Adaptive polishing method for turbine blade based on industrial robot with abrasive belt polishing machine

Abstract

The adaptive grinding and polishing method of the industrial robot turbine blade based on the abrasive belt grinding and polishing machine comprises the following steps: calibrating the coordinate systems of the grinding and polishing wheel and the scanner, clamping the blade by the robot to obtain blade measurement data; pre-processing the measurement data to obtain a point cloud model, reconstructing the repair area model of the point cloud model to obtain a reconstructed model; calculating the machining allowance and the machining area of the repair area according to the measurement data and the reconstructed model; planning the path for the machining area; post-processing the point position information of the path planning in combination with the type of the robot control and the kinematic parameters; and polishing the blade by the grinding and polishing machine according to the path planning. The present application is simple to operate and ensures the stability of the product quality. It not only improves the machining efficiency and the overall quality, but also reduces the rate of unqualified blades, bringing innovation to the traditional machining mode.

Description

Technical Field

[0001] This invention relates to the field of blade grinding and polishing technology, and in particular to an adaptive grinding and polishing method for turbine blades using an industrial robot based on a belt grinding and polishing machine. Background Technology

[0002] As a critical power component, aero-engine turbine rotor blades are susceptible to damage such as wear, cracks, ablation, and even breakage at the blade tips due to prolonged exposure to strong corrosion, gas impingement, and high dynamic loads, posing a threat to engine operational safety. After blade repair, the surface still requires grinding and polishing to ensure quality standards are met. However, current grinding and polishing operations are primarily performed manually by workers, involving multiple measurements and polishing steps. This manual method presents three major problems: first, it is inefficient and cannot meet the increasing demands for efficiency; second, it relies heavily on worker experience, potentially leading to inconsistent product quality; and third, the metal dust and noise generated during the grinding and polishing process pose safety hazards to workers. Summary of the Invention

[0003] The purpose of this invention is to provide an adaptive grinding and polishing method for turbine blades of industrial robots based on a belt grinder, so as to solve the problems mentioned in the background section above.

[0004] To achieve the above objectives, the present invention adopts the following technical solution:

[0005] An adaptive grinding and polishing method for turbine blades using an industrial robot based on a belt polisher includes:

[0006] The coordinate systems of the polishing wheel and scanner are calibrated, and the robot clamps the blade to acquire blade measurement data;

[0007] The measurement data is preprocessed to obtain a point cloud model, and the point cloud model is reconstructed by repairing the region model to obtain a reconstructed model.

[0008] Based on the measurement data and reconstruction model, calculate the processing allowance and processing area of ​​the repair area, and perform path planning for the processing area;

[0009] The location information of the path planning is combined with the robot's control type and kinematic parameters for post-processing;

[0010] The polishing machine polishes the blades according to the planned path.

[0011] Furthermore, the coordinate systems of the polishing wheel and scanner are calibrated, and the robot grips the blade to acquire blade measurement data, including:

[0012] The calibration of the workpiece coordinate system at the contact point of the polishing wheel of the belt grinder and the calibration of the attitude transformation matrix of the 3D scanner relative to the end flange of the robot are performed. The scanner scans the blade and acquires the blade measurement data. The theoretical model of the blade is divided according to the field of view of a single measurement, and the robot pose information of the current scanning area is calculated according to the scanner's viewpoint attitude to complete the planning of the entire blade measurement path.

[0013] Furthermore, based on the reflective properties of the object being measured and the size of the measurement field of view, the blade is divided into measurement areas. Then, the robot pose information at each viewpoint position is recorded sequentially, and this pose information is optimized to ensure the shortest measurement path. Finally, the measurement data of the blade is stitched and fused based on this pose information.

[0014] Furthermore, the coordinate systems of the polishing wheel and the scanner are calibrated, specifically including:

[0015] The camera is operated by a robotic arm to capture multiple images, and the images are corrected using the camera parameters and distortion coefficients obtained from camera calibration. Then, the corrected images and the robotic arm posture obtained from robotic arm calibration are used to perform hand-eye calibration.

[0016] Furthermore, the measurement data is preprocessed to obtain a point cloud model, and the point cloud model is reconstructed by repairing the region model to obtain a reconstructed model:

[0017] First, an outlier removal and denoising algorithm is used to remove noise from the entire measurement data. Then, a curvature-based method is used to simplify the blade measurement data. Finally, the process geometry model of the blade repair area is reconstructed based on the preprocessed data.

[0018] Furthermore, based on the measurement data and reconstruction model, the processing allowance and processing area of ​​the repair area are calculated, and path planning is performed for the processing area:

[0019] The reconstructed model and measurement data are aligned, then the machining allowance and machining area are calculated, and then the repair area is path planned according to the process parameters during the machining process.

[0020] Furthermore, the reconstructed geometric model is first used as a reference object, the measurement data is used as a test object, and the machining allowance is used as a constraint condition for digital model alignment. The area to be repaired and the allowance to be repaired are calculated based on the aligned model. Then, the point information and number of machining points of a single machining path are determined based on the process parameters obtained from the process experiment. The interval between two adjacent paths is calculated in combination with the residual height and roughness requirements. The machining path planning for each machining area is completed in sequence.

[0021] Furthermore, the point information of the path planning is post-processed in conjunction with the robot's control type and kinematic parameters:

[0022] Based on the location, the inverse kinematics of the robot's kinematics is solved to determine whether the target point is reachable and whether it will enter a singularity. The pose information is then converted according to the type of robot motion controller.

[0023] Furthermore, the polishing machine grinds the blades according to a planned path:

[0024] The grinding and polishing machine sequentially performs coarse grinding on the blade body area, fine grinding on the blade body area, coarse grinding and polishing on the leading and trailing edges of the blade, and precise grinding and polishing on the leading and trailing edges of the blade.

[0025] Further, after polishing, inspection is carried out: the profile and surface roughness of the blade repair area are inspected on a coordinate measuring machine. If the inspection is qualified, the processing is completed and the next process continues; if the inspection is unqualified, it is determined whether it can be reworked. If it can be reworked, the blade is reprocessed.

[0026] Compared with the prior art, the present invention has the following technical effects:

[0027] The turbine blade repair and polishing process based on a belt polishing machine proposed in this invention features high automation, safety and stability, high efficiency and high flexibility. It is also easy to operate, and the consistency of product quality is easy to ensure. It improves processing efficiency and quality, reduces the defect rate of blades, innovates existing processing methods, and liberates labor. At the same time, this invention is not only applicable to the grinding and polishing repair of turbine blades, but also applicable to the processing of complex curved surface parts. It is portable, and only requires rescanning the object to be processed as data input to realize the grinding and polishing process of the parts.

[0028] The technical solution adopted in this invention features a high degree of automation, safety, and stability, significantly improving processing efficiency and flexibility. Its ease of operation ensures consistent product quality. This not only improves processing efficiency and overall quality but also reduces the rate of defective blades, bringing innovation to traditional processing methods. Furthermore, this invention is not only applicable to the grinding and polishing of specific blades but also to the processing of more complex curved surface parts, possessing wide applicability and portability, greatly enhancing processing flexibility and convenience. Attached Figure Description

[0029] Figure 1 Flowchart of an industrial robot-based turbine blade repair and polishing method using a belt polisher.

[0030] Figure 2 Schematic diagram of the components of an industrial robot grinding and polishing system for turbine blade repair. Detailed Implementation

[0031] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0032] In the description of this invention, it should be understood that the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0033] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0034] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Additionally, the character " / " in this invention generally indicates that the preceding and following objects have an "or" relationship.

[0035] It should be understood that although terms such as first, second, third, etc., may be used in the embodiments of the present invention to describe the preset range, these preset ranges should not be limited to these terms. These terms are only used to distinguish the preset ranges from one another. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0036] Depending on the context, the word "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0037] The accompanying drawings illustrate various structural schematic diagrams according to embodiments disclosed in this invention. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The shapes of the various regions and layers shown in the drawings, as well as their relative sizes and positional relationships, are merely exemplary and may deviate from reality due to manufacturing tolerances or technical limitations. Furthermore, those skilled in the art can design regions / layers with different shapes, sizes, and relative positions as needed.

[0038] Example 1: An adaptive grinding and polishing method for industrial robot turbine blades based on a belt polisher, comprising:

[0039] The coordinate systems of the polishing wheel and scanner are calibrated, and the robot clamps the blade to acquire blade measurement data;

[0040] The measurement data is preprocessed to obtain a point cloud model, and the point cloud model is reconstructed by repairing the region model to obtain a reconstructed model.

[0041] Based on the measurement data and reconstruction model, calculate the processing allowance and processing area of ​​the repair area, and perform path planning for the processing area;

[0042] The location information of the path planning is combined with the robot's control type and kinematic parameters for post-processing;

[0043] The polishing machine polishes the blades according to the planned path.

[0044] Example 2, please refer to Figure 1 S101, the coordinate system of the calibration polisher and scanner.

[0045] The purpose of hand-eye calibration is to determine the position and orientation of the camera relative to the robotic arm. Multiple images are captured by manipulating the camera through the robotic arm, and the images are corrected using the camera parameters and distortion coefficients obtained from camera calibration. Then, hand-eye calibration is performed using the corrected images and the robotic arm orientation obtained from robotic arm calibration. The calibration of the grinding and polishing machine is to determine the transformation relationship between the tool's point of action and the robot's end flange. In the specific operation, the robot is manually manipulated so that the TCP (tool reference point) just touches the fixed point in four different tool orientations. The first three points are arbitrary orientations; the fourth point uses the tool's reference point perpendicular to the fixed point; the fifth point moves the tool reference point from the fixed point towards the TCP to be set in the x-direction; and the sixth point moves the tool reference point from the fixed point towards the TCP to be set in the z-direction. The transformation matrix during the operation is recorded, and then the tool coordinate system is calculated. After the calculation is completed, the accuracy of the calibration results needs to be verified through actual operation. If a large error is found, adjustments and optimizations may be needed to improve the calibration accuracy.

[0046] S102. Loading is done via a loading trolley.

[0047] S103, The robot automatically picks up the blade.

[0048] S104. The 3D scanning equipment scans the blade. To achieve automatic measurement of the blade, the measurement area of ​​the blade is divided according to the reflective properties of the object being measured and the size of the measurement field of view. Then, the robot pose information at each viewpoint position is recorded sequentially, and this pose information is optimized to ensure the shortest measurement path. Finally, the measurement data of the blade is stitched and fused based on this position information.

[0049] S105. Processing of Measurement Data and Construction of Process Model for the Processing Area. Due to the influence of the measurement environment, the obtained data contains some noise, which will affect the accuracy of data processing. Since the noise in the measurement data is close to that in the real data, a statistical outlier denoising algorithm can be used to denoise the original measurement data. Then, a curvature-based sampling method is used to simplify the denoised data to improve the data processing speed. Next, the model of the repair area is reconstructed based on the predicted data.

[0050] S106. Machining Path Planning. First, using the reconstructed geometric model from S105 as a reference object and the measurement data from S102 as a test object, the model is aligned using machining allowance as a constraint. Based on the aligned model, the areas requiring repair and the required repair allowance are calculated. Next, based on process parameters obtained from process experiments, such as rotational speed, contact force, and feed rate, the point information and number of machining points for each machining path are determined. The interval between adjacent paths is calculated in conjunction with residual height and surface roughness requirements. The machining path planning for each machining area is completed sequentially.

[0051] S107. Post-processing of machining path point location information. During robot movement, due to the constraints of the robot's kinematic geometry and kinematics, there are some unreachable points and singularities. Therefore, it is necessary to perform reachability and non-singularity analysis on each machining point in each machining area sequentially. The robot's inverse kinematics can be solved based on its operational model, and singularities can be used as constraints to analyze the machinability of the current point. If unreachable or singular points exist, some transition points need to be added. After performing reachability and non-singularity analysis on the machining paths of all machining areas, these points are transformed according to the robot motion control coding rules so that the robot control system can parse these point information line by line.

[0052] S108. The polishing machine performs rough grinding on the blade area. S109. The polishing machine performs fine grinding on the blade area. S110. The polishing machine performs rough grinding on the leading and trailing edges of the blade. S111. The leading and trailing edges of the blade are then finely ground.

[0053] The entire grinding and polishing process is divided into blade body machining and leading and trailing edge machining. Because the inlet and outlet edges of the blades are very thin and have strict dimensional tolerance requirements, frequent changes of grinding tools are necessary during machining. Considering the considerable flexibility of the suspended part of the abrasive belt, it is selected to grind and polish the inlet and outlet edges of the blades. Rough grinding is mainly used to remove more than 90% of the excess material from the workpiece surface, while fine grinding further removes a smaller amount of excess material, achieving a bright surface finish and meeting the surface roughness requirements.

[0054] S111. The robot unloads the blades onto the unloading trolley. After the polishing of the blades is completed, the robot picks up the blades and places them onto the unloading trolley, thus completing the entire processing.

[0055] S115. Blade Grinding and Polishing Quality Inspection. Different grinding and polishing programs and process parameters are used depending on the precision requirements of the blade repair area. After processing, a series of inspections are performed on the polished blade, including profile accuracy and surface roughness. If the inspection results meet the requirements, processing is complete, and subsequent processes continue. If the inspection fails, an assessment is made as to whether rework is possible. If rework is possible, processing is repeated, and the blade is returned to the grinding and polishing step. If rework is not possible, the blade is scrapped.

[0056] In this embodiment, the industrial robot blade grinding and polishing system applied in this invention is specifically composed as follows: Figure 2 As shown, the system includes a robot 201, a belt polisher 205 (No. 1), a belt polisher 206 (No. 2), a belt polisher 208 (No. 3), a scanner 203, a loading / unloading trolley 202, a polisher control cabinet 204, and a central integrated dust collector 207. The robot 201's end effector uses a designed gripper to pick up and unload blades on the loading / unloading trolley 202, achieving highly flexible movement. All three polishing wheels can perform rough and fine grinding of the blades. The scanner 203 scans the blades and performs data stitching and fusion.

[0057] This solution details an automated process for blade grinding and polishing, from coordinate system calibration and material loading to final grinding and polishing quality inspection. The entire process embodies:

[0058] High degree of automation: Every step in the process is completed by robots and automated equipment, greatly improving production efficiency and reducing labor costs. This highly automated production method reduces the impact of human factors on product quality, while also reducing the labor intensity of workers.

[0059] A precise coordinate system: The calibration of the coordinate system for the polishing wheel and scanner, mentioned in step S101, ensures the accuracy of subsequent measurements and polishing operations. This precise coordinate system enables the machine to accurately identify the position and shape of the blades, providing a solid foundation for subsequent processing.

[0060] Intelligent data processing: The denoising, simplification, and point cloud model repair and reconstruction in step S105 demonstrate the advantages of intelligent data processing. This method filters out useless data, improves data processing efficiency, and ensures the accuracy of the reconstructed model, providing reliable data support for subsequent processing.

[0061] Refined processing: The polishing process in this solution is divided into two stages: coarse grinding and fine grinding, ensuring the quality of blade polishing. This refined processing method can effectively control the polishing depth and flatness of the blades, making the blade surface smoother and flatter, thus improving the blade's performance and lifespan.

[0062] Flexible path planning: The path planning in step S106 is based on measurement data and a reconstructed model, generating the optimal machining path according to the actual shape of the blade and machining requirements. This flexible path planning method maximizes the machine's machining capabilities, improving machining efficiency and quality.

[0063] Safe and reliable point information processing: The post-processing of point information in step S107 ensures that the generated point information can be correctly identified and executed by the robot. This processing method can prevent the robot from getting stuck in singularities or other safety problems during movement, ensuring the safety and reliability of the entire production process.

[0064] Comprehensive quality inspection: Step S113 inspects the polishing quality of the blades, ensuring the consistency and stability of product quality. This comprehensive quality inspection method can promptly identify and correct problems in the production process, avoiding the generation of defective products and improving the product qualification rate.

[0065] High scalability: This solution utilizes a modular design, making the entire production process easy to expand and upgrade. When new processing equipment needs to be added or existing equipment needs to be improved, only the corresponding modules need to be modified and upgraded, without requiring large-scale adjustments to the entire production process.

[0066] Energy saving and environmental protection: The automated equipment and intelligent processing methods in this solution can effectively reduce energy consumption and material waste, reduce pollution emissions during the production process, and meet the requirements of modern industry for energy saving and environmental protection.

[0067] Improved production efficiency: The entire solution significantly enhances production efficiency through automation and intelligent technology. From material feeding to grinding and polishing to quality inspection, the entire process achieves a fast, accurate, and efficient production model, giving enterprises more market opportunities and competitive advantages.

[0068] In summary, this solution significantly improves the production efficiency and quality of blade grinding and polishing through highly automated, intelligent, and refined processing and comprehensive quality inspection, while reducing labor costs and energy consumption, thus meeting the development trends and requirements of modern industry.

[0069] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. An adaptive grinding and polishing method for turbine blades of an industrial robot based on a belt polisher, characterized in that, include: The coordinate systems of the polishing wheel and scanner are calibrated, and the robot clamps the blade to acquire blade measurement data; The measurement data is preprocessed to obtain a point cloud model, and the point cloud model is reconstructed by repairing the region model to obtain a reconstructed model. Based on the measurement data and reconstruction model, calculate the processing allowance and processing area of ​​the repair area, and perform path planning for the processing area; The location information of the path planning is combined with the robot's control type and kinematic parameters for post-processing; The polishing machine grinds the blades according to the planned path; First, the reconstructed geometric model is used as a reference object, the measurement data is used as a test object, and the machining allowance is used as a constraint condition for digital model alignment. Then, the area to be repaired and the allowance to be repaired are calculated based on the aligned model. Next, the point information and number of machining points of a single machining path are determined based on the process parameters obtained from the process experiment. The interval between two adjacent paths is calculated in combination with the residual height and roughness requirements. The machining path planning for each machining area is completed in sequence. The coordinate systems of the polishing wheel and scanner are calibrated, and the robot holds the blade to acquire blade measurement data, including: The calibration of the workpiece coordinate system at the contact point of the polishing wheel of the belt polisher and the calibration of the attitude transformation matrix of the 3D scanner relative to the end flange of the robot are performed. The scanner scans the blade and acquires the blade measurement data. The theoretical model of the blade is divided according to the field of view of a single measurement, and the robot pose information of the current scanning area is calculated according to the scanner's viewpoint attitude to complete the planning of the entire blade measurement path. Based on the reflective properties of the object being measured and the size of the field of view, the blade is divided into measurement areas. Then, the robot pose information at each viewpoint is recorded sequentially, and this pose information is optimized to ensure the shortest measurement path. Finally, the measurement data of the blade is stitched and fused based on this pose information. The coordinate systems for calibrating the polishing wheel and scanner are specifically included in: The camera is operated by a robotic arm to take multiple images, and the images are corrected using the camera parameters and distortion coefficients obtained from camera calibration. Then, the corrected images and the robotic arm posture obtained from robotic arm calibration are used to perform hand-eye calibration. The measurement data is preprocessed to obtain a point cloud model. The point cloud model is then reconstructed by repairing the region model to obtain the reconstructed model. First, an outlier removal and noise reduction algorithm is used to remove noise from the entire measurement data. Then, a curvature-based method is used to simplify the blade measurement data. Finally, the process geometry model of the blade repair area is reconstructed based on the preprocessed data. Based on the measurement data and reconstruction model, the processing allowance and processing area of ​​the repair area are calculated, and path planning is performed for the processing area: The reconstructed model and measurement data are aligned, then the machining allowance and machining area are calculated, and then the repair area is path planned according to the process parameters during the machining process.

2. The adaptive grinding and polishing method for industrial robot turbine blades based on a belt grinder as described in claim 1, characterized in that, Post-processing is performed on the point information of the path planning, combined with the robot's control type and kinematic parameters: Based on the location, the inverse kinematics of the robot's kinematics is solved to determine whether the target point is reachable and whether it will enter a singularity. The pose information is then converted according to the type of robot motion controller.

3. The adaptive grinding and polishing method for industrial robot turbine blades based on a belt grinder as described in claim 1, characterized in that, The polishing machine grinds the blades according to a planned path: The grinding and polishing machine sequentially performs coarse grinding on the blade body area, fine grinding on the blade body area, coarse grinding and polishing on the leading and trailing edges of the blade, and precise grinding and polishing on the leading and trailing edges of the blade.

4. The adaptive grinding and polishing method for industrial robot turbine blades based on a belt grinder as described in claim 3, characterized in that, After grinding, an inspection is carried out: the profile and surface roughness of the blade repair area are inspected on a coordinate measuring machine. If the inspection is qualified, the processing is completed and the next process continues; if the inspection is unqualified, it is determined whether it can be reworked. If it can be reworked, the blade is reprocessed.

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