A method for polishing a coating of a turbine blade

Abstract

The present invention discloses a method for polishing a turbine blade coating, comprising the following steps: obtaining a three-dimensional model of the blade to be polished, reading a first point cloud data set on the surface of the three-dimensional model, and identifying a theoretical point cloud set and a comparative theoretical point position set; obtaining the wall thickness data on the blade to be polished and determining whether the blade to be polished needs to be polished according to the wall thickness data; respectively using the positions where the point cloud data in the comparative theoretical point position set are located as data acquisition points to determine a second point cloud data set on the surface of the blade to be polished; matching the point cloud data in the first point cloud data set and the second point cloud data set to determine the position and attitude of the blade to be polished; determining a polishing path according to the position and attitude of the blade; determining the pre-pressure amount of the polishing wheel at each position on the polishing path according to each wall thickness data and the corresponding standard wall thickness value and correcting the polishing path. This method has strong universality and improves the polishing quality and polishing stability of the blade.

Description

Technical Field

[0001] The present invention belongs to the technical field of blade polishing and specifically relates to a method for polishing the coating of a turbine blade. Background Art

[0002] Before coating repair of the high-pressure turbine blade of an aeroengine, it is necessary to remove the surface thermal barrier coating by polishing. The blade structure is very complex and the surface curvature changes greatly. Generally, automated polishing is used for coating removal currently.

[0003] The automated polishing equipment sets the polishing program according to the theoretical model size of the blade. The following problems exist in the actual polishing process:

[0004] 1. It cannot adapt to blades with different deformation amounts and has poor universality;

[0005] 2. During the polishing process, the polishing quality stability for blades of different batches is poor. Over-polishing or insufficient polishing often occurs. Some blades are scrapped due to unqualified local wall thickness of the blade body after polishing, resulting in a low polishing qualification rate and high production costs. Summary of the Invention

[0006] To solve the problems of poor universality and low polishing qualification rate of the existing methods, the present invention provides a method for polishing the coating of a turbine blade, which has strong universality and improves the polishing quality and stability of the blade.

[0007] The purpose of the present invention is achieved through the following technical solutions:

[0008] The present invention provides a method for polishing the coating of a turbine blade, including the following steps:

[0009] Obtain the three-dimensional model of the blade to be polished, read the first point cloud data set on the surface of the three-dimensional model, confirm the theoretical point cloud set from the first point cloud data set and confirm the comparison theoretical point position set from the theoretical point cloud set. The theoretical point cloud set includes at least 58 point cloud data, and the comparison theoretical point position set includes at least 9 point cloud data;

[0010] Obtain the wall thickness data at the positions corresponding to each point cloud data in the theoretical point cloud set on the blade to be polished and determine whether the blade to be polished needs to be polished according to the wall thickness data;

[0011] In response to the blade to be polished needing to be polished, respectively take the positions of each point cloud data in the comparison theoretical point position set as data acquisition points to determine the second point cloud data set on the surface of the blade to be polished;

[0012] Match the point cloud data in the first point cloud data set and the second point cloud data set to determine the position and posture of the blade to be polished;

[0013] Determine the polishing path according to the position and attitude of the blade;

[0014] Determine the pre-pressure amount of the polishing wheel at each position on the polishing path according to the wall thickness data and the corresponding standard wall thickness value, and correct the polishing path.

[0015] Compared with the prior art, the present invention has at least the following advantages and beneficial effects:

[0016] 1. The method of the present invention is suitable for polishing the surface coatings of high-pressure turbine blades with different deformation amounts, and has strong universality.

[0017] 2. The method of the present invention detects the wall thickness at multiple points on the blade to be polished, places the blade to be polished at the corresponding position through the theoretical point cloud set, measures the second point cloud data set, obtains the position and attitude that the blade to be polished needs to be adjusted to through point cloud matching, plans the polishing path, and corrects the path according to the blade wall thickness data, so that the wall thickness control is more accurate, reduces the unqualified wall thickness caused by over-polishing, and improves the accuracy and qualification rate of blade polishing and grinding. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0019] Figure 1 is a flow chart of the method of the present invention;

[0020] Figure 2 is a schematic cross-sectional view of point collection of a high-pressure turbine blade;

[0021] Figure 3 is a schematic diagram of the point collection positions on the blade basin of a high-pressure turbine blade;

[0022] Figure 4 is Figure 3 an enlarged view of part A in

[0023] Figure 5 is a schematic diagram of the point collection positions on the blade back of a high-pressure turbine blade. DETAILED DESCRIPTION OF THE INVENTION

[0024] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. The components of the embodiments of the present invention usually described and illustrated in the drawings here can be arranged and designed in various different configurations.

[0025] Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed present invention, but merely represents selected embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0026] It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other.

[0027] It should be noted that similar reference numerals and letters indicate similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings.

[0028] In the description of the present invention, it should be noted that the orientation or positional relationship indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings, or the orientation or positional relationship when the product of the invention is normally placed, or the orientation or positional relationship commonly understood by those skilled in the art. It is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation of the present invention. In addition, the terms "first", "second", etc. are only used for descriptive distinction and cannot be understood as indicating or implying relative importance.

[0029] In the description of the present invention, it should also be noted that unless otherwise clearly defined and limited, the terms "set", "install", "connected", "connected to" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0030] The present invention discloses a method for polishing a coating of a turbine blade. As Figure 1 shown, this method includes step S01 to step S05.

[0031] Step S01: Obtain the three-dimensional model of the blade to be polished, read the first point cloud data set on the surface of the three-dimensional model, confirm the theoretical point cloud set from the first point cloud data set, and confirm the comparison theoretical point position set from the theoretical point cloud set. The theoretical point cloud set includes at least 58 point cloud data, and the comparison theoretical point position set includes at least 9 point cloud data.

[0032] Specifically, in this step, by importing the three-dimensional model of the blade to be polished into the polishing robot control software, the determination of the point cloud data in the theoretical point cloud set can be either manually selected or randomly selected. In order to comprehensively show the changes in the surface position and pose and improve the polishing quality, nine scattered points on the blade body are preferentially selected as the comparison theoretical point positions. The comparison theoretical point position set is the point cloud in the theoretical point cloud set, that is, the number of point clouds in the comparison theoretical point position set is less than or equal to the number of point clouds in the theoretical point cloud set.

[0033] After the three-dimensional model is imported into the polishing robot control software, its three-dimensional coordinates can use the direction from the origin on the blade surface to the blade tip as the Y-axis, the Z-axis is perpendicular to the blade surface, set the surface parameters, divide the blade's concave surface into several lines according to the inner cavity central axis, divide the blade's convex surface into several lines according to the inner cavity central axis, and set 4 cross-sections along the axial direction of the blade body according to the wall thickness detection requirements. Obtain the coordinates of several intersection points of each line and the cross-section on the blade coordinate system according to the blade model, and obtain the theoretical point cloud data on the surface of the blade three-dimensional model.

[0034] Among them, the point clouds in the theoretical point cloud set are related to the polishing quality. Therefore, preferably, the theoretical point cloud set includes the point clouds at the blade tip, the point clouds on the concave surface, and the point clouds on the convex surface; among them, there are at least 13 point clouds at the blade tip, the point clouds on the concave surface include at least 7 point clouds on the concave surface section II, at least 7 point clouds on the concave surface section III, and at least 7 point clouds on the concave surface section V; the point clouds on the convex surface include at least 8 point clouds on the convex surface section II, at least 8 point clouds on the convex surface section III, and at least 8 point clouds on the convex surface section IV.

[0035] In order to improve the polishing quality, the position of the point cloud data in the theoretical point cloud set should not be too close to the inlet edge. The distance between the point cloud data and the inlet edge of the blade is greater than or equal to 3 mm, so that the point positions correspond to the inner cavity of the blade. The specific position of the inlet edge refers to Figure 3 the inlet edge endpoint 2 of the point collection position on the concave surface section II and the trailing edge endpoint 3 of the concave surface section I in the middle Figure 5 the exhaust edge endpoint 5 of the point collection position on the concave surface section III and the inlet edge endpoint 6 of the convex surface section I in the middle

[0036] Among them, the two outer endpoints of the section II, section III, section V, and section IV are not less than 3 mm from both ends of the inlet edge. Preferably, this distance is greater than or equal to 5 mm.

[0037] Step S02: Obtain the wall thickness data at the positions corresponding to each point cloud data in the theoretical point cloud set of the blade to be polished, and determine whether the blade to be polished needs to be polished according to the wall thickness data.

[0038] The wall thickness measurement positions of the blade to be polished are the same as the positions of each point cloud data in the theoretical point cloud set.

[0039] Exemplarily, if the theoretical point cloud set in step S01 includes 13 point clouds at the blade tips, 7 point clouds on the second section of the blade concave surface, 7 point clouds on the third section of the blade concave surface, 7 point clouds on the fifth section of the blade concave surface, 8 point clouds on the second section of the blade convex surface, 8 point clouds on the third section of the blade convex surface, and 8 point clouds on the fourth section of the blade convex surface, then in this step, it is also necessary to measure the wall thickness data of the blade to be polished at the corresponding 13 blade tips, 7 on the second section of the blade concave surface, 7 on the third section of the blade concave surface, 7 on the fifth section of the blade concave surface, 8 on the second section of the blade convex surface, 8 on the third section of the blade convex surface, and 8 on the fourth section of the blade convex surface.

[0040] When measuring the wall thickness data, first measure the wall thickness at the detection points at the blade tips, and then determine the minimum wall thickness value among the wall thickness data at the blade tips; finally, judge the size relationship between the minimum wall thickness value and the standard wall thickness value at its corresponding position. If the minimum wall thickness value is greater than or equal to the standard wall thickness value at its corresponding position, the blade to be polished needs to be polished, and the subsequent steps can be continued; if the minimum wall thickness value is less than the standard wall thickness value at its corresponding position, the blade to be polished does not need to be polished, and the polishing is suspended.

[0041] On the premise that the wall thickness at the blade tips is detected to be qualified; then measure the wall thickness at the corresponding detection points on the first blade concave surface and the fourth blade convex surface. Set 4 measurement sections in the direction perpendicular to the main axis of the blade, as Figure 2 shown; Exemplarily, 7 points are detected on the second section of the blade concave surface, 7 points are detected on the third section of the blade concave surface, and 7 points are detected on the fifth section of the blade concave surface, as Figure 3 shown; 8 points are detected on the second section of the blade convex surface, 8 points are detected on the third section of the blade convex surface, and 8 points are detected on the fourth section of the blade convex surface, as Figure 5 shown, and a total of 58 points need to be detected.

[0042] In this step, the acquisition of the wall thickness data can be measured using an ultrasonic thickness gauge, where Figure 4 where h is the wall thickness of a certain point at the blade tip. During measurement, glycerol can be used as the coupling agent, and at the same time, marks are made on the blade body for the points.

[0043] After the detection is completed, first judge whether the wall thickness is qualified. If it is unqualified, stop the repair. If it is qualified, the maximum preloading amount of the points needs to be calculated.

[0044] Step S03: In response to the need for polishing of the blade to be polished, taking the positions of the respective point cloud data concentrated in the comparison theoretical points as data collection points, determine the second point cloud data set on the surface of the blade to be polished.

[0045] In this step, an online calibration of the blade to be polished can be performed using a laser sensor. Set the position 20 cm away from the laser sensor as the origin of the tool coordinate system, and the Z-axis of the tool coordinate system is along the laser direction.

[0046] Input the comparison theoretical point data into the five-axis CNC machine tool, control the machine tool to move to the corresponding positions respectively, that is, control the theoretical point cloud data to move to the origin of the laser sensor coordinate system respectively, and use the laser sensor to perform online calibration on the blade to be polished.

[0047] Specifically, according to the theoretical point cloud set obtained in step S01, calculate the pose of the robot when a point on the surface of the blade three-dimensional model moves to the origin of the tool coordinate system; control the robot to move to the above pose state, and use the laser sensor to measure the point data of the blade to be polished; when the distance measured by the laser sensor is not 0, keep the state of the laser sensor, that is, the laser sensor is always located at the actually measured point, and make the blade to be polished move along the Z-axis of the tool coordinate system until the distance measured by the laser sensor is 0. At this time, there is no assembly error at this point on the blade to be polished, and calculate the actual point cloud data, that is, the second point cloud data set, in the corresponding blade surface coordinate system according to the pose of the robot at this time.

[0048] In this step, if there is no assembly error between the machine tool and the blade to be polished, then when controlling the blade to be polished to move to the corresponding theoretical point, the distance measured by the laser sensor is 0. In fact, due to the offset of the workpiece coordinate system, when the laser hits the corresponding point on the blade to be polished, the laser sensor does not show 0 at this time; if the distance is greater than 0, when using a sand belt for grinding and polishing, there will be an under-polishing phenomenon, and on the contrary, there will be an over-polishing phenomenon.

[0049] When the distance of the actually calibrated point on the blade is not 0, keep the laser sensor always located at the actually measured point, control the machine tool to clamp the blade and move along the Z-axis of the tool coordinate system, that is, the laser direction, so that the blade moves to the position where the distance measurement is 0, that is, the position of the coordinate system origin, and read the pose of the machine tool at this time as the actual pose data of the theoretical point.

[0050] When performing online calibration on the blade three-dimensional model, select 9 scattered point data from 58 points for ultrasonic wall thickness measurement for calibration.

[0051] Step S04: Match the point cloud data in the first point cloud data set and the second point cloud data set to determine the position and pose of the blade to be polished.

[0052] Through steps S01 and S03, the theoretical points and corresponding actual points, that is, the first point cloud dataset and the second point cloud dataset, are obtained. In this regard, under the condition of the known theoretical workpiece coordinate system, the coordinate transformation relationship between the point clouds can be further calculated, and the theoretical coordinate system can be updated online according to the calibration result for adaptive adjustment to obtain the position of the actual workpiece coordinate system, realizing the calibration of the coordinate system to optimize the grinding and polishing trajectory and improve the machining accuracy.

[0053] Specifically, the particle swarm algorithm is used to search for the position after the offset of the point cloud data in the first point cloud dataset around the point cloud data in the second point cloud dataset. The maximum distance error of the fitting surface is used as the fitness function to determine the transformation matrix between the point cloud data corresponding to the minimum fitness function value, that is, the rotation and translation transformation for the pose adjustment of the actual blade to be polished and repaired, that is, to confirm the position and posture of the blade to be polished and repaired, realizing the calibration of the assembly error of the blade.

[0054] To improve the calibration accuracy and calibration efficiency, when using the particle swarm algorithm for searching, the number of particle groups is 50 groups, the search radius is 0.05 mm, and the number of iterations is 150 times.

[0055] After calibration, to improve the accuracy, it is necessary to judge the accuracy of the error calibration. When judging, the fitting surface is used as the evaluation criterion. Specifically, first, the surface fitting is performed on the theoretical point cloud set and the calibrated actual point cloud data respectively; then, the distance between the corresponding positions on the two fitted surfaces is calculated. When the maximum value of the distances between the positions on the two surfaces meets the requirements, it indicates that the calibration result meets the accuracy requirements and the surface machining can be carried out; otherwise, the point cloud matching is performed again, the positions are corrected, and then the fitting surface is performed and the distance is calculated.

[0056] Step S05: Determine the polishing and repair path according to the position and posture of the blade.

[0057] The polishing and repair path can be planned by partitioning the point cloud area of the blade to be polished and repaired and performing grinding in different areas. The abrasive belt grinds in a Z-shaped path relative to the blade on the blade surface to improve the polishing and grinding accuracy.

[0058] Specifically, start the polishing and repair from the root point near the boundary of the blade to be polished and repaired. Select the adjacent point with the same Y coordinate as the first point as the second point, and the point with the same X coordinate as the first point and adjacent in the Y direction as the third point. In the next cycle, use the above third point as the starting point and select points according to the same rule until reaching the top of the blade, that is, a Z-shaped path is obtained.

[0059] Step S06: Determine the pre-pressure amount of the polishing wheel at each position on the polishing and repair path according to the wall thickness data and the corresponding standard wall thickness value and correct the polishing and repair path.

[0060] This step can adopt a multi-axis machining strategy. The pre-pressure of the polishing wheel is set by the tool diameter. According to the wall thickness data, the program is manually adjusted to reduce the actual pre-pressure at the points with a smaller wall thickness in the blade movement path, or skip the positions on the blade that do not need to be polished. According to the result of the path planning, the blade is polished on the abrasive belt. During the blade polishing process, the polishing force of the blade is controlled within a certain range by a force control device to ensure uniform polishing quality on the blade surface.

[0061] The pre-pressure of the polishing wheel at each position on the polishing path is determined according to the difference between the wall thickness at this position of the blade to be polished and the corresponding qualified wall thickness value, that is, the standard wall thickness. Through the collected wall thickness data, the polishing path is corrected to achieve the purpose of reducing the pre-pressure at the points with a smaller wall thickness and improving the polishing quality.

[0062] By using the above method, the point position data is online calibrated through the three-dimensional model of the blade to be polished. According to the point position data of the three-dimensional model, the actual blade to be polished is online calibrated to obtain the actual point position data. By matching and correcting the point position information of the blade model and the actual blade point position information, the assembly error is calibrated, and the wall thickness at the corresponding points of the blade is measured, so as to correct the grinding trajectory and realize the wall thickness control of polishing.

[0063] Based on the method disclosed in the present invention, it can adapt to the polishing of blade coatings with different deformation amounts. The calibrated curved surface is more fitting, the wall thickness control is more accurate, the accuracy of blade calibration is improved, the unqualified wall thickness caused by over-polishing is reduced, and the accuracy and qualification rate of blade polishing and grinding are improved.

[0064] Although the present invention has been described in detail with reference to the foregoing embodiments, for those skilled in the art, they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for polishing a coating of a turbine blade, characterized in that, Including the following steps: Obtain a three-dimensional model of the blade to be polished, read the first point cloud data set on the surface of the three-dimensional model, confirm a theoretical point cloud set from the first point cloud data set, and confirm a comparison theoretical point position set from the theoretical point cloud set. The theoretical point cloud set includes at least 58 point cloud data, and the comparison theoretical point position set includes at least 9 point cloud data; Obtain the wall thickness data at the positions corresponding to each point cloud data in the theoretical point cloud set on the blade to be polished, and determine whether the blade to be polished needs to be polished according to the wall thickness data; In response to the blade to be polished needing to be polished, respectively use the positions of each point cloud data in the comparison theoretical point position set as data collection points to determine a second point cloud data set on the surface of the blade to be polished; Match the point cloud data in the first point cloud data set and the second point cloud data set to determine the position and posture of the blade to be polished; Determine a polishing path according to the position and posture of the blade; Determine the pre-pressure amount of the polishing wheel at each position on the polishing path according to each wall thickness data and the corresponding standard wall thickness value, and correct the polishing path; The theoretical point cloud set includes point clouds at the blade tip, on the blade basin, and on the blade back; Among them, there are at least 13 point clouds at the blade tip, The point clouds on the blade basin include at least 7 point clouds on the blade basin section II, at least 7 point clouds on the blade basin section III, and at least 7 point clouds on the blade basin section V; The point clouds on the blade back include at least 8 point clouds on the blade back section II, at least 8 point clouds on the blade back section III, and at least 8 point clouds on the blade back section IV.

2. A method for polishing a coating of a turbine blade according to claim 1, characterized in that: The point clouds in the comparison theoretical point position set are scattered point clouds.

3. A method for polishing a coating of a turbine blade according to claim 1, characterized in that, The determining whether the blade to be polished needs to be polished according to the wall thickness data includes: Determine the minimum wall thickness value in the wall thickness data at the blade tip on the blade to be polished; Judge the magnitude relationship between the minimum wall thickness value and the standard wall thickness value at its corresponding position, If the minimum wall thickness value is greater than or equal to the standard wall thickness value at its corresponding position, the blade to be polished needs to be polished; If the minimum wall thickness value is less than the standard wall thickness value at its corresponding position, the blade to be polished does not need to be polished.

4. A method for polishing a coating of a turbine blade according to claim 1, characterized in that: The respectively using the positions of each point cloud data in the comparison theoretical point position set as data collection points to determine a second point cloud data set on the surface of the blade to be polished includes: According to the theoretical point cloud set, calculate the pose of the robot when a point on the surface of the blade three-dimensional model moves to the origin of the tool coordinate system. The origin of the tool coordinate system is 20 cm away from the laser sensor, and the Z axis of the tool coordinate system is along the laser direction; Respectively control the robot to move to the pose, and use the laser sensor to measure the point position data of the blade to be polished; In response to the laser sensor ranging not being 0, keep the laser sensor state, control the blade to be polished to move along the Z axis of the tool coordinate system until the laser sensor ranging is 0, and calculate the second point cloud data set in the surface coordinate system of the blade to be polished according to the robot pose at this time.

5. A method for polishing a coating of a turbine blade according to claim 1, characterized in that: The matching the point cloud data in the first point cloud data set and the second point cloud data set to determine the position and posture of the blade to be polished includes: Use the particle swarm optimization algorithm to search for the position after the offset of the point cloud data in the first point cloud dataset around the point cloud data in the second point cloud dataset, and use the maximum distance error of the fitted surface as the fitness function to determine the transformation matrix between the point cloud data corresponding to the minimum fitness function value.

6. A method for polishing a coating of a turbine blade according to claim 5, characterized in that: When using the particle swarm optimization algorithm to search for the position after the offset of the point cloud data in the first point cloud dataset around the point cloud data in the second point cloud dataset, the number of particle groups is 50, the search radius is 0.05 mm, and the number of iterations is 150.

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