Surface polishing quality evaluation method based on flexible tactile sensor

Abstract

The application discloses a surface polishing quality evaluation method based on a flexible tactile sensor. In the application, the process of the quality evaluation method is that the flexible tactile sensor is connected at the end of a mechanical arm, so that the flexible tactile sensor is fully contacted with a polishing piece according to a polishing path, the flexible tactile sensor acquires parameters in the process of walking along the path, and after a series of algorithm processing, the surface quality of the polishing piece is represented, and the coordinate points with substandard quality evaluation values are processed again until the whole surface meets the requirements. The system can accurately position the polishing quality of the workpiece surface that does not meet the requirements and optimize the polishing, cooperates with the polishing, is important for improving the polishing quality and efficiency, and introduces a mechanical arm control cabinet to polish the workpiece again so that the calibration position area meets the process requirements, improves the precision and efficiency of traditional polishing surface quality monitoring, can be applied to the quality detection stage of the polishing process, and thus improves the process parameters of the workpiece, and thus improves the surface quality of the subsequent polishing workpiece.

Description

Technical Field

[0001] This invention belongs to the field of industrial robot automated processing and flexible sensor technology, specifically a surface polishing quality assessment method based on a flexible tactile sensor. Background Technology

[0002] Industrial robots are gradually appearing in fields such as grinding. Compared with traditional manual grinding and CNC grinding, they have the advantages of greater processing flexibility, collaborative processing, advantageous price, and high efficiency, thus becoming an important process for improving the surface quality of processed parts.

[0003] However, the development of robotic grinding technology faces two major challenges: firstly, solving the precision machining problem of small-scale complex curved surfaces; and secondly, the efficiency problem of machining large-scale complex structures. Its machining accuracy lags significantly behind CNC machining. Current research in robotic grinding mainly focuses on high-precision online measurement, grinding allowance control, and constant force control, aiming to construct a complete "measurement-operation-machining" robotic grinding system. Currently, methods for detecting the surface quality of workpieces after grinding primarily rely on manual inspection and machine vision. Visual inspection is inefficient, and the accuracy of machine vision needs improvement. Designing a highly automated and precise method for detecting the surface quality of ground surfaces is a key technological challenge in the field of industrial robotic grinding.

[0004] To address this problem, this invention proposes a method for improving the precision of robotic grinding by acquiring workpiece surface quality parameters through a flexible tactile sensor. Summary of the Invention

[0005] The purpose of this invention is to provide a method for evaluating the surface polishing quality based on a flexible tactile sensor in order to solve the problems mentioned above.

[0006] The technical solution adopted in this invention is as follows: a surface polishing quality assessment method based on a flexible tactile sensor, the method comprising the following steps:

[0007] S1: Place a flexible tactile sensor on the end effector of the robotic arm;

[0008] S2: The flexible tentacles move according to the path generated during the pre-grinding of the workpiece;

[0009] S3: The flexible tactile sensor makes real-time contact with the workpiece along the planned path to obtain information such as the workpiece surface position;

[0010] S4: Import positioning information into the PC and establish a surface morphology model;

[0011] S5: Characterize surface quality through surface morphology features;

[0012] S6: Determine whether the surface quality is qualified by comparing the surface quality assessment value with the quality threshold, and mark the unqualified points;

[0013] S7: Optimize the path, perform secondary polishing on unqualified points, and then end the entire process.

[0014] In a preferred embodiment, in step S1, the grinding paths, grinding tools, and process parameters vary for workpieces of different materials and shapes, so it is necessary to select and configure flexible tactile sensors and robotic arm end effectors that meet the detection accuracy requirements.

[0015] In a preferred embodiment, in step S2, several points need to be taken according to the pre-polished path to drive the flexible tentacle, and the contact force and contact angle of the contact points are tested. By adjusting and optimizing the path, sufficient contact is achieved, and surface information is obtained completely and accurately.

[0016] In a preferred embodiment, in step S3, the flexible tactile sensor contacts the workpiece surface through its own tiny sensing elements, transmits contact position information through a signal processing unit connected to each sensing element, and determines the positioning code through signal lines.

[0017] In a preferred embodiment, in step S4, the flexible sensor is closely and continuously attached to the surface of the workpiece to be tested, and a mapping is established between the coordinate system of the monitored object surface and the distributed sensing elements of the flexible tactile sensor, so that the monitored tactile information corresponds to the coordinates of the workpiece surface and the surface morphology is reproduced after data processing.

[0018] In a preferred embodiment, in step S5, some of the surface morphology information obtained in step S4 above, such as position and force, is collected to construct a surface quality evaluation algorithm network. The algorithm includes grinding quality judgment, defect location calibration, and obtains parameters sufficient to characterize the grinding surface process characteristics, thereby evaluating the surface quality.

[0019] In a preferred embodiment, in step S6, before using a flexible sensor to characterize the surface quality, it is necessary to set a quality monitoring threshold for the surface quality of robot grinding based on the parameters required by the traditional grinding process, distinguish between qualified and unqualified grinding areas, and calibrate the range of unqualified points.

[0020] In a preferred embodiment, in step S6, a historical defect database is established based on the surface quality information obtained in step S5, and a training test set is constructed based on the historical defect data. The training test set includes grinding part parameter information and evaluation results.

[0021] In a preferred embodiment, in step S7, the grinding path is replanned to address the grinding defects that occurred in step S6, the processing trajectory is exported as a robot running instruction program, and imported into the robotic arm control cabinet to perform secondary grinding on the workpiece so that the calibrated position area meets the process requirements.

[0022] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0023] In this invention, when grinding a workpiece, the grinding path can be replanned to address the grinding defects that appear. The processing trajectory is exported as a robot operation instruction program and imported into the robotic arm control cabinet for secondary grinding of the workpiece. This ensures that the calibrated position area meets the process requirements, improving the accuracy and efficiency of traditional grinding surface quality monitoring. It can be applied to the quality inspection stage of the grinding process, thereby improving the process parameters of the workpiece, which in turn improves the surface quality of subsequent grinding workpieces, increases the yield rate, and enhances product quality. Attached Figure Description

[0024] Figure 1 This is a flowchart of the quality assessment process for the present invention;

[0025] Figure 2 This is a schematic diagram of the quality assessment system in this invention;

[0026] Figure 3 This is a schematic diagram of the flexible claw contacting the workpiece and connecting to the PC to transmit signals in this invention. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0028] Reference Figure 1-3 ,

[0029] Example:

[0030] A surface polishing quality assessment method based on a flexible tactile sensor, comprising the following steps:

[0031] S1: Place a flexible tactile sensor on the end effector of the robotic arm;

[0032] S2: The flexible tentacles move according to the path generated during the pre-grinding of the workpiece;

[0033] S3: The flexible tactile sensor makes real-time contact with the workpiece along the planned path to obtain information such as the workpiece surface position;

[0034] S4: Import positioning information into the PC and establish a surface morphology model;

[0035] S5: Characterize surface quality through surface morphology features;

[0036] S6: Determine whether the surface quality is qualified by comparing the surface quality assessment value with the quality threshold, and mark the unqualified points;

[0037] S7: Optimize the path, perform secondary polishing on unqualified points, and then end the entire process.

[0038] In step S1, for workpieces of different materials and shapes, the grinding paths, grinding tools, and process parameters vary. Therefore, it is necessary to select and configure flexible tactile sensors and robotic arm end effectors that meet the detection accuracy requirements.

[0039] In step S2, several points need to be selected according to the pre-polished path to drive the flexible tentacles. The contact force and contact angle of the contact points are tested. The path is adjusted and optimized to ensure sufficient contact and obtain complete and accurate surface information.

[0040] In step S3, the flexible tactile sensor contacts the workpiece surface through its tiny sensing elements, transmits contact position information through the signal processing unit connecting each sensing element, and determines the positioning code through the signal line.

[0041] In step S4, the flexible sensor is closely and continuously attached to the surface of the workpiece to be tested, and a mapping is established between the coordinate system of the monitored object surface and the distributed sensor elements of the flexible tactile sensor. In this way, the monitored tactile information corresponds to the coordinates of the workpiece surface, and the surface morphology is reproduced after data processing.

[0042] In step S5, some of the surface morphology information obtained in step S4 above, such as position and force, is collected to construct a surface quality evaluation algorithm network. The algorithm includes grinding quality judgment and defect location calibration, and obtains parameters sufficient to characterize the grinding surface process characteristics, thereby evaluating the surface quality.

[0043] In step S6, before using a flexible sensor to characterize the surface quality, it is necessary to set a quality monitoring threshold for the surface quality of robot grinding based on the parameters required by the traditional grinding process, distinguish between qualified and unqualified grinding areas, and calibrate the range of unqualified points.

[0044] In step S6, a historical defect database is established based on the surface quality information obtained in step S5, and a training test set is constructed based on the historical defect data. The training test set includes grinding part parameter information and evaluation results.

[0045] In step S7, the grinding path is replanned to address the grinding defects that occurred in step S6. The processing trajectory is exported as a robot running instruction program and imported into the robotic arm control cabinet to perform secondary grinding on the workpiece so that the calibrated position area meets the process requirements.

[0046] In this invention, when grinding a workpiece, the grinding path can be replanned to address the grinding defects that appear. The processing trajectory is exported as a robot operation instruction program and imported into the robotic arm control cabinet for secondary grinding of the workpiece. This ensures that the calibrated position area meets the process requirements, improving the accuracy and efficiency of traditional grinding surface quality monitoring. It can be applied to the quality inspection stage of the grinding process, thereby improving the process parameters of the workpiece, which in turn improves the surface quality of subsequent grinding workpieces, increases the yield rate, and enhances product quality.

[0047] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0048] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for evaluating the surface polishing quality based on a flexible tactile sensor, characterized in that, Includes the following steps: S1: Place a flexible tactile sensor on the end effector of the robotic arm; S2: Run the flexible tactile sensor according to the path generated during the pre-grinding of the workpiece; S3: The flexible tactile sensor makes real-time contact with the workpiece along the planned path; the flexible tactile sensor contacts the workpiece surface through its own tiny sensing elements, transmits contact position information through the signal processing unit connected to each sensing element, and determines the positioning code through the signal line; S4: The flexible tactile sensor is closely and continuously attached to the surface of the workpiece to be tested, and a mapping is established between the coordinate system of the monitored object surface and the distributed sensor elements of the flexible tactile sensor, so that the monitored tactile information corresponds to the coordinates of the workpiece surface and the surface morphology is reproduced after data processing. S5: Collect some of the surface morphology information obtained in step S4 above, including position and force information, construct a surface quality evaluation algorithm network, the algorithm includes grinding quality judgment, defect location calibration, obtain parameters sufficient to characterize the grinding surface process characteristics, and then evaluate the surface quality; S6: Determine whether the surface quality is qualified by comparing the surface quality assessment value with the quality threshold, and mark the unqualified points; S7: Optimize the path, perform secondary polishing on unqualified points, and then end the entire process.

2. The method as described in claim 1, characterized in that, In step S1, for workpieces of different materials and shapes, the grinding paths, grinding tools, and process parameters vary. Therefore, it is necessary to select and configure flexible tactile sensors and robotic arm end effectors that meet the detection accuracy requirements.

3. The method as described in claim 1, characterized in that, In step S2, the flexible tactile sensor needs to be driven to take several points according to the pre-polished path to test the contact force and contact angle of the contact points. By adjusting and optimizing the path, sufficient contact is achieved, and surface information is obtained completely and accurately.

4. The method as described in claim 1, characterized in that, In step S6, before using a flexible sensor to characterize the surface quality, it is necessary to set a quality monitoring threshold for the surface quality of robot grinding based on the parameters required by the traditional grinding process, distinguish between qualified and unqualified grinding areas, and calibrate the range of unqualified points.

5. The method as described in claim 1, characterized in that, In step S6, a historical defect database is established based on the surface quality information obtained in step S5, and a training test set is constructed based on the historical defect data. The training test set includes grinding part parameter information and evaluation results.

6. The method as described in claim 1, characterized in that, In step S7, the grinding path is replanned to address the grinding defects that occurred in step S6. The processing trajectory is exported as a robot running instruction program and imported into the robotic arm control cabinet to perform secondary grinding on the workpiece so that the calibrated position area meets the process requirements.

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