Complex curved surface adaptive abrasive jet strengthening method and system

Abstract

The application relates to a complex curved surface adaptive abrasive jet strengthening method and system, which comprises the following steps: acquiring a three-dimensional point cloud data set of a workpiece; analyzing the three-dimensional point cloud data set to obtain a first principal component vector; setting a cutting plane, calculating the intersection line of the cutting plane and the three-dimensional point cloud data set based on the first principal component vector, and the intersection line is an initial path; calculating the normal vector of each discrete point on the initial path, calculating the latest unit outer normal vector of the discrete point based on the normal vector and a self-defined viewpoint, and the latest unit outer normal vector is perpendicular to the complex curved surface on the workpiece; calculating the corresponding actual position coordinates of the nozzle relative to each discrete point based on the unit outer normal vector of the discrete point, and forming a continuous strengthening path based on the actual position coordinates. Through the application, the deviation between a CAD model and a real object can be eliminated, the nozzle strengthening path planning has curved surface adaptive capacity, and jet energy is uniformly distributed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of surface strengthening processing, in particular to a complex curved surface self-adaptive abrasive jet strengthening method and system. BACKGROUND

[0002] TC4 titanium alloy is often used as the main material of the compressor blade of an aero-engine due to its high strength and corrosion resistance. In view of the demand for key aero parts with high reliability and high service performance, how to improve the performance, durability and safety of the blade to cope with severe working environment is a current research hotspot. In general, in order to obtain excellent aerodynamic performance, the blade surface is optimized in combination with aerodynamics, so that it has complex streamline characteristics of bending and twisting, which belongs to a typical complex curved surface.

[0003] The existing research on shot peening strengthening of complex curved surfaces such as engine blades mainly focuses on residual stress and deformation. However, the strengthening performance of traditional strengthening methods is related to the jet angle and target distance. Moreover, these traditional strengthening methods generally have the problems that the jet angle and target distance are difficult to keep constant, resulting in uneven strengthening effect; they rely on CAD models, which have poor adaptability due to the deviation from actual parts; the process parameters are complex to adjust, and the experimental period is long and the cost is high; and the strengthening path planning lacks the ability to adapt to curved surfaces, affecting the strengthening precision and consistency. In general, a jet angle close to 90° is a relatively ideal shot peening angle. According to the foregoing research results, the target distance affects the kinetic energy transmission and energy distribution of the shot peening medium, and determines the surface layer performance of the material after shot peening. Therefore, there is an urgent need for an intelligent strengthening method that can adapt to complex curved surface shapes, integrate complex curved surface information with strengthening processes to maintain optimal jet angles and target distances. SUMMARY

[0004] Based on this, the purpose of the present application is to provide a complex curved surface self-adaptive abrasive jet strengthening method and system to solve the problems in the prior art.

[0005] To achieve the above-mentioned purpose, the present application provides a complex curved surface self-adaptive abrasive jet strengthening method, which comprises:

[0006] acquiring a three-dimensional point cloud data set of the complex curved surface on the workpiece through a binocular structured light three-dimensional reconstruction system;

[0007] analyzing the three-dimensional point cloud data set by principal component analysis to obtain a first principal component vector, the first principal component vector being the direction of the most dispersed point cloud distribution;

[0008] The intersection line of the cutting plane and the three-dimensional point cloud data set is calculated based on the first principal component vector and by an intersection method, and the intersection line is an initial path, and adjacent cutting planes are arranged at equal intervals;

[0009] A normal vector of each discrete point on the initial path is calculated, and a latest unit outer normal vector of the discrete point is obtained based on the normal vector and a custom viewpoint, and the latest unit outer normal vector is perpendicular to the complex curved surface of the workpiece;

[0010] Actual position coordinates of the nozzle relative to each discrete point are calculated based on a preset target distance and the unit outer normal vector of each discrete point, and a continuous reinforcement path is formed by linear and circular arc interpolation based on the actual position coordinates and in combination with inverse kinematics of the industrial robot, and the continuous reinforcement path is a movement trajectory of the nozzle.

[0011] The beneficial effects of the present application are as follows: the three-dimensional point cloud data set of the workpiece is obtained by the binocular structured light three-dimensional reconstruction system, the three-dimensional point cloud data set is analyzed by principal component analysis to obtain the first principal component vector, then the cutting plane is set based on the preset feed amount, the intersection line of the cutting plane and the three-dimensional point cloud data set is calculated based on the first principal component vector and by an intersection method, that is, the initial path, the normal vector of each discrete point on the initial path is calculated, the latest unit outer normal vector of the discrete point is obtained based on the normal vector and a custom viewpoint, the actual position coordinates of the nozzle relative to each discrete point are calculated based on a preset target distance and the unit outer normal vector, and a continuous reinforcement path is formed by linear and circular arc interpolation based on the actual position coordinates and in combination with inverse kinematics of the industrial robot, that is, the movement trajectory of the nozzle, so as to perform a spraying operation based on the movement trajectory, which is different from the prior art, can eliminate the deviation between the CAD model and the actual object, has strong adaptability to parts with manufacturing tolerances, clamping deformation or unknown curved surfaces, and the reinforcement path planning of the nozzle has a curved surface self-adaptive ability, ensures that the jet impact angle always remains close to the optimal spraying angle on the entire complex curved surface, makes the jet energy distribution uniform, avoids insufficient or excessive reinforcement caused by changes in angle and distance, and thus obtains a residual compressive stress layer and a microhardness with consistent depth and higher values, and significantly improves the fatigue resistance of the part.

[0012] Further, the binocular structured light three-dimensional system comprises a DLP projector and two industrial cameras, and the step of obtaining the three-dimensional point cloud data set of the complex curved surface on the workpiece by the binocular structured light three-dimensional reconstruction system comprises:

[0013] transmit a series of coded sinusoidal fringe light to a workpiece placed in a measurement field of view through the DLP projector, when the sinusoidal fringe light is modulated by the shape of the complex surface on the workpiece and deformed, capture the deformed fringe image through two industrial cameras;

[0014] Based on the deformed fringe image, the principal value phase in the preset interval is calculated by four-step phase shift method, the high-frequency phases are heterodyned by multi-frequency heterodyne technology, the unwrapped phase is obtained, and the absolute phase with an equivalent frequency of 1 is obtained by twice heterodyning the unwrapped phase;

[0015] Taking the absolute phase as the matching basis, the deformed fringe image is densely matched by a sliding window and absolute error algorithm, the parallax of each pixel point is calculated, the parallax is converted into three-dimensional space coordinates by triangulation principle, and a three-dimensional point cloud data set is obtained, the three-dimensional point cloud data set includes a plurality of three-dimensional point cloud data.

[0016] Further, after capturing the deformed fringe image through the two industrial cameras, the method further comprises:

[0017] Based on the high-precision planar circular target calibration board, the internal and external parameters of each industrial camera are obtained by Zhang Zhengyou calibration method, and the two deformed fringe images are stereographically corrected based on the internal and external parameters.

[0018] Further, the step of obtaining the first principal component vector by analyzing the three-dimensional point cloud data set by the principal component analysis method comprises:

[0019] The three-dimensional point cloud data set is processed to obtain a decentralized point cloud data set, a covariance matrix representing the correlation coefficient of the surface point cloud is constructed based on the decentralized point cloud data set, and the first principal component vector is obtained by singular value decomposition of the covariance matrix.

[0020] Further, the expression of the decentralized point cloud data set is as follows:

[0021]

[0022] Wherein, The decentralized point cloud data set is represented by The three-dimensional point cloud data set is represented by The mean value of the three-dimensional point cloud data set is represented by The number of data points on the workpiece is represented by The three-dimensional point cloud data of the i-th data point is represented by The data of the i-th data point in the x direction is represented by represents the data of the i-th data point in the y direction, represents the data of the i-th data point in the z direction.

[0023] Further, the step of calculating the intersection line of the cutting plane and the three-dimensional point cloud data set based on the first principal component vector and by intersection method comprises:

[0024] translating the cutting plane based on the first principal component vector to obtain a positive plane and a negative plane, and taking the three-dimensional point cloud data on the positive plane as a positive neighborhood neighboring point cloud and taking the three-dimensional point cloud data on the negative plane as a negative neighborhood neighboring point cloud;

[0025] finding the nearest point of the measuring point in the positive neighborhood neighboring point cloud in the negative neighborhood neighboring point cloud to form a matching point pair, and traversing all point clouds to determine the unique matching point pair corresponding to each measuring point in the positive neighborhood neighboring point cloud;

[0026] calculating the intersection point of the line segment between each unique matching point pair and the cutting plane, and constructing the intersection line of the cutting plane and the three-dimensional point cloud data set based on all the intersection points.

[0027] Further, the expression of the actual position coordinates is as follows:

[0028]

[0029] wherein, represents the discrete points on the initial path the actual position coordinates of the corresponding nozzle, represents the target distance of the abrasive jet strengthening, represents the outward vector of the discrete point estimated by the expression of the local fitting plane.

[0030] To achieve the above object, the application further provides a complex curved surface adaptive abrasive jet strengthening system for realizing the complex curved surface adaptive abrasive jet strengthening method described in the above method, and the system comprises:

[0031] An acquisition module is configured to acquire a three-dimensional point cloud data set of a complex curved surface on a workpiece through a binocular structured light three-dimensional reconstruction system.

[0032] An analysis module is configured to analyze the three-dimensional point cloud data set by principal component analysis to obtain a first principal component vector, wherein the first principal component vector is a direction in which the point cloud is most dispersed.

[0033] A first calculation module is configured to set a cutting plane based on a preset feed amount, calculate an intersection line of the cutting plane and the three-dimensional point cloud data set based on the first principal component vector and by intersection method, and set adjacent cutting planes at equal intervals.

[0034] a second calculation module, configured to calculate a normal vector of each discrete point on the initial path, and calculate a latest unit external normal vector of the discrete point based on the normal vector and a self-defined viewpoint, the latest unit external normal vector being perpendicular to the complex curved surface of the workpiece;

[0035] a forming module, configured to calculate a corresponding actual position coordinate of a nozzle relative to each discrete point based on a preset target distance and the unit external normal vector of each discrete point, and form a continuous strengthening path by linear and circular arc interpolation based on a plurality of the actual position coordinates and in combination with inverse kinematics of an industrial robot, the continuous strengthening path being a moving track of the nozzle. BRIEF DESCRIPTION OF DRAWINGS

[0036] Figure 1 a flowchart of a complex curved surface adaptive abrasive jet strengthening method according to an embodiment of the present application;

[0037] Figure 2 a flowchart of step S101 according to an embodiment of the present application;

[0038] Figure 3 a flowchart of steps S102 and S103 according to an embodiment of the present application;

[0039] Figure 4 a schematic diagram of a binocular structured light three-dimensional reconstruction system and an abrasive jet strengthening system according to an embodiment of the present application;

[0040] Figure 5 a schematic diagram of two kinds of strengthening paths according to an embodiment of the present application;

[0041] Figure 6 a schematic diagram of strengthening topographies under two kinds of strengthening paths according to an embodiment of the present application;

[0042] Figure 7 a schematic diagram of three-dimensional topographies under two kinds of strengthening paths according to an embodiment of the present application;

[0043] Figure 8 a schematic diagram of strengthening stripe features under two kinds of paths according to an embodiment of the present application;

[0044] Figure 9 a schematic diagram of surface roughness under two kinds of paths according to an embodiment of the present application;

[0045] Figure 10 a schematic diagram of surface residual stress under two kinds of paths according to an embodiment of the present application;

[0046] Figure 11 a schematic diagram of surface microhardness under two kinds of paths according to an embodiment of the present application.

[0047] The following detailed description will further describe the present application with reference to the above mentioned drawings. DETAILED DESCRIPTION

[0048] In order to make the purposes, technical solutions and advantages of the present application clearer, the present application is described and explained below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and should not be used to limit the present application. Based on the embodiments provided in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of the present application.

[0049] Obviously, the drawings in the following description are only some examples or embodiments of the present application, and for those of ordinary skill in the art, the present application can be applied to other similar scenarios without creative efforts based on these drawings. In addition, it can be understood that although the efforts made in this development process can be complex and lengthy, for those of ordinary skill in the art related to the content disclosed in the present application, some designs, manufacturing or production changes based on the technical content disclosed in the present application are only routine technical means and should not be understood as insufficient disclosure of the content disclosed in the present application.

[0050] In the present application, the phrase "embodiments" means that the specific features, structures or characteristics described in combination with the embodiments can be included in at least one embodiment of the present application. The appearance of this phrase at various places in the specification does not necessarily mean the same embodiment, nor is it an independent or alternative embodiment that is not mutually exclusive with other embodiments. Those of ordinary skill in the art explicitly and implicitly understand that the embodiments described in the present application can be combined with other embodiments without conflict.

[0051] Unless otherwise defined, technical terms and scientific terms used in the present application shall have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. The terms "a", "an", "one", "this", and similar referents in the context of describing the application are to be construed to be open-ended, referring to one or more than one, unless otherwise noted. The terms "including", "comprising", "having" and variations thereof in this application are meant to encompass the possibility of non-exclusive inclusion, such that processes, methods, systems, products, or apparatuses that comprise a list of steps or elements are not limited to only those steps or elements but can include other steps or elements not expressly listed or inherent to such processes, methods, systems, products, or apparatuses. The terms "connected", "coupled", "attached", and similar referents in the context of this application are to be construed as can be either direct or indirect connection, coupling, or attachment, and can include electrical connection, whether direct or indirect. The term "multiple" refers to two or more. The term "and / or" describes associated objects in association with the associated objects, which means that there are three relationships, for example, "A and / or B" can mean that A exists alone, A and B exist together, and B exists alone. The character " / " generally represents an "or" relationship between the associated objects. The terms "first", "second", "third", and the like in the present application are only to distinguish similar objects, and do not represent a specific order of the objects.

[0052] Embodiment one

[0053] Please refer to Figure 1 The flow chart of the complex curved surface adaptive abrasive jet strengthening method in the first embodiment of the present application, the complex curved surface adaptive abrasive jet strengthening method, by combining high-precision three-dimensional reconstruction technology with innovative path planning algorithm, eliminates the deviation between CAD model and physical object, provides accurate geometric basis for path planning. And ensure that the jet nozzle is always perpendicular to the workpiece surface and maintains the optimal target distance throughout the strengthening process. Through integrated system to realize automatic operation, greatly shorten the process development cycle, reduce the dependence on the experience of operators, improve the processing efficiency and consistency. Finally, the surface integrity of the complex curved surface part after strengthening is significantly improved, including obtaining higher and more uniform residual compressive stress layer, higher microhardness and better surface roughness, thereby prolonging the fatigue life of the part. The method comprises the following steps:

[0054] Step S101: obtaining three-dimensional point cloud data set of complex curved surface on workpiece through binocular structured light three-dimensional reconstruction system;

[0055] Wherein, the three-dimensional point cloud data set is obtained by using a binocular vision-based structured light three-dimensional measurement technology, specifically, the binocular structured light three-dimensional reconstruction system is composed of a DLP projector and two high-resolution industrial cameras, the DLP projector projects a series of coded sinusoidal fringe light to the workpiece placed in the measurement field. The sinusoidal fringe light is deformed after being modulated by the surface shape of the workpiece, and is captured by two high-resolution industrial cameras triggered synchronously.

[0056] Step S102: analyzing the three-dimensional point cloud data set by principal component analysis method to obtain a first principal component vector, the first principal component vector is the most dispersed direction of point cloud distribution;

[0057] Further, the step of analyzing the three-dimensional point cloud data set by principal component analysis method to obtain a first principal component vector comprises:

[0058] The three-dimensional point cloud data set is decentered to obtain a decentered point cloud data set, a covariance matrix representing the correlation coefficient of the surface point cloud is constructed based on the decentered point cloud data set, and the first principal component vector is obtained by singular value decomposition of the covariance matrix.

[0059] Wherein, based on the reconstructed point cloud, the original CAD model is no longer relied on. The principal component analysis method is used to analyze the point cloud, find the most dispersed direction of point cloud distribution (first principal component vector), and take the first principal component vector as the "principal normal vector" direction to extract the direction with the largest point cloud distribution, so as to realize the purpose of the cutting plane perpendicular to the surface point cloud.

[0060] It should be noted that the principal normal vector estimation is specifically, for a three-dimensional point cloud data containing n measurement points, the three-dimensional point cloud data set is , and the three-dimensional principal component analysis index variable has three. The three-dimensional point cloud data in the three-dimensional point cloud data set is decentered to eliminate data offset, and the decentered point cloud data set is obtained, that is, the decentered point cloud . Then, the covariance matrix representing the correlation coefficient of the surface point cloud is constructed based on the decentered point cloud , and then the singular value decomposition of the covariance matrix is performed, and the eigenvector corresponding to the maximum eigenvalue is taken as the principal normal vector direction of the complex surface, that is, the first principal component vector.

[0061] Step S103: setting a cutting plane based on a preset feed amount, calculating the intersection line of the cutting plane and the three-dimensional point cloud data set based on the first principal component vector and by intersection method, the intersection line is the initial path, and the adjacent cutting planes are arranged at equal intervals;

[0062] Wherein, the first principal component vector in step S102 is taken as the normal of the cutting plane, and the equidistant cutting planes are set by referring to the preset feed amount, and the intersection line of the cutting planes and the point cloud is the initial path.

[0063] Step S104: calculating the normal vector of each discrete point on the initial path, and calculating the latest unit outer normal vector of the discrete point based on the normal vector and the custom viewpoint, wherein the latest unit outer normal vector is perpendicular to the complex curved surface of the workpiece.

[0064] Wherein, first, in order to control the nozzle posture to be always perpendicular to the complex curved surface of the workpiece, the normal vector of each discrete point on the initial path needs to be calculated. A local plane fitting method based on Gaussian weight is adopted. For each discrete point on the initial path and its K nearest neighbors searched, a local plane is fitted by using the least square method;

[0065] Then, in order to ensure that the estimated normal vector on the machining path remains consistent in the global range, a custom viewpoint is artificially introduced to calculate the viewing vector The inner product of the viewing vector and the normal vector ensures that the normal vectors of all discrete points are consistent in direction (pointing to the outside of the curved surface), and makes the center line of the nozzle coincide with the normal vector, that is, the latest unit outer normal vector is perpendicular to the complex curved surface of the workpiece, and ensures that the spray angle is 90°.

[0066] Step S105: calculating the actual position coordinates of the nozzle relative to each discrete point based on the preset target distance and the unit outer normal vector of each discrete point, and forming a continuous reinforcement path by linear and circular arc interpolation based on the actual position coordinates and in combination with the inverse kinematics of the industrial robot, wherein the continuous reinforcement path is the moving track of the nozzle.

[0067] Wherein, the abrasive jet reinforcement is a non-contact machining, and the nozzle does not contact the surface of the workpiece. Therefore, the actual trajectory of the nozzle needs to be offset outward from the surface path of the workpiece by a constant target distance. The unit outer normal vector of each discrete point calculated in the previous step is used to obtain the actual position coordinates of the nozzle through simple vector operation; all discrete points are traversed, and the actual position coordinates of more than 133 discrete points are output, which include three-dimensional coordinates and normal vectors (characterizing the position and posture of the nozzle); the planned nozzle trajectory points (position and posture) are converted into angle instructions of each joint of the industrial robot through inverse kinematics solution. Linear or circular arc interpolation algorithm is adopted to connect the discrete points into a smooth and continuous path. The abrasive jet nozzle is moved along this path strictly by the robot arm.

[0068] Meanwhile, the high-pressure plunger pump and the abrasive supply device work according to the optimized jet pressure (such as 70 MPa) and the transverse speed (such as 344.655 mm / min) in the process parameter library, so as to uniformly and consistently strengthen the workpiece surface.

[0069] Through the above steps, the three-dimensional point cloud dataset of the workpiece is acquired by the binocular structured light three-dimensional reconstruction system, the first principal component vector is acquired by analyzing the three-dimensional point cloud dataset through principal component analysis, then the preset feed amount is set to set the cutting plane, the intersection line of the cutting plane and the three-dimensional point cloud dataset is calculated based on the first principal component vector and by the intersection method, that is, the initial path, the normal vector of each discrete point on the initial path is calculated, the latest unit outer normal vector of the discrete point is obtained based on the normal vector and the self-defined viewpoint, the actual position coordinates of the nozzle relative to each discrete point are calculated based on the preset target distance and the unit outer normal vector, and the continuous strengthening path, that is, the moving track of the nozzle, is formed through linear and circular arc interpolation based on the plurality of actual position coordinates and in combination with the inverse kinematics of the industrial robot, so that the spraying operation is performed based on the moving track. Different from the prior art, the deviation between the CAD model and the actual object can be eliminated, the parts with manufacturing tolerances, clamping deformation or unknown surfaces have strong adaptability, and the strengthening path planning of the nozzle has the surface self-adaptation capability, so that the jet impact angle is always close to the optimal spraying angle on the entire complex surface, the jet energy is uniformly distributed, the insufficient or excessive strengthening caused by the change of the angle and the distance is avoided, and therefore the residual compressive stress layer with consistent depth and higher numerical value and the microhardness are obtained, and the fatigue resistance of the part is significantly improved.

[0070] Further, the binocular structured light three-dimensional system includes a DLP projector and two industrial cameras, and the step of acquiring the three-dimensional point cloud dataset of the complex surface on the workpiece by the binocular structured light three-dimensional reconstruction system includes:

[0071] A series of coded sinusoidal fringe lights are transmitted to the workpiece placed in the measurement field of view by the DLP projector, when the sinusoidal fringe light is deformed after being modulated by the shape of the complex surface on the workpiece, the deformed fringe images after deformation are captured by the two industrial cameras;

[0072] The principal value phase in the preset interval is calculated based on the deformed fringe images by the four-step phase shift method, the high-frequency phases are heterodyned by the multi-frequency heterodyne technique, the unwrapped phases are obtained, and the absolute phases with an equivalent frequency of 1 are obtained by twice heterodyning the unwrapped phases;

[0073] Wherein, for the captured deformed fringe image, the principal value phase wrapped in the interval [-π, π] is calculated by using four-step phase shifting method, that is, the preset interval is -π~π. Since the principal value phase has 2π jump, it is not unique and cannot be directly used for matching. Therefore, by using multi-frequency heterodyne technology, the principal value phase of two high frequencies is first heterodyned to obtain an unfolded phase with a lower frequency (such as f12=6, f23=5), and then the principal value phase (unfolded phase) of these intermediate frequencies is secondly heterodyned by using multi-frequency heterodyne technology to obtain an absolute phase with an equivalent frequency of 1. The absolute phase is monotonically increasing in the entire field of view and has uniqueness, which can be used as an ideal element for stereo matching.

[0074] According to the absolute phase, the deformed fringe image is densely matched by using a sliding window and an absolute error algorithm, and the disparity of each pixel point is calculated. The disparity is converted into a three-dimensional space coordinate by using a triangulation principle, so as to obtain a three-dimensional point cloud data set, and the three-dimensional point cloud data set includes a plurality of three-dimensional point cloud data.

[0075] According to the absolute phase, the deformed fringe image is densely matched by using a sliding window and an absolute error algorithm, and the disparity of each pixel point is calculated. The disparity is converted into a three-dimensional space coordinate by using a triangulation principle, so as to obtain a three-dimensional point cloud data set, and the three-dimensional point cloud data set includes a plurality of three-dimensional point cloud data.

[0076] Further, after the deformed fringe images are captured by the two industrial cameras, the method further comprises:

[0077] Based on a high-precision planar circular target calibration board, the internal parameters and the external parameters of each industrial camera are obtained by using Zhang Zhengyou calibration method, and based on the internal parameters and the external parameters, the two deformed fringe images are stereoscopically corrected.

[0078] Wherein, by using a high-precision planar circular target calibration board, the internal parameters and the external parameters of the left and right cameras are accurately obtained by using Zhang Zhengyou calibration method, and then the two deformed fringe images are stereoscopically corrected, so that the epipolar lines of the two images are strictly horizontally aligned, the two-dimensional matching problem is simplified to one-dimensional search, and the accuracy and efficiency of subsequent matching are improved.

[0079] Further, the expression of the decentralized point cloud data set is as follows:

[0080]

[0081] Wherein, The decentralized point cloud data set is represented as representing a three-dimensional point cloud data set, representing a mean value of a three-dimensional point cloud data set, representing a number of measurement points on a workpiece, representing a three-dimensional point cloud data of the i th data point, representing data of the i th data point in the x direction, representing data of the i th data point in the y direction, representing data of the i th data point in the z direction.

[0082] Further, the calculation formula of the covariance matrix is as follows:

[0083]

[0084] wherein, representing a covariance matrix, representing a correlation coefficient of the s th index and the t th index, representing an inverse operator.

[0085] Further, the step of calculating the intersection line of the cutting plane and the three-dimensional point cloud data set based on the first principal component vector and by using the intersection method comprises:

[0086] translating the cutting plane based on the first principal component vector to obtain a positive plane and a negative plane, and taking the three-dimensional point cloud data on the positive plane as a positive neighborhood neighboring point cloud and taking the three-dimensional point cloud data on the negative plane as a negative neighborhood neighboring point cloud;

[0087] finding the nearest point of the measurement point in the positive neighborhood neighboring point cloud in the negative neighborhood neighboring point cloud to form a matching point pair, and traversing all point clouds to determine the unique matching point pair corresponding to each measurement point in the positive neighborhood neighboring point cloud;

[0088] calculating the intersection point of the line segment between each unique matching point pair and the cutting plane, and constructing the intersection line of the cutting plane and the three-dimensional point cloud data set based on all the intersection points.

[0089] wherein, the cutting plane is translated along the first principal component direction to obtain a positive plane and a negative plane , and the positive neighborhood neighboring point cloud and the negative neighborhood neighboring point cloud are divided;

[0090] for the measurement point P in the positive neighborhood neighboring point cloud, finding the nearest point Q in the negative neighborhood neighboring point cloud to form a matching point pair , traversing all point clouds to confirm the unique matching point pair , which corresponds to the final matching point pair , connecting the final matching point pair with a line segment, denoted as ;

[0091] Calculate line segments The intersections with the cut-off plane form a smooth enhancement path, requiring no additional smoothing processing.

[0092] Furthermore, the expression for the local fitting plane is as follows:

[0093]

[0094] in, This represents the unit normal vector of the locally fitted plane Z. This represents the value of the independent variable parameter when it takes its minimum value within the domain. This represents the distance from the local fitting plane to the origin of the coordinate system. The points within the neighborhood k are compared with the estimated points. The distance is set with Gaussian weighting coefficients.

[0095] Furthermore, the expression for the actual position coordinates is as follows:

[0096]

[0097] in, Represents discrete points on the initial path The corresponding actual position coordinates of the nozzle This indicates the target distance for abrasive jet reinforcement. The expression representing the local fitted plane estimates the outward vector of the discrete point.

[0098] Example 2

[0099] The adaptive abrasive jet enhancement method for complex curved surfaces in the second embodiment of the present invention includes a three-dimensional surface reconstruction process and an abrasive jet enhancement process. The three-dimensional surface reconstruction process is established and trained before the abrasive jet enhancement process, which is the core content of this invention.

[0100] The core idea and process of the complex curved surface abrasive jet strengthening method are as follows: Figure 1 As shown, in the process of strengthening complex curved surfaces with abrasive jets, a complex point cloud is obtained based on the 3D reconstruction of the curved surface. The principal vector of the blade is then calculated based on the feed rate and the discrete curved surface, thereby extracting the strengthening path. Normal vector estimation is then performed to complete the entire process of surface strengthening. This flowchart clearly presents the integration logic of surface information and strengthening process, providing overall guidance for strengthening path planning and execution.

[0101] Figure 2 yes Figure 1The result diagram of each process of three-dimensional reconstruction of complex curved surface using binocular structured light. This diagram shows the complete process of binocular structured light three-dimensional reconstruction based on four-step phase shift and multi-frequency heterodyne, including DLP projector projecting 12 different frequency and phase sinusoidal fringe patterns, left and right cameras synchronously capturing fringe images, camera calibration, epipolar constraint and stereo rectification, four-step phase shift solving principal value phase, multi-frequency heterodyne expanding absolute phase, phase stereo matching and three-dimensional coordinate calculation, clearly presenting the whole link logic from structured light coding to obtaining high-precision point cloud data of complex curved surface, and clearly showing the input-output relationship of each link, providing process guidance for three-dimensional reconstruction implementation. Finally, the blade point cloud diagram after filtering and denoising and removing invalid areas is obtained, the point cloud has high density and good uniformity in spatial distribution, and can accurately reflect the rich geometric features of the blade surface details, proving that three-dimensional reconstruction can effectively capture the blade surface profile and lay a data foundation for subsequent reinforcement path planning.

[0102] Figure 3 is Figure 1 The complex curved surface reinforcement path planning flowchart considering the complex curved surface information. This diagram first shows the principle of point cloud slicing using intersection method, marking the blade point cloud, slicing plane , positive neighborhood, negative neighborhood and matching point pair , clearly presenting the process of obtaining the intersection contour line by dividing the positive / negative neighborhood, finding the nearest matching point pair, calculating the intersection of line segment and slicing plane, providing an intuitive reference for understanding the principle of obtaining reinforcement path by point cloud slicing, and clearly showing the generation logic of slicing plane and point cloud intersection contour line (reinforcement path). Then based on the principle of point cloud normal vector estimation using local fitting method, the viewpoint , neighborhood of point cloud , unit normal vector and viewing vector are marked, and the judgment logic of normal vector direction unification is clearly shown by the inner product of normal vector and viewing vector, providing principle support for ensuring the global consistency of normal vector on machining path. Then the calculation principle of actual reinforcement path of nozzle is shown, marking the curved surface reinforcement path, discrete points , discrete point outer normal vector , nozzle and actual reinforcement path. Clearly present the process of translating discrete points by target distance , the process of obtaining the nozzle end real trajectory (actual strengthening path) intuitively explains the logic of determining the nozzle position by the normal bias method, and ensures the constant target distance in the strengthening process. Finally, through the comparison chart of the surface surface strengthening path and the actual strengthening path, the coordinate unit is meter. The discrete point set of the solid line path in the figure is the surface contour line, and the dashed line path is the final shot path, and the original curved surface point cloud and the normal vector of the discrete points are labeled. The spatial position relationship of the two paths is intuitively displayed, which verifies that the actual strengthening path can maintain a constant target distance with the surface surface strengthening path, and the nozzle attitude is consistent with the normal vector, which provides path data reference for the mechanical arm to perform the strengthening task.

[0103] Experimental platform construction:

[0104] The conclusions of the method in the experiment are too idealized, and cannot fully reflect the real effect of the method of strengthening the complex curved surface by abrasive jet in the invention. This section adopts the method of building an experimental platform for practice to verify the effectiveness of the method.

[0105] The construction of the experimental platform is as Figure 4 , which is divided into a binocular structured light three-dimensional reconstruction system and an abrasive jet strengthening system. The hardware of the binocular structured light three-dimensional reconstruction system selects the DLP4500 light structure of the United States Ti company to build a projector, the binocular camera selects the MER-503-20GC-P of Dahuang, the sensor is 2 / 3" Global Shutter Sony IMX264 CMOS, and the lens selects Computar M1620-MPW2. The projector and the binocular camera are fixed on the optical platform, the relative position is adjusted to make the working distance of the reconstruction system, and the camera field of view can completely cover the aero-engine blade (TC4 titanium alloy material, curved and twisted complex curved surface) to be reconstructed. The software is loaded on an industrial computer, which realizes the functions of camera calibration, stereo correction, four-step phase shift, multi-frequency heterodyne, SAD stereo matching and three-dimensional coordinate calculation, and accelerates the program through Numba technology to improve the data processing efficiency; the projector external trigger function is used to realize the synchronous control with the camera, which ensures that the time of the projector projecting stripes and the camera capturing images is synchronized. The abrasive jet strengthening system includes an industrial robot, a high-pressure plunger pump and an abrasive supply device. The binocular structured light three-dimensional reconstruction system and the strengthening system are integrated, the communication between the computer and the robot, the high-pressure pump and the abrasive supply device is realized through industrial Ethernet, which ensures that the strengthening path data can be transmitted to the robot in real time, and the process parameters can be accurately controlled.

[0106] Before the experiment, the system parameters are calibrated, then the complex curved surface three-dimensional reconstruction is carried out, and then the strengthening path is planned and the nozzle trajectory is calculated. After completing the above work, the abrasive jet strengthening is carried out and the results are verified.

[0107] Comparative experiment:

[0108] In order to verify the superiority of the method of strengthening complex curved surface by the curve strengthening path of abrasive jet in this paper, further experiments are carried out using the experimental platform built. As shown in Figure 5 Fig. 6, the advantages of the strengthening method under the curve strengthening path provided by the patent in this paper are compared with the traditional straight line strengthening path. A total of 6 groups of experiments are carried out, as shown in Figure 6 to Figure 11 The strengthening topography, three-dimensional morphology, strengthening stripe characteristics of the two strengthening paths, and the surface roughness, surface residual stress and surface microhardness of the two types of blade under the straight line strengthening path and the curve strengthening path are compared.

[0109] Figure 5 Fig. 6 shows the schematic diagram of the two strengthening paths. In this paper, two different surface type TC4 titanium alloy aero-engine compressor blades are selected as experimental objects, and comparative experiments are carried out by using the curve strengthening path and the traditional straight line strengthening path. (a) is the schematic diagram of the traditional straight line strengthening path, which marks the distance between the nozzle and the blade There is a change in the situation) and the jet angle °, which intuitively reflects the defects of the target distance and the jet angle changing with the surface type under the straight line path; (b) is the schematic diagram of the curve strengthening path proposed in this paper, which marks the jet angle ° and the constant target distance , which clearly shows the advantages of the curve path that can always ensure the nozzle perpendicular to the curved surface and the constant target distance. Through the comparison of the two paths, the rationality of the method in this paper is highlighted.

[0110] Figure 6 Fig. 6 shows the schematic diagram of the strengthening topography under the two strengthening paths, Figure 6 (a) in Fig. 6 is the straight line strengthening of blade 1, Figure 6 (b) in Fig. 6 is the curve strengthening of blade 1, Figure 6 (c) in Fig. 6 is the straight line strengthening of blade 2, Figure 6 (d) in Fig. 6 is the curve strengthening of blade 2, and the analysis of the strengthening topography structure under the two strengthening paths shown in Fig. 6 shows that the stripe profile gradually becomes shallow along the transverse velocity direction under the straight line strengthening path, while the stripe profile has no obvious change under the curve strengthening path, which intuitively reflects the difference in strengthening effect of the two paths and verifies that the curve path can ensure more uniform strengthening quality. Analysis Figure 7 Three-dimensional morphology under the two strengthening paths.

[0111] Figure 7 (a) in Fig. 6 is the straight line strengthening of blade 1, Figure 7 (b) in Fig. 6 is the curve strengthening of blade 1, Figure 7 (c) in Fig. 6 is the straight line strengthening of blade 2, Figure 7(d) represents the blade 2-curve reinforcement. By comparing the three-dimensional contour details with the roughness data, the reinforcement advantage of the curve path was quantitatively verified.

[0112] Figure 8 The diagram shows the enhancement stripe features under two enhancement paths. Figure 8 (a) in the text represents leaf 1. Figure 8 (b) in the image represents leaf 2. Analysis Figure 8 The strengthening stripe characteristics under straight and curved strengthening paths for the two blade types show that the stripe width (blade 1: 571.7±91.9 um; blade 2: 618.2±46.1 um) and depth (blade 1: 11.4±0.8 um; blade 2: 11.0±1.5 um) under the curved strengthening path are smaller than those under the straight path, and the standard deviation is also lower, which intuitively quantifies the stability and high precision of the stripe characteristics under the curved path.

[0113] analyze Figure 9 The surface roughness analysis of two blade profiles under straight and curved reinforcement paths shows that the roughness at most measuring points is lower under the curved reinforcement path than under the straight path. Blade 1 shows a maximum reduction of 0.85 μm (compared to 2.991 μm under the straight path), and blade 2 shows a maximum reduction of 0.888 μm (compared to 3.258 μm under the straight path). The average roughness is also reduced, verifying that the curved path effectively improves surface quality and reduces roughness. Figure 10 The residual stress on the surface of the two blade types under the straight and curved reinforcement paths shows that the residual compressive stress amplitude at most measuring points under the curved reinforcement path is greater than that under the straight path. The maximum increase is 60.5 MPa for blade 1 (up to 845.7 MPa) and 100.5 MPa for blade 2 (up to 885.3 MPa). The average residual compressive stress is also significantly increased. The data distribution directly verifies that the curved path can effectively improve the surface residual compressive stress.

[0114] analyze Figure 11 The surface microhardness of the two blade types under straight and curved reinforcement paths shows that the microhardness of most measuring points under the curved reinforcement path is higher than that under the straight path. The maximum increase is 21.1 HV for blade 1 (up to 477.2 HV) and 35.2 HV for blade 2 (up to 495.2 HV). The average microhardness increases from 443.1 HV and 458.5 HV to 453.2 HV and 470.3 HV, respectively, which quantitatively verifies that the curved path can enhance the surface hardness of the material.

[0115] The experimental results show that the complex curved surface abrasive jet strengthening method provided in the present application can always maintain an ideal jet angle and a constant target distance by fusing surface information and strengthening processes through binocular structured light three-dimensional reconstruction and the microelement thought, compared with the traditional straight path, significantly improves the blade surface residual compressive stress and microhardness, and reduces the surface roughness and stripe fluctuation, and provides a reliable technical solution for the high-performance strengthening of the complex curved surface blade of the aero-engine.

[0116] Embodiment three

[0117] The structural block diagram of the complex curved surface self-adaptive abrasive jet strengthening system in the third embodiment of the present application, the complex curved surface self-adaptive abrasive jet strengthening system is used to realize the complex curved surface self-adaptive abrasive jet strengthening method as described in the first embodiment, and the system comprises:

[0118] The acquisition module is used to acquire the three-dimensional point cloud data set of the complex curved surface on the workpiece through the binocular structured light three-dimensional reconstruction system;

[0119] The analysis module is used to analyze the three-dimensional point cloud data set through the principal component analysis method, and a first principal component vector is acquired, the first principal component vector is the most dispersed direction of the point cloud distribution;

[0120] The first calculation module is used to set a cutting plane based on a preset feed amount, calculate the intersection line of the cutting plane and the three-dimensional point cloud data set based on the first principal component vector and through the intersection method, the intersection line is an initial path, and adjacent cutting planes are arranged at equal intervals;

[0121] The second calculation module is used to calculate the normal vector of each discrete point on the initial path, calculate the latest unit outer normal vector of the discrete point based on the normal vector and a user-defined viewpoint, and the latest unit outer normal vector is perpendicular to the complex curved surface of the workpiece;

[0122] The forming module is used to calculate the corresponding actual position coordinates of the nozzle relative to each discrete point based on a preset target distance and the unit outer normal vector of each discrete point, form a continuous strengthening path through linear and circular arc interpolation based on a plurality of actual position coordinates and in combination with the inverse kinematics of the industrial robot, and the continuous strengthening path is the movement track of the nozzle.

[0123] In specific implementation, a three-dimensional point cloud dataset of the workpiece is acquired by a binocular structured light three-dimensional reconstruction system, a first principal component vector is acquired by analyzing the three-dimensional point cloud dataset by principal component analysis, a preset feed amount is set as a section plane, an intersection line of the section plane and the three-dimensional point cloud dataset, i.e. an initial path, is calculated based on the first principal component vector and by intersection method, a normal vector of each discrete point on the initial path is calculated, a latest unit outer normal vector of the discrete point is obtained based on the normal vector and a self-defined viewpoint, actual position coordinates of the nozzle relative to each discrete point are calculated based on a preset target distance and the unit outer normal vector, and a continuous reinforcement path, i.e. a moving track of the nozzle, is formed by linear and circular arc interpolation based on the actual position coordinates and in combination with inverse kinematics of the industrial robot, so that a spraying operation is performed based on the moving track. Different from the prior art, the deviation between the CAD model and the actual object can be eliminated, the parts with manufacturing tolerance, clamping deformation or unknown surface have strong adaptability, the reinforcement path planning of the nozzle has the surface self-adaptation capability, the jet impact angle is always kept close to the optimal spraying angle on the entire complex surface, the jet energy is uniformly distributed, the reinforcement deficiency or over-reinforcement caused by the change of the angle and the distance is avoided, and therefore the residual compressive stress layer and the microhardness with consistent depth and higher value are obtained, and the fatigue resistance of the part is significantly improved.

[0124] Further, the binocular structured light three-dimensional system includes a DLP projector and two industrial cameras, and the acquisition module includes:

[0125] A capturing unit is configured to transmit a series of coded sinusoidal fringe lights to a workpiece placed in a measurement field of view by the DLP projector, and capture deformed fringe images after deformation of the sinusoidal fringe lights modulated by a complex surface on the workpiece by the two industrial cameras.

[0126] A heterodyne unit is configured to calculate principal values of phases in a preset interval based on the deformed fringe images by a four-step phase shift method, perform heterodyning on high-frequency phases by a multi-frequency heterodyning technique to obtain unwrapped phases, and perform secondary heterodyning on the unwrapped phases to obtain absolute phases with an equivalent frequency of 1.

[0127] A obtaining unit is configured to perform dense matching on the deformed fringe images by a sliding window and absolute error algorithm based on the absolute phases as matching basis, calculate a disparity of each pixel point, and convert the disparity into a three-dimensional space coordinate by a triangulation principle to obtain a three-dimensional point cloud dataset, wherein the three-dimensional point cloud dataset includes a plurality of three-dimensional point cloud data.

[0128] Further, the system further includes, after the capturing unit:

[0129] A correction unit is configured to calibrate two deformation fringe images based on internal parameters and external parameters of each industrial camera obtained by Zhang Zhengyou calibration method based on a high-precision planar circular target calibration plate.

[0130] Further, the analysis module comprises:

[0131] A decentralization unit is configured to perform decentralization processing on the three-dimensional point cloud dataset to obtain a decentralized point cloud dataset, construct a covariance matrix representing correlation coefficients of the surface point cloud based on the decentralized point cloud dataset, and perform singular value decomposition on the covariance matrix to obtain a first principal component vector.

[0132] The expression of the decentralized point cloud dataset is as follows:

[0133]

[0134] Wherein, represents the decentralized point cloud dataset, represents the three-dimensional point cloud dataset, represents the mean of the three-dimensional point cloud dataset, represents the number of data points on the workpiece, represents the three-dimensional point cloud data of the i-th data point, represents the data of the i-th data point in the x direction, represents the data of the i-th data point in the y direction, represents the data of the i-th data point in the z direction.

[0135] Further, the first calculation module comprises:

[0136] A translation unit is configured to translate the tangent plane based on the first principal component vector to obtain a positive plane and a negative plane, and take the three-dimensional point cloud data on the positive plane as a positive neighborhood neighboring point cloud and take the three-dimensional point cloud data on the negative plane as a negative neighborhood neighboring point cloud.

[0137] A forming unit is configured to find the nearest point of the data point corresponding to the three-dimensional point cloud data in the positive neighborhood neighboring point cloud in the negative neighborhood neighboring point cloud to form a matching point pair, and traverse all point clouds to determine the matching point pair of each data point in the positive neighborhood neighboring point cloud.

[0138] A constituting unit is configured to calculate the intersection of the line segment between each unique matching point pair and the tangent plane, and constitute the intersection line of the tangent plane and the three-dimensional point cloud dataset based on all the intersections.

[0139] Further, the expression of the local fitting plane is as follows:

[0140]

[0141] wherein, denotes the unit normal vector of the local fitting plane Z, denotes the parameter value of the independent variable at which the local fitting plane takes a minimum value, denotes the distance of the local fitting plane to the coordinate origin, denotes the points within the neighborhood k according to the distance to the estimation point are set to the Gaussian weight coefficients.

[0142] Further, the expression of the actual position coordinates is as follows:

[0143]

[0144] wherein, denotes the actual position coordinates of the corresponding nozzle of the discrete point on the initial path, denotes the target distance of the abrasive jet strengthening, denotes the outward normal vector of the discrete point estimated by the expression of the local fitting plane.

[0145] Embodiment four

[0146] The fourth embodiment of the present application, based on the same inventive concept, the present application proposes a computer readable storage medium, the computer readable storage medium stores a computer program, the computer program is executed by the processor to realize the steps of the complex curved surface adaptive abrasive jet strengthening method of the above-mentioned embodiments.

[0147] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered a list of executable instructions for implementing logic functions, and can be specifically embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor- based system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions, or in conjunction with which the instructions may be executed. For the purposes of this specification, a "computer-readable medium" can be any device that contains or stores a program for use by or in connection with an instruction execution system, apparatus, or device, or that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable medium can be, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, device, or propagation medium.

[0148] More specific examples (a non-exhaustive list) of the computer-readable medium include the following: an electrical connection (electronic) having one or more wires, a portable computer diskette (magnetic), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, for instance via an optical scanner, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.

[0149] The memory can include mass storage for data or instructions. By way of example, and not limitation, the memory can include a Hard Disk Drive (HDD), a floppy disk drive, a Solid State Drive (SSD), a flash drive, a Compact Disc (CD) ROM, a Digital Versatile Disc (DVD) ROM, a Blu-ray disk, a magnetic tape, or a Universal Serial Bus (USB) drive, or a combination of two or more of these. The memory can be removable and / or non-removable (or fixed) as appropriate. The memory can be internal or external as appropriate. In certain embodiments, the memory is a non-volatile memory. In certain embodiments, the memory includes a Read-Only Memory (ROM) and a Random Access Memory (RAM). The ROM can be a mask-programmed ROM, a Programmable Read-Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), an Electrically Alterable Read-Only Memory (EAROM), or a FLASH memory, or a combination of two or more of these, as appropriate. The RAM can be a Static Random-Access Memory (SRAM) or a Dynamic Random Access Memory (DRAM), which can be a Fast Page Mode Dynamic Random Access Memory (FPMDRAM), an Extended Data Output Dynamic Random Access Memory (EDODRAM), a Synchronous Dynamic Random-Access Memory (SDRAM), or the like, as appropriate.

[0150] Embodiment Five

[0151] The fifth embodiment of the present application is based on the same inventive concept, and the present application provides a terminal, which comprises a processor, a memory, the processor and the memory communicate with each other, the memory is used for storing instructions, and the processor is used for executing the instructions in the memory to execute the complex curved surface adaptive abrasive jet strengthening method of the above-mentioned embodiments.

[0152] It should be understood that parts of the present application can be realized by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be realized by software or firmware stored in the memory and executed by a suitable instruction execution system. For example, if realized by hardware, and as in another embodiment, any one or a combination of the following technologies known in the art can be used: discrete logic circuit with logic gate circuit for implementing logic function on data signal, application specific integrated circuit with suitable combination logic gate circuit, programmable gate array (PGA), field programmable gate array (FPGA), etc.

[0153] In the description of the present application, the description of the terms "one embodiment", "some embodiments", "an example", "a specific example" or "some examples" means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present application, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0154] The above-mentioned additional technical features can be freely combined and used by those skilled in the art without conflict.

[0155] The above-mentioned only the preferred embodiments of the present application, and not to limit the present application, any modification, equivalent replacement and improvement made within the spirit and principles of the present application, etc., should be included in the protection scope of the present application.

Claims

1. A method for adaptive abrasive jet strengthening of complex curved surfaces, characterized in that, The method includes: A three-dimensional point cloud dataset of complex curved surfaces on a workpiece is obtained using a binocular structured light three-dimensional reconstruction system. The three-dimensional point cloud dataset is analyzed by principal component analysis to obtain the first principal component vector, which is the direction in which the point cloud distribution is most dispersed. The cutting plane is set based on the preset feed rate. Based on the first principal component vector, the intersection line between the cutting plane and the three-dimensional point cloud dataset is calculated by the intersection method. This intersection line is the initial path, and adjacent cutting planes are set at equal intervals. Calculate the normal vector of each discrete point on the initial path, and calculate the latest unit outward normal vector of the discrete point based on the normal vector and the custom viewpoint. The latest unit outward normal vector is perpendicular to the complex surface of the workpiece. Based on the preset target distance and the unit outward normal vector of each discrete point, the actual position coordinates of the nozzle relative to each discrete point are calculated. Based on multiple actual position coordinates and combined with the inverse kinematics of the industrial robotic arm, a continuous reinforcement path is formed by linear circular interpolation. The continuous reinforcement path is the movement trajectory of the nozzle. The step of calculating the intersection line between the cutting plane and the three-dimensional point cloud dataset based on the first principal component vector and using the intersection method includes: The cutting plane is translated based on the first principal component vector to obtain a positive plane and a negative plane. The three-dimensional point cloud data on the positive plane is taken as the positive neighboring point cloud, and the three-dimensional point cloud data on the negative plane is taken as the negative neighboring point cloud. Find the nearest point of the measurement point in the positive neighboring point cloud in the negative neighboring point cloud to form a matching point pair, and traverse all point clouds to determine the unique matching point pair corresponding to each measurement point in the positive neighboring point cloud; Calculate the intersection points of the line segments between each unique matching point pair and the cutting plane, and construct the intersection line between the cutting plane and the three-dimensional point cloud dataset based on all the intersection points.

2. The adaptive abrasive jet strengthening method for complex curved surfaces according to claim 1, characterized in that, The binocular structured light 3D system includes a DLP projector and two industrial cameras. The steps of acquiring a 3D point cloud dataset of a complex curved surface on a workpiece using the binocular structured light 3D reconstruction system include: The DLP projector transmits a series of coded sinusoidal stripe lights onto the workpiece placed within the measurement field of view. When the sinusoidal stripe lights are deformed by the shape modulation of the complex curved surface on the workpiece, the deformed stripe images are captured by two industrial cameras. Based on the deformed stripe image, the principal phase within the preset interval is calculated by the four-step phase shift method. The high-frequency phases are heterodyned using multi-frequency heterodyne technology to obtain the expanded phase. The expanded phases are then heterodyned twice to obtain the absolute phase with an equivalent frequency of 1. Based on the absolute phase, the deformed stripe image is densely matched using an algorithm of sliding window and absolute error. The disparity of each pixel is calculated, and the disparity is converted into three-dimensional spatial coordinates using the principle of triangulation to obtain a three-dimensional point cloud dataset, which includes multiple three-dimensional point cloud data.

3. The adaptive abrasive jet strengthening method for complex curved surfaces according to claim 2, characterized in that, After capturing the deformed stripe images using the two industrial cameras, the method further includes: Based on a high-precision planar circular target calibration plate, and by using the Zhang Zhengyou calibration method, the internal and external parameters of each industrial camera are obtained. Based on the internal and external parameters, stereo correction is performed on the two deformed stripe images.

4. The adaptive abrasive jet strengthening method for complex curved surfaces according to claim 1, characterized in that, The step of analyzing the 3D point cloud dataset using principal component analysis to obtain the first principal component vector includes: The three-dimensional point cloud dataset is decentralized to obtain a decentralized point cloud dataset. A covariance matrix representing the correlation coefficient of the surface point cloud is constructed based on the decentralized point cloud dataset. Singular value decomposition is performed on the covariance matrix to obtain the first principal component vector.

5. The adaptive abrasive jet strengthening method for complex curved surfaces according to claim 4, characterized in that, The expression for the decentralized point cloud dataset is as follows: in, This represents a decentralized point cloud dataset. Represents a 3D point cloud dataset. This represents the mean of the 3D point cloud dataset. This indicates the number of data points on the workpiece. This represents the 3D point cloud data of the i-th data point. This represents the data of the i-th data point in the x-direction. This represents the data of the i-th data point in the y-direction. This represents the data of the i-th data point in the z-direction.

6. The adaptive abrasive jet strengthening method for complex curved surfaces according to claim 1, characterized in that, The expression for the actual position coordinates is as follows: in, Represents discrete points on the initial path The corresponding actual position coordinates of the nozzle This indicates the target distance for abrasive jet reinforcement. The expression representing the local fitted plane estimates the outward vector of the discrete point.

7. A complex curved surface adaptive abrasive jet strengthening system, used to implement the complex curved surface adaptive abrasive jet strengthening method as described in any one of claims 1-6, characterized in that, The system includes: The acquisition module is used to acquire a 3D point cloud dataset of complex curved surfaces on a workpiece through a binocular structured light 3D reconstruction system. The analysis module is used to analyze the three-dimensional point cloud dataset using principal component analysis to obtain the first principal component vector, which is the direction in which the point cloud distribution is most dispersed. The first calculation module is used to set the cutting plane based on the preset feed amount, and calculate the intersection line between the cutting plane and the three-dimensional point cloud dataset based on the first principal component vector and by the intersection method. The intersection line is the initial path, and adjacent cutting planes are set at equal intervals. The second calculation module is used to calculate the normal vector of each discrete point on the initial path, and to calculate the latest unit outward normal vector of the discrete point based on the normal vector and the custom viewpoint. The latest unit outward normal vector is perpendicular to the complex surface of the workpiece. The forming module is used to calculate the actual position coordinates of the nozzle relative to each of the discrete points based on the preset target distance and the unit outward normal vector of each discrete point. Based on multiple actual position coordinates and combined with the inverse kinematics of the industrial robotic arm, a continuous reinforcement path is formed by linear circular interpolation. The continuous reinforcement path is the movement trajectory of the nozzle.

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