Method for rapidly improving surface texture and roughness of cast aluminum alloy parts

Abstract

The application provides a method for rapidly improving the surface structure and roughness of a cast aluminum alloy part, and relates to the technical field of laser beam processing, and comprises the following steps: fixing the cast aluminum alloy part on a multi-axis movable object platform; using a continuous laser beam to scan the initial surface layer of the cast aluminum alloy part, and controlling the laser power and scanning speed to make adjacent molten pools continuously overlap to form a uniform molten layer; when the thickness of the uniform molten layer reaches a first preset thickness required for surface structure reconstruction, stopping the laser scanning; the uniform molten layer is self-cooled and solidified in a room temperature environment to form a solidified surface layer; wherein the solidified surface layer forms a submicron equiaxed crystal structure, and the roughness of the solidified surface layer is smaller than that of the initial surface layer. The method directly generates a submicron equiaxed crystal structure under the condition of room temperature self-solidification by accurately controlling the molten pool overlap and the cooling rate, and achieves the purpose of rapidly modifying the surface layer of the cast aluminum alloy part.

Description

Technical Field

[0001] This application relates to the field of laser beam processing technology, specifically to a method for rapidly improving the surface microstructure and roughness of cast aluminum alloy parts. Background Technology

[0002] Cast aluminum alloys are widely used in aerospace, automotive manufacturing, and high-end decorative parts. Their surface quality directly determines the fatigue strength, corrosion resistance, and assembly accuracy of the parts. Currently, the industry commonly uses shot peening to improve surface properties, but this technology has significant drawbacks:

[0003] Severe work hardening: High-speed shot impact causes surface lattice distortion, creating residual stress concentration zones and accelerating stress corrosion cracking.

[0004] Surface integrity damage: The pits and bumps formed after shot peening worsen the surface roughness, requiring subsequent grinding and polishing, which increases processing costs;

[0005] To overcome the above problems, existing technologies employ secondary processing such as surface heat treatment or mechanical grinding, but this prolongs the processing cycle. Especially for precision castings with curved surfaces / angles, such as turbocharger housings and engine manifolds, traditional methods struggle to quickly achieve uniform modification across the entire surface. Summary of the Invention

[0006] In view of the above-mentioned defects or deficiencies in the prior art, this application aims to provide a method for rapidly improving the surface microstructure and roughness of cast aluminum alloy parts, comprising the following steps:

[0007] The cast aluminum alloy parts are fixed on a multi-axis movable platform;

[0008] A continuous laser beam is used to scan the initial surface layer of the cast aluminum alloy part, and the laser power and scanning speed are controlled to make adjacent molten pools continuously overlap to form a uniform molten layer.

[0009] When the thickness of the uniform molten layer reaches the first preset thickness required for surface tissue reconstruction, the laser scanning is stopped.

[0010] The uniform molten layer self-cools and solidifies at room temperature to form a solidified surface layer; wherein the solidified surface layer forms a submicron-scale equiaxed crystal structure, and the roughness of the solidified surface layer is less than that of the initial surface layer.

[0011] According to the technical solution provided in this application, the spot shape of the continuous laser beam is a single ring, a double ring, or a composite shape of ring and circle;

[0012] Before scanning the initial surface layer of the cast aluminum alloy part with a continuous laser beam, the following steps are also included:

[0013] The three-dimensional morphology data of the initial surface layer of the cast aluminum alloy part are retrieved to obtain the distribution of the angled region, curved region and planar region in the initial surface layer;

[0014] The method of scanning the initial surface layer of the cast aluminum alloy part using a continuous laser beam includes the following steps:

[0015] Based on the regional distribution of the initial surface layer, the corresponding light spot shapes are matched for scanning, wherein the angled region matches the double ring, the curved surface region matches the composite shape, and the planar region matches the single ring.

[0016] According to the technical solution provided in this application, during the scanning of the initial surface layer of the cast aluminum alloy part by using a continuous laser beam, the position and orientation of the cast aluminum alloy part are adjusted by controlling the multi-axis motion of the carrying platform so that the continuous laser beam is perpendicularly incident on the surface in the angled region and / or the curved surface region.

[0017] According to the technical solution provided in this application, before scanning the initial surface layer of the cast aluminum alloy part with a continuous laser beam, the following steps are also included:

[0018] Obtain the initial surface roughness of the initial surface layer;

[0019] The process database is retrieved and traversed to obtain the initial laser parameters corresponding to the initial surface roughness. The process database includes multiple processing modes, surface roughness ranges corresponding to each processing mode, and processing parameters corresponding to each processing mode. The processing parameters include power range, scanning speed, and penetration depth requirements. The initial laser parameters are the processing parameters corresponding to the processing mode in which the initial surface roughness falls within the surface roughness range.

[0020] The method of scanning the initial surface layer of the cast aluminum alloy part using a continuous laser beam includes the following steps:

[0021] Based on the power range and scanning speed in the initial laser parameters, the continuous laser beam is activated to scan the initial surface layer of the cast aluminum alloy part.

[0022] According to the technical solution provided in this application, controlling the laser power and scanning speed to continuously overlap adjacent molten pools to form a uniform molten layer includes the following steps:

[0023] Real-time monitoring of molten pool width and solidification front status;

[0024] The laser power and / or the scanning speed are dynamically adjusted to simultaneously maintain: the ratio of the line spacing to the molten pool width is maintained within the critical range for inducing dendrite nucleation, and the overlap rate of adjacent molten pools is greater than or equal to a first preset threshold. The critical range must satisfy the requirement that the melt at the leading edge of the subsequent molten pool penetrates the solidification micro-region of the previous molten pool, inducing dendrites as heterogeneous nucleation points; the line spacing is the center distance between adjacent laser scanning paths.

[0025] Repeat the above steps until the thickness of the uniform molten layer reaches the first preset thickness, which is the melting depth requirement in the initial laser parameters.

[0026] According to the technical solution provided in this application, the method further includes determining whether the thickness of the uniform molten layer reaches a first preset thickness;

[0027] Determining whether the thickness of the uniform molten layer has reached the first preset thickness includes the following steps:

[0028] If the thickness of each detected unit of the uniform molten layer reaches the first preset thickness, it is determined that the thickness of the uniform molten layer has reached the first preset thickness; all the detected units constitute the entire uniform molten layer.

[0029] According to the technical solution provided in this application, the method further includes the following steps:

[0030] During the laser scanning process, the theoretical melting depth of each detected unit is calculated in real time based on the laser power, the scanning speed, and the material properties; the material properties are the thermal diffusivity of the cast aluminum alloy part.

[0031] The displacement and rotation angle of each axis of the platform are obtained, and the theoretical melting depth is converted into the vertical melting depth in the part coordinate system through a coordinate transformation matrix. The vertical melting depth is the thickness of the unit being tested.

[0032] According to the technical solution provided in this application, the detected unit is set in the following manner:

[0033] During laser scanning, a continuous scanning path segment in which the laser power and the scanning speed remain constant is defined as a detected unit;

[0034] The length of the detected unit is dynamically adjusted according to the processing path, and the lengths of adjacent detected units are allowed to be unequal.

[0035] According to the technical solution provided in this application, the theoretical melting depth of the detected unit is calculated by a melting depth calculation model. The melting depth calculation model characterizes the relationship between the theoretical melting depth and the laser power, the scanning speed, the material thermal diffusivity, and the thermal input coefficient.

[0036] After calculating the theoretical melting depth of each detected unit in real time based on the laser power, scanning speed, and material properties during the laser scanning process, the method further includes the following steps:

[0037] The verification information of the unit under test is retrieved, wherein the verification information is the acoustic emission signal of the unit under test acquired in real time during the laser scanning process by an acoustic emission sensor;

[0038] The characteristic values ​​of the acoustic emission signal in the 20-200kHz frequency band are extracted, and the characteristic values ​​include the peak value of the dominant frequency, the signal energy integral value, and the kurtosis coefficient.

[0039] Based on the characteristic values, the measured melt depth deviation rate of the detected unit is obtained;

[0040] If the measured melt depth deviation rate is less than or equal to the second preset threshold, the melt depth calculation model is continuously used to calculate the theoretical melt depth of the next detected unit.

[0041] According to the technical solution provided in this application, after obtaining the measured melt depth deviation rate of the detected unit based on the feature value, the method further includes the following steps:

[0042] If the absolute value of the measured melt depth deviation rate is greater than the second preset threshold, the heat input coefficient is corrected based on the measured melt depth deviation rate to obtain the corrected melt depth calculation model.

[0043] The theoretical depth of the next detected unit is calculated using the modified depth of penetration calculation model.

[0044] Compared with the prior art, the beneficial effects of this application are as follows: This application directly generates submicron-level equiaxed grain structure (0.2μm-2μm) under room temperature self-solidification conditions by precisely controlling the overlap of the molten pool and the cooling rate. This is more than 10 times finer than the micron-level fragmented grains (5-10μm) after shot peening, which significantly improves fatigue resistance. At the same time, the flow and spreading effect of the molten layer reduces the surface roughness. The typical roughness can be reduced by 3-4 levels, eliminating the need for subsequent polishing processes and achieving the purpose of rapid modification. Moreover, this method only changes the surface microstructure of the cast aluminum alloy, and its composition remains unchanged. In addition, this application also has high-speed processing capabilities, which accelerates the progress of surface modification from another dimension: multi-axis platform collaborative laser scanning achieves full coverage of complex curved surfaces, shortens the processing time of a single part, and the adaptive melt depth control and real-time verification system avoids manual parameter adjustment, improving the pass rate. By rotating the platform in real time, it ensures that the laser is always perpendicularly incident in the angle / curved surface area, solving the problem of uniform processing of dead corners such as deep cavities and narrow grooves, forming a uniform equiaxed crystal layer on the entire surface, eliminating the edge effect and heat-affected zone gradient of traditional processes, and rapidly improving the surface layer structure of the parts. Attached Figure Description

[0045] Figure 1 A flowchart illustrating the steps of the method for rapidly improving the surface microstructure and roughness of cast aluminum alloy parts provided in this application. Detailed Implementation

[0046] The present application will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings.

[0047] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0048] Example 1

[0049] As mentioned in the background section, this application proposes a method for rapidly improving the surface microstructure and roughness of cast aluminum alloy parts, addressing the problems in the prior art. Figure 1 As shown, it includes the following steps:

[0050] S1. Fix the cast aluminum alloy parts onto a multi-axis moving platform; specifically, fix the cast aluminum alloy parts (such as wheel hubs and engine housings) onto a six-degree-of-freedom platform using a custom fixture. This platform must have X / Y / Z translation and three-axis rotation functions (±180°).

[0051] S2. A continuous laser beam is used to scan the initial surface layer of the cast aluminum alloy part, and the laser power and scanning speed are controlled to make adjacent molten pools continuously overlap to form a uniform molten layer.

[0052] Furthermore, during the scanning of the initial surface layer of the cast aluminum alloy part using a continuous laser beam, the orientation of the cast aluminum alloy part is adjusted by controlling the multi-axis motion of the platform, so that the continuous laser beam is perpendicularly incident on the surface in the angled region and / or the curved surface region.

[0053] Furthermore, before scanning the initial surface layer of the cast aluminum alloy part with a continuous laser beam, the following steps are also included:

[0054] Obtain the initial surface roughness of the initial surface layer;

[0055] The process database is retrieved and traversed to obtain the initial laser parameters corresponding to the initial surface roughness. The process database includes multiple processing modes, surface roughness ranges corresponding to each processing mode, and processing parameters corresponding to each processing mode. The processing parameters include power range, scanning speed, and penetration depth requirements. The initial laser parameters are the processing parameters corresponding to the processing mode in which the initial surface roughness falls within the surface roughness range.

[0056] The method of scanning the initial surface layer of the cast aluminum alloy part using a continuous laser beam includes the following steps:

[0057] Based on the power range and scanning speed in the initial laser parameters, the continuous laser beam is activated to scan the initial surface layer of the cast aluminum alloy part.

[0058] Specifically, considering the surface condition grading, the initial roughness (Ra) directly reflects the depth of surface defects (such as porosity and cracks). A high Ra value requires a deeper molten layer reconstruction. The laser power and scanning speed are dynamically allocated based on the Ra value to ensure the molten depth accurately covers the defect layer. Therefore, this implementation first uses a white light interferometer or laser profilometer to obtain the initial surface roughness: 5×5 grid points are selected on the part surface, avoiding the edges by 10mm. Each point is measured 3 times, and the average value is taken. The final Ra value is the average of all grid points. The process database is shown in Table 1 below:

[0059] Table 1

[0060]

[0061] Furthermore, the step of controlling the laser power and scanning speed to continuously overlap adjacent molten pools to form a uniform molten layer includes the following steps:

[0062] Real-time monitoring of the molten pool width and solidification front state; specifically, the solidification front state is the solid-liquid two-phase coexistence zone at the edge of the molten pool, characterized by a temperature gradient (>100 K / mm) and dendrite growth morphology (cellular / columnar). The location and morphology of the semi-solid region are identified using a dual-color infrared thermometer. Temperature signal processing: The temperature distribution between the solidus line (Ts=577℃) and the liquidus line (Tl=660℃) is extracted and processed using a formula... Calculate the transverse temperature gradient dT / dx of the molten pool, where W represents the width of the molten pool and T... 凝固前沿 The temperature represents the liquid-solid boundary temperature, and Tcenter represents the highest temperature at the center of the molten pool. The solidification front state is obtained based on the range of the lateral temperature gradient dT / dx of the molten pool. A dT / dx range (K / mm) >150 represents a planar interface, 50-150 represents cellular dendrites, and <50 represents coarse columnar dendrites. The molten pool width is monitored using a high-speed CMOS camera.

[0063] The laser power and / or the scanning speed are dynamically adjusted to simultaneously maintain: the ratio of the line spacing to the molten pool width is maintained within the critical range for inducing dendrite nucleation, and the overlap rate of adjacent molten pools is greater than or equal to a first preset threshold. The critical range must satisfy the requirement that the melt at the leading edge of the subsequent molten pool penetrates the solidification micro-region of the previous molten pool, inducing dendrites as heterogeneous nucleation points; the line spacing is the center distance between adjacent laser scanning paths.

[0064] Repeat the above steps until the thickness of the uniform molten layer reaches the first preset thickness, which is the melting depth requirement in the initial laser parameters.

[0065] Specifically, the overlap rate of adjacent molten pools is calculated using the molten pool width and line spacing, generally maintained within the range of 0.3-0.8 mm. This coordinates with the line spacing to ensure the overlap rate between molten pools. For example, during scanning, if W=0.65 mm and line spacing D=0.15 mm are detected, the overlap rate η is calculated as (0.65-0.15) / 0.65=76.9%. Then, the transverse temperature gradient of the molten pool is obtained through temperature field acquisition to determine the dendrite morphology. By adjusting the laser power and / or scanning speed in real time, three objectives are achieved: Objective 1: Maintain the overlap rate η≥0.6 (first preset threshold); Objective 2: Control the line spacing ratio D / W=0.4-0.6 (critical range); Objective 3: Ensure the solidification front is cellular dendrites (dT / dx=50-150 K / mm). For example, when η<0.6, the scanning speed is reduced by 10% or the power is increased by 5%, increasing the molten pool width W to improve coverage continuity. When D / W > 0.6, the line spacing D decreases to 0.8W, shortening the scan spacing and increasing the penetration depth of the subsequent melt pool. When columnar dendrites (dT / dx < 50), the control power is increased by 5% and the scan speed is decreased by 5% to increase the heat input, change the temperature gradient, and suppress columnar crystal growth.

[0066] Specifically, this embodiment controls the thermo-mechanical coupling effect of adjacent molten pools: the high-temperature melt (1600-1800℃) of the downstream molten pool impacts the semi-solid zone (solidity 40-60%) of the upstream molten pool, mechanically breaking the incompletely solidified dendritic network. The resulting micron-sized crystal fragments serve as nucleation nuclei, enabling the melt to trigger equiaxed crystal nucleation when it is 5-8K below the equilibrium solidification point, thus achieving microstructure refinement.

[0067] S3. When the thickness of the uniform molten layer reaches the first preset thickness required for surface structure reconstruction, stop the laser scanning;

[0068] S4. The uniform molten layer self-cools and solidifies at room temperature to form a solidified surface layer; wherein the solidified surface layer forms a submicron-scale equiaxed crystal structure, and the roughness of the solidified surface layer is less than that of the initial surface layer.

[0069] Specifically, the technical principle of this method is explained below: Surface reconstruction is achieved through laser ultrafast melting followed by ultra-high-speed solidification. Its physical mechanism involves three key processes: Melt layer leveling effect: High-power laser (0.8-6 kW) melts micron-sized protrusions on the surface into liquid metal, which flows towards the pitted areas under surface tension, directly filling surface defects (such as pores and shrinkage), reducing the original roughness. Non-equilibrium solidification mechanism: The molten layer achieves >10⁻¹⁰ solidification at room temperature through forced gas cooling (nitrogen flow rate 20-50 L / min). 4 The ultra-high cooling rate of K / s inhibits dendrite growth in the aluminum matrix, promotes uniform nucleation, and forms submicron-sized equiaxed crystals (0.2-2μm). Precise control of the heat-affected zone: By limiting the molten layer thickness to 50-300 μm (i.e., the first preset thickness), it ensures that heat is not excessively conducted to the matrix, avoiding degradation of the matrix's microstructure and properties.

[0070] The following describes the method steps: Step 1, Part Fixing: Surface Pretreatment: Ultrasonic cleaning of the part with acetone for 5 minutes to remove oil and oxide layers, followed by drying with compressed air to ensure no residue remains on the surface. Clamping and Positioning: Place the part on a six-axis platform (e.g., a KUKA KR60HA robotic arm integrated CNC rotary table) and fix it with a vacuum chuck to prevent displacement during machining.

[0071] Step 2, Laser Scanning: Initial Parameter Setting: Measure the initial surface roughness (e.g., Ra = 6.176 μm measured by a white light interferometer). Retrieve the process database and match "Mode C" corresponding to the roughness range > 5.0 μm: Laser power: 5.0 kW (range 4.0-6.0 kW), scanning speed: 1.2 m / s (range 0.5-1.5 m / s), target melt depth: 250 μm (range 200-300 μm, i.e., the first preset thickness); Dynamic Control of the Melt Pool: Real-time Monitoring: Melt Pool Width: Capture the melt pool image using a 2000fps high-speed CMOS camera, and calculate the width W using an edge detection algorithm; Solidification Front: Monitor the temperature gradient using a dual-color infrared thermometer to identify the semi-solid region (solid-liquid phase interval). Dynamic adjustment rules: The overlap rate is calculated using the following formula: η = (W - D) / W (D is the line spacing, preset to 0.15 mm). If η < 0.6 (i.e., risk of molten pool discontinuity), the scanning speed is reduced by 10% (e.g., 1.2 m / s → 1.08 m / s) or the power is increased by 5% (5.0 kW → 5.25 kW). Maintaining dendrite fragment nucleation conditions: The line spacing ratio D / W is strictly controlled between 0.4 and 0.6. The underlying principle is that the downstream molten pool intrudes into the solidification micro-region of the upstream molten pool by >20 μm, mechanically peeling off dendrite fragments (size 1-5 μm). These fragments act as heterogeneous nucleation points, promoting grain refinement. Scan execution: The galvanometer performs a Zigzag path scan with a 0.15 mm line spacing (covering an area ≥300 mm × 300 mm). The default laser spot shape is a single ring (planar area), and the power density distribution is uniform.

[0072] Step 3: Determining the thickness of the molten layer: Termination conditions: You can choose to use an infrared thermal imager to monitor the depth of the molten pool in real time and turn off the laser when the target molten depth of 250μm is reached. Alternatively, you can control the melting time or determine the thickness using the method described later.

[0073] Step 4: Room temperature self-cooling: Immediately after the laser stops, open the annular nitrogen nozzle (50 mm from the surface), with an airflow velocity of 30 m / s and a cooling rate > 1.2 × 10⁻⁶ m / s. 4 K / s. Liquid metal skips the dendrite growth region and directly forms equiaxed crystals under ultra-high cooling rates. The grain boundaries are intact and there is no precipitate agglomeration (SEM-EDS verification, taking A356 cast aluminum alloy as an example, the composition is still composed of α-Al and Si two phases).

[0074] In a preferred embodiment, the spot shape of the continuous laser beam is a single ring, a double ring, or a composite shape of ring and circle;

[0075] Before scanning the initial surface layer of the cast aluminum alloy part with a continuous laser beam, the following steps are also included:

[0076] The three-dimensional morphology data of the initial surface layer of the cast aluminum alloy part are retrieved to obtain the distribution of the angled region, curved region and planar region in the initial surface layer;

[0077] Specifically, point cloud data is acquired through a laser scanner, and curvature analysis is used to obtain angular regions, curved regions, and planar regions. Regions with a curvature radius greater than 1000 mm are defined as planar regions, regions with a curvature radius between 50 and 1000 mm are defined as curved regions, and regions with an angle between two planes less than 90 degrees are defined as angular regions.

[0078] The method of scanning the initial surface layer of the cast aluminum alloy part using a continuous laser beam includes the following steps:

[0079] Based on the regional distribution of the initial surface layer, the corresponding light spot shapes are matched for scanning, wherein the angled region matches the double ring, the curved surface region matches the composite shape, and the planar region matches the single ring.

[0080] Specifically, in planar regions, a single-ring pattern is used, where the energy distribution is high at the edges and weak at the center. Using a single-ring spot in planar regions avoids overheating at the center and ensures uniform melt depth. In angular regions, a double-ring pattern is used, where the energy distribution is bimodal. Using a single-ring spot in planar regions counteracts heat accumulation and prevents overheating at the angle. In curved regions, a composite pattern is used, where the energy distribution is proportionally adjustable (e.g., 70% ring + 30% circle). Using a composite pattern in curved regions can adapt to curvature changes and maintain melt pool stability. For example: in high curvature regions (R<30mm): convex surfaces dissipate heat easily, requiring high energy to maintain melt depth → ring:circle = 70%:30%; in medium curvature regions (30mm≤R<80mm): balancing heat input → ring:circle = 80%:20%; in low curvature regions (R≥80mm): approximately planar, weak edge effect → ring:circle = 90%:10%.

[0081] Specifically, the following is another implementation method that uses an infrared thermal imager to monitor the depth of the molten pool in real time and then makes a judgment. The above implementation method uses direct measurement by the instrument, while this implementation method uses calculation to obtain the depth. Different adaptive monitoring methods can be used in different scenarios.

[0082] In a preferred embodiment, the method further includes determining whether the thickness of the uniform molten layer reaches a first preset thickness;

[0083] Determining whether the thickness of the uniform molten layer has reached the first preset thickness includes the following steps:

[0084] If the thickness of each detected unit of the uniform molten layer reaches the first preset thickness, it is determined that the thickness of the uniform molten layer has reached the first preset thickness; all the detected units constitute the entire uniform molten layer.

[0085] Furthermore, the method also includes the following steps:

[0086] During the laser scanning process, the theoretical melting depth of each detected unit is calculated in real time based on the laser power, the scanning speed, and the material properties; the material properties are the thermal diffusivity of the cast aluminum alloy part.

[0087] The displacement and rotation angle of each axis of the platform are obtained, and the theoretical melting depth is converted into the vertical melting depth in the part coordinate system through a coordinate transformation matrix. The vertical melting depth is the thickness of the unit being tested.

[0088] Furthermore, the detected unit is configured in the following manner:

[0089] During laser scanning, a continuous scanning path segment in which the laser power and the scanning speed remain constant is defined as a detected unit;

[0090] The length of the detected unit is dynamically adjusted according to the processing path, and the lengths of adjacent detected units are allowed to be unequal.

[0091] In a preferred embodiment, the theoretical melting depth of the detected unit is calculated by a melting depth calculation model, wherein the melting depth calculation model characterizes the relationship between the theoretical melting depth and laser power, scanning speed, material thermal diffusivity, and thermal input coefficient.

[0092] After calculating the theoretical melting depth of each detected unit in real time based on the laser power, scanning speed, and material properties during the laser scanning process, the method further includes the following steps:

[0093] The verification information of the unit under test is retrieved, wherein the verification information is the acoustic emission signal of the unit under test acquired in real time during the laser scanning process by an acoustic emission sensor;

[0094] Specifically, the sensor arrangement for acoustic emission signal acquisition is as follows: a piezoelectric ceramic sensor (frequency response 20-400kHz) is mounted on the platform fixture.

[0095] The characteristic values ​​of the acoustic emission signal in the 20-200kHz frequency band are extracted, and the characteristic values ​​include the peak value of the dominant frequency, the signal energy integral value, and the kurtosis coefficient.

[0096] Based on the characteristic values, the measured melt depth deviation rate of the detected unit is obtained;

[0097] If the measured melt depth deviation rate is less than or equal to the second preset threshold, the melt depth calculation model is continuously used to calculate the theoretical melt depth of the next detected unit.

[0098] Specifically, the melting depth calculation model is as follows: ,in, Indicates theoretical melting depth. This represents the overall correction factor. , This represents the initial heat input coefficient (default 0.85). x (R) represents the curvature compensation coefficient, for convex surfaces. x (R) = 1.2 - 0.2e -0.05R concave surface x (R) = 0.8 + 0.2e -0.05R P represents laser power, v represents scanning speed, and T represents laser speed. m T0 represents the melting point, and T0 represents room temperature. denoted by , where represents the thermal diffusivity of the material, and t represents the laser dwell time.

[0099] Specifically, based on the characteristic value, the measured melt depth deviation rate is obtained using the following formula:

[0100] ;

[0101] Where f1 represents the peak clock frequency, E 1 represents the signal energy integral value. K 1 represents the kurtosis coefficient, and 128kHz represents the dominant frequency reference value, which is the characteristic frequency of the molten pool oscillation and is related to the molten pool size and surface tension. 3.2 is the energy integral reference value, which is the total energy of the acoustic emission signal and reflects the intensity of the dynamic behavior of the molten pool. 3.2 is the kurtosis reference value, which is the sharpness of the signal pulse and reflects the sudden event of dendrite breakage. Under ideal melting depth, dendrite breakage is uniform and the kurtosis is stable at 3.2.

[0102] Furthermore, after obtaining the measured melt depth deviation rate of the detected unit based on the feature value, the method further includes the following steps:

[0103] If the absolute value of the measured melt depth deviation rate is greater than the second preset threshold, the heat input coefficient is corrected based on the measured melt depth deviation rate to obtain the corrected melt depth calculation model.

[0104] The theoretical depth of the next detected unit is calculated using the modified depth of penetration calculation model.

[0105] Specifically, the first preset threshold can be selected as 5%. If the measured melt depth deviation rate is less than or equal to 5%, it indicates that the melt depth calculation model is reliable and can continue to be used to calculate the theoretical melt depth. When the measured melt depth deviation rate is greater than 5%, it indicates that the melt depth calculation model is unreliable, and the heat input coefficient is reduced to compensate for overmelting. When the measured melt depth deviation rate is less than -5%, it indicates that the melt depth calculation model is unreliable, and the heat input coefficient is increased to compensate for undermelting.

[0106] This embodiment is used in scenarios where the thickness of the molten pool is limited by infrared thermal imagers, such as highly reflective surfaces where optical obstruction prevents measurement. It uses an acoustic emission characteristic molten depth inversion model to monitor the molten depth and achieve the goal of surface refinement.

[0107] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. The above descriptions are only preferred embodiments of this application. It should be noted that due to the limitations of written expression, while there are objectively infinite specific structures, those skilled in the art can make several improvements, modifications, or changes without departing from the principles of this invention, and can also combine the above technical features in an appropriate manner. These improvements, modifications, changes, or combinations, or the direct application of the inventive concept and technical solution to other situations without modification, should all be considered within the scope of protection of this application.

Claims

1. A method for rapidly improving the surface microstructure and roughness of cast aluminum alloy parts, characterized in that, Includes the following steps: The cast aluminum alloy parts are fixed on a multi-axis movable platform; A continuous laser beam is used to scan the initial surface layer of the cast aluminum alloy part, and the laser power and scanning speed are controlled to make adjacent molten pools continuously overlap to form a uniform molten layer. When the thickness of the uniform molten layer reaches the first preset thickness required for surface tissue reconstruction, the laser scanning is stopped. The uniform molten layer self-cools and solidifies at room temperature to form a solidified surface layer; wherein the solidified surface layer forms a submicron-scale equiaxed crystal structure, and the roughness of the solidified surface layer is less than that of the initial surface layer. The spot shape of the continuous laser beam is a single ring, a double ring, or a combination of ring and circle. Before scanning the initial surface layer of the cast aluminum alloy part with a continuous laser beam, the following steps are also included: The three-dimensional morphology data of the initial surface layer of the cast aluminum alloy part are retrieved to obtain the distribution of the angled region, curved region and planar region in the initial surface layer; The method of scanning the initial surface layer of the cast aluminum alloy part using a continuous laser beam includes the following steps: Based on the regional distribution of the initial surface layer, the corresponding light spot shapes are matched for scanning, wherein the angled region matches the double ring, the curved surface region matches the composite shape, and the planar region matches the single ring.

2. The method for rapidly improving the surface microstructure and roughness of cast aluminum alloy parts according to claim 1, characterized in that: During the scanning of the initial surface layer of the cast aluminum alloy part using a continuous laser beam, the orientation of the cast aluminum alloy part is adjusted by controlling the multi-axis motion of the platform so that the continuous laser beam is perpendicularly incident on the surface in the angled region and / or the curved surface region.

3. The method for rapidly improving the surface microstructure and roughness of cast aluminum alloy parts according to claim 1, characterized in that: Before scanning the initial surface layer of the cast aluminum alloy part with a continuous laser beam, the following steps are also included: Obtain the initial surface roughness of the initial surface layer; The process database is retrieved and traversed to obtain the initial laser parameters corresponding to the initial surface roughness. The process database includes multiple processing modes, surface roughness ranges corresponding to each processing mode, and processing parameters corresponding to each processing mode. The processing parameters include power range, scanning speed, and penetration depth requirements. The initial laser parameters are the processing parameters corresponding to the processing mode in which the initial surface roughness falls within the surface roughness range. The method of scanning the initial surface layer of the cast aluminum alloy part using a continuous laser beam includes the following steps: Based on the power range and scanning speed in the initial laser parameters, the continuous laser beam is activated to scan the initial surface layer of the cast aluminum alloy part.

4. The method for rapidly improving the surface microstructure and roughness of cast aluminum alloy parts according to claim 3, characterized in that: The process of controlling laser power and scanning speed to ensure continuous overlap of adjacent molten pools to form a uniform molten layer includes the following steps: Real-time monitoring of molten pool width and solidification front status; The laser power and / or the scanning speed are dynamically adjusted to simultaneously maintain: the ratio of the line spacing to the molten pool width is maintained within the critical range for inducing dendrite nucleation, and the overlap rate of adjacent molten pools is greater than or equal to a first preset threshold. The critical range must satisfy the requirement that the melt at the leading edge of the subsequent molten pool penetrates the solidification micro-region of the previous molten pool, inducing dendrites as heterogeneous nucleation points; the line spacing is the center distance between adjacent laser scanning paths. Repeat the above steps until the thickness of the uniform molten layer reaches the first preset thickness, which is the melting depth requirement in the initial laser parameters.

5. The method for rapidly improving the surface microstructure and roughness of cast aluminum alloy parts according to claim 1, characterized in that: The method also includes determining whether the thickness of the uniform molten layer reaches a first preset thickness; Determining whether the thickness of the uniform molten layer has reached the first preset thickness includes the following steps: If the thickness of each detected unit of the uniform molten layer reaches the first preset thickness, it is determined that the thickness of the uniform molten layer has reached the first preset thickness; all the detected units constitute the entire uniform molten layer.

6. The method for rapidly improving the surface microstructure and roughness of cast aluminum alloy parts according to claim 5, characterized in that: The method also includes the following steps: During the laser scanning process, the theoretical melting depth of each detected unit is calculated in real time based on the laser power, the scanning speed, and the material properties; the material properties are the thermal diffusivity of the cast aluminum alloy part. The displacement and rotation angle of each axis of the platform are obtained, and the theoretical melting depth is converted into the vertical melting depth in the part coordinate system through a coordinate transformation matrix. The vertical melting depth is the thickness of the unit being tested.

7. The method for rapidly improving the surface microstructure and roughness of cast aluminum alloy parts according to claim 5, characterized in that: The detected unit is configured in the following manner: During laser scanning, a continuous scanning path segment in which the laser power and the scanning speed remain constant is defined as a detected unit; The length of the detected unit is dynamically adjusted according to the processing path, and the lengths of adjacent detected units are allowed to be unequal.

8. The method for rapidly improving the surface microstructure and roughness of cast aluminum alloy parts according to claim 6, characterized in that: The theoretical melting depth of the detected unit is calculated by a melting depth calculation model, which characterizes the relationship between the theoretical melting depth and the laser power, the scanning speed, the material thermal diffusivity, and the thermal input coefficient. After calculating the theoretical melting depth of each detected unit in real time based on the laser power, scanning speed, and material properties during the laser scanning process, the method further includes the following steps: The verification information of the unit under test is retrieved, wherein the verification information is the acoustic emission signal of the unit under test acquired in real time during the laser scanning process by an acoustic emission sensor; The characteristic values ​​of the acoustic emission signal in the 20-200kHz frequency band are extracted, and the characteristic values ​​include the peak value of the dominant frequency, the signal energy integral value, and the kurtosis coefficient. Based on the characteristic values, the measured melt depth deviation rate of the detected unit is obtained; If the measured melt depth deviation rate is less than or equal to the second preset threshold, the melt depth calculation model is continuously used to calculate the theoretical melt depth of the next detected unit.

9. The method for rapidly improving the surface microstructure and roughness of cast aluminum alloy parts according to claim 8, characterized in that: After obtaining the measured melt depth deviation rate of the detected unit based on the feature value, the method further includes the following steps: If the absolute value of the measured melt depth deviation rate is greater than the second preset threshold, the heat input coefficient is corrected based on the measured melt depth deviation rate to obtain the corrected melt depth calculation model. The theoretical depth of the next detected unit is calculated using the modified depth of penetration calculation model.

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