Method for processing cutting edge through composite laser based on dynamic parameter adjustment and real-time detection

Abstract

The invention provides a method for machining a cutting edge through composite laser based on dynamic parameter adjustment and real-time detection, and relates to the technical field of cutter machining. COMSOL is used for conducting simulation of the composite laser reinforced cutting edge, a COMSOL simulation database is established to match preset parameters, and the preset parameters are matched with the COMSOL simulation database; the heat affected zone of the cutter material strengthened by the composite laser and the corrosion amount are directly displayed in a simulation result, so that the efficiency of strengthening the cutting edge of the cutter by the laser is greatly improved; an XZ two-dimensional high-precision micro-motion platform is used, the stability and the machining precision of a laser are guaranteed, meanwhile, a two-dimensional confocal microscope is used for observing and collecting data, the data are fed back to a COMSOL database in real time by adjusting an evaluation model P, machining parameters are continuously corrected, and the machining precision is improved. And meanwhile, the preparation precision of the cutting edge of the cutter can be accurately controlled by dynamically adjusting the threshold value Q, a laser machining parameter feedback mechanism and optimizing current laser machining parameter setting, so that an ideal cutting edge of the cutter is obtained.

Description

Technical Field

[0001] The present invention relates to the technical field of tool processing, and in particular to a method for composite laser processing cutting edges based on dynamic parameter adjustment and real-time detection. Background Art

[0002] Traditional edge hardening methods have the disadvantages of low efficiency, low precision, poor stability, etc. for manufacturing complex-shaped tool edges and super-hard material tool edges, which easily lead to failure. Therefore, it is difficult to meet the needs of machining and strengthening tool edges using traditional edge hardening methods. The development focus of modern laser processing technology includes the construction of simulation models and parameter optimization. COMSOL Multiphysics M, as a multi-physics simulation software, plays an important role in the field of laser processing. It can simulate the interaction between laser and matter and predict the physical changes in the processing process, thus providing a theoretical basis for the setting and optimization of laser processing parameters.

[0003] Laser processing is a non-contact material removal technology, in which the laser beam transfers energy to the workpiece. This energy is locally absorbed on the surface of the workpiece, causing the limited temperature of the material to rise. When the applied impact is greater than the minimum material-specific impact required for material ablation, phase change melting and vaporization will occur, and the material will be removed by molten material ejection and vaporization. Laser processing technology has unique advantages in tool edge preparation by utilizing its unique ablation mechanism. However, the existing laser processing technology has high laser beam energy density and extremely fast processing speed during the processing process. The processing part is localized and has no or no effect on the non-laser irradiated part. The effect is very small, and the amount of erosion in the local processing is difficult to control, and the accuracy is not high. Traditional parameter settings usually rely on experience or static preset values, which limits the adaptability to changes in material properties and edge shape during the processing process. Secondly, there is a certain disconnect between the existing laser processing methods between simulation and actual processing. Although COMSOL simulation can provide theoretical parameter optimization, in the actual processing process, due to various external factors and the complexity of material properties, there is often a deviation between the simulation results and the actual processing effects. Therefore, the lack of real-time data feedback and dynamic adjustment mechanism has become the main obstacle to improving processing accuracy and efficiency;

[0004] Therefore, in order to meet the current demand for efficient, precise and flexible processing of complex tool edges, a new laser processing method is needed to further weaken the laser heat-affected zone and optimize the processing accuracy, which is the direction that needs to be improved at present;

[0005] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0006] The purpose of the present invention is to provide a method for composite laser processing cutting edge based on dynamic parameter adjustment and real-time detection, so as to solve the problems raised in the above-mentioned background technology.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A method for composite laser processing cutting edge based on dynamic parameter adjustment and real-time detection, the specific steps comprising:

[0009] S1, constructing a COMSOL simulation database, wherein the COMSOL simulation database includes a COMSOL simulation model and definitions of laser processing parameters and structural parameter data of a cutting edge, using several groups of historical data of cutting edge laser processing to update the COMSOL simulation model to construct a complete simulation system, and executing the COMSOL simulation model to obtain an updated COMSOL simulation database;

[0010] S2, obtaining structural parameter data of the cutting edge of the tool to be processed, wherein the structural parameter data of the cutting edge includes the geometric shape and material properties of the cutting edge, and creating a composite simulation model of the cutting edge of the tool to be processed in COMSOL software, wherein the composite simulation model covers a time scale from nanoseconds to picoseconds;

[0011] S3, matching the created composite simulation model with the COMSOL simulation model in the COMSOL simulation database to obtain the COMSOL simulation model with the highest matching degree, inputting the preset cutting edge parameters into the COMSOL simulation model with the highest matching degree for simulation, thereby obtaining a simulation result, and matching the simulation result with the updated COMSOL simulation database to preliminarily determine the first laser processing parameter;

[0012] S4, obtaining laser processing parameters and structural parameter data of the cutting edge of the tool to be processed, constructing a laser adjustment evaluation model P, and generating adjustment strategies for various input parameters in the COMSOL simulation model based on the value range of the adjustment evaluation model P, wherein the input parameters include the structural parameter data of the cutting edge and the laser processing parameters;

[0013] S5, fine-tuning the first laser processing parameters according to the adjustment strategy, fixing the tool to be processed on the XZ two-dimensional micro-motion platform, and using nanosecond laser and picosecond laser in sequence to perform secondary strengthening on the cutting edge of the processing tool fixed on the XZ two-dimensional micro-motion platform according to the fine-tuned first laser processing parameters;

[0014] S6, observe and evaluate the secondary strengthening effect of the cutting edge. If the preset cutting edge parameters are not reached, the adjustment strategy is corrected by adjusting the evaluation model P to update the fine-tuned first laser processing parameters to the second laser processing parameters. According to the second laser processing parameters, the cutting edge of the processing tool fixed on the XZ two-dimensional micro-motion platform is corrected and strengthened by using nanosecond laser and picosecond laser in sequence;

[0015] S7, repeat step S6 until the strengthening effect of the cutting edge is observed and evaluated to reach the preset cutting edge parameters.

[0016] Preferably, the preset cutting edge parameters are expected structural parameter data of the tool to be processed, including tool arc radius, tool rake angle, tool clearance angle, tool length and tool edge shape, and each parameter is calibrated in turn to form tool arc radius r1, tool rake angle Qj, tool clearance angle Hj, tool length Cd, and tool edge shape Rx;

[0017] The preset cutting edge parameters also include material properties of the cutting edge, the material properties include the heat affected zone and the amount of erosion of the tool material strengthened by the composite laser, and the heat affected zone and the amount of erosion are calibrated as HAZ and MRV respectively, forming the heat affected zone HAZ and the amount of erosion MRV;

[0018] The laser processing parameters specifically include pulse laser power, laser spot radius, laser pulse frequency, scanning speed and laser impact number, and are calibrated in sequence to form pulse laser power JGG l, laser spot radius JGBj, laser pulse frequency JGPl, scanning speed SMSd, and laser impact number JGCj;

[0019] The composite simulation model includes the following contents:

[0020] Construct a preset three-dimensional tool edge model, construct a two-dimensional heat transfer and deformation geometry physical field, set material physical parameters, set model initial conditions and boundary conditions, set multi-physics field coupling, construct mesh division, and study calculation and analysis;

[0021] The matching of the created composite simulation model with the COMSOL simulation model in the COMSOL simulation database specifically includes the following contents:

[0022] The matching retrieval specifically adopts loading the COMSOL library in MATLAB, using the API function of COMSOL to obtain the parameters and variables in the COMSOL model, using the isequa l function in MATLAB to compare the input parameters with the parameters in the COMSOL database, when the matched processing parameters are not completely corresponding to the database, the processed image and the image in the database are displayed by the imshow function in MATLAB, the imabsd function calculates the absolute difference between the two images, and the difference is represented by visual quantification, when the difference calculated by the imabsd iff function in MATLAB is less than 5%, the parameters are input into the laser; and the input parameters are laser processing parameters, and the output is tool edge parameters.

[0023] Preferably, the laser processing parameters and the structural parameter data of the cutting edge of the tool to be processed are obtained, and the adjustment evaluation model P of the laser is constructed. Based on the value range of the adjustment evaluation model P, an adjustment strategy for various input parameters in the COMSOL simulation model is generated. The input parameters include the structural parameter data of the cutting edge and the laser processing parameters, and specifically include the following contents:

[0024] Define the following functions respectively:

[0025] After obtaining the data of pulse laser power, laser spot radius, laser pulse frequency, scanning speed and laser impact times, a laser adjustment function F (JGG l, JGBj, JGPl, SMSd, JGCj) is generated, and the result of laser processing parameter adjustment is outputted; the formula of laser adjustment function F (JGG l, JGBj, JGPl, SMSd, JGCj) is expressed as:

[0026]

[0027] in:

[0028] (α, β, γ, δ, ò) are constants used to adjust the weights of each parameter;

[0029] JGG l(t), JGBj(t), JGPl(t), SMSd(t), and JGCj(t) are the values ​​of pulsed laser power, laser spot radius, laser pulse frequency, scanning speed, and number of laser impacts at time (t), respectively;

[0030] After obtaining the heat affected zone and ablation data of the material, the material influence function G (HAZ, MRV) is generated, and the influence of the material on the adjustment of laser processing parameters is outputted; the formula of the material influence function G (HAZ, MRV) is:

[0031]

[0032] in:

[0033] (φ,ψ) are constants used to adjust the influence weights of the heat affected zone and the erosion amount;

[0034] HAZ(t) and MRV(t) are the heat affected zone and the amount of erosion at time (t), respectively;

[0035] Measure the material volume V before cutting edge processing initial , and the volume of the processed material V final The data is analyzed to generate the erosion expression formula:

[0036] MRV=V initial -V final

[0037] Among them, V initial is the volume of material before processing, V final is the volume of material after processing;

[0038] The HAZ calculation formula is as follows:

[0039] HAZ=C·t

[0040] in:

[0041] HAZ is the depth of the heat affected zone.

[0042] C is a constant related to the material and welding process.

[0043] t is the time during the welding process;

[0044] After obtaining the arc radius, rake angle, relief angle, length and blade shape data of the cutting edge, a cutting edge geometric parameter function H (r1, Qj, Hj, Cd, Rx) is generated, and the geometric influence on the adjustment of laser processing parameters is outputted;

[0045] The cutting edge geometric parameter function H(r1,Qj,Hj,Cd,Rx) is expressed as:

[0046]

[0047] Where b1 and b2 are deviation factors, 0.21≤b1≤0.68, 0.11≤b2≤0.89;

[0048] Based on the above definition, the adjustment evaluation model P is constructed, and the calculation formula is:

[0049]

[0050] in:

[0051] P is the evaluation value of the adjusted evaluation model;

[0052] T is the total time for laser processing a single workpiece;

[0053] JGG l(t), JGBj(t), JGP l(t), SMSd(t), JGCj(t) are the pulsed laser power, laser spot radius, laser pulse frequency, scanning speed, and number of laser impacts that vary with time respectively;

[0054] HAZ(t), MRV(t) are the heat affected zone and the amount of erosion that vary with time;

[0055] r1(t), Qj(t), Hj(t), Cd(t), Rx(t) are the edge arc radius, rake angle, clearance angle, length, and edge type data that vary with time;

[0056] Range interpretation:

[0057] The value range of formula P is defined as (0, 1). Based on the real-time and historical data of the laser power adjustment function, material influence function, and edge geometry parameter function, the comparison threshold of the value range of formula P is set as Q, and the expected value E of the laser processing effect is determined according to the preset edge parameters.

[0058] When (0 < P < Q), it means that the laser processing effect does not meet the expected value E, and it is necessary to further adjust the simulation parameters and laser processing parameters in sequence to optimize the strengthening effect and realize the continuous strengthening of the edge in the nanosecond-picosecond laser.

[0059] When (P = Q), it means that the laser processing parameters just reach the preset edge parameter effect and just meet the expected value E, and it is possible to selectively adjust the simulation parameters and laser processing parameters in sequence for fine-tuning.

[0060] When (Q < P < 1), it means that the laser processing effect exceeds the expected value E, the strengthening effect is good, and there is no need to adjust the simulation parameters and laser processing parameters in sequence.

[0061] Preferably, the adjustment strategy further includes dynamically adjusting the threshold Q, setting a feedback mechanism for laser processing parameters, and optimizing the current laser processing parameters;

[0062] The dynamic adjustment of the threshold Q includes the following:

[0063] a. Obtain the real-time and historical data of the laser processing parameters, dynamically adjust the threshold Q, and set the range of P value within the interval of 0.8 to 1 as the proximity interval;

[0064] If the evaluation model P is in the approximate interval in the continuous K times of edge processing operations, Q is automatically reduced by M1 units to reduce the adjustment range of laser processing parameters and simulation parameters. Conversely, if the P value of 4 / 5K times is lower than Q in the continuous K times of edge processing operations, and the edge meets the expected value E of the laser processing effect, the threshold Q is increased by M2 units to increase the adjustment space;

[0065] The laser processing parameter feedback mechanism includes the following contents:

[0066] b. When the laser processing parameters exceed the preset range, the model will automatically adjust other parameters to ensure that the operation is carried out within a safe range;

[0067] Specifically set the laser processing parameters as follows:

[0068] The predetermined range of the pulse laser power JGGl is expressed as JGGl∈[I min ,I max ];

[0069] Among them I min is the minimum pulse laser power, I max is the maximum pulse laser power;

[0070] The predetermined range of the laser spot radius JGBj is expressed as JGBj∈[R min ,R max ];

[0071] Where R min is the minimum laser spot radius, R max is the maximum laser spot radius;

[0072] The predetermined range of the laser pulse frequency JGPl is expressed as JGPl∈[F min ,F max ];

[0073] where F min is the minimum laser pulse frequency, F max is the maximum laser pulse frequency;

[0074] The predetermined range of scanning speed SMSd is expressed as SMSd∈[V min ,V max ];

[0075] Where V min is the minimum scanning speed, V max is the maximum scanning speed;

[0076] The predetermined range of laser shock times JGCj is expressed as JGCj∈[N min ,N max ];

[0077] Where N min is the minimum number of laser shocks, N max is the maximum number of laser shocks;

[0078] First, define the adjustment model, and define the formula as follows:

[0079] Z new =k×(X safe -X)+Z

[0080] Wherein X is any one of I, R, F, V, and N, and Z is any one of JGGl, JGBj, JGPl, SMSd, and JGCj. new is the adjusted data, Z is the current data, and K is the adjustment coefficient;

[0081] The optimization of the current laser processing parameters includes the following contents:

[0082] c. Based on the laser power adjustment function, material influence function and cutting edge geometry parameter function, the historical processing data of the cutting edge is collected and used to guide and optimize the current laser processing parameter settings to improve the prediction accuracy and efficiency.

[0083] Compared with the prior art, the present invention has the following beneficial effects:

[0084] (1) By using COMSOL to simulate the composite laser-hardened cutting edge, a COMSOL simulation database is established to match the preset parameters. The heat-affected zone and the amount of erosion of the tool material after composite laser hardening are directly displayed in the simulation results, greatly improving the efficiency of laser-hardened tool cutting edges;

[0085] (2) The stability and processing accuracy of the laser are guaranteed by using an XZ two-dimensional high-precision micro-motion platform. At the same time, a two-dimensional confocal microscope is used to observe and collect data. The evaluation model P is adjusted and fed back to the COMSOL database in real time to continuously correct the processing parameters. At the same time, the threshold Q is dynamically adjusted, the laser processing parameter feedback mechanism is used, and the current laser processing parameter settings are optimized to accurately control the tool edge preparation accuracy and obtain an ideal tool edge. BRIEF DESCRIPTION OF THE DRAWINGS

[0086] Figure 1 It is a schematic diagram of the overall method flow of the present invention;

[0087] Figure 2 It is a schematic diagram of composite laser processing;

[0088] Figure 3 The process flow chart of composite laser machining cutting edge for dynamic parameter adjustment and real-time detection;

[0089] Figure 4This is a microscopic morphology of the tool edge detected in real time before the composite laser strengthening treatment;

[0090] Figure 5 This is a microscopic morphology of the tool edge detected in real time after composite laser strengthening treatment;

[0091] Figure 6 To detect the cutting edge in real time. DETAILED DESCRIPTION

[0093] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0094] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0095] See also Figures 1 to 6 , the present invention provides a technical solution:

[0096] Embodiment 1:

[0097] The present invention proposes a method for composite laser processing cutting edge based on dynamic parameter adjustment and real-time detection, and the specific steps include:

[0098] S1, constructing a COMSOL simulation database, wherein the COMSOL simulation database includes a COMSOL simulation model and definitions of laser processing parameters and structural parameter data of a cutting edge, using several sets of historical data of cutting edge laser processing to update the COMSOL simulation model to construct a complete simulation system, and executing the COMSOL simulation model to obtain an updated COMSOL simulation database;

[0099] S2, obtaining structural parameter data of the cutting edge of the tool to be processed, wherein the structural parameter data of the cutting edge includes the geometric shape and material properties of the cutting edge, and creating a composite simulation model of the cutting edge of the tool to be processed in COMSOL software, wherein the composite simulation model covers a time scale from nanoseconds to picoseconds;

[0100] S3, matching the created composite simulation model with the COMSOL simulation model in the COMSOL simulation database to obtain the COMSOL simulation model with the highest matching degree, inputting the preset cutting edge parameters into the COMSOL simulation model with the highest matching degree for simulation, thereby obtaining a simulation result, and matching the simulation result with the updated COMSOL simulation database to preliminarily determine the first laser processing parameter;

[0101] S4, obtaining laser processing parameters and structural parameter data of the cutting edge of the tool to be processed, constructing a laser adjustment evaluation model P, and generating adjustment strategies for various input parameters in the COMSOL simulation model based on the value range of the adjustment evaluation model P, wherein the input parameters include the structural parameter data of the cutting edge and the laser processing parameters;

[0102] S5, fine-tuning the first laser processing parameters according to the adjustment strategy, fixing the tool to be processed on the XZ two-dimensional micro-motion platform, and using nanosecond laser and picosecond laser in sequence to perform secondary strengthening on the cutting edge of the processing tool fixed on the XZ two-dimensional micro-motion platform according to the fine-tuned first laser processing parameters;

[0103] S6, observe and evaluate the secondary strengthening effect of the cutting edge. If the preset cutting edge parameters are not reached, the adjustment strategy is corrected by adjusting the evaluation model P to update the fine-tuned first laser processing parameters to the second laser processing parameters. According to the second laser processing parameters, the cutting edge of the processing tool fixed on the XZ two-dimensional micro-motion platform is corrected and strengthened by using nanosecond laser and picosecond laser in sequence;

[0104] S7, repeat step S6 until the strengthening effect of the cutting edge is observed and evaluated to reach the preset cutting edge parameters.

[0105] Embodiment 2:

[0106] Further explained on the basis of Example 1, the preset cutting edge parameters are the expected structural parameter data of the tool to be processed, which include the tool arc radius, tool rake angle, tool clearance angle, tool length and tool blade shape, and each parameter is calibrated in turn to form the tool arc radius r1, tool rake angle Qj, tool clearance angle Hj, tool length Cd, and tool blade shape Rx;

[0107] In this embodiment, the tool arc radius range is set to 20-30 μm, the tool rake angle range is 5°-10°, the tool back angle range is 5°-10°, the tool length range is 14-16 mm, and the tool blade type is classified into a trumpet blade and a waterfall blade;

[0108] The base material of the tool is cemented carbide, high temperature alloy, ceramic tool, diamond tool, and other tools can be selected according to actual conditions, which is not limited here;

[0109] The preset cutting edge parameters also include material properties of the cutting edge, the material properties include the heat affected zone and the amount of erosion of the tool material strengthened by the composite laser, and the heat affected zone and the amount of erosion are calibrated as HAZ and MRV respectively, forming the heat affected zone HAZ and the amount of erosion MRV;

[0110] The preset edge parameter collection method is as follows:

[0111] The tool arc radius r1 is obtained by measuring with a measuring tool or 3D scanning;

[0112] The tool rake angle Qj and relief angle Hj are determined by angle measuring instruments of precision measuring equipment;

[0113] The tool length Cd is measured using a caliper of a standard measuring tool;

[0114] The tool edge profile Rx is obtained through high-precision scanning and image analysis technology;

[0115] Material characteristic parameters:

[0116] Heat affected zone (HAZ) The size of the heat affected zone of the tool is measured using an electron microscope with microscopic analysis technology;

[0117] Ablation volume MRV measures the weight and volume difference before and after material ablation through microbalance and microscopy measurement technology;

[0118] The laser processing parameters specifically include pulse laser power, laser spot radius, laser pulse frequency, scanning speed and laser impact number, and are calibrated in sequence to form pulse laser power JGG l, laser spot radius JGBj, laser pulse frequency JGPl, scanning speed SMSd, and laser impact number JGCj;

[0119] In this embodiment, the specific laser strengthening parameter value range includes: pulse laser power range of 10W to 50W, laser spot radius range of 1 to 30μm, laser pulse frequency range of 20KHZ to 80KHZ, scanning speed range of 500 to 2000mm / s, and laser impact times range of 1 to 20 times;

[0120] The laser processing parameters are collected as follows:

[0121] The pulsed laser power JGG l is directly measured by a laser power meter;

[0122] The laser spot radius JGBj is measured using a spot analyzer;

[0123] Laser pulse frequency JGPl is data provided by the laser control system;

[0124] The scanning speed SMSd and the number of laser impacts JGCj are recorded and adjusted by the laser processing control system;

[0125] The composite simulation model includes the following contents:

[0126] Construct a preset three-dimensional tool edge model, construct a two-dimensional heat transfer and deformation geometry physical field, set material physical parameters, set model initial conditions and boundary conditions, set multi-physics field coupling, construct mesh division, and study calculation and analysis; the above contents are parameters set and calculated in the physical simulation software COMSOL, which can be obtained and adjusted through the software interface;

[0127] Specifically, a preset three-dimensional tool edge model is constructed, a ramp function and a Gaussian pulse function are defined to simulate the light source, an analytical function and a piecewise function are used to simulate the pulse laser time, a solid heat transfer physical field is constructed to simulate the heat source of the light source contacting the material body, thermal insulation and heat flux boundary conditions are set, a deformation geometry physical field is established to simulate the deformation of the material due to laser ablation, a specified grid displacement and a specified normal grid velocity are set, multi-physical field coupling is set, a grid division is constructed to divide the cutting edge and the non-cutting edge into two parts, the cutting edge grid contains 11243 domain units and 309 boundary units, the non-cutting edge grid contains 13712 domain units and 400 boundary units, and the calculation and analysis are studied in a transient manner;

[0128] The matching of the created composite simulation model with the COMSOL simulation model in the COMSOL simulation database specifically includes the following contents:

[0129] The matching retrieval specifically adopts loading the COMSOL library in MATLAB, using the API function of COMSOL to obtain the parameters and variables in the COMSOL model, using the isequa l function in MATLAB to compare the input parameters with the parameters in the COMSOL database, when the matched processing parameters are not completely corresponding to the database, the processed image and the image in the database are displayed by the imshow function in MATLAB, the imabsd function calculates the absolute difference between the two images, and the difference is represented by visual quantification, when the difference calculated by the imabsd iff function in MATLAB is less than 5%, the parameters are input into the laser; and the input parameters are laser processing parameters, and the output is tool edge parameters.

[0130] Embodiment three:

[0131] Further explanation is given on the basis of the second embodiment, the laser processing parameters and the structural parameter data of the cutting edge of the tool to be processed are obtained, and the adjustment evaluation model P of the laser is constructed. Based on the value range of the adjustment evaluation model P, the adjustment strategy for various input parameters in the COMSOL simulation model is generated. The input parameters include the structural parameter data of the cutting edge and the laser processing parameters, which specifically include the following contents:

[0132] Define the following functions respectively:

[0133] After obtaining the data of pulse laser power, laser spot radius, laser pulse frequency, scanning speed and laser impact times, a laser adjustment function F (JGG l, JGBj, JGPl, SMSd, JGCj) is generated, and the result of laser processing parameter adjustment is outputted; the formula of laser adjustment function F (JGG l, JGBj, JGPl, SMSd, JGCj) is expressed as:

[0134]

[0135] in:

[0136] (α, β, γ, δ, ò) are constants used to adjust the influence weights of each parameter;

[0137] JGGl(t), JGBj(t), JGPl(t), SMSd(t), and JGCj(t) are the values ​​of pulsed laser power, laser spot radius, laser pulse frequency, scanning speed, and number of laser impacts at time (t), respectively;

[0138] After obtaining the heat affected zone and ablation data of the material, the material influence function G (HAZ, MRV) is generated, and the influence of the material on the adjustment of laser processing parameters is outputted; the formula of the material influence function G (HAZ, MRV) is:

[0139]

[0140] in:

[0141] (φ,ψ) are constants used to adjust the influence weights of the heat affected zone and the erosion amount;

[0142] HAZ(t) and MRV(t) are the heat affected zone and the amount of erosion at time (t), respectively;

[0143] MRV refers to the volume of material removed from the workpiece during laser processing. The quantification of the amount of material removed can be achieved by measuring the remaining volume of the material and the volume change before and after processing. The volume V of the material before processing is measured. initial , and the volume of the processed material V final The data is analyzed to generate the erosion expression formula:

[0144] MRV=V initial -V final

[0145] Among them, V initial is the volume of material before processing, V final is the volume of material after processing;

[0146] The heat affected zone is the area where the material structure changes due to heat input during laser processing.

[0147] The HAZ calculation formula is as follows:

[0148] HAZ=C·t

[0149] in:

[0150] HAZ is the depth of the heat affected zone.

[0151] C is a constant related to the material and welding process.

[0152] t is the time during the welding process;

[0153] After obtaining the arc radius, rake angle, relief angle, length and blade shape data of the cutting edge, a cutting edge geometric parameter function H (r1, Qj, Hj, Cd, Rx) is generated, and the geometric influence on the adjustment of laser processing parameters is outputted;

[0154] The cutting edge geometric parameter function H(r1,Qj,Hj,Cd,Rx) is expressed as:

[0155]

[0156] Where b1 and b2 are deviation factors, 0.21≤b1≤0.68, 0.11≤b2≤0.89;

[0157] The tool blade type Rx includes a trumpet blade and a waterfall blade, and the tool blade type Rx is quantified as follows:

[0158] The horn blade is composed of a conical blade surface, which is quantified by the blade diameter D, blade angle θ, and blade length L;

[0159] The mathematical formula of the blade type Rx of the horn blade is:

[0160] R x =c1·D c2 +c3·θc4+c5·L c6

[0161] In this formula, c1, c2, c3, c4, c5 and c6 are coefficients to be determined, which are determined by fitting experimental data or based on professional knowledge. Such a functional form allows the influence of cutting edge diameter, taper angle and length on laser cutting effect to be adjusted;

[0162] The waterfall edge is quantified by the edge width W, edge angle α and edge height H.

[0163] Other possible parameters include the cutting edge height H.

[0164] The mathematical formula of the blade type Rx of the waterfall blade is:

[0165] [R x =d1·W d2 +d3·α d4 +d5·H d6 ]

[0166] In this formula, d1, d2, d3, d4, d5 and d6 are coefficients to be determined, which are fitted by experimental data or determined based on professional knowledge, allowing the adjustment of the influence of cutting edge diameter, taper angle and length on laser cutting effect;

[0167] Based on the above definition, the adjustment evaluation model P is constructed, and the calculation formula is:

[0168]

[0169] in:

[0170] P is the evaluation value of the adjusted evaluation model;

[0171] T is the total time for laser processing a single workpiece;

[0172] JGGl(t), JGBj(t), JGPl(t), SMSd(t), and JGCj(t) are the time-varying pulse laser power, laser spot radius, laser pulse frequency, scanning speed, and number of laser impacts, respectively;

[0173] HAZ(t), MRV(t) are the heat affected zone and erosion amount varying with time;

[0174] r1(t), Qj(t), Hj(t), Cd(t), Rx(t) are the cutting edge arc radius, rake angle, back angle, length and cutting edge shape data that change with time;

[0175] Range explanation:

[0176] The value range of formula P is defined as (0, 1). Based on the real-time and historical data of the laser power adjustment function, material influence function, and edge geometry parameter function, the comparison threshold of the value range of formula P is set as Q, and the expected value E of the laser processing effect is determined according to the preset edge parameters. The expected value E represents the adjustment amount of the laser power adjustment function, material influence function, and edge geometry parameter function corresponding to the preset edge parameters. For example, the tool rake angle range in the preset edge parameters is 5° to 10°, and the tool rake angle of the tool to be processed is 15°. The difference of 5° meets the requirements. Therefore, the lowest target expected value E it represents is 5°. The determination of the expected value E needs to be combined with the preset edge parameters and the actual parameters obtained from the tool edge image. Therefore, the rest of the parameters can be deduced by analogy;

[0177] When (0 < P < Q), it means that the laser processing effect does not meet the expected value E, and it is necessary to further adjust the simulation parameters and laser processing parameters in sequence to optimize the strengthening effect and realize the continuous strengthening of the edge in the nanosecond-picosecond laser;

[0178] When (P = Q), it means that the laser processing parameters just reach the preset edge parameter effect and just meet the expected value E, and it is possible to selectively adjust the simulation parameters and laser processing parameters in sequence for fine-tuning;

[0179] When (Q < P < 1), it means that the laser processing effect exceeds the expected value E, the strengthening effect is good, and there is no need to adjust the simulation parameters and laser processing parameters in sequence.

[0180] Example 4:

[0181] Based on Example 3, it is further explained that the adjustment strategy also includes dynamically adjusting the threshold Q, setting a laser processing parameter feedback mechanism, and optimizing the current laser processing parameters;

[0182] The dynamic adjustment of the threshold Q includes the following:

[0183] a. Obtain the real-time and historical data of the laser processing parameters, dynamically adjust the threshold Q, and set the range of 0.8 to 1 for the P value as the proximity range;

[0184] If in continuous K edge processing operations, the evaluation model P is in the proximity range, automatically reduce Q by M1 units to reduce the adjustment range of the laser processing parameters and simulation parameters. On the contrary, if in continuous K edge processing operations, 4 / 5K times of the P value is lower than Q and the edge meets the expected value E of the laser processing effect, increase the threshold Q by M2 units to increase the adjustment space;

[0185] For example, suppose that in the past series of operations, P fluctuated between 0.8 and 0.9, and Q was set to 0.85. If in the next operation, P reaches 0.87, the system will automatically lower Q to 0.86 to reduce the focus adjustment range and improve accuracy.

[0186] The experimental table is as follows:

[0187]

[0188]

[0189] Table 1

[0190] The laser processing parameter feedback mechanism includes the following contents:

[0191] b. When laser processing parameters exceed the predetermined range, such as laser power exceeding the safe value, the model will automatically adjust other parameters, such as reducing the scanning speed, to ensure that the operation is carried out within the safe range;

[0192] Specifically set the laser processing parameters as follows:

[0193] The predetermined range of the pulse laser power JGGl is expressed as JGGl∈[I min ,I max ];

[0194] Among them I min is the minimum pulse laser power, I max is the maximum pulse laser power;

[0195] The predetermined range of the laser spot radius JGBj is expressed as JGBj∈[R min ,R max ];

[0196] Where R min is the minimum laser spot radius, R max is the maximum laser spot radius;

[0197] The predetermined range of the laser pulse frequency JGPl is expressed as JGPl∈[F min ,F max ];

[0198] Among them, F min is the minimum laser pulse frequency, F max is the maximum laser pulse frequency;

[0199] The predetermined range of scanning speed SMSd is expressed as SMSd∈[V min ,V max ];

[0200] Where V minis the minimum scanning speed, V max is the maximum scanning speed;

[0201] The predetermined range of laser shock times JGCj is expressed as JGCj∈[N min ,N max ];

[0202] Where N min is the minimum number of laser shocks, N max is the maximum number of laser shocks;

[0203] First, define the adjustment model, and define the formula as follows:

[0204] Z new =k×(X safe -X)+Z

[0205] Wherein X is any one of I, R, F, V, and N, and Z is any one of JGGl, JGBj, JGPl, SMSd, and JGCj. new is the adjusted data, Z is the current data, and K is the adjustment coefficient; assuming that when the pulse laser power exceeds the safety value, the model will automatically adjust the scanning speed SMSd, and substitute SMSd and I respectively to obtain the following formula;

[0206] SMSd new =k×(I safe -I)+SMSd

[0207] Among them, SMS new is the adjusted scanning speed, I safe is the safe pulse laser power, I is the current pulse laser power, and k is the adjustment coefficient;

[0208] Assume that the pulse laser power JGG1 is within the following predetermined range:

[0209] I min =100W, I max =500W; V min =10m / s, V max =50m / s; other parameter ranges are similarly defined;

[0210] If the current pulse laser power I=600W, it exceeds the safety value I max =500W, then the following formula is obtained according to the adjustment model:

[0211] MS new =k×(500-600)+SMSd=k×(-100)+SMSd

[0212] Assuming k = 0.5, we get:

[0213] SMSd new =0.5×(-100)+SMSd=-50+SMSd

[0214] This means that the scanning speed will be reduced by 50m / s to ensure that the operation is carried out within a safe range and the laser focus is kept effective;

[0215] The optimization of the current laser processing parameters includes the following contents:

[0216] c. Based on the laser power adjustment function, material influence function and cutting edge geometry parameter function, the historical processing data of the cutting edge is collected and used to guide and optimize the current laser processing parameter settings to improve the prediction accuracy and efficiency;

[0217] First, historical data of processing on different materials using different laser processing parameters were collected. The laser processing parameters included pulse laser power, laser spot radius, laser pulse frequency, scanning speed, and number of laser impacts.

[0218] Analyze historical data to identify the laser processing parameter combinations that perform best on specific materials;

[0219] Parameter comparison and optimization:

[0220] According to the value range (0,1) of formula P, combined with the real-time and historical data of the laser power adjustment function, the material influence function and the cutting edge geometric parameter function, the comparison threshold Q is determined;

[0221] Determine the expected value E of the laser processing effect according to the preset cutting edge parameters;

[0222] Use the optimal parameters from historical data as a benchmark and adjust according to current processing materials and requirements;

[0223] After processing is implemented, new processing data is collected and compared with historical data;

[0224] Continuously update the historical database to ensure that each processing is based on the best available information;

[0225] Specific laser processing parameter adjustment range:

[0226] The focal length adjustment range of the nanosecond laser is set to 50-200 mm, and the focal length of the picosecond laser is set to 100-500 mm;

[0227] The adjustment method of the nanosecond laser based on the value range of P is as follows:

[0228] When 0 < P < Q: It indicates that the laser processing effect does not meet the expected value E. Since the laser focal length is too long, the laser energy distribution is not concentrated. At this time, the focal length should be gradually reduced, for example, adjusted to the lower limit of the focal length range, to enhance the laser intensity and accuracy and improve the processing effect.

[0229] When P = Q: At this time, the laser processing effect reaches the expectation, and the focal length is already in an ideal state. Make fine adjustments according to the specific situation, and make fine adjustments within the range of 50 - 200 millimeters to maintain or slightly improve the processing quality.

[0230] When Q < P < 1: It indicates that the laser processing effect exceeds the expected value E. At this time, the focal length does not need to be adjusted significantly. The current focal length can be maintained, or very fine adjustments can be made to verify whether the effect can be further improved.

[0231] The adjustment method for the picosecond laser based on the value range of P is as follows:

[0232] When 0 < P < Q: Similar to the nanosecond laser, the processing effect is not ideal due to an inappropriate focal length. For the picosecond laser, the adjustment range of the focal length needs to be larger, and it can be adjusted to a shorter focal length range to enhance the laser concentration and accuracy.

[0233] When P = Q: The laser processing parameters have well matched the processing requirements, and fine adjustments can be made, such as making small adjustments within the range of 100 - 500 millimeters to fine-tune the processing effect.

[0234] When Q < P < 1: It indicates that the laser processing effect exceeds the expected value E. Adjustment of the focal length is not necessary, and fine adjustments can be made to avoid damaging the already very good processing effect.

[0235] Example Five:

[0236] On the basis of Example Three, further illustrate that an adjustment evaluation model P is constructed to improve the laser processing process. This model comprehensively considers the total time T for processing a single workpiece by laser, the pulsed laser power JGG l(t) varying with time, the laser spot radius JGBj(t), the laser pulse frequency JGPl(t), the scanning speed SMSd(t), the number of laser impacts JGCj(t), the heat affected zone HAZ(t), and the material removal volume MRV(t), as well as the edge arc radius r1(t), the rake angle Qj(t), the clearance angle Hj(t), the length Cd(t), and the edge type data Rx(t).

[0237] The experimental preparation includes selecting five workpieces of different types, testing each workpiece under different laser processing conditions, using nanosecond and picosecond lasers, adjusting relevant laser processing parameters such as the focal length range, and recording the changes in each parameter. All parameters will be normalized according to their types to be limited to the range of 0 to 1 to ensure the consistency and comparability of the data;

[0238] During the experiment, the P value of each workpiece will be monitored and recorded, and the Q threshold will be dynamically adjusted according to these values. The adjustment of the Q threshold is shown in Table 1; The purpose of the experiment is to verify whether our system can effectively improve the accuracy and effect of laser processing by adjusting Q and laser processing parameters.

[0239] The table is as follows:

[0240]

[0241] Table 2

[0242] Data analysis of the table:

[0243] Through the analysis of the above table data, the following conclusions are drawn:

[0244] Adjustment of the evaluation model P from 0 to 1: We observe the changes of 0 to 1 under different workpieces and laser processing conditions. This index reflects the overall laser processing effect, considering the influence of various parameters. The goal is to maximize 0 to 1 by adjusting Q;

[0245] Effectiveness of dynamically adjusting the Q threshold: By dynamically adjusting the Q threshold in the experiment, we can see the flexible adjustment of Q by the system in different operations. For example, if P is often lower than Q, the system will increase Q to increase the adjustment space, and vice versa. This self - adaptability increases the adaptability of the system to different operating conditions;

[0246] Comparison of the focal length adjustment ranges of different types of lasers: Experiments are carried out using nanosecond and picosecond lasers, and their focal length adjustment ranges are observed. For example, the focal length range of the nanosecond laser is 50 - 200 mm, while that of the picosecond laser is 100 - 500 mm. This provides flexibility in choosing for different application scenarios;

[0247] Influence of focal length adjustment on the processing effect: According to the relationship between P and Q, analyze the influence of focal length adjustment on the laser processing effect. When (0 < P < Q), too long a focal length leads to uneven laser energy distribution, and the focal length needs to be gradually reduced. Conversely, when (Q < P < 1), focal length adjustment is not necessary, and the current focal length can be maintained or very fine adjustments can be made. This demonstrates the practicality and flexibility of our invention in different situations.

[0248] Example 6:

[0249] Further explanation based on the fourth embodiment, before fixing the tool to be processed on the XZ two-dimensional micro-motion platform, the tool to be processed is also cleaned and dried, which specifically includes the following contents:

[0250] The tool to be processed is cleaned with an ultrasonic cleaning machine and anhydrous ethanol as the cleaning solution. The cleaning time is at least 5 minutes. After cleaning, the tool is taken out and blown dry.

[0251] The purpose of using an ultrasonic cleaner is to completely remove stains, impurities and other substances from the surface of an object or small gaps through the collapse of tiny bubbles generated by high-frequency sound wave vibrations. The purpose of using anhydrous ethanol is to dissolve and remove organic substances such as fat, grease, stains and other organic substances on the surface of the tool to restore the tool to a clean state. At the same time, anhydrous ethanol has a fast volatility. After use, the tool dries quickly to reduce moisture residue, thereby avoiding rust and corrosion problems;

[0252] The cleaning parameters of the ultrasonic cleaning machine include: cleaning time 5 to 10 minutes, temperature control at 40 to 60°, ultrasonic frequency 20 to 40 KHZ, and cleaning tank capacity of 2 liters;

[0253] The method of sequentially using nanosecond laser and picosecond laser to perform secondary strengthening on the cutting edge of a machining tool fixed on an XZ two-dimensional micro-motion platform specifically includes the following contents:

[0254] During the first strengthening, the X-axis stroke of the XZ two-dimensional micro-motion platform is 0mm-50mm, and the Z-axis stroke is 0mm-50mm. The XZ two-dimensional micro-motion platform stroke is controlled by a servo motor in conjunction with a grating ruler, and the repeat positioning accuracy is ±1μm. The nanosecond laser and the tool edge are kept on the same vertical line by controlling the X-axis translation, and the focal length of the nanosecond laser is adjusted by controlling the Z-axis translation, and the error during focusing is ±1μm.

[0255] The simulation parameters configured and linked to the nanosecond laser for strengthening include nanosecond pulse laser power, nanosecond laser spot radius, nanosecond laser pulse frequency, nanosecond laser scanning speed, and nanosecond laser impact times;

[0256] The nanosecond laser processing parameter range settings specifically include: nanosecond pulse laser power of 10W to 50W, nanosecond laser spot radius of 20 to 30μm, nanosecond laser pulse frequency of 40KHZ to 80KHZ, nanosecond laser scanning speed of 780 to 2000mm / s, and nanosecond laser impact times of 1 to 20 times. The working parameters of the nanosecond laser are selected according to actual conditions.

[0257] Embodiment seven:

[0258] Further explanation is given on the basis of Example 6.

[0259] During the second strengthening, the XZ two-dimensional micro-motion platform stroke is controlled by a servo motor in conjunction with a grating ruler, and the repeat positioning accuracy is ±1μm. The X-axis stroke of the XZ two-dimensional micro-motion platform is 0mm-50mm, and the Z-axis stroke is 0mm-50mm. The picosecond laser and the tool edge are kept on the same vertical line by controlling the X-axis translation, and the focal length of the picosecond laser is adjusted by controlling the Z-axis translation, and the error during focusing is ±1μm.

[0260] Adjust the simulation parameters linked to the picosecond laser for enhancement, including picosecond laser pulse power, picosecond laser spot radius, picosecond laser pulse frequency, picosecond laser scanning speed, and picosecond laser impact times;

[0261] The picosecond laser processing parameter range settings specifically include: picosecond pulse laser power of 10W~30W, picosecond laser spot radius of 1~10μm, picosecond laser pulse frequency of 20KHZ~40KHZ, picosecond laser scanning speed of 500~1240mm / s, and picosecond laser impact times of 1~20 times. The working parameters of the picosecond laser are selected according to actual conditions.

[0262] Embodiment eight:

[0263] Further explanation is given on the basis of Example 7, the observation and evaluation of the secondary strengthening effect of the cutting edge specifically includes the following contents:

[0264] The laser strengthening effect of the cutting edge was observed and evaluated by two-dimensional confocal microscopy, including the following:

[0265] The two-dimensional confocal microscope observation parameters include tool arc radius, tool rake angle, tool clearance angle, tool length, and tool edge shape;

[0266] The method of judging whether the laser strengthening effect reaches the preset edge parameters uses a two-dimensional confocal microscope to take images, and performs image processing and analysis through the image processing library OpenCV in Python.

[0267] The enhancement effect is observed by two-dimensional confocal microscopy 2D-COSM. 2D-COSM can provide very high spatial resolution and can observe the tiny details and structures on the sample surface. It can achieve sub-nanometer resolution. 2D-COSM uses point scanning and reasonable focusing of the probe beam to effectively reduce the influence of background interference and scattered light. At the same time, it can perform three-dimensional scanning and depth detection of samples, such as Figure 5 The figure shows the microscopic morphology of the tool edge surface before processing. The tool arc radius is 20μm, the tool rake angle is 3°, the tool back angle is 5°, and the tool edge type is a waterfall edge.

[0268] like Figure 6As shown, the specific steps include: reading the image of the tool edge after strengthening, then performing image processing and analyzing its code, extracting the code of the edge shape and the tool tip arc radius, outputting different parameters according to the edge shape and the tool tip arc radius, returning the parameter result, and the deviation from the actual requirement is within ±5%, that is, it meets the requirements. If the strengthening effect does not match the simulation database matched for the first time, the Nelder-Mead method in the COMSOL gradient optimization algorithm is used to track the constraint surface, write an optimization program, modify multiple parameter targets, and output the modified parameters to the COMSOL database;

[0269] The strengthening effect was observed by two-dimensional confocal microscopy. The microscopic morphology of the cutting edge surface after strengthening is as follows: Figure 5 As shown, image processing and analysis are performed through the image processing library OpenCV in Python.

[0270] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0271] The specific values ​​of δ, ε, ∈, σ, etc. in the formula are generally determined by those skilled in the art according to actual conditions. The essence of the formula of the present application is to perform comprehensive analysis by weighted summation. Those skilled in the art collect multiple groups of sample data and set corresponding preset proportional coefficients for each group of sample data; substitute the preset proportional coefficients and the collected sample data into the formula, any four formulas constitute a set of four-variable linear equations, screen the calculated coefficients and take the average, and obtain the values ​​of δ, ε, ∈, σ, etc.;

[0272] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product. Those skilled in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented by computer software, electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software depends on the specific application and design constraints of the technical solution.

[0273] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0274] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A method for composite laser processing cutting edge based on dynamic parameter adjustment and real-time detection, characterized in that: The specific steps include: S1, constructing a COMSOL simulation database, wherein the COMSOL simulation database includes a COMSOL simulation model and definitions of laser processing parameters and structural parameter data of a cutting edge, using several groups of historical data of cutting edge laser processing to update the COMSOL simulation model to construct a complete simulation system, and executing the COMSOL simulation model to obtain an updated COMSOL simulation database; S2, obtaining structural parameter data of the cutting edge of the tool to be processed, wherein the structural parameter data of the cutting edge includes the geometric shape and material properties of the cutting edge, and creating a composite simulation model of the cutting edge of the tool to be processed in COMSOL software, wherein the composite simulation model covers a time scale from nanoseconds to picoseconds; S3, matching the created composite simulation model with the COMSOL simulation model in the COMSOL simulation database to obtain the COMSOL simulation model with the highest matching degree, inputting the preset cutting edge parameters into the COMSOL simulation model with the highest matching degree for simulation, thereby obtaining a simulation result, and matching the simulation result with the updated COMSOL simulation database to preliminarily determine the first laser processing parameter; S4, obtaining laser processing parameters and structural parameter data of the cutting edge of the tool to be processed, constructing a laser adjustment evaluation model P, and generating adjustment strategies for various input parameters in the COMSOL simulation model based on the value range of the adjustment evaluation model P, wherein the input parameters include the structural parameter data of the cutting edge and the laser processing parameters; S5, fine-tuning the first laser processing parameters according to the adjustment strategy, fixing the tool to be processed on the XZ two-dimensional micro-motion platform, and using nanosecond laser and picosecond laser in sequence to perform secondary strengthening on the cutting edge of the processing tool fixed on the XZ two-dimensional micro-motion platform according to the fine-tuned first laser processing parameters; S6, observe and evaluate the secondary strengthening effect of the cutting edge. If the preset cutting edge parameters are not reached, the adjustment strategy is corrected by adjusting the evaluation model P to update the fine-tuned first laser processing parameters to the second laser processing parameters. According to the second laser processing parameters, the cutting edge of the processing tool fixed on the XZ two-dimensional micro-motion platform is corrected and strengthened by using nanosecond laser and picosecond laser in sequence; S7, repeat step S6 until the strengthening effect of the cutting edge is observed and evaluated to reach the preset cutting edge parameters.

2. The method for composite laser processing cutting edge based on dynamic parameter adjustment and real-time detection according to claim 1, characterized in that: The preset cutting edge parameters are the expected structural parameter data of the tool to be processed, which include the tool arc radius, tool rake angle, tool clearance angle, tool length and tool edge shape, and each parameter is calibrated in turn to form the tool arc radius r1, tool rake angle Qj, tool clearance angle Hj, tool length Cd, and tool edge shape Rx; The preset cutting edge parameters also include material properties of the cutting edge, the material properties include the heat affected zone and the amount of erosion of the tool material strengthened by the composite laser, and the heat affected zone and the amount of erosion are calibrated as HAZ and MRV respectively, forming the heat affected zone HAZ and the amount of erosion MRV; The laser processing parameters specifically include pulse laser power, laser spot radius, laser pulse frequency, scanning speed and laser impact times, and are calibrated in sequence to form pulse laser power JGGl, laser spot radius JGBj, laser pulse frequency JGPl, scanning speed SMSd, and laser impact times JGCj; The composite simulation model includes the following contents: Construct a preset three-dimensional tool edge model, construct a two-dimensional heat transfer and deformation geometry physical field, set material physical parameters, set model initial conditions and boundary conditions, set multi-physics field coupling, construct mesh division, and study calculation and analysis; The matching of the created composite simulation model with the COMSOL simulation model in the COMSOL simulation database specifically includes the following contents: The matching retrieval specifically adopts loading the COMSOL library in MATLAB, using the API function of COMSOL to obtain the parameters and variables in the COMSOL model, using the isequal function in MATLAB to compare the input parameters with the parameters in the COMSOL database, and when the matched processing parameters are not completely corresponding to the database, the processed image and the image in the database are displayed by the imshow function in MATLAB, and the imabsd function calculates the absolute difference between the two images and represents the difference through visual quantification. When the difference calculated by the imabsdiff function in MATLAB is less than 5%, the parameters are input into the laser; and the input parameters are laser processing parameters, and the output is tool edge parameters.

3. The method for composite laser processing cutting edge based on dynamic parameter adjustment and real-time detection according to claim 2 is characterized in that: The laser processing parameters and the structural parameter data of the cutting edge of the tool to be processed are obtained, and the adjustment evaluation model P of the laser is constructed. Based on the value range of the adjustment evaluation model P, the adjustment strategy for various input parameters in the COMSOL simulation model is generated. The input parameters include the structural parameter data of the cutting edge and the laser processing parameters, which specifically include the following contents: Define the following functions respectively: After obtaining the data of pulse laser power, laser spot radius, laser pulse frequency, scanning speed and laser impact times, a laser adjustment function F (JGGl, JGBj, JGPl, SMSd, JGCj) is generated, and the result of laser processing parameter adjustment is outputted; the formula of laser adjustment function F (JGGl, JGBj, JGPl, SMSd, JGCj) is expressed as follows: in: (α, β, γ, δ, ò) are constants used to adjust the weights of each parameter; JGGl(t), JGBj(t), JGPl(t), SMSd(t), and JGCj(t) are the values ​​of pulsed laser power, laser spot radius, laser pulse frequency, scanning speed, and number of laser impacts at time (t), respectively; After obtaining the heat affected zone and ablation data of the material, the material influence function G (HAZ, MRV) is generated, and the influence of the material on the adjustment of laser processing parameters is outputted; the formula of the material influence function G (HAZ, MRV) is: in: (φ,ψ) are constants used to adjust the influence weights of the heat affected zone and the erosion amount; HAZ(t) and MRV(t) are the heat affected zone and the material removal volume at time (t), respectively; Measure the material volume V before cutting edge processing initial , and the volume of material after processing V final The data is analyzed to generate the erosion expression formula: MRV=V initial -V final Among them, V initial is the volume of material before processing, V final is the volume of material after processing; The calculation formula of HAZ is as follows: HAZ = C·t Where: HAZ is the depth of the heat affected zone, C is a constant related to the material and the welding process, t is the time during the welding process; After obtaining the arc radius, rake angle, clearance angle, length and edge type data of the edge, a geometric parameter function of the edge H(r1, Qj, Hj, Cd, Rx) is generated, and the geometric influence on the adjustment of laser processing parameters is output accordingly; The geometric parameter function of the edge H(r1, Qj, Hj, Cd, Rx) is expressed as: Where b1 and b2 are deviation factors, 0.21 ≤ b1 ≤ 0.68, 0.11 ≤ b2 ≤ 0.89; Based on the above definitions, an adjustment evaluation model P is constructed, and the calculation formula is: Where: P is the evaluation value of the adjustment evaluation model; T is the total time for laser processing a single workpiece; JGGl(t), JGBj(t), JGPl(t), SMSd(t), JGCj(t) are the pulsed laser power, laser spot radius, laser pulse frequency, scanning speed and number of laser shocks varying with time, respectively; HAZ(t), MRV(t) are the heat affected zone and the material removal volume varying with time; r1(t), Qj(t), Hj(t), Cd(t), Rx(t) are the arc radius, rake angle, clearance angle, length and edge type data of the edge varying with time; Range interpretation: The value range of formula P is defined as (0, 1). Based on the real-time and historical data of the laser power adjustment function, material influence function and geometric parameter function of the edge, the comparison threshold of the value range of formula P is set as Q, and the expected value E of the laser processing effect is determined according to the preset edge parameters. When (0 < P < Q), it means that the laser processing effect does not meet the expected value E, and the simulation parameters and laser processing parameters need to be further adjusted in sequence to optimize the strengthening effect and realize the continuous strengthening of the edge in the nanosecond-picosecond laser; When (P = Q), it means that the laser processing parameters just reach the preset edge parameter effect and just meet the expected value E, and the simulation parameters and laser processing parameters can be selectively adjusted in sequence for fine-tuning; When (Q < P < 1), it means that the laser processing effect exceeds the expected value E and the strengthening effect is good, and there is no need to adjust the simulation parameters and laser processing parameters in sequence.

4. The method for composite laser processing cutting edge based on dynamic parameter adjustment and real-time detection according to claim 3 is characterized in that: The adjustment strategy also includes dynamically adjusting the threshold Q, setting a feedback mechanism for laser processing parameters, and optimizing the current laser processing parameters; The dynamic adjustment of the threshold Q includes the following: a. Obtain the real-time and historical data of the laser processing parameters, dynamically adjust the threshold Q, and set the range of P value between 0.8 and 1 as the proximity range; If in continuous K edge processing operations, the evaluation model P is in the proximity range, automatically reduce Q by M1 units to reduce the adjustment range of the simulation parameters and laser processing parameters. Conversely, if in continuous K edge processing operations, 4 / 5K times of the P value is lower than Q and the edge meets the expected value E of the laser processing effect, increase the threshold Q by M2 units to increase the adjustment space; The setting of the feedback mechanism for laser processing parameters includes the following: b. When the laser processing parameters exceed the preset range, the model will automatically adjust other parameters to ensure that the operation is carried out within a safe range; Specifically set the laser processing parameters as follows: The predetermined range of the pulse laser power JGGl is expressed as JGGl∈[I min ,I max ]; Among them I min is the minimum pulse laser power, I max is the maximum pulse laser power; The predetermined range of the laser spot radius JGBj is expressed as JGBj∈[R min ,R max ]; Where R min is the minimum laser spot radius, R max is the maximum laser spot radius; The predetermined range of the laser pulse frequency JGPl is expressed as JGPl∈[F min ,F max ]; where F min is the minimum laser pulse frequency, F max is the maximum laser pulse frequency; The predetermined range of scanning speed SMSd is expressed as SMSd∈[V min ,V max ]; Where V min is the minimum scanning speed, V max is the maximum scanning speed; The predetermined range of laser shock times JGCj is expressed as JGCj∈[N min ,N max ]; Where N min is the minimum number of laser shocks, N max is the maximum number of laser shocks; First, define the adjustment model, and define the formula as follows: Z new =k×(X safe -X)+Z Wherein X is any one of I, R, F, V, and N, and Z is any one of JGGl, JGBj, JGPl, SMSd, and JGCj. new is the adjusted data, Z is the current data, and K is the adjustment coefficient; The optimization of the current laser processing parameters includes the following contents: c. Based on the laser power adjustment function, material influence function and cutting edge geometry parameter function, the historical processing data of the cutting edge is collected and used to guide and optimize the current laser processing parameter settings to improve the prediction accuracy and efficiency.

5. The method for composite laser processing cutting edge based on dynamic parameter adjustment and real-time detection according to claim 4 is characterized in that: The method of sequentially using nanosecond laser and picosecond laser to perform secondary strengthening on the cutting edge of a machining tool fixed on an XZ two-dimensional micro-motion platform specifically includes the following contents: During the first strengthening, the XZ two-dimensional micro-motion platform has an X-axis travel of 0mm-50mm and a Z-axis travel of 0mm-50mm. The nanosecond laser and the tool edge are kept on the same vertical line by controlling the X-axis translation, and the focal length of the nanosecond laser is adjusted by controlling the Z-axis translation. The simulation parameters configured and linked to the nanosecond laser for strengthening include nanosecond pulse laser power, nanosecond laser spot radius, nanosecond laser pulse frequency, nanosecond laser scanning speed, and nanosecond laser impact times.

6. The method for composite laser processing cutting edge based on dynamic parameter adjustment and real-time detection according to claim 5, characterized in that: During the second strengthening, the processing parameters of the picosecond laser are adjusted through the XZ two-dimensional micro-motion platform to strengthen the edge position for the second time; at the same time, the simulation parameters are adjusted to link to the picosecond laser for strengthening. The processing parameters are focal length parameters. The X-axis travel of the XZ two-dimensional micro-motion platform is 0mm-50mm, and the Z-axis travel is 0mm-50mm. The picosecond laser and the tool edge are kept on the same vertical line by controlling the X-axis translation, and the focal length of the picosecond laser is adjusted by controlling the Z-axis translation. The simulation parameters are adjusted and linked to the picosecond laser for enhancement, including picosecond laser pulse power, picosecond laser spot radius, picosecond laser pulse frequency, picosecond laser scanning speed, and picosecond laser impact times.

7. The method for composite laser processing cutting edge based on dynamic parameter adjustment and real-time detection according to claim 6, characterized in that: The observation and evaluation of the secondary strengthening effect of the cutting edge specifically includes the following contents: The laser hardening effect of the cutting edge was observed and evaluated by two-dimensional confocal microscopy. The two-dimensional confocal microscope observation parameters include tool arc radius, tool rake angle, tool clearance angle, tool length, and tool edge shape; To determine whether the laser strengthening effect reaches the preset edge parameters, a two-dimensional confocal microscope is used to take images, and the image processing library OpenCV in Python is used for image processing and analysis.

Images