Involute tooth surface laser non-centering discrete strengthening processing method and system based on binocular vision

Abstract

The invention provides an involute tooth surface laser non-centering discrete strengthening processing method and system based on binocular vision, and the method comprises the following steps: carrying out the image collection and three-dimensional reconstruction of a tooth profile of a to-be-processed gear through a binocular vision system, and obtaining the three-dimensional point cloud data of the tooth surface; processing the three-dimensional point cloud data, and fitting to obtain an involute tooth profile model; based on the involute tooth profile model, a processing path point set of laser discrete strengthening is planned on the tooth surface; the laser head is controlled to deviate from the initial position of the vertical center line of the gear, and a laser beam is emitted at an incident angle inclined to the normal direction of the tooth surface; and performing laser discrete strengthening on the tooth surface point by point according to the processing path point set. According to the method, the technical bottlenecks that in traditional laser strengthening, the lap joint area is qualitative, the machining efficiency is low, and adjacent teeth interfere with one another are effectively solved, and the uniformity and consistency of the tooth surface strengthening effect and the overall fatigue performance of the gear are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of gear processing and strengthening, and in particular to a method and system for laser non-centering discrete strengthening of involute tooth surfaces based on binocular vision. Background Technology

[0002] Traditional gear surface heat treatment involves rapid cooling of the gear surface to achieve high hardness and wear resistance. However, this process results in significant deformation, leading to excessive grinding allowance, low grinding efficiency, and high costs. Traditional gear manufacturing methods involve carburizing low-carbon steel followed by quenching and tempering, or chemical heat treatment. While these processes currently meet performance requirements, they are lengthy, energy-intensive, costly, and cause environmental pollution.

[0003] Laser strengthening of gear surfaces involves rapidly irradiating the workpiece surface with a high-energy-density laser beam. The strengthened area instantly absorbs the light energy and converts it into heat, causing a rapid rise in temperature in the laser-affected zone. This results in a distortion-strengthening effect, significantly increasing the material's strength. After laser strengthening and quenching, gears exhibit a hard surface, soft root, high wear resistance, minimal deformation, and a short production cycle. This simplifies the manufacturing process, improves efficiency, reduces costs, and expands the range of gear materials available.

[0004] Existing technology discloses a laser strengthening method for gear tooth surfaces. This method involves forming a protective layer on the area to be strengthened on the tooth surface to absorb laser light energy. Multiple laser scans are performed on the area to be strengthened according to preset parameters, ensuring that the overlap rate of the laser spots between adjacent scans is within a certain range. During the laser scanning process, a constraint layer is formed on the side of the protective layer away from the tooth surface. The protective layer is then removed to form the strengthened area. Its advantages include ensuring uniform distribution of stress and hardness, guaranteeing the strengthening effect of the gear. Its disadvantages include the need for multiple scans of the strengthened area during the strengthening process, resulting in relatively low efficiency and high cost.

[0005] Existing technology discloses a laser shock peening (LSP) method for machining gear teeth that considers the actual tooth surface morphology. By introducing a tooth surface equation during the LSP process, a more accurate LSP trajectory can be obtained. Its advantages include that accurate gear spatial relationships can more effectively avoid interference between adjacent tooth tips and the laser beam path, preventing ablation of adjacent tooth tips during the impact process. Its disadvantages include the difficulty in maintaining a constant angle λ between the laser direction and the tooth surface normal, and the difficulty in uniformly distributing residual compressive stress on the tooth surface.

[0006] Existing technology discloses a laser processing method for microtexturing gear tooth surfaces. By establishing a mapping relationship between pulsed laser processing parameters and the shape and size of the microtexture on the tooth surface, a laser processing device capable of adapting to various tooth profile shapes is constructed to obtain a precise processing technology for the microtexture on the gear surface. A lifting drive device is used to achieve the lifting of the platform relative to the base. Its advantages include simple processing technology, strong controllability, adaptability to different types of gears, and no pollution. Its disadvantages are that, limited by the special geometry and material properties of gears, most microtexturing processing methods are not suitable for processing microtextures on gear surfaces.

[0007] In summary, although numerous experts and scholars have conducted extensive research on laser strengthening of tooth surfaces, problems still exist, such as morphological degradation of the overlapping area, low efficiency over large areas, and unstrengthened areas due to laser interference between adjacent teeth. A complete technical system for solving laser non-centering discrete strengthening has not yet been established, encompassing design and processing. The aforementioned technical solutions are costly, lack applicability, and all have problems in engineering applications, failing to fully achieve laser non-centering discrete strengthening. Summary of the Invention

[0008] To address the shortcomings of existing technologies, this invention provides a laser non-centering discrete strengthening method for involute tooth surfaces based on binocular vision. By performing real-time three-dimensional scanning and involute model fitting on each tooth, precise compensation is achieved for individual gear manufacturing errors and system installation errors. This allows the laser strengthening path to adaptively conform to the true geometric shape of each tooth surface, fundamentally solving the problems of strengthening area offset, omission, or poor consistency caused by inaccurate positioning, and elevating the processing accuracy from the machine tool coordinate system to the tooth surface body coordinate system.

[0009] The present invention achieves the above-mentioned technical objectives through the following technical means.

[0010] A method for laser-assisted non-centering discrete strengthening of involute tooth surfaces based on binocular vision includes the following steps:

[0011] Using a binocular vision system, images of the tooth profile of the gear to be processed are acquired and three-dimensionally reconstructed to obtain three-dimensional point cloud data of the tooth surface.

[0012] The 3D point cloud data is processed and fitted to obtain an involute tooth profile model; based on the involute tooth profile model, a set of processing path points for laser discrete strengthening is planned on the tooth surface.

[0013] The laser head is controlled to be initially positioned away from the vertical center line of the gear, so that the laser beam is incident at an angle inclined to the normal of the tooth surface; according to the processing path point set, the tooth surface is laser discretely strengthened point by point.

[0014] Furthermore, obtaining the three-dimensional point cloud data of the tooth surface specifically includes the following steps:

[0015] The binocular vision system is calibrated to obtain the camera's intrinsic and extrinsic parameters;

[0016] Images of the gear end face are acquired using a binocular camera, and image preprocessing is performed.

[0017] Stereo matching is performed on the preprocessed image to generate a disparity map;

[0018] Using the principles of triangulation and based on the camera's intrinsic and extrinsic parameters and disparity map, the initial point cloud dataset P of the entire gear end face's three-dimensional shape is obtained. initial ;

[0019] For the initial point cloud dataset P initial Denoising and segmentation are performed to extract the point cloud data P of the tooth surface to be processed. tooth .

[0020] Furthermore, using the principle of triangulation and based on the camera's intrinsic and extrinsic parameters and disparity map, the initial point cloud dataset P of the entire gear end face's three-dimensional shape is obtained. initial Specifically:

[0021] Based on the intrinsic and extrinsic parameters obtained from camera calibration and the disparity value d of each pixel, calculate the pixel ( The three-dimensional coordinates (X, Y, Z) in the world coordinate system are calculated using the following formula:

[0022]

[0023] in, Baseline distance, For disparity values, For camera Directional focal length, For camera Directional focal length;

[0024] The 3D coordinates of all pixels in the parallax map in the world coordinate system form the initial point cloud dataset P representing the 3D shape of the entire gear end face. initial .

[0025] Furthermore, the 3D point cloud data is processed to fit an involute tooth profile model, specifically including the following steps:

[0026] The three-dimensional point cloud data of the tooth surface is projected onto the end face plane of the gear to obtain a two-dimensional tooth profile point set;

[0027] The involute parametric equation is used as the fitting model. The nonlinear least squares method is used to fit the two-dimensional tooth profile point set to the involute parametric equation, and the base circle radius and the range of the development angle are solved to obtain the optimized involute fitting model.

[0028] Furthermore, the optimized involute fitting model undergoes processing pose compensation, as detailed below:

[0029] Based on the optimized involute fitting model, calculate the coordinates of point P at the tooth tip circle. theoretical_top and tooth tip circle radius r a ;

[0030] Find the point in the 3D point cloud data of the tooth surface that is farthest from the origin when projected onto the end face, and use it as the actual tooth tip position point. ;

[0031] Origin O G Located at the center of the gear end face, the calculation origin O G With coordinate point P theoretical_top The theoretical tooth tip vector V theoretical Calculate the origin O G Compared with the actual tooth tip position The actual tooth tip vector V current ; Calculate the theoretical tooth tip vector V theoretical With the actual tooth tip vector V current The angle θ in the XY plane correct ;

[0032] If θ correct greater than the set threshold, θ correct The compensation rotation angle is used to compensate for gear indexing errors and installation errors.

[0033] Furthermore, based on the involute tooth profile model, a set of laser-discretely-strengthened machining path points is planned on the tooth surface, specifically including the following steps:

[0034] Divide the arc length equally along the fitted involute;

[0035] Calculate the angle of development corresponding to the division points;

[0036] Substitute the development angle of each equally divided point into the involute fitting model to obtain the two-dimensional coordinates of the equally divided points on the gear end face;

[0037] Layering is performed along the tooth width direction to generate a three-dimensional machining path point set covering the entire tooth surface.

[0038] A machining system for laser non-centering discrete strengthening of involute tooth surfaces based on binocular vision includes:

[0039] A vision measurement unit is used to acquire images of the tooth profile of the gear to be processed;

[0040] The data processing and path planning unit is used to fit the tooth surface model and generate the machining path.

[0041] A laser processing execution unit includes a laser, an optical system, and a motion platform for multi-axis linkage, used to make the laser beam process along the processing path.

[0042] Furthermore, the motion platform includes at least an X-axis motion platform for tooth profile direction feeding, a Y-axis motion platform for realizing laser non-centering offset, a Z-axis motion platform for tooth width direction feeding and focal length adjustment, and a rotary platform for gear indexing.

[0043] The beneficial effects of this invention are as follows:

[0044] 1. The laser non-centering discrete strengthening method for involute tooth surfaces based on binocular vision described in this invention achieves precise compensation for individual gear manufacturing errors and system installation errors by performing real-time three-dimensional scanning and involute model fitting on each tooth. This allows the laser strengthening path to adaptively conform to the true geometric shape of each tooth surface, fundamentally solving the problems of strengthening area offset, omission, or poor consistency caused by inaccurate positioning, and elevating the processing accuracy from the machine tool coordinate system to the tooth surface body coordinate system.

[0045] 2. The binocular vision-based laser non-centering discrete strengthening method for involute tooth surfaces described in this invention effectively avoids the risk of laser beam interference with adjacent teeth by using a laser head with an angled incidence angle deviating from the gear centerline. This non-centering processing strategy provides greater operational freedom for the laser head within the confined tooth space, enabling the use of a more optimized beam incidence angle and eliminating dead zones or shadow areas present in traditional centering processing. Furthermore, by using an angled incidence angle deviating from the gear centerline, the stability of the tooth surface affected by the discrete strengthening points under load torque can be minimized, reducing the frictional power consumption of the gear pair and the impact of tooth surface damage.

[0046] 3. The binocular vision-based laser non-centered discrete strengthening method for involute tooth surfaces described in this invention achieves truly equidistant distribution of strengthening points on complex curved surfaces by deeply fusing an arc-length equal division algorithm with the involute parametric equation to generate path points. Compared with the traditional method of equal division on a two-dimensional projection, the method of this invention follows the geometric characteristics of the involute, ensuring the consistency of energy accumulation and plastic deformation in each laser-impacted region, and improving the uniformity of residual compressive stress distribution from a microscopic mechanism perspective.

[0047] 4. The binocular vision-based laser non-centering discrete strengthening method for involute tooth surfaces described in this invention achieves extremely high consistency in strengthening quality and process reliability across the entire gear range by independently executing a closed-loop process of three-dimensional scanning, model reconstruction, path planning, and processing execution for each tooth. This method treats each tooth as an independent processing unit and can automatically adapt to and compensate for microscopic variations in tooth profile caused by previous processes such as heat treatment and forging, thereby significantly improving the contact fatigue strength and service life stability of mass-produced gears. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. The drawings described below are some embodiments of the present invention. For those skilled in the art, it is obvious that other drawings can be obtained from these drawings without creative effort.

[0049] Figure 1 This is a flowchart of the laser non-centering discrete strengthening process for involute tooth surfaces based on binocular vision, as described in this invention.

[0050] Figure 2 This is a schematic diagram of the processing system described in this invention.

[0051] Figure 3 This is a schematic diagram of the binocular vision calibration described in this invention.

[0052] Figure 4 This is a schematic diagram of the involute fitting described in this invention.

[0053] Figure 5 This is a schematic diagram of the grid isomorphism described in this invention. Detailed Implementation

[0054] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0055] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "axial," "radial," "vertical," "horizontal," "inner," and "outer," etc., indicating orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings, are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0056] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0057] like Figure 1 As shown in the embodiment, the laser non-centering discrete strengthening method for involute tooth surface based on binocular vision, taking the processing of involute cylindrical gears as an example, has a gear module m=3mm, number of teeth z=30, and pressure angle α0=20°. The specific steps are as follows:

[0058] S01: Process parameter presets, specifically including the following parameters:

[0059] The laser power is set to P=500W, the single-point duration is λ=10ms, the laser spot radius is r=0.5mm, and the laser beam is not aligned with the center line of the gear, so that the laser beam is incident at an angle tilted to the normal of the tooth surface.

[0060] Preset gear rotation angle Δθ L =360° / z, the feed amount of the machining head in the tooth profile direction ΔXL, the feed amount in the tooth thickness direction ΔYL, and the focal length adjustment range ΔZL.

[0061] like Figure 3As shown, in the horizontal direction, the industrial-grade binocular camera is mounted facing the side of the gear to ensure a clear image of the gear profile within the camera's field of view. The distance between the camera and the gear is adjusted so that the field of view covers the maximum outer diameter of the processed gear, avoiding edge distortion. In the vertical direction, the mounting height of the binocular vision camera must ensure that the optical axis passes through the center of the processed gear. This height can be calibrated using a laser rangefinder or calibration plate to ensure that the center of the gear is in the center of the binocular camera's field of view. Using a high-precision checkerboard calibration plate, the intrinsic and extrinsic parameters of the binocular vision camera are obtained using the Zhang Zhengyou calibration method. The intrinsic parameters include the camera's focal lengths fx and fy in different directions, the principal point coordinates (cx, cy), and the distortion coefficient. The extrinsic parameters include the two cameras... The rotational torque R and translation vector T between the two cameras are calculated, where the magnitude of the translation vector is the baseline distance B. The relative positions of the two cameras are calculated to establish the geometric relationship of the binocular epipolar lines, thereby correcting image distortion in real time and ensuring the accuracy of depth calculation. The world coordinate Z-axis is aligned with the gear axis by positioning through a calibration plate or gear shaft hole. The baseline distance of the binocular cameras is adjusted according to the gear size to balance the field of view and depth resolution. After calibration, the system performs a self-test by taking images of the calibration plate in different poses and calculating the average projection error. If the error exceeds the threshold, the system is recalibrated.

[0062] S02: Acquisition of 3D point cloud of tooth profile, specifically including the following steps:

[0063] S2.1: Gear installation and positioning;

[0064] The involute gear to be machined is mounted on the rotation center of a four-axis motion platform using a precision mandrel or special fixture. Precision instruments such as dial indicators or laser displacement sensors are used to calibrate the gear's end face runout and radial runout. The total runout after calibration is ensured to be less than 0.02 mm to guarantee that the gear axis coincides with the rotary table's rotation axis, i.e., aligned with the Z-axis of the world coordinate system.

[0065] S2.2: Synchronous acquisition and preprocessing of binocular images;

[0066] A binocular depth camera is perpendicular to the central axis of the gear being machined, synchronously triggering the acquisition of initial images of the gear tooth tips. The acquired images undergo preprocessing, including distortion correction, image filtering, edge detection, and contour filtering and sorting. The specific implementation of the algorithms and processes is based on OpenCV, as detailed below:

[0067] The acquired images are converted to grayscale using a weighted average method.

[0068] Preserve edge details using bilateral filtering;

[0069] Image edge detection and contour extraction algorithms are used to extract gear tooth profiles, and the gear profile image is stereo corrected. Combined with involute priors, edge connections are optimized to obtain a binary image of the tooth profile.

[0070] S2.3: Stereo matching and disparity map generation;

[0071] The SGBM algorithm is used to perform stereo matching on the preprocessed left and right images. The SGBM algorithm achieves a good balance between accuracy and efficiency, making it suitable for matching gear tooth profiles. By calculating the similarity between pixels in the left image and corresponding pixels in the right image, a disparity value d is assigned to each pixel in the left image.

[0072] Collect the disparity values ​​d of all pixels to generate a grayscale image (i.e., a disparity map), where the grayscale value of each pixel represents the disparity magnitude of that point.

[0073] S2.4: 3D point cloud reconstruction, as detailed below:

[0074] Based on the principle of triangulation, and using the intrinsic and extrinsic parameters obtained from camera calibration and the disparity value d of each pixel, the pixel ( The three-dimensional coordinates (X, Y, Z) in the world coordinate system. The calculation formula is as follows:

[0075] ,

[0076] in, Baseline distance, For disparity values, For camera Directional focal length, For camera Directional focal length;

[0077] The three-dimensional coordinates of all pixels in the disparity map are calculated in the world coordinate system, ultimately yielding the initial point cloud dataset P describing the three-dimensional shape of the entire gear end face. initial ;

[0078] S2.5: Point cloud post-processing; initial point cloud dataset P initial It contains a large amount of noise and background data, which needs to be cleaned and segmented, as detailed below.

[0079] S2.5.1: Use a statistical outlier removal algorithm. This algorithm calculates the average distance of each point to its k nearest neighbors (e.g., k=50), assuming these distances follow a Gaussian distribution. A standard deviation multiplier threshold (e.g., 1.0) is set, and all points whose average distance falls outside the range of the global average distance ± (standard deviation × threshold) are considered noise and removed. This step effectively removes floating, discrete noise points.

[0080] S2.5.2: Tooth Surface Point Cloud Segmentation: The DBSCAN clustering algorithm is used to segment the filtered point cloud. DBSCAN clusters based on density, which can effectively separate interconnected objects with different densities. By setting an appropriate neighborhood radius and minimum number of points, the algorithm automatically separates the gear body (dense point cloud) from the fixture and background (sparse point cloud).

[0081] Based on the DBSCAN clustering algorithm, the point cloud of the gear body and the background is separated, and the point cloud data P of the tooth surface of a single tooth to be processed is extracted. tooth .

[0082] S03: Involute model fitting and path planning, specifically including the following steps:

[0083] S3.1: As Figure 4 As shown, the point cloud data P of the tooth surface to be processed is... tooth Projecting this onto the end face plane of the gear (i.e., the plane where Z = 0) yields a two-dimensional point set P. 2D = { (x i , y i The coordinates of the i-th point in the two-dimensional point set are denoted as x. i y i ;

[0084] Constructing an involute fitting model: The rectangular coordinate parametric equation of the involute is used as the fitting model, and the equation is:

[0085]

[0086] in: The radius of the base circle; For the exhibition angle, , The angle of development at the termination point of the involute;

[0087] S3.2: The nonlinear least squares method (Levenberg-Marquardt algorithm) is used to fit the points on the involute in the model to the two-dimensional point set P. 2D The objective is to minimize the mean squared error (MSE) to obtain the optimized result. and ; Use the optimized and The optimized involute fitting model was obtained.

[0088] S3.3: Machining pose compensation calculation;

[0089] Theoretical tooth tip position determination: Based on the optimized involute fitting model, calculate the coordinate point P at the tooth tip circle. theoretical_top tooth tip circle radius r a It can be calculated based on the gear parameters.

[0090] Actual tooth tip position identification: from point cloud data P of the tooth surface to be machined tooth Find the point on the end face that is furthest from the origin, and use it as the actual tooth tip position. .

[0091] Compensation angle calculation: Origin O G Located at the center of the gear end face, the calculation origin O G With coordinate point P theoretical_top The theoretical tooth tip vector V theoretical Calculate the origin O G Compared with the actual tooth tip position The actual tooth tip vector V current And calculate the theoretical tooth tip vector V theoretical With the actual tooth tip vector V current The angle between the two points on the XY plane is θ. correct ;

[0092] If θ correct If the value exceeds a set threshold, it will be sent to the motion controller, which will pre-rotate the rotary table by θ before machining the tooth. correct This ensures that the machining path of the tooth is precisely aligned with the actual tooth surface.

[0093] S3.4: For example Figure 5 As shown, the mesh is divided into equal parts, and a processing path is generated;

[0094] For the optimized involute fitting model, calculate the change from the development angle θ=0 to θ= The total arc length L of the involute, ,in This is the optimized base circle.

[0095] Based on the reinforcement point density required by the processing technology, determine the equal arc length spacing Δs, and calculate the total number of equal parts N = ceil(L / Δs). ceil() means taking the value upwards. Assuming L / Δs = 10.2, then ceil(10.2) = 11.

[0096] Calculate the angle of development corresponding to the kth division point. ,in ;where s k This represents the cumulative arc length from the starting point of the involute (spread angle θ=0) to the kth division point;

[0097] The angle θ of each equally divided point k Substituting the optimized involute fitting model, we obtain its two-dimensional coordinates (x, y) on the gear end face. k ,y k ).

[0098] To cover the entire tooth surface, multi-layer planning is required along the tooth width direction (Z-axis). The number of layers M in the tooth width direction and the Z-coordinate of each layer Z are defined. m For example, from the tooth width end Z min To the other end Z max Uniformly distributed.

[0099] The three-dimensional coordinates of each laser-enhanced point are (x k ,y k Z m ), forming a laser processing path point cloud Path={(x k ,y k Z m This point cloud data describes all the locations that the laser head needs to visit sequentially.

[0100] S04: Laser non-centered discrete strengthening processing of a single tooth surface, specifically including the following steps:

[0101] The turntable drives the gears to rotate, and the resulting θ correct Compensation is performed to ensure that the tooth tip of the tooth surface to be processed is precisely aligned with the starting position of the laser head.

[0102] The laser head is always kept in a non-centered position so that the laser incident angle and the normal of the tooth surface are at an angle, generally between 10 and 25°, preferably 15°.

[0103] The motion controller precisely controls the X, Y, and Z axes to work in conjunction with the turntable based on the point cloud of the laser processing path.

[0104] For Z in the tooth width direction m Layer, the laser focus is moved sequentially to each equally divided point (x) on the tooth profile of that layer. k ,y k Z m Strengthening is performed. At each strengthening point, the laser emits light according to the set parameters P=500W, λ=10ms, forming a hard strengthening unit on the tooth surface.

[0105] Feed in the tooth width direction: Complete Z m After all points in the layer are reached, the machining head and the rotary table system move in coordination, translating a distance ΔZ equal to the diameter of a laser spot along the tooth width direction (Z-axis), thus moving the laser focus to the height Z of the next layer. m+1 Repeat the single-layer machining and tooth width direction feed until the entire tooth width is covered.

[0106] S05: Gear indexing and full gear cycle machining, specifically including the following steps:

[0107] After all the strengthening points on the current tooth surface have been processed, the laser is turned off. To prevent interference with adjacent teeth, the laser head follows an avoidance trajectory: it typically moves radially (negative Y-axis) out of the tooth groove first, and then rises to a safe height along the tooth width direction (Z-axis).

[0108] Based on the theoretical tooth pitch angle, the turntable drives the gear to rotate precisely 360° / z, rotating the next tooth to be processed to the visual inspection and laser processing station.

[0109] Extract the point cloud data of the next tooth surface to be processed, and repeat steps S03-S04. This ensures that each tooth is processed based on its actual geometry, fundamentally eliminating the impact of gear eccentricity, indexing error and installation error on the reinforcement quality.

[0110] The control system counts the number of teeth processed until the number of processed teeth equals the total number of teeth z of the gear, at which point the system automatically terminates the processing flow.

[0111] like Figure 2 As shown, the processing system of the laser non-centering discrete strengthening processing method for involute tooth surfaces based on binocular vision described in this invention includes a vision measurement unit, a data processing and path planning unit, and a laser processing execution unit.

[0112] The vision measurement unit employs a pair of MER-500-14U3M industrial cameras arranged horizontally to form a binocular vision system for acquiring images of the tooth profile of the gear to be processed. The data processing and path planning unit is used to fit the tooth surface model and generate the processing path. The laser processing execution unit includes a laser, an optical system, and a motion platform for multi-axis linkage, used to make the laser beam process according to the processing path. The motion platform includes at least an X-axis motion platform for tooth profile direction feed, a Y-axis motion platform for laser non-centering offset, a Z-axis motion platform for tooth width direction feed and focal length adjustment, and a rotary platform for gear indexing.

[0113] It should be understood that although this specification is described according to various embodiments, not every embodiment contains only one independent technical solution. This way of describing the specification is only for clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment can also be appropriately combined to form other implementation methods that can be understood by those skilled in the art.

[0114] The detailed descriptions listed above are merely specific illustrations of feasible embodiments of the present invention and are not intended to limit the scope of protection of the present invention. All equivalent embodiments or modifications made without departing from the spirit of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for laser-assisted non-centering discrete strengthening of involute tooth surfaces based on binocular vision, characterized in that, Includes the following steps: Using a binocular vision system, images of the tooth profile of the gear to be processed are acquired and three-dimensionally reconstructed to obtain three-dimensional point cloud data of the tooth surface. The 3D point cloud data is processed and fitted to obtain an involute tooth profile model; based on the involute tooth profile model, a set of processing path points for laser discrete strengthening is planned on the tooth surface. The laser head is controlled to be initially positioned away from the vertical center line of the gear, so that the laser beam is incident at an angle inclined to the normal of the tooth surface; according to the processing path point set, the tooth surface is laser discretely strengthened point by point.

2. The laser-based non-centered discrete strengthening method for involute tooth surfaces based on binocular vision according to claim 1, characterized in that, Obtaining the 3D point cloud data of the tooth surface specifically includes the following steps: The binocular vision system is calibrated to obtain the camera's intrinsic and extrinsic parameters; Images of the gear end face are acquired using a binocular camera, and image preprocessing is performed. Stereo matching is performed on the preprocessed image to generate a disparity map; Using the principles of triangulation and based on the camera's intrinsic and extrinsic parameters and disparity map, the initial point cloud dataset P of the entire gear end face's three-dimensional shape is obtained. initial ; For the initial point cloud dataset P initial Denoising and segmentation are performed to extract the point cloud data P of the tooth surface to be processed. tooth .

3. The laser-based non-centered discrete strengthening method for involute tooth surfaces based on binocular vision according to claim 2, characterized in that, Using the principles of triangulation and based on the camera's intrinsic and extrinsic parameters and disparity map, the initial point cloud dataset P of the entire gear end face's three-dimensional shape is obtained. initial Specifically: Based on the intrinsic and extrinsic parameters obtained from camera calibration and the disparity value d of each pixel, calculate the pixel ( The three-dimensional coordinates (X, Y, Z) in the world coordinate system are calculated using the following formula: ， in, Baseline distance, For disparity values, For camera Directional focal length, For camera Directional focal length; The 3D coordinates of all pixels in the parallax map in the world coordinate system form the initial point cloud dataset P representing the 3D shape of the entire gear end face. initial .

4. The laser-based non-centered discrete strengthening method for involute tooth surfaces based on binocular vision according to claim 1, characterized in that, The three-dimensional point cloud data is processed to fit an involute tooth profile model, which includes the following steps: The three-dimensional point cloud data of the tooth surface is projected onto the end face plane of the gear to obtain a two-dimensional tooth profile point set; The involute parametric equation is used as the fitting model. The nonlinear least squares method is used to fit the two-dimensional tooth profile point set to the involute parametric equation, and the base circle radius and the range of the development angle are solved to obtain the optimized involute fitting model.

5. The laser non-centering discrete strengthening method for involute tooth surfaces based on binocular vision according to claim 4, characterized in that, The optimized involute fitting model is then subjected to machining pose compensation, as detailed below: Based on the optimized involute fitting model, calculate the coordinates of point P at the tooth tip circle. theoretical_top and tooth tip circle radius r a ; Find the point in the 3D point cloud data of the tooth surface that is farthest from the origin when projected onto the end face, and use it as the actual tooth tip position point. ; Origin O G Located at the center of the gear end face, the calculation origin O G With coordinate point P theoretical_top The theoretical tooth tip vector V theoretical Calculate the origin O G Compared with the actual tooth tip position The actual tooth tip vector V current ; Calculate the theoretical tooth tip vector V theoretical With the actual tooth tip vector V current The angle θ in the XY plane correct ; If θ correct greater than the set threshold, θ correct The compensation rotation angle is used to compensate for gear indexing errors and installation errors.

6. The laser-based non-centered discrete strengthening method for involute tooth surfaces based on binocular vision according to claim 1, characterized in that, Based on the involute tooth profile model, a set of laser-discretely-strengthened machining path points is planned on the tooth surface, specifically including the following steps: Divide the arc length equally along the fitted involute; Calculate the angle of development corresponding to the division points; Substitute the development angle of each equally divided point into the involute fitting model to obtain the two-dimensional coordinates of the equally divided points on the gear end face; Layering is performed along the tooth width direction to generate a three-dimensional machining path point set covering the entire tooth surface.

7. A machining system for a laser non-centering discrete strengthening machining method for involute tooth surfaces based on binocular vision according to any one of claims 1-6, characterized in that, include: A vision measurement unit is used to acquire images of the tooth profile of the gear to be processed; The data processing and path planning unit is used to fit the tooth surface model and generate the machining path. A laser processing execution unit includes a laser, an optical system, and a motion platform for multi-axis linkage, used to make the laser beam process along the processing path.

8. The machining system of the laser non-centering discrete strengthening machining method for involute tooth surfaces based on binocular vision according to claim 7, characterized in that, The motion platform includes at least an X-axis motion platform for tooth profile direction feeding, a Y-axis motion platform for laser non-centering offset, a Z-axis motion platform for tooth width direction feeding and focal length adjustment, and a rotary platform for gear indexing.

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