ are the progressive speed adjustment coefficients, which are used to dynamically adjust the annular expansion speed according to the thickness deviation of the thick and thin areas. In the thick area, the progressive speed is reduced to fully deposit the laser energy in the local area, and in the thin area, the progressive speed is increased to reduce local overheating.

[0052] S35, distribute the calculated number of layers N L (x,y) and the progressive speed v r (x,y) is input into the laser welding control system. According to steps S1-S2 and thickness distribution information, a dynamic circular scanning path that meets the requirements of different thickness areas of stainless steel is generated. The thick material area is scanned in an encrypted layer and the expansion speed of the thin material area is increased.

[0053] Optionally, S5 specifically includes the following contents:

[0054] S51, obtaining real-time temperature monitoring data T(x, y, t) and thickness detection data t'(x, y) during the welding process;

[0055] S52. Calculate the local heat input deviation ΔH(x,y,t) of each welding point in real time based on the temperature distribution T(x,y,t) and thickness data t'(x,y):

[0056]

[0057] in, k is the instantaneous rate of change of the temperature of the welding point (x, y) with time, tis the thermal conductivity coefficient, which indicates the effect of thickness on heat diffusion, and τ is the time variable;

[0058] S53, adjusting the number of layers N of the dynamic annular scanning path in real time according to the calculated heat input deviation ΔH(x, y, t) L (x,y,t):

[0059] N L (x,y,t)=N L (x,y)+γ1·ΔH(x,y,t);

[0060] Among them, γ1 is the path layer response coefficient, which represents the sensitivity of the layer number to the heat input deviation;

[0061] S54, adjust the scanning path radius progressive speed v in real time according to the heat input deviation ΔH(x,y,t) and thickness data t'(x,y) r (x,y,t):

[0062]

[0063] Among them, δ1 is the progressive speed response coefficient, H ref is the reference heat input value;

[0064] S55, real-time update of the layer number distribution N of the dynamic annular scanning path L (x,y,t), progressive speed v r (x, y, t) and path radius r(x, y, t), and the adjusted parameters are input into the laser welding control system to dynamically adjust the layer distribution density and path expansion speed of the welding path, increase the path density in the thick material area to uniformly heat, and reduce the path density in the thin material area to reduce heat input, so as to achieve real-time balance between temperature and heat distribution in the welding area.

[0065] Optionally, S6 specifically includes the following contents:

[0066] S61. Based on the heat input deviation and temperature distribution data after dynamic adjustment of the path level, the laser welding control system adjusts the laser power in real time, increasing the laser power in the thick material area and reducing the laser power in the thin material area;

[0067] S62. Dynamically adjust the laser focus position based on real-time temperature change trends and thickness data to adapt it to the depth requirements of the welding area. In thick material areas, the focus position is adjusted toward the interior of the material to enhance deep heat input. In thin material areas, the focus position is adjusted toward the surface to reduce thermal impact.

[0068] S63. Optimize the scanning amplitude based on the adjustment of laser power and focus position to match the laser coverage in the welding area with the energy requirement. For thick material areas, expand the scanning amplitude to evenly distribute the heat; for thin material areas, reduce the scanning amplitude to control the heat input.

[0069] S64, real-time optimization of the scanning frequency, increase or decrease the speed and frequency of the laser scanning according to the temperature distribution of the welding area, increase the scanning frequency to speed up the welding speed and reduce the heat dwell time in the thin material area, and reduce the scanning frequency to extend the heat deposition time in the thick material area;

[0070] S65, dynamically adjust the welding speed to match the temperature and thickness changes in the welding area, slow down the welding speed in thick material areas to enhance the deposition effect of laser energy, and increase the welding speed in thin material areas to reduce local heat accumulation;

[0071] S66. Input the adjusted laser power, focus position, scanning amplitude, scanning frequency and welding speed data into the laser welding control system in real time. By controlling various parameters, efficient heat input and uniform heating are achieved in thick material areas, and energy distribution and temperature control are achieved in thin material areas, so that the overall temperature balance of the welding area and the consistency of weld quality are achieved.

[0072] The beneficial effects of the present invention are:

[0073] (1) The present invention introduces a real-time adjustment mechanism for the number of layers, progressive speed, and path radius in the dynamic annular scanning path, thereby achieving fine control of heat input according to the thickness distribution and temperature changes in the welding area. In terms of algorithm design, the present invention utilizes the real-time monitored thickness matrix and temperature distribution data to dynamically optimize the number of layers and expansion speed of the scanning path, thereby avoiding the problem of uneven heat distribution caused by fixed paths in traditional welding. In thick material areas, the local heat deposition efficiency is improved by increasing the number of path layers and slowing down the expansion speed. In thin material areas, the number of path layers is reduced and the expansion speed is increased, thereby effectively reducing the risk of welding defects caused by excessive heat input.

[0074] (2) The present invention proposes an intelligent optimization algorithm for laser power and focal position based on real-time temperature and thickness feedback data. In thick material areas, the laser power and focal position are dynamically adjusted to enhance welding depth and heat input stability. In thin material areas, local overheating and the generation of weld defects are avoided by reducing laser power, adjusting the focal position and optimizing the scanning amplitude. Compared with the traditional method of using fixed laser parameters, the dynamic adjustment mechanism of the present invention effectively reduces the occurrence of welding defects such as pores and cracks, and significantly improves the mechanical strength and surface finish of the weld.

[0075] (3) The present invention optimizes the laser scanning frequency and welding speed in real time for different thickness areas by combining dynamic scanning path adjustment and parameter adaptive optimization algorithm to ensure that the energy distribution and welding efficiency are optimally balanced. The scanning frequency is reduced in the thick material area and the welding speed is appropriately reduced to achieve deep heating. The scanning frequency is increased and the welding speed is accelerated in the thin material area to avoid heat accumulation. The fixed setting of parameters in traditional welding technology often leads to a loss of efficiency and quality. The multi-parameter optimization mechanism of the present invention not only improves the welding efficiency, but also significantly expands the adaptability of the technology, and can meet the high-quality welding requirements of complex-shaped and multi-thickness stainless steel workpieces. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0077] Figure 1 This is a flow chart of a stainless steel laser welding parameter optimization method based on a dynamic annular scanning path proposed by the present invention. DETAILED DESCRIPTION

[0078] The present invention will now be described in further detail with reference to the accompanying drawings, which are simplified schematic diagrams that illustrate the basic structure of the present invention in a schematic manner.

[0079] refer to Figure 1 , a stainless steel laser welding parameter optimization method based on a dynamic annular scanning path, comprising the following steps:

[0080] S1. Set welding parameters in the laser welding control system according to the thickness characteristics of the stainless steel material, and initialize the welding parameter settings to control the welding heat distribution;

[0081] S2. Measure the material thickness of the stainless steel workpiece welding area before welding and input the material thickness data obtained from the test into the laser welding control system;

[0082] S3. Based on the welding parameters, the laser welding control system generates a dynamic circular scanning path adapted to different thickness areas of stainless steel according to the detected material thickness data, and determines the number of layers and progressive speed of the scanning path;

[0083] S4. During the welding process, the temperature distribution of the welding area is monitored in real time, and the temperature monitoring data of the welding area is fed back to the laser welding control system. The welding control system adjusts the welding parameters according to the temperature monitoring data;

[0084] S5. Based on real-time temperature monitoring data and thickness detection data, the laser welding control system adjusts the number of layers, progressive speed, and scanning path radius of the dynamic circular scanning path in real time;

[0085] S6. Based on the dynamic adjustment of the path level, the laser welding control system further adjusts the laser power and focus position according to the temperature distribution in the welding area, and optimizes the scanning amplitude, scanning frequency, and welding speed in real time;

[0086] S7. After welding is completed, the weld quality shall be inspected, including the evaluation of the weld finish, the size of the heat-affected zone, and the weld strength, and the inspection data shall be compared with the preset welding quality standards.

[0087] In this embodiment, S1 specifically includes the following contents:

[0088] S11. Calculate the initial laser power P0 based on the thickness characteristics of the stainless steel material:

[0089] P0=k1·t+P min ;

[0090] Where k1 is the power coefficient, which is related to the thermal conductivity and reflectivity of the stainless steel material, t is the measured thickness of the stainless steel material, P min is the minimum initial power value;

[0091] S12, the initial radius r0 of the dynamic annular scanning path according to the thickness t of the stainless steel material and the laser energy distribution requirements;

[0092] S13. According to the surface flatness and thickness distribution of the stainless steel material, the focus position f is related to the welding depth h and the path radius r0, and the following relationship is satisfied:

[0093] f=β·h+γ·r0;

[0094] Among them, β is the focus adjustment coefficient, which represents the influence weight of laser focus with welding depth, γ is the influence coefficient of path radius, and h is the target welding depth, which is determined by the material thickness t;

[0095] S14, welding speed v is set according to the initial laser power P0 and focus position f:

[0096]

[0097] Among them, η is the laser energy utilization efficiency coefficient, ρ is the thermal conductivity of the material, which indicates the material's conduction rate of thermal energy;

[0098] S15. Input the calculated initial laser power, scanning path radius, laser focus position and welding speed v into the laser welding control system as welding parameter initialization settings.

[0099] In this embodiment, S2 specifically includes the following contents:

[0100] S21, measuring the material thickness t(x, y) of the welding area of ​​the stainless steel workpiece in real time using a non-contact measuring device, where x, y are the two-dimensional coordinates of the welding area;

[0101] S22. Smoothly interpolate the obtained material thickness t(x, y) in the welding area D, convert the discrete measurement value into a continuous distribution value t'(x, y) by double integration, and generate a thickness distribution map:

[0102]

[0103] Among them, λ2 is the interpolation smoothing parameter, which is used to smooth the thickness data according to the welding requirements of stainless steel materials, and t(u,v) is the thickness value at the coordinate point (u,v);

[0104] S23, inputting the data of the thickness distribution map into the laser welding control system to generate a thickness matrix T = {t′(x, y)}, where each element of the matrix corresponds to the thickness of a point in the welding area;

[0105] S24, perform partition calculation on the thickness matrix T to determine the thickness-thin zone boundary threshold t c , the threshold value of the thick and thin areas t c Dynamic adjustment to changes in thickness distribution and local inhomogeneities:

[0106]

[0107] in, is the average thickness value of the thickness matrix T, t′ i is the thickness value of the i-th thickness point after interpolation, w i is the weight, n is the total number of points after interpolation;

[0108] Θ i is the thickness distribution complexity factor, which is calculated by the local change of the thickness distribution graph t'(x,y):

[0109]

[0110] in, and At thickness point t′ i The partial derivative of the thickness distribution diagram t'(x,y) with respect to x and y at the location, λ is the thickness change sensitivity coefficient;

[0111] S25, based on the calculated thickness-thinness threshold t c , t′(x,y)>tc The region where t'(x, y) > t is defined as a thick region, and the region where t'(x, y) < t is defined as a thin region. c The region where t'(x, y) > t is defined as a thick region, and the region where t'(x, y) < t is defined as a thin region.

[0112] In this embodiment, S3 specifically includes the following contents:

[0113] S31, defining the number of layers N of the dynamic circular scanning path at each coordinate point (x, y) L (x, y) and the progressive speed v r (x, y), the number of layers represents the number of superpositions of the circular scanning path at the point, and the progressive speed represents the speed of the radius of the circular path when expanding between layers, the number of layers is increased for the thick material region of the stainless steel to encrypt the path, and the number of layers is reduced and the progressive speed is increased for the thin material region;

[0114] S33, defining the number of layers N of the dynamic circular scanning path L (x, y) and the thickness distribution t'(x, y), when t'(x, y) > t c :

[0115] N L (x, y) = N0+ a · [t'(x, y) - t c ];

[0116] When t'(x, y) < t c :

[0117] N L (x, y) = max{N min , N0- a' · [t c - t'(x, y)]};

[0118] Wherein, N0 is the reference number of layers, which is related to the set values of the initial laser power P0 and the initial radius r0 of the scanning path, N min is the minimum number of layers, which is used to avoid insufficient energy caused by excessive reduction of the number of layers, and a and a' are the number of layer adjustment coefficients, which represent the increasing and decreasing rates of the number of layers with the thickness difference;

[0119] S34, defining the progressive speed v r (x, y) of the dynamic circular scanning path, which is a function of the thickness distribution t'(x, y) and takes the initial welding speed v as a reference value, when t'(x, y) > t c :

[0120]

[0121] When t'(x, y) < t c :

[0122]

[0123] Among them, μ and μ′ are the progressive speed adjustment coefficients, which are used to dynamically adjust the annular expansion speed according to the thickness deviation of the thick and thin areas. In the thick area, the progressive speed is reduced to fully deposit the laser energy in the local area, and in the thin area, the progressive speed is increased to reduce local overheating.

[0124] S35, distribute the calculated number of layers N L (x,y) and the progressive speed v r (x,y) is input into the laser welding control system. According to steps S1-S2 and thickness distribution information, a dynamic circular scanning path that meets the requirements of different thickness areas of stainless steel is generated. The thick material area is scanned in an encrypted layer and the expansion speed of the thin material area is increased.

[0125] In this embodiment, S5 specifically includes the following contents:

[0126] S51, obtaining real-time temperature monitoring data T(x, y, t) and thickness detection data t'(x, y) during the welding process;

[0127] S52. Calculate the local heat input deviation ΔH(x,y,t) of each welding point in real time based on the temperature distribution T(x,y,t) and thickness data t'(x,y):

[0128]

[0129] in, k is the instantaneous rate of change of the temperature of the welding point (x, y) with time, t is the thermal conductivity coefficient, which indicates the effect of thickness on heat diffusion, and τ is the time variable;

[0130] S53, adjusting the number of layers N of the dynamic annular scanning path in real time according to the calculated heat input deviation ΔH(x, y, t) L (x,y,t):

[0131] N L (x,y,t)=N L (x,y)+γ1·ΔH(x,y,t);

[0132] Among them, γ1 is the path layer response coefficient, which represents the sensitivity of the layer number to the heat input deviation;

[0133] S54, adjust the scanning path radius progressive speed v in real time according to the heat input deviation ΔH(x,y,t) and thickness data t'(x,y) r (x,y,t):

[0134]

[0135] Among them, δ1 is the progressive speed response coefficient, Href is the reference heat input value;

[0136] S55, real-time update of the layer number distribution N of the dynamic annular scanning path L (x,y,t), progressive speed v r (x, y, t) and path radius r(x, y, t), and the adjusted parameters are input into the laser welding control system to dynamically adjust the layer distribution density and path expansion speed of the welding path, increase the path density in the thick material area to uniformly heat, and reduce the path density in the thin material area to reduce heat input, so as to achieve real-time balance between temperature and heat distribution in the welding area.

[0137] In this embodiment, S6 specifically includes the following contents:

[0138] S61. Based on the heat input deviation and temperature distribution data after dynamic adjustment of the path level, the laser welding control system adjusts the laser power in real time, increasing the laser power in the thick material area and reducing the laser power in the thin material area;

[0139] S62. Dynamically adjust the laser focus position based on real-time temperature change trends and thickness data to adapt it to the depth requirements of the welding area. In thick material areas, the focus position is adjusted toward the interior of the material to enhance deep heat input. In thin material areas, the focus position is adjusted toward the surface to reduce thermal impact.

[0140] S63. Optimize the scanning amplitude based on the adjustment of laser power and focus position to match the laser coverage in the welding area with the energy requirement. For thick material areas, expand the scanning amplitude to evenly distribute the heat; for thin material areas, reduce the scanning amplitude to control the heat input.

[0141] S64, real-time optimization of the scanning frequency, increase or decrease the speed and frequency of the laser scanning according to the temperature distribution of the welding area, increase the scanning frequency to speed up the welding speed and reduce the heat dwell time in the thin material area, and reduce the scanning frequency to extend the heat deposition time in the thick material area;

[0142] S65, dynamically adjust the welding speed to match the temperature and thickness changes in the welding area, slow down the welding speed in thick material areas to enhance the deposition effect of laser energy, and increase the welding speed in thin material areas to reduce local heat accumulation;

[0143] S66. Input the adjusted laser power, focus position, scanning amplitude, scanning frequency and welding speed data into the laser welding control system in real time. By controlling various parameters, efficient heat input and uniform heating are achieved in thick material areas, and energy distribution and temperature control are achieved in thin material areas, so that the overall temperature balance of the welding area and the consistency of weld quality are achieved.

[0144] Example 1:

[0145] Example: In a certain aviation manufacturing company, an aviation manufacturing company received a batch production order and needed to complete the welding tasks of a batch of complex-shaped stainless steel parts. The welding requirements of the parts were strict, and they needed to achieve high strength, low defect rate, and meet the aviation industry's stringent standards for thermal deformation control and weld finish. Due to the complex shape of the parts, the welding area included both thick material areas (3 mm thick) and thin material areas (1.5 mm thick). Traditional laser welding methods often face problems such as uneven heat distribution, many weld defects, and a large heat-affected zone in this scenario.

[0146] The welding task involves the splicing of complex curved parts with a total weld length of 1.5 meters, including inflection points with large curvature and the interface between thick and thin materials. The weld strength must reach more than 95% of the parent material strength, and the weld surface finish must be controlled within 1μm. At the same time, the width of the heat-affected zone cannot exceed 2.5 mm to avoid deformation of the workpiece due to heat diffusion. The production task is arranged in the company's high-precision laser welding workshop. The equipment includes a fiber laser welder equipped with a temperature monitoring system and thickness detection equipment. Before welding begins, the technical team conducts a comprehensive inspection and data modeling of the welding area.

[0147] The thickness detection equipment first completed the scan of the welding area and detected that the thickness of the main weld area was 3 mm, while the thickness of the connecting plate gradually transitioned from 1.5 mm to 3 mm. The detection data generated a thickness matrix, the main weld area was marked as a thick material area, and the connecting plate transition area was divided into a thin material area. The technical team input the detection data into the laser welding control system, and the system generated the initial parameters of the dynamic annular scanning path. According to the algorithm calculation results, the number of path layers in the main weld area was set to 6, and the progressive speed was 0.8 mm / s; the number of path layers in the thin material area was 3, and the progressive speed was 1.5 mm / s.

[0148] The system also sets the initial values ​​of laser power and focal position. The laser power in the main weld area is set to 1200 watts, and the focal position is adjusted to 0.2 mm inside the material. The laser power in the thin material area is set to 1000 watts, and the focal position is adjusted to 0.1 mm from the material surface. The parameters will be dynamically adjusted according to temperature changes and heat input feedback during the real-time welding process.

[0149] Welding officially begins, and the temperature monitoring equipment records the temperature changes in the welding area in real time. The temperature in the initial area quickly rises to 600°C. The laser power in the main weld area is gradually increased from 1200 watts to 1400 watts to improve heat deposition. Due to the thinning of the connection area, the laser power is adjusted to 800 watts to avoid overheating. At the same time, the scanning frequency and welding speed are dynamically adjusted with temperature changes. In the main weld area, the scanning frequency is maintained at 200 Hz and the welding speed is 3 mm / s. In the connection area, the scanning frequency is increased to 300 Hz and the welding speed is increased to 5 mm / s, which significantly reduces the heat input in the thin material area.

[0150] When welding to the inflection point of the curve, the system detected an abnormal temperature rise (over 800°C). The control system immediately adjusted the number of path layers from the original 3 layers to 2 layers, while further increasing the progressive speed to 2 mm / s. The laser power was also reduced to 700 watts, and the focus position was adjusted to 0.05 mm from the surface. Through this series of dynamic adjustments, heat accumulation in the inflection point area was successfully avoided, maintaining the consistency of weld quality and shape. The welding task was completed in a total of 45 minutes. There were no obvious pores or cracks on the weld surface, and the welding quality was good.

[0151] After welding is completed, the technical team conducts a comprehensive inspection of the workpiece, evaluating the weld strength, surface finish, heat-affected zone width and defect rate, and comparing them with traditional welding methods.

[0152] In terms of weld strength, the weld strength of the method of the present invention reaches 98% of the parent material strength, which is much higher than the 84% of the traditional method. The realization of high-strength welds is due to the multi-level heat input optimization and parameter adaptive adjustment of the dynamic annular scanning path. In terms of surface finish, the test results of the weld surface finish show that the method of the present invention controls the surface roughness within 0.9μm, meeting the aviation grade standard, while the surface roughness of the traditional method is 2.1μm, with a significant difference. In terms of heat-affected zone and workpiece deformation, the width of the heat-affected zone is controlled at 2.0 mm, which is 52% less than that of the traditional method, and the workpiece deformation is reduced to 0.5 mm. This shows that the method of the present invention has obvious advantages in controlling welding heat input and reducing thermal effects. In terms of welding efficiency and defect rate, the method of the present invention has improved welding efficiency by 30%, and the weld defect rate has been reduced to 2%, mainly because the dynamic adjustment mechanism effectively avoids the generation of pores and cracks.

[0153] Through practical application, the method of this invention has successfully solved the problems of large heat-affected zones, numerous weld defects, and uneven weld quality in complex welding tasks, significantly improving welding quality and efficiency. Compared with traditional methods, this method demonstrates excellent adaptability and technical advantages in the demanding scenarios of aviation manufacturing.

[0154] The present invention introduces a real-time adjustment mechanism for the number of layers, progressive speed and path radius in the dynamic annular scanning path, thereby achieving fine control of heat input according to the thickness distribution and temperature changes in the welding area. In terms of algorithm design, the present invention utilizes real-time monitored thickness matrix and temperature distribution data to dynamically optimize the number of layers and expansion speed of the scanning path, thereby avoiding the problem of uneven heat distribution caused by fixed path in traditional welding. In thick material areas, the local heat deposition efficiency is improved by increasing the number of path layers and slowing down the expansion speed. In thin material areas, the number of path layers is reduced and the expansion speed is increased, thereby effectively reducing the risk of welding defects caused by excessive heat input.

[0155] The present invention proposes an intelligent optimization algorithm for laser power and focal position based on real-time temperature and thickness feedback data. In thick material areas, the laser power and focal position are dynamically adjusted to enhance welding depth and heat input stability. In thin material areas, local overheating and the generation of weld defects are avoided by reducing laser power, adjusting the focal position and optimizing the scanning amplitude. Compared with the traditional method of using fixed laser parameters, the dynamic adjustment mechanism of the present invention effectively reduces the occurrence of welding defects such as pores and cracks, and significantly improves the mechanical strength and surface finish of the weld.

[0156] The present invention optimizes the laser scanning frequency and welding speed in real time for different thickness areas by combining dynamic scanning path adjustment and parameter adaptive optimization algorithm to ensure the best balance between energy distribution and welding efficiency. The scanning frequency is reduced in thick material areas and the welding speed is appropriately reduced to achieve deep heating. The scanning frequency is increased and the welding speed is accelerated in thin material areas to avoid heat accumulation. The fixed setting of parameters in traditional welding technology often leads to a loss of efficiency and quality. The multi-parameter optimization mechanism of the present invention not only improves welding efficiency, but also significantly expands the adaptability of the technology, and can meet the high-quality welding requirements of complex-shaped and multi-thickness stainless steel workpieces.

[0157] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solution and inventive concept of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. A stainless steel laser welding parameter optimization method based on a dynamic annular scanning path, characterized in that: The steps include: S1. Set welding parameters in the laser welding control system according to the thickness characteristics of the stainless steel material, and initialize the welding parameter settings to control the welding heat distribution; S2. Measure the material thickness of the stainless steel workpiece welding area before welding and input the material thickness data obtained from the test into the laser welding control system; S3. Based on the welding parameters, the laser welding control system generates a dynamic circular scanning path adapted to different thickness areas of stainless steel according to the detected material thickness data, and determines the number of layers and progressive speed of the scanning path; S4. During the welding process, the temperature distribution of the welding area is monitored in real time, and the temperature monitoring data of the welding area is fed back to the laser welding control system. The welding control system adjusts the welding parameters according to the temperature monitoring data; S5. Based on real-time temperature monitoring data and thickness detection data, the laser welding control system adjusts the number of layers, progressive speed, and scanning path radius of the dynamic circular scanning path in real time; S6. Based on the dynamic adjustment of the path level, the laser welding control system further adjusts the laser power and focus position according to the temperature distribution in the welding area, and optimizes the scanning amplitude, scanning frequency, and welding speed in real time; S7. After welding is completed, the weld quality shall be inspected, including the evaluation of the weld finish, the size of the heat-affected zone, and the weld strength, and the inspection data shall be compared with the preset welding quality standards.

2. The stainless steel laser welding parameter optimization method based on dynamic annular scanning path according to claim 1 is characterized in that: The S1 specifically includes the following contents: S11. Calculate the initial laser power P0 based on the thickness characteristics of the stainless steel material: P0=k1·t+P min ; Where k1 is the power coefficient, which is related to the thermal conductivity and reflectivity of the stainless steel material, t is the measured thickness of the stainless steel material, P min is the minimum initial power value; S12, the initial radius r0 of the dynamic annular scanning path according to the thickness t of the stainless steel material and the laser energy distribution requirements; S13. According to the surface flatness and thickness distribution of the stainless steel material, the focus position f is related to the welding depth h and the path radius r0, and the following relationship is satisfied: f=β·h+γ·r0; Among them, β is the focus adjustment coefficient, which represents the influence weight of laser focus with welding depth, γ is the influence coefficient of path radius, and h is the target welding depth, which is determined by the material thickness t; S14, welding speed v is set according to the initial laser power P0 and focus position f: Among them, η is the laser energy utilization efficiency coefficient, ρ is the thermal conductivity of the material, which indicates the material's conduction rate of thermal energy; S15. Input the calculated initial laser power, scanning path radius, laser focus position and welding speed v into the laser welding control system as welding parameter initialization settings.

3. The stainless steel laser welding parameter optimization method based on dynamic annular scanning path according to claim 1 is characterized in that: The S2 specifically includes the following contents: S21, measuring the material thickness t(x, y) of the welding area of ​​the stainless steel workpiece in real time using a non-contact measuring device, where x, y are the two-dimensional coordinates of the welding area; S22. Smoothly interpolate the obtained material thickness t(x, y) in the welding area D, convert the discrete measurement value into a continuous distribution value t'(x, y) by double integration, and generate a thickness distribution map: Among them, λ2 is the interpolation smoothing parameter, which is used to smooth the thickness data according to the welding requirements of stainless steel materials, and t(u,v) is the thickness value at the coordinate point (u,v); S23, inputting the data of the thickness distribution map into the laser welding control system to generate a thickness matrix T = {t′(x,y)}, where each element of the matrix corresponds to the thickness of a point in the welding area; S24, perform partition calculation on the thickness matrix T to determine the thickness-thin zone boundary threshold t c , the threshold value of the thick and thin areas t c Dynamic adjustment to changes in thickness distribution and local inhomogeneities: in, is the average thickness value of the thickness matrix T, t′ i is the thickness value of the i-th thickness point after interpolation, w i is the weight, n is the total number of points after interpolation; Θ i is the thickness distribution complexity factor, which is calculated by the local change of the thickness distribution graph t'(x,y): in, and At thickness point t′ i The partial derivative of the thickness distribution diagram t′(x,y) with respect to x and y at the location, λ is the thickness change sensitivity coefficient; S25, based on the calculated thickness-thinness threshold t c , t′(x,y)>t c The area is defined as the thick area, and t′(x,y)≤t c The area is defined as the thin area.

4. The stainless steel laser welding parameter optimization method based on dynamic annular scanning path according to claim 1, characterized in that: The S3 specifically includes the following contents: S31, define the number of layers N of the dynamic annular scanning path at each coordinate point (x, y) L (x,y) and the progressive speed v r (x, y), the number of layers indicates the number of times the circular scanning path is superimposed at that point, and the progressive speed indicates the speed at which the circular path radius expands between layers. For thick stainless steel areas, the number of layers is increased to encrypt the path, while for thin material areas, the number of layers is reduced and the progressive speed is increased; S33, define the number of layers N of the dynamic annular scanning path L (x, y) and the functional relationship of the thickness distribution t'(x, y), when t'(x, y)>t c hour: N L (x,y)=N0+α·[t′(x,y)-t c ]; When t′(x,y)≤t c hour: N L (x,y)=max{N min ,N0-α′·[t c -t′(x,y)]}; Among them, N0 is the reference layer number, which is related to the setting value of the initial laser power P0 and the initial radius r0 of the scanning path. min is the minimum layer value, which is used to avoid insufficient energy due to excessive reduction of the number of layers. α and α′ are the layer adjustment coefficients, which represent the rate of increase and decrease of the number of layers with thickness difference. S34, defining the progressive speed v of the dynamic annular scanning path r The functional relationship between (x, y) and thickness distribution t'(x, y), with the initial welding speed v as the reference value, when t'(x, y)>t c hour: When t′(x,y)≤t c hour: Among them, μ and μ′ are the progressive speed adjustment coefficients, which are used to dynamically adjust the annular expansion speed according to the thickness deviation of the thick and thin areas. In the thick area, the progressive speed is reduced to fully deposit the laser energy in the local area, and in the thin area, the progressive speed is increased to reduce local overheating. S35, distribute the calculated number of layers N L (x,y) and the progressive speed v r (x,y) is input into the laser welding control system. According to steps S1-S2 and thickness distribution information, a dynamic circular scanning path that meets the requirements of different thickness areas of stainless steel is generated. The thick material area is scanned in an encrypted layer and the expansion speed of the thin material area is increased.

5. The stainless steel laser welding parameter optimization method based on dynamic annular scanning path according to claim 1 is characterized in that: The S5 specifically includes the following contents: S51, obtaining real-time temperature monitoring data T(x, y, t) and thickness detection data t'(x, y) during the welding process; S52. Calculate the local heat input deviation ΔH(x,y,t) of each welding point in real time based on the temperature distribution T(x,y,t) and thickness data t'(x,y): in, k is the instantaneous rate of change of the temperature of the welding point (x, y) with time, t is the thermal conductivity coefficient, which indicates the effect of thickness on heat diffusion, and τ is the time variable; S53, adjusting the number of layers N of the dynamic annular scanning path in real time according to the calculated heat input deviation ΔH(x, y, t) L (x,y,t): N L (x,y,t)=N L (x,y)+γ1·ΔH(x,y,t); Among them, γ1 is the path layer response coefficient, which represents the sensitivity of the layer number to the heat input deviation; S54, adjust the scanning path radius progressive speed v in real time according to the heat input deviation ΔH(x,y,t) and thickness data t'(x,y) r (x,y,t): Among them, δ1 is the progressive speed response coefficient, H ref is the reference heat input value; S55, real-time update of the layer number distribution N of the dynamic annular scanning path L (x,y,t), progressive speed v r (x, y, t) and path radius r(x, y, t), and the adjusted parameters are input into the laser welding control system to dynamically adjust the layer distribution density and path expansion speed of the welding path, increase the path density in the thick material area to uniformly heat, and reduce the path density in the thin material area to reduce heat input, so as to achieve real-time balance between temperature and heat distribution in the welding area.

6. The stainless steel laser welding parameter optimization method based on dynamic annular scanning path according to claim 1 is characterized in that: The S6 specifically includes the following contents: S61. Based on the heat input deviation and temperature distribution data after dynamic adjustment of the path level, the laser welding control system adjusts the laser power in real time, increasing the laser power in the thick material area and reducing the laser power in the thin material area; S62. Dynamically adjust the laser focus position based on real-time temperature change trends and thickness data to adapt it to the depth requirements of the welding area. In thick material areas, the focus position is adjusted toward the interior of the material to enhance deep heat input. In thin material areas, the focus position is adjusted toward the surface to reduce thermal impact. S63. Optimize the scanning amplitude based on the adjustment of laser power and focus position to match the laser coverage in the welding area with the energy requirement. For thick material areas, expand the scanning amplitude to evenly distribute the heat; for thin material areas, reduce the scanning amplitude to control the heat input. S64, real-time optimization of the scanning frequency, increase or decrease the speed and frequency of the laser scanning according to the temperature distribution of the welding area, increase the scanning frequency to speed up the welding speed and reduce the heat dwell time in the thin material area, and reduce the scanning frequency to extend the heat deposition time in the thick material area; S65, dynamically adjust the welding speed to match the temperature and thickness changes in the welding area, slow down the welding speed in thick material areas to enhance the deposition effect of laser energy, and increase the welding speed in thin material areas to reduce local heat accumulation; S66. Input the adjusted laser power, focus position, scanning amplitude, scanning frequency and welding speed data into the laser welding control system in real time. By controlling various parameters, efficient heat input and uniform heating are achieved in thick material areas, and energy distribution and temperature control are achieved in thin material areas, so that the overall temperature balance of the welding area and the consistency of weld quality are achieved.

Images