Method and device for detecting workpiece clamping abnormality

Abstract

The present invention discloses a method and device for detecting abnormalities in workpiece clamping, which obtains multiple first side profile data of a sample workpiece by scanning to generate a standard profile, and then scans multiple second side profile data of the workpiece to be measured, calculates its 2D rigid body change with the standard profile, and obtains rigid body transformation parameters: including vertical offset, radial offset, and rotation angle, and judges whether the clamping posture is normal based on this. The method provided by the present invention utilizes a laser profiler to automatically collect data, and combined with data processing unit analysis, it can simultaneously detect multiple clamping anomalies. Compared with traditional manual subjective measurement methods such as micrometers and plug gauges, the influence of human factors on the test results is eliminated, and the consistency of measurement standards is guaranteed; it breaks through the bottleneck of manual measurement accuracy, realizes full-process automated closed-loop, and the detection accuracy reaches tens of microns, greatly improving the detection efficiency and meeting the real-time and continuity requirements of automated production.

Description

Technical Field

[0001] The present invention relates to the technical field of workpiece clamping detection, and in particular to a method and device for detecting workpiece clamping abnormality. Background Art

[0002] In the field of workpiece clamping anomaly detection, traditional technologies mostly rely on manual measurement or low-precision mechanical devices, making it difficult to achieve real-time and accurate detection and adjustment of the workpiece posture, and unable to meet the needs of modern, automated, and high-precision production.

[0003] Taking the cylindrical workpiece with contour as an example, the abnormal posture of the workpiece clamping is mainly manifested as follows: the workpiece 1 and the turntable 2 are not concentric and produce radial offset, such as Figure 1 As shown in the figure, the workpiece 1 is not in contact with the turntable 2 due to the foreign matter 3 inserted into it, resulting in an overall vertical offset. Figure 2 As shown in the figure, a foreign object 3 is inserted into one side of the workpiece 1, causing the workpiece 1 to tilt. Figure 3 As shown in the figure, multiple factors may even cause complex offsets, which seriously affect machining accuracy and production efficiency.

[0004] At present, the traditional clamping inspection method for this type of workpiece is still mainly based on manual measurement. Operators use precision tools such as micrometers and plug gauges to manually measure key parts such as the contact surface between the turntable and the workpiece, the vertical and radial positions of the workpiece, etc. This method has many defects: First, the measurement accuracy is greatly affected by human operation. When facing irregular workpieces, manual selection and insertion of plug gauges are prone to errors, resulting in inaccurate posture judgment; second, the measurement process is cumbersome and time-consuming, requiring multiple measurements and analyses at multiple positions on the workpiece. Repeated operations are required for each rotation of the workpiece, which is extremely inefficient; taking radial offset measurement as an example, Figure 1 As shown, B represents the current position of the center of the workpiece (1). When the angle of ∠BOA is α, the length of OC is: , mathematical analysis shows that its maximum and minimum values ​​are R+r and Rr respectively, that is, the length values ​​corresponding to one rotation of the turntable form a one-dimensional curve, and the maximum variation of this curve is 2r. Therefore, it is necessary to use a micrometer or a point laser ranging sensor to measure the distance from a fixed position to the workpiece on the side of the workpiece. The radial offset of the workpiece can be detected by the variation of the distance; however, this method can only detect radial offset; it is not applicable to vertical offset and tilt. Third, differences in skills and habits among different operators will cause inconsistencies in measurement standards and results; fourth, manual measurement cannot automatically feedback and adjust the workpiece posture. Relying on manual adjustment is not only labor-intensive, but also prone to introducing new errors. With the development of laser scanning and digital image processing technology, although laser profilers have been used for workpiece posture monitoring, further innovation and optimization are still needed to address the pain points of existing workpiece clamping abnormality detection. Summary of the Invention

[0005] In view of the deficiencies in the prior art, the present invention provides a method and device for detecting abnormalities in workpiece clamping.

[0006] The present invention discloses a method for detecting workpiece clamping abnormality, comprising:

[0007] Step 1: Scan and obtain multiple first side profile data of a sample workpiece, and generate a standard profile based on the multiple first side profile data;

[0008] Step 2: Scan and obtain multiple second side profile data of the workpiece to be measured, calculate the 2D rigid body change between the second profile and the standard profile, and obtain the rigid body transformation parameters: Tj=(ΔZj, ΔXj, ΔAj), where ΔZj represents the vertical offset of the j-th second profile, ΔXj represents the radial offset of the j-th second profile, and ΔAj represents the rotation angle of the j-th second profile relative to the standard profile;

[0009] Step 3: Based on the rigid body transformation parameters, determine whether the clamping posture of the workpiece to be measured is normal.

[0010] As a further improvement of the present invention, in step 1, generating a standard profile based on multiple first side profile data specifically includes: fusing multiple first side profile data of the sample workpiece to obtain the standard profile after fusion; wherein the fusing process includes taking the median of the X coordinates of the points with the same Z coordinate in all the first side profile data.

[0011] As a further improvement of the present invention, in step 2, the method for calculating the rigid body transformation parameters includes generalized Hough transform, geometric hash algorithm or iterative closest point algorithm.

[0012] As a further improvement of the present invention, when the calculation method of the rigid body transformation parameters is generalized Hough transform, it specifically includes:

[0013] Create a reference model based on the standard outline;

[0014] Matching each point of the contour of the workpiece to be measured with the reference model, and accumulating votes in the translation (ΔZ, ΔX) and rotation (ΔA) parameter spaces;

[0015] The optimal transformation parameters are determined by detecting the voting peaks to align the test contour with the standard contour.

[0016] As a further improvement of the present invention, in step 3, the method of judging whether the workpiece clamping posture is abnormal based on the rigid body transformation parameters includes:

[0017] At least one of ΔZj, ΔXj, and ΔAj in the rigid body transformation parameters is regarded as a scalar sequence that changes with the scan number j, and a one-dimensional curve is drawn with the scan number j as the horizontal coordinate and the corresponding parameter value as the vertical coordinate to obtain a ΔZ curve, a ΔX curve, or / and a ΔA curve.

[0018] The drawn ΔZ curve, ΔX curve, and / or ΔA curve are filtered, and whether the workpiece clamping is abnormal is determined based on the fluctuation amplitude of the filtered ΔZ curve, ΔX curve, and / or ΔA curve.

[0019] As a further improvement of the present invention, judging whether the workpiece clamping is abnormal based on the fluctuation amplitude of the filtered ΔZ curve, ΔX curve, and / or ΔA curve specifically includes:

[0020] If the fluctuation amplitude of the ΔZ curve exceeds the preset threshold, it is determined that the workpiece has abnormal vertical offset;

[0021] If the fluctuation amplitude of the ΔX curve exceeds the preset threshold, it is determined that the workpiece has radial deviation abnormality;

[0022] If the fluctuation amplitude of the ΔA curve exceeds the preset threshold, it is determined that the workpiece has an abnormal tilt.

[0023] As a further improvement of the present invention, the filtering process includes median filtering, Gaussian filtering or mean filtering.

[0024] As a further improvement of the present invention, in step 3, the method of judging whether the workpiece clamping posture is abnormal based on the rigid body transformation parameters includes: uniformly modeling the rigid body transformation parameters as three-dimensional vectors, and calculating the comprehensive offset; if the comprehensive offset exceeds a preset threshold, the clamping is judged to be abnormal.

[0025] The present invention discloses a device for detecting abnormal clamping of a workpiece, comprising:

[0026] A processing platform, comprising a turntable and a clamping jaw provided on the turntable, wherein the clamping jaw is used to clamp a workpiece to be measured;

[0027] A laser scanning unit, which is used to scan and obtain side profile data of a standard workpiece and a workpiece to be measured;

[0028] a data processing unit, which is in communication with the laser scanning unit and is used to execute the above-mentioned method for detecting workpiece clamping abnormalities;

[0029] The communication unit is used to receive scanning instructions from the processing platform and feed back the detection results to the processing platform to trigger an alarm or clamping adjustment.

[0030] As a further improvement of the present invention, the laser scanning unit is a laser profiler, which is placed on the side of the workpiece, and the light plane of the laser profiler is perpendicular to the surface of the turntable and faces the rotation center of the turntable.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] This invention uses a laser profiler to automatically collect workpiece side profile data, and combines it with a data processing unit to analyze multiple profiles of the workpiece during one rotation, thereby simultaneously detecting various clamping anomalies such as radial offset, vertical offset, and tilt. Compared with the traditional subjective measurement method using tools such as micrometers and plug gauges, this method completely eliminates the influence of operator skills, habits, or experience on the test results, eliminates the problem of inconsistent measurement standards caused by human factors, and ensures the consistency and reliability of the test results.

[0033] The present invention leverages the high-precision scanning capability and data processing algorithm of the laser profiler to break through the technical bottlenecks of limited manual measurement accuracy and large deviations in gap judgment using plug gauges, significantly improving detection accuracy and efficiency. At the same time, the detection process requires no human intervention, and a closed-loop process is achieved through automated scanning and data processing, avoiding the tedious operations of traditional manual measurement. This significantly improves detection efficiency and meets the real-time and continuity requirements of automated production. The overall system can achieve an accuracy of tens of microns. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 Schematic diagram of radial offset of the workpiece to be measured;

[0035] Figure 2 It is a schematic diagram of the vertical offset of the workpiece to be measured;

[0036] Figure 3 This is a schematic diagram of the tilt of the workpiece to be measured;

[0037] Figure 4 A schematic flow chart of a method for detecting workpiece clamping abnormality disclosed in an embodiment of the present invention;

[0038] Figure 5 A schematic diagram of matching a standard profile and a test profile in a method for detecting workpiece clamping anomalies disclosed in an embodiment of the present invention;

[0039] Figure 6 A schematic diagram of fluctuations of ΔZ and ΔX curves during radial deviation of a method for detecting abnormal workpiece clamping disclosed in an embodiment of the present invention;

[0040] Figure 7 The present invention is a schematic structural diagram of a device for detecting abnormal workpiece clamping according to an embodiment of the present invention.

[0041] In the picture:

[0042] 1. Workpiece; 2. Turntable; 3. Foreign matter; 4. Laser profiler; 41. Light plane; 5. Data processing unit; 6. Bracket. DETAILED DESCRIPTION

[0043] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, 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. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0044] In the description of the present invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings and are intended solely to facilitate and simplify the description of the present invention. They are not intended to indicate or imply that the devices or components referred to must have, be constructed, or operate in a specific orientation, and therefore should not be construed as limitations on the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0045] In the description of the present invention, it should also be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood broadly. For example, they may refer to fixed, detachable, or integral connections; mechanical or electrical connections; direct or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on the specific circumstances.

[0046] The present invention is described in further detail below with reference to the accompanying drawings:

[0047] like Figure 4 As shown, a method for detecting workpiece clamping abnormality according to the present invention includes:

[0048] The training phase is used to establish the standard profile of the workpiece side:

[0049] Step 1: Scan and obtain multiple first side profile data of a sample workpiece, and generate a standard profile based on the multiple first side profile data;

[0050] Specifically,

[0051] A sample workpiece is mounted on the turntable 2, and the turntable 2 is rotated once to scan and obtain M first side profiles {Qj} of the sample workpiece, where j = 1, 2, ..., M, and M is the set number of scanned profiles. Then, a standard profile is extracted from it;

[0052] Multiple first-side profile data items of the sample workpiece are fused to produce a standard profile. This fusion process involves taking the median of the X coordinates of all points with the same Z coordinate in the first-side profile data. Compared to the mean profile, the median profile method can eliminate the effects of the clamp used to secure the workpiece to the turntable 2. In this embodiment, Z represents the horizontal coordinate of each point in the contour line direction, reflecting the vertical position of the workpiece 1 (i.e., the height of the workpiece). X represents the distance from the laser to the workpiece surface, i.e., the radial position of the workpiece (radially offset from the center).

[0053] The detection phase is used to obtain the installation posture of the workpiece to be measured using the standard profile and the scan profile:

[0054] Step 2: Scan and obtain multiple second side profile data of the workpiece to be measured, calculate the 2D rigid body change between the second profile and the standard profile, and obtain the rigid body transformation parameters: Tj=(ΔZj, ΔXj, ΔAj), where ΔZj represents the vertical offset of the j-th second profile, ΔXj represents the radial offset of the j-th second profile, and ΔAj represents the rotation angle of the j-th second profile relative to the standard profile;

[0055] Specifically,

[0056] During the detection phase, the workpiece to be measured is mounted on the turntable 2, and the turntable 2 is rotated one circle to scan and obtain M second side profiles {Pj} of the workpiece to be measured, where j = 1, 2, ..., M, and M is the set number of scanned profiles;

[0057] For each second side profile of the workpiece, a 2D rigid body transformation between it and the standard profile is calculated to obtain Tj=(ΔZj, ΔXj, ΔAj), where Tj represents the rigid body transformation parameter triple required to match the j-th second side profile to the standard profile, ΔZj represents the vertical offset of the j-th second profile, ΔXj represents the radial offset of the j-th second profile, and ΔAj represents the rotation angle of the j-th second profile relative to the standard profile.

[0058] In this step, the calculation method for the rigid body transformation parameters includes generalized Hough transform, geometric hash algorithm or iterative closest point algorithm. When the calculation method for the rigid body transformation parameters is generalized Hough transform, it specifically includes:

[0059] Create a reference model based on the standard outline;

[0060] Match each point of the contour of the workpiece to be measured with the reference model and accumulate votes in the translation (ΔZ, ΔX) and rotation (ΔA) parameter spaces;

[0061] The optimal transformation parameters are determined by detecting the voting peaks to align the test contour with the standard contour.

[0062] In this embodiment, the generalized Hough transform achieves high-precision offset calculation through global matching, making it suitable for contour registration in noisy environments. Figure 5 shows a standard contour (solid line) and a test contour (dashed line), corresponding to a radial offset of the workpiece. The generalized Hough transform accurately calculates the transformation between the two.

[0063] Step 3: Based on the rigid body transformation parameters, determine whether the clamping posture of the workpiece to be measured is normal.

[0064] Specifically,

[0065] Treat at least one of the rigid body transformation parameters, ΔZj, ΔXj, and ΔAj, as a scalar sequence that varies with scan number j. A one-dimensional curve is plotted with scan number j as the abscissa and the corresponding parameter value as the ordinate, yielding a ΔZ curve, a ΔX curve, and / or a ΔA curve. Specifically, a ΔZ curve is plotted with scan number j as the abscissa and ΔZj as the ordinate; a ΔX curve is plotted with scan number j as the abscissa and ΔXj as the ordinate; and a ΔA curve is plotted with scan number j as the abscissa and ΔAj as the ordinate.

[0066] The drawn ΔZ curve, ΔX curve, and / or ΔA curve are filtered, and whether the workpiece clamping is abnormal is determined according to the fluctuation amplitude of the filtered ΔZ curve, ΔX curve, and / or ΔA curve, which specifically includes:

[0067] If the fluctuation amplitude of the ΔZ curve exceeds the preset threshold, it is determined that the workpiece has abnormal vertical offset;

[0068] If the fluctuation amplitude of the ΔX curve exceeds the preset threshold, it is determined that the workpiece has radial deviation abnormality;

[0069] If the fluctuation amplitude of the ΔA curve exceeds the preset threshold, it is determined that the workpiece has an abnormal tilt.

[0070] In this step, filtering includes median filtering, Gaussian filtering or mean filtering. In this embodiment, the filtering method adopts median low-pass filtering, which can effectively remove the jitter of the contour matching result caused by factors such as the vibration of the turntable 2, and adopts a one-dimensional curve to make it intuitive.

[0071] like Figure 6As shown in the figure, it shows the ΔZ (solid line) curve and ΔX (dashed line) curve when the workpiece to be measured only undergoes radial offset. It can be seen from the figure that when only radial offset occurs, the ΔX curve has a large fluctuation, while the ΔZ curve has a small fluctuation; similarly, the degree of inclination of the workpiece can also be judged based on the ΔA curve.

[0072] In another embodiment, in step 3, the method of judging whether the workpiece clamping posture is abnormal based on the rigid body transformation parameters includes: uniformly modeling the rigid body transformation parameters as three-dimensional vectors and calculating the comprehensive offset Dj; wherein Dj can be obtained by calculate;

[0073] Where k is the dimensional balance coefficient between the rotation angle and the position offset; if the maximum value or average value of all Dj exceeds the preset threshold, the clamping is judged to be abnormal.

[0074] like Figure 7 As shown, a device for detecting abnormal clamping of a workpiece according to the present invention includes a processing platform, a laser scanning unit, a data processing unit 5 and a communication unit: wherein the processing platform includes a turntable 2 and a clamping jaw arranged on the turntable 2, and the clamping jaw is used to clamp the workpiece to be measured; the laser scanning unit is used to scan and obtain the side profile data of the standard workpiece and the workpiece to be measured; the data processing unit 5 is communicatively connected to the laser scanning unit and is used to execute the above-mentioned method for detecting abnormal clamping of the workpiece; the communication unit is used to receive the scanning instruction of the processing platform and feed back the detection result to the processing platform to trigger an alarm or clamping adjustment.

[0075] In the above embodiment, preferably, the laser scanning unit is a laser profiler 4, which is arranged on the side of the workpiece 1 through a bracket 6, and the light plane 41 of the laser profiler 4 is perpendicular to the surface of the turntable 2 and toward the rotation center of the turntable 2.

[0076] In the above embodiment, the profile captured by the laser profiler 4 is preferably a set of points P = {(Zi, Xi)}, where i = 1:N, and N represents the number of points in the profile. Zi and Xi are the Z and X coordinates of the i-th point on the profile P, corresponding to the vertical and radial positions of the side surface of the workpiece 1, respectively. That is, Z represents the horizontal coordinate of each point along the profile line, reflecting the vertical position of the workpiece 1 (i.e., the height of the workpiece); X represents the distance from the laser to the workpiece surface, i.e., the radial position of the workpiece (radially offset from the center). As the turntable 2 rotates the workpiece 1 one revolution, the laser profiler 4 captures multiple side profiles {Pj} of the workpiece, evenly distributed along the rotation angle, where j = 1:M, and M represents the total number of profiles.

[0077] In the above embodiment, preferably, by arranging a laser profiler 4 on the side of the workpiece 1, the profile data of the side of the workpiece 1 is automatically collected while the workpiece 1 rotates one circle on the turntable 2. By analyzing the profile data by the data processing unit 5, the radial offset, vertical offset and tilt of the workpiece 1 and other poor clamping can be detected at the same time, thereby realizing accurate detection of the clamping posture of the workpiece 1.

[0078] Advantages of the present invention:

[0079] The present invention uses a laser profiler 4 to automatically collect workpiece side profile data, and combines it with a data processing unit 5 to analyze multiple profiles of the workpiece 1 during one rotation, thereby simultaneously detecting various clamping anomalies such as radial offset, vertical offset, and tilt. Compared with the traditional subjective measurement method using tools such as micrometers and plug gauges, this method completely eliminates the influence of operator skills, habits, or experience on the test results, eliminates the problem of inconsistent measurement standards caused by human factors, and ensures the consistency and reliability of the test results.

[0080] The present invention makes use of the high-precision scanning capability and data processing algorithm of the laser profiler 4 to break through the technical bottleneck of limited manual measurement accuracy and large deviation of the plug gauge in judging the gap, and significantly improves the detection accuracy and efficiency. At the same time, the detection process does not require manual intervention, and the entire process is closed-loop through automated scanning and data processing, avoiding the tedious operations of traditional manual measurement, greatly improving the detection efficiency, and meeting the real-time and continuity requirements of automated production. The overall system can achieve an accuracy of tens of microns.

[0081] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A method for detecting abnormal clamping of a workpiece, characterized in that: include: Step 1: Scan and obtain multiple first side profile data of a sample workpiece, and generate a standard profile based on the multiple first side profile data; In step 1, generating a standard profile based on multiple pieces of first side profile data specifically includes: fusing multiple pieces of first side profile data of the sample workpiece to obtain the standard profile after fusion; wherein the fusing process includes taking the median of the X coordinates of the points with the same Z coordinate in all pieces of the first side profile data; Step 2: Scan and obtain multiple second side profile data of the workpiece to be measured, calculate the 2D rigid body change between the second profile and the standard profile, and obtain the rigid body transformation parameters: Tj=(ΔZj, ΔXj, ΔAj), where ΔZj represents the vertical offset of the j-th second profile, ΔXj represents the radial offset of the j-th second profile, and ΔAj represents the rotation angle of the j-th second profile relative to the standard profile; Step 3: Based on the rigid body transformation parameters, determine whether the clamping posture of the workpiece to be measured is normal.

2. The method for detecting workpiece clamping abnormality according to claim 1, characterized in that: In step 2, the method for calculating the rigid body transformation parameters includes generalized Hough transform, geometric hash algorithm or iterative closest point algorithm.

3. The method for detecting workpiece clamping abnormality according to claim 2, characterized in that: When the calculation method of the rigid body transformation parameters is generalized Hough transform, it specifically includes: Create a reference model based on the standard outline; Matching each point of the contour of the workpiece to be measured with the reference model, and accumulating votes in the translation (ΔZ, ΔX) and rotation (ΔA) parameter spaces; The optimal transformation parameters are determined by detecting the voting peaks to align the test contour with the standard contour.

4. The method for detecting workpiece clamping abnormality according to claim 1, characterized in that: In step 3, the method of judging whether the workpiece clamping posture is abnormal based on the rigid body transformation parameters includes: Treat at least one of ΔZj, ΔXj, and ΔAj in the rigid body transformation parameters as a scalar sequence that changes with the scan number j, and draw a one-dimensional curve with the scan number j as the abscissa and the corresponding parameter value as the ordinate to obtain a ΔZ curve, a ΔX curve, or / and a ΔA curve; The drawn ΔZ curve, ΔX curve, and / or ΔA curve are filtered, and whether the workpiece clamping is abnormal is determined based on the fluctuation amplitude of the filtered ΔZ curve, ΔX curve, and / or ΔA curve.

5. The method for detecting workpiece clamping abnormality according to claim 4, characterized in that: The fluctuation amplitude of the filtered ΔZ curve, ΔX curve, and / or ΔA curve is used to determine whether the workpiece clamping is abnormal, specifically including: If the fluctuation amplitude of the ΔZ curve exceeds the preset threshold, it is determined that the workpiece has abnormal vertical offset; If the fluctuation amplitude of the ΔX curve exceeds the preset threshold, it is determined that the workpiece has radial deviation abnormality; If the fluctuation amplitude of the ΔA curve exceeds the preset threshold, it is determined that the workpiece has an abnormal tilt.

6. The method for detecting workpiece clamping abnormality according to claim 4, characterized in that: The filtering process includes median filtering, Gaussian filtering or mean filtering.

7. The method for detecting workpiece clamping abnormality according to claim 1, characterized in that: In step 3, the method of judging whether the workpiece clamping posture is abnormal based on the rigid body transformation parameters includes: uniformly modeling the rigid body transformation parameters as three-dimensional vectors and calculating the comprehensive offset; if the comprehensive offset exceeds a preset threshold, the clamping is judged to be abnormal.

8. A device for detecting abnormal clamping of a workpiece, characterized in that: include: A processing platform, comprising a turntable and a clamping jaw provided on the turntable, wherein the clamping jaw is used to clamp a workpiece to be measured; A laser scanning unit, which is used to scan and obtain side profile data of a standard workpiece and a workpiece to be measured; a data processing unit, which is in communication with the laser scanning unit and is used to execute the method for detecting workpiece clamping abnormality according to any one of claims 1 to 7; The communication unit is used to receive scanning instructions from the processing platform and feed back the detection results to the processing platform to trigger an alarm or clamping adjustment.

9. The device for detecting abnormal clamping of a workpiece according to claim 8, characterized in that: The laser scanning unit is a laser profiler, which is placed on the side of the workpiece. The light plane of the laser profiler is perpendicular to the surface of the turntable and faces the rotation center of the turntable.

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