Stainless steel laser welding parameter optimization method based on dynamic annular scanning path

Abstract

The invention discloses a stainless steel laser welding parameter optimization method based on a dynamic annular scanning path. The stainless steel laser welding parameter optimization method comprises the steps that S1, welding parameter setting is initialized to be suitable for controlling welding heat distribution; s2, measuring the material thickness of the welding area of the stainless steel workpiece before welding; s3, the scanning path layer number and the progressive speed are determined according to the welding parameters; s4, the welding control system adjusts welding parameters according to the temperature monitoring data; s5, the laser welding control system adjusts the layer number, the progressive speed and the scanning path radius of the dynamic annular scanning path in real time; s6, the scanning amplitude, the scanning frequency and the welding speed are optimized in real time; and S7, after welding is completed, quality detection is conducted on a welding seam, and detection data are compared with a preset welding quality standard. According to the method, accurate control over welding heat input, remarkable improvement of the welding seam quality and comprehensive optimization of the welding efficiency are achieved.

Description

Technical Field

[0001] The 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. Stainless steel laser welding is an efficient and precise processing technology, and its process quality directly affects the structural strength and service life of the material. However, the existing stainless steel laser welding process still has many technical challenges in practical applications, especially in the control of heat-affected zone and prevention of weld defects in high-quality welding.

[0003] At present, the traditional laser welding process usually adopts a fixed scanning path or a simple straight path mode. The traditional method is easy to cause heat concentration in the welding area when processing heat-sensitive stainless steel materials, which in turn causes problems such as excessive heat-affected zone and obvious thermal deformation of the material. At the same time, due to the lack of dynamic adjustment ability of the laser power, scanning speed and focus position parameters, weld porosity and crack defects often appear in the stainless steel welding process, affecting the consistency of weld quality and the mechanical properties of the material.

[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 thickness in 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 realizes precise control of welding heat input, significant improvement of weld quality and comprehensive optimization of welding efficiency.

[0007] A stainless steel laser welding parameter optimization method based on a dynamic annular scanning path according to an embodiment of the present invention comprises the following steps:

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

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

[0010] S3. According to the welding parameters, the laser welding control system generates a dynamic annular scanning path adapted to different thickness areas of stainless steel according to the detected material thickness data, and determines the number of scanning path layers and the progressive speed;

[0011] 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, and the welding control system adjusts the welding parameters according to the temperature monitoring data;

[0012] 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 annular scanning path in real time;

[0013] 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 of the welding area, and optimizes the scanning amplitude, scanning frequency and welding speed in real time;

[0014] S7. After welding is completed, the weld quality shall be inspected, including the smoothness of the weld, the size of the heat-affected zone and the evaluation of the weld strength, and the inspection data shall be compared with the preset welding quality standards.

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

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

[0017] P0=k1·t+P min ;

[0018] 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, and P min is the minimum initial power value;

[0019] 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;

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

[0021] f=β·h+γ·r0;

[0022] Among them, β is the focus adjustment coefficient, which represents the influence weight of the laser focus with the welding depth, γ is the influence coefficient of the 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 the focal 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, inputting 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 by a non-contact measuring device, wherein x, y are 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-to-thinness boundary threshold t c , the threshold value of the thick and thin areas t c Dynamic adjustment as thickness distribution changes and local inhomogeneities occur:

[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 diagram t'(x,y):

[0037]

[0038] in, and At the 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 boundary 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, the 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 this point, and the progressive speed indicates the speed at which the radius of the circular path expands between layers. For thick stainless steel material areas, the number of layers is increased to encrypt the path, and 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 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 indicate the increase and decrease rate of the number of layers with the thickness difference;

[0047] S34, define the progressive speed v of the dynamic annular scanning path r The functional relationship between (x, y) and thickness distribution t'(x, y), taking 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 laser energy is fully deposited in the local area by reducing the progressive speed, and in the thin area, the local overheating phenomenon is reduced by increasing the progressive speed.

[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 annular scanning path that meets the requirements of different thickness areas of stainless steel is generated, and the thick material area is scanned in encrypted layers to increase the expansion speed of the thin material area.

[0053] Optionally, the 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 welding;

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

[0056]

[0057] in, is the instantaneous rate of change of the temperature of the welding point (x, y) with time, k 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 number response coefficient, which represents the response sensitivity of the layer number to the thermal input deviation;

[0061] S54, adjusting the scanning path radius advancement 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 The adjusted parameters are input into the laser welding control system to dynamically adjust the hierarchical distribution density and path expansion speed of the welding path, increase the path density for thick material areas to achieve uniform heating, and reduce the path density for thin material areas to reduce heat input, thereby achieving real-time balance between temperature and heat distribution in the welding area.

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

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

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

[0068] S63. Optimize the scanning amplitude based on adjusting the laser power and focus position so that the laser coverage in the welding area matches the energy requirement. For thick material areas, expand the scanning amplitude to evenly disperse the heat; for thin material areas, reduce the scanning amplitude to control the heat input;

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

[0070] S65, dynamically adjust the welding speed to match the temperature and thickness changes in the welding area, slow down the welding speed in the thick material area to enhance the deposition effect of the laser energy, and increase the welding speed in the thin material area 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 for thick material areas, and energy distribution and temperature control are achieved for 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 number of path layers is increased and the expansion speed is slowed down, thereby improving the local heat deposition efficiency. 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 the thick material area, the laser power and focal position are dynamically adjusted to enhance the welding depth and heat input stability. In the thin material area, local overheating and the generation of weld defects are avoided by reducing the 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 pores and cracks in welding defects, 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 the best balance between energy distribution and welding efficiency. 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 the 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 stainless steel workpieces with complex shapes and multiple thicknesses. 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 The present invention is a flowchart of a stainless steel laser welding parameter optimization method based on a dynamic annular scanning path. DETAILED DESCRIPTION

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

[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. According to the thickness characteristics of the stainless steel material, the welding parameters are set in the laser welding control system, and the initialization welding parameter settings are suitable for controlling 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 by the detection into the laser welding control system;

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

[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, and 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 annular 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 of 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 smoothness of the weld, the size of the heat-affected zone and the evaluation of the weld strength, and the inspection data shall be compared with the preset welding quality standards.

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

[0088] S11. Calculate the initial laser power P0 according to 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, and 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 stainless steel materials, the focus position f is related to the welding depth h and the path radius r0, satisfying the following relationship:

[0093] f=β·h+γ·r0;

[0094] Among them, β is the focus adjustment coefficient, which represents the influence weight of the laser focus with the welding depth, γ is the influence coefficient of the 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 the focal 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, inputting 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 implementation, 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 by a non-contact measuring device, wherein 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-to-thinness boundary threshold t c , the threshold value of the thick and thin areas t c Dynamic adjustment as thickness distribution changes and local inhomogeneities occur:

[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 diagram t'(x,y):

[0109]

[0110] in, and At the 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 boundary threshold t c , t′(x,y)>tc The area is defined as the thick area, and t′(x,y)≤t c The area is defined as the thin area.

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

[0113] 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 this point, and the progressive speed indicates the speed at which the radius of the circular path expands between layers. For thick stainless steel material areas, the number of layers is increased to encrypt the path, and for thin material areas, the number of layers is reduced and the progressive speed is increased;

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

[0115] N L (x,y)=N0+α·[t′(x,y)-t c ];

[0116] When t′(x,y)≤t c hour:

[0117] N L (x,y)=max{N min ,N0-α′·[t c -t′(x,y)]};

[0118] 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 indicate the increase and decrease rate of the number of layers with the thickness difference;

[0119] S34, define the progressive speed v of the dynamic annular scanning path r The functional relationship between (x, y) and thickness distribution t'(x, y), taking the initial welding speed v as the reference value, when t'(x, y)>t c hour:

[0120]

[0121] When t′(x,y)≤t c hour:

[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 laser energy is fully deposited in the local area by reducing the progressive speed, and in the thin area, the local overheating phenomenon is reduced by increasing the progressive speed.

[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 annular scanning path that meets the requirements of different thickness areas of stainless steel is generated, and the thick material area is scanned in encrypted layers to increase the expansion speed of the thin material area.

[0125] In this implementation, 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 welding;

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

[0128]

[0129] in, is the instantaneous rate of change of the temperature of the welding point (x, y) with time, k 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 number response coefficient, which represents the response sensitivity of the layer number to the thermal input deviation;

[0133] S54, adjusting the scanning path radius advancement 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 The adjusted parameters are input into the laser welding control system to dynamically adjust the hierarchical distribution density and path expansion speed of the welding path, increase the path density for thick material areas to achieve uniform heating, and reduce the path density for thin material areas to reduce heat input, thereby achieving real-time balance between temperature and heat distribution in the welding area.

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

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

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

[0140] S63. Optimize the scanning amplitude based on adjusting the laser power and focus position so that the laser coverage in the welding area matches the energy requirement. For thick material areas, expand the scanning amplitude to evenly disperse the heat; for thin material areas, reduce the scanning amplitude to control the heat input;

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

[0142] S65, dynamically adjust the welding speed to match the temperature and thickness changes in the welding area, slow down the welding speed in the thick material area to enhance the deposition effect of the laser energy, and increase the welding speed in the thin material area 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 for thick material areas, and energy distribution and temperature control are achieved for thin material areas, so that the overall temperature balance of the welding area and the consistency of weld quality are achieved.

[0144] Embodiment 1:

[0145] Example: In an aviation manufacturing company, an aviation manufacturing company received a batch production order and needed to complete a batch of stainless steel parts with complex shapes. The welding requirements of the parts were strict and needed to achieve high strength and 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 large heat-affected zones in this scenario.

[0146] The welding task involves the splicing of complex curved parts. The total length of the weld is 1.5 meters, including the inflection point with large curvature and the junction area of ​​thick and thin materials. The weld strength must reach more than 95% of the strength of the parent material. The surface finish of the weld 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 circular 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; in the thin material area, the number of path layers 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 with 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 increase heat deposition. Due to the thinning of the thickness in 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 increase in temperature (over 800°C), and 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, the heat accumulation phenomenon in the inflection point area was successfully avoided, and the consistency of the weld quality and shape was maintained. 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 benefits from 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 the traditional method, and the workpiece deformation is reduced to 0.5 mm, which 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 improves welding efficiency by 30%, and the weld defect rate is reduced to 2%, mainly because the dynamic adjustment mechanism effectively avoids the generation of pores and cracks.

[0153] Through practical application, the method of the invention has successfully solved the problems of large heat-affected zone, multiple weld defects and uneven quality in complex welding tasks, and significantly improved welding quality and efficiency. Compared with traditional methods, the invention has shown excellent adaptability and technical advantages in high-demand 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 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 path in traditional welding. In the thick material area, the local heat deposition efficiency is improved by increasing the number of path layers and slowing down the expansion speed. In the thin material area, 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 the thick material area, the laser power and focal position will be dynamically adjusted to enhance the welding depth and heat input stability. In the thin material area, local overheating and the generation of weld defects are avoided by reducing the 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 porosity and crack welding defects, 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 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 the 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 stainless steel workpieces with complex shapes and multiple thicknesses.

[0157] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope 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. According to the thickness characteristics of the stainless steel material, the welding parameters are set in the laser welding control system, and the initialization welding parameter settings are suitable for controlling 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 by the detection into the laser welding control system; S3. According to the welding parameters, the laser welding control system generates a dynamic annular scanning path adapted to different thickness areas of stainless steel according to the detected material thickness data, and determines the number of scanning path layers and the progressive speed; 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, and 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 annular 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 of 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 smoothness of the weld, the size of the heat-affected zone and the evaluation of 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 according to 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, and 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 stainless steel materials, the focus position f is related to the welding depth h and the path radius r0, satisfying the following relationship: f=β·h+γ·r0; Among them, β is the focus adjustment coefficient, which represents the influence weight of the laser focus with the welding depth, γ is the influence coefficient of the 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 the focal 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, inputting 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 by a non-contact measuring device, wherein 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-to-thinness boundary threshold t c , the threshold value of the thick and thin areas t c Dynamic adjustment as thickness distribution changes and local inhomogeneities occur: 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 diagram t'(x,y): in, and At the 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 boundary 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 is 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 this point, and the progressive speed indicates the speed at which the radius of the circular path expands between layers. For thick stainless steel material areas, the number of layers is increased to encrypt the path, and 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 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 indicate the rate of increase or decrease of the number of layers with the thickness difference. S34, define the progressive speed v of the dynamic annular scanning path r The functional relationship between (x, y) and thickness distribution t'(x, y), taking 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 laser energy is fully deposited in the local area by reducing the progressive speed, and in the thin area, the local overheating phenomenon is reduced by increasing the progressive speed. 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 annular scanning path that meets the requirements of different thickness areas of stainless steel is generated, and the thick material area is scanned in encrypted layers to increase the expansion speed of the thin material area.

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 welding; S52, based on the temperature distribution T(x, y, t) and the thickness data t'(x, y), the local heat input deviation ΔH(x, y, t) of each welding point is calculated in real time: in, is the instantaneous rate of change of the temperature of the welding point (x, y) with time, k 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 number response coefficient, which represents the response sensitivity of the layer number to the thermal input deviation; S54, adjusting the scanning path radius advancement 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 The adjusted parameters are input into the laser welding control system to dynamically adjust the hierarchical distribution density and path expansion speed of the welding path, increase the path density for thick material areas to achieve uniform heating, and reduce the path density for thin material areas to reduce heat input, thereby achieving 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 hierarchy, the laser welding control system adjusts the laser power in real time, increases the laser power in the thick material area, and reduces the laser power in the thin material area; S62. Dynamically adjust the laser focus position according to the real-time temperature change trend and thickness data to adapt it to the depth requirements of the welding area. In the thick material area, the focus position is adjusted toward the inside of the material to enhance the deep heat input. In the thin material area, the focus position is adjusted toward the surface to reduce the heat impact. S63. Optimize the scanning amplitude based on adjusting the laser power and focus position so that the laser coverage in the welding area matches the energy requirement. For thick material areas, expand the scanning amplitude to evenly disperse the heat; for thin material areas, reduce the scanning amplitude to control the heat input; S64, optimize the scanning frequency in real time, increase or decrease the speed and frequency of laser scanning according to the temperature distribution of the welding area, increase the scanning frequency in the thin material area to speed up the welding speed and reduce the heat dwell time, and reduce the scanning frequency in the thick material area to extend the heat deposition time; S65, dynamically adjust the welding speed to match the temperature and thickness changes in the welding area, slow down the welding speed in the thick material area to enhance the deposition effect of the laser energy, and increase the welding speed in the thin material area 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 for thick material areas, and energy distribution and temperature control are achieved for thin material areas, so that the overall temperature balance of the welding area and the consistency of weld quality are achieved.

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