Method and device for detecting abnormal clamping of workpiece

Abstract

The invention discloses a method and device for detecting abnormal clamping of a workpiece, and the method comprises the steps: obtaining a plurality of pieces of first side contour data of a sample workpiece through scanning to generate a standard contour, scanning a plurality of pieces of second side contour data of a to-be-detected workpiece, and calculating the 2D rigid body change of the second side contour data and the standard contour; rigid body transformation parameters including vertical offset, radial offset and a rotation angle are obtained, and whether the clamping posture is normal or not is judged according to the rigid body transformation parameters. According to the method provided by the invention, the laser contourgraph is used for automatically collecting data, and the data processing unit is combined for analysis, so that various clamping abnormities can be synchronously detected. Compared with traditional subjective measurement modes of manually using dial gauges, plug gauges and the like, the influence of human factors on detection results is eliminated, and the consistency of measurement standards is ensured; the precision bottleneck of manual measurement is broken through, full-process automatic closed loop is realized, the detection precision reaches dozens of microns, the detection efficiency is greatly improved, and the real-time and continuous requirements of automatic production are met.

Description

Technical Field

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

[0002] In the field of abnormal workpiece clamping 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 requirements of modern, automated, and high-precision production.

[0003] Taking cylindrical workpieces such as contours as an example, the abnormal postures of workpiece clamping are mainly manifested as: the workpiece 1 and the turntable 2 are not concentric, resulting in radial offset, as Figure 1 shown; the workpiece 1 is not in contact with the turntable 2 due to a foreign object 3 being inserted, resulting in an overall vertical offset, as Figure 2 shown; a foreign object 3 is inserted on one side of the workpiece 1, causing the workpiece 1 to tilt, as Figure 3 shown; even multiple factors are superimposed, resulting in complex offset situations. These situations seriously affect the machining accuracy and production efficiency.

[0004] Currently, the traditional clamping detection method for such workpieces still mainly relies 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. This method has many defects: First, the measurement accuracy is greatly affected by manual operation. When facing irregular workpieces, it is easy to produce errors when manually selecting and inserting the plug gauge, resulting in inaccurate posture judgment; Second, the measurement process is cumbersome and time-consuming. It is necessary to measure and analyze multiple positions of the workpiece multiple times. Each time the workpiece rotates one circle, repeated operations are required, and the efficiency is extremely low; Taking the measurement of radial offset as an example, as Figure 1 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: , through mathematical analysis, its maximum and minimum values are R + r and R - r respectively, that is, the length values corresponding to rotating the turntable one week form a one-dimensional curve, and the maximum change amplitude of this curve is 2r. Therefore, it is necessary to measure the distance from a fixed position to the workpiece on the side of the workpiece through a micrometer or a point laser distance sensor, and the radial offset of the workpiece can be detected through the change amplitude of the distance; however, this method can only detect radial offset; it is not applicable to vertical offset and tilt. Third, the skills and habits of different operators will cause inconsistent measurement standards and results; Fourth, manual measurement cannot automatically feedback and adjust the workpiece posture. Relying on manual adjustment not only has a large labor intensity but also easily introduces new errors. With the development of laser scanning and digital image processing technologies, although laser profilometers have been applied to workpiece posture monitoring, in view of the pain points of existing workpiece clamping abnormal detection, further innovation and optimization are still required. Summary of the Invention

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

[0006] The present invention discloses a method for detecting abnormal workpiece clamping, including: Step 1: Scan and obtain multiple pieces of first side profile data of a sample workpiece, and generate a standard profile based on the multiple pieces of first side profile data; Step 2: Scan and obtain multiple pieces of second side profile data of the workpiece to be measured, calculate the 2D rigid body transformation between it and the standard profile, and obtain the rigid body transformation parameters: Tj = (ΔZj, ΔXj, ΔAj), where ΔZj represents the offset of the j-th second profile in the vertical direction, ΔXj represents the offset of the j-th second profile in the radial direction, 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.

[0007] As a further improvement of the present invention, in Step 1, generating a standard profile based on multiple pieces of first side profile data specifically includes: performing fusion processing on the multiple pieces of first side profile data of the sample workpiece, and obtaining the standard profile after fusion; wherein, the fusion processing includes taking the median value of the X coordinates of the same Z coordinate points of all the first side profile data.

[0008] As a further improvement of the present invention, in Step 2, the method for calculating the rigid body transformation parameters includes the Generalized Hough Transform, the Geometric Hashing Algorithm, or the Iterative Closest Point Algorithm.

[0009] As a further improvement of the present invention, when the calculation method of the rigid body transformation parameters is the Generalized Hough Transform, it specifically includes: Establish a reference model based on the standard profile; Match each point of the profile of the workpiece to be measured with the reference model, and accumulate votes in the translation (ΔZ, ΔX) and rotation (ΔA) parameter spaces; Determine the optimal transformation parameters by detecting the voting peak to align the test profile with the standard profile.

[0010] As a further improvement of the present invention, in Step 3, the method for determining whether the clamping posture of the workpiece is abnormal based on the rigid body transformation parameters includes: Regard at least one of ΔZj, ΔXj, and ΔAj in the rigid body transformation parameters as a scalar sequence that changes with the scanning serial number j, and draw a one-dimensional curve with the scanning serial 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.

[0011] Perform filtering on the drawn ΔZ curve, ΔX curve, or / and ΔA curve, and determine whether the workpiece clamping is abnormal according to the fluctuation amplitude of the filtered ΔZ curve, ΔX curve, or / and ΔA curve.

[0012] As a further improvement of the present invention, determining whether the workpiece clamping is abnormal according to the fluctuation amplitude of the filtered ΔZ curve, ΔX curve, or / and ΔA curve specifically includes: 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 abnormal radial offset; If the fluctuation amplitude of the ΔA curve exceeds the preset threshold, it is determined that the workpiece has abnormal tilt.

[0013] As a further improvement of the present invention, the filtering process includes median filtering, Gaussian filtering, or mean filtering.

[0014] As a further improvement of the present invention, in the step 3, the method for determining whether the workpiece clamping posture is abnormal based on the rigid body transformation parameters includes: uniformly modeling the rigid body transformation parameters as a three-dimensional vector and calculating the comprehensive offset; if the comprehensive offset exceeds the preset threshold, it is determined that the clamping is abnormal.

[0015] The present invention discloses a device for detecting abnormal workpiece clamping, including: A processing platform, which includes a turntable and clamping jaws arranged on the turntable, and the clamping jaws are used to clamp the workpiece to be measured; A laser scanning unit, which is used to scan and obtain the side profile data of the standard workpiece and the workpiece to be measured; A data processing unit, which is communicatively connected to the laser scanning unit and is used to execute the method for detecting abnormal workpiece clamping described above; A communication unit, which is used to receive the scanning instruction of the processing platform and feedback the detection result to the processing platform to trigger an alarm or clamping adjustment.

[0016] As a further improvement of the present invention, the laser scanning unit is a laser profiler, the laser profiler 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 direction of the turntable rotation center.

[0017] Compared with the prior art, the beneficial effects of the present invention are: The present invention automatically collects the profile data of the workpiece side by means of a laser profiler, and analyzes multiple profiles of the workpiece rotating one week in combination with a data processing unit, so as to synchronously detect various clamping abnormalities such as radial offset, vertical offset and tilt. Compared with the traditional subjective measurement method using tools such as micrometers and plug gauges by manual labor, it completely eliminates the influence of operator skills, habits or experience on the detection results, eliminates the problem of inconsistent measurement standards caused by human factors, and ensures the consistency and reliability of the detection results. With the high-precision scanning ability of the laser profiler and the data processing algorithm of the present invention, the technical bottlenecks of limited manual measurement accuracy and large gap deviation judgment of plug gauges are broken through. While significantly improving the detection accuracy and efficiency, the detection process does not require manual intervention, and realizes a full-process closed loop through automatic scanning and data processing, avoiding the cumbersome operations of traditional manual measurement, greatly improving the detection efficiency, meeting the requirements of automation production for real-time and continuity, and the overall system can achieve an accuracy of dozens of micrometers. Brief Description of the Drawings

[0018] Figure 1 It is a schematic diagram of the radial offset of the workpiece to be measured; Figure 2 It is a schematic diagram of the vertical offset of the workpiece to be measured; Figure 3 It is a schematic diagram of the tilt of the workpiece to be measured; Figure 4 It is a schematic flow chart of a method for detecting clamping abnormalities of workpieces disclosed in an embodiment of the present invention; Figure 5 It is a schematic diagram of the matching of the standard profile and the test profile of a method for detecting clamping abnormalities of workpieces disclosed in an embodiment of the present invention; Figure 6 It is a schematic diagram of the curve fluctuation of ΔZ and ΔX during radial offset of a method for detecting clamping abnormalities of workpieces disclosed in an embodiment of the present invention; Figure 7 It is a schematic structural diagram of a device for detecting clamping abnormalities of workpieces disclosed in an embodiment of the present invention.

[0019] In the figure: 1. Workpiece; 2. Turntable; 3. Foreign object; 4. Laser profiler; 41. Light plane; 5. Data processing unit; 6. Bracket. Detailed Description of the Invention

[0020] 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 with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are only a part rather than all of the 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 making creative efforts shall fall within the protection scope of the present invention.

[0021] 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 accompanying drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as a limitation of the present invention. In addition, the terms "first", "second", and "third" are only used for descriptive purposes and should not be construed as indicating or implying relative importance.

[0022] In the description of the present invention, it should also be noted that unless otherwise clearly defined and limited, the terms "installed", "connected", and "connected" 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.

[0023] The following further describes the present invention in detail with reference to the accompanying drawings: As Figure 4 shown, a method for detecting abnormal workpiece clamping according to the present invention includes: A training stage, which is used to establish a standard profile of the workpiece side: Step 1: Scan and obtain multiple pieces of first side profile data of the sample workpiece, and generate a standard profile based on the multiple pieces of first side profile data; Specifically, Install a sample workpiece on the turntable 2, rotate the turntable 2 one week to scan and obtain M pieces of first side profiles {Qj} of the sample workpiece, where j = 1, 2,..., M, and M is the set number of scanned profiles. Then extract the standard profile from them; Fuse multiple pieces of first side profile data of the sample workpiece, and obtain a standard profile after fusion. Among them, the fusion process includes taking the median of the X coordinates of the points with the same Z coordinate in all the first side profile data. Using the median profile method can remove the influence of the jaws and the like used to fix the workpiece on the turntable 2 compared with the mean profile. In this embodiment, Z represents the abscissa of each point in the contour line direction, reflecting the position of the workpiece 1 in the vertical direction (i.e., the height direction of the workpiece); X represents the distance from the laser to the workpiece surface, that is, the position of the workpiece in the radial direction (deviating from the center along the radius direction).

[0024] The detection stage is used to obtain the installation posture of the workpiece to be measured by using the standard profile and the scanned profile: Step 2: Scan to obtain multiple pieces of second side profile data of the workpiece to be measured, calculate the 2D rigid body transformation between it 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; Specifically, In the detection stage, install the workpiece to be measured on the turntable 2, and rotate the turntable 2 one week 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; For each second side profile of the workpiece to be measured, calculate a 2D rigid body transformation between it and the standard profile, and obtain Tj = (ΔZj, ΔXj, ΔAj), where Tj represents the triple of rigid body transformation parameters 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; In this step, the calculation methods for the rigid body transformation parameters include the generalized Hough transform, the geometric hashing algorithm, or the iterative closest point algorithm. Among them, when the calculation method for the rigid body transformation parameters is the generalized Hough transform, it specifically includes: Establish a reference model based on the standard profile; Match each point of the profile of the workpiece to be measured with the reference model, and accumulate votes in the translation (ΔZ, ΔX) and rotation (ΔA) parameter spaces; Determine the optimal transformation parameters by detecting the vote peak to align the test profile with the standard profile.

[0025] In this embodiment, the generalized Hough transform realizes high-precision offset calculation through global matching and is applicable to contour registration in a noisy environment. Figure 5 shows a standard contour (shown as a solid line) and a test contour (shown as a dashed line), corresponding to the case where the workpiece has a radial offset. Through the generalized Hough transform, the transformation between the two can be accurately calculated.

[0026] Step 3: Based on the rigid body transformation parameters, determine whether the clamping posture of the workpiece to be measured is normal.

[0027] Specifically, Regard at least one of ΔZj, ΔXj, and ΔAj in the rigid body transformation parameters as a scalar sequence that varies with the scanning sequence number j, and draw a one-dimensional curve with the scanning sequence 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. That is: with the scanning sequence number j as the abscissa and ΔZj as the ordinate, draw a ΔZ curve; with the scanning sequence number j as the abscissa and ΔXj as the ordinate, draw a ΔX curve; with the scanning sequence number j as the abscissa and ΔAj as the ordinate, draw a ΔA curve.

[0028] Perform filtering processing on the drawn ΔZ curve, ΔX curve, or / and ΔA curve, and judge whether the workpiece clamping is abnormal according to the fluctuation amplitude of the filtered ΔZ curve, ΔX curve, or / and ΔA curve. Specifically, it includes: If the fluctuation amplitude of the ΔZ curve exceeds the preset threshold, it is determined that the workpiece has an abnormal vertical offset; If the fluctuation amplitude of the ΔX curve exceeds the preset threshold, it is determined that the workpiece has an abnormal radial offset; If the fluctuation amplitude of the ΔA curve exceeds the preset threshold, it is determined that the workpiece has an abnormal tilt.

[0029] In this step, the filtering processing includes median filtering, Gaussian filtering, or mean filtering. In this embodiment, the filtering processing 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. At the same time, using a one-dimensional curve makes it intuitive.

[0030] As Figure 6 shown, it shows the ΔZ (solid line) curve and the ΔX (dashed line) curve when the workpiece to be measured only has a radial offset. It can be seen from the attached figure that when only a radial offset occurs, the ΔX curve has a large fluctuation, while the ΔZ curve has a small fluctuation; similarly, the tilt degree of the workpiece can also be judged according to the curve of ΔA.

[0031] In another embodiment, in step 3, the method for judging whether the clamping posture of the workpiece is abnormal based on the rigid body transformation parameters includes: uniformly modeling the rigid body transformation parameters as a three-dimensional vector and calculating the comprehensive offset amount Dj; where Dj can be calculated through Calculation; Among them, k is the dimensional balance coefficient of the rotation angle and the position offset; if the maximum value or the average value of all Dj exceeds the preset threshold, it is determined that the clamping is abnormal.

[0032] As Figure 7 As shown, a device for detecting abnormal workpiece clamping provided by the present invention includes a processing platform, a laser scanning unit, a data processing unit 5 and a communication unit: Among them, 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 method for detecting abnormal workpiece clamping described above; the communication unit is used to receive the scanning instruction of the processing platform and feedback the detection result to the processing platform to trigger an alarm or clamping adjustment.

[0033] In the above embodiment, preferably, the laser scanning unit is a laser profiler 4, and the laser profiler 4 is arranged on the side of the workpiece 1 through a bracket 6. The light plane 41 of the laser profiler 4 is perpendicular to the surface of the turntable 2 and faces the rotation center direction of the turntable 2.

[0034] In the above embodiment, preferably, the profile collected by the laser profiler 4 is a set of point sets P = {(Zi, Xi)}, i = 1:N, N represents the number of points of the profile, where Zi and Xi are the Z coordinate and X coordinate of the i-th point on the profile P respectively, corresponding to the vertical and radial positions of the side surface of the workpiece 1 respectively, that is, Z represents the abscissa of each point in the profile line direction, reflecting the position of the workpiece 1 in the vertical direction (i.e., the height direction of the workpiece); X represents the distance from the laser to the workpiece surface, that is, the position of the workpiece in the radial direction (deviating from the center along the radius direction). The turntable 2 drives the workpiece 1 to rotate one week, and the laser profiler 4 collects multiple side profiles {Pj} of the workpiece evenly distributed along the rotation angle, j = 1:M, M represents the total number of profiles.

[0035] In the above embodiment, preferably, by arranging a laser profiler 4 on the side of the workpiece 1, while the workpiece 1 rotates one week on the turntable 2, the profile data of the side of the workpiece 1 is automatically collected. Through the analysis of the profile data by the data processing unit 5, the radial offset, vertical offset and tilt of the workpiece 1 and other clamping defects can be detected simultaneously, and the precise detection of the clamping posture of the workpiece 1 can be realized.

[0036] Advantages of the present invention: In the present invention, the lateral contour data of the workpiece is automatically collected by the laser profiler 4, and the data processing unit 5 is combined to analyze multiple contours of the workpiece 1 rotating one week, so that various clamping abnormalities such as radial offset, vertical offset and tilt can be synchronously detected. Compared with the traditional subjective measurement method using tools such as micrometers and plug gauges by manual, the influence of operator skills, habits or experience on the detection results is completely eliminated, the problem of inconsistent measurement standards caused by human factors is eliminated, and the consistency and reliability of the detection results are ensured. With the high-precision scanning ability and data processing algorithm of the laser profiler 4, the present invention breaks through the technical bottlenecks of limited manual measurement accuracy and large gap deviation judgment of plug gauges. While significantly improving the detection accuracy and efficiency, the detection process does not require manual intervention, and the whole process is closed-loop through automatic scanning and data processing, avoiding the cumbersome operations of traditional manual measurement, greatly improving the detection efficiency, meeting the requirements of automation production for real-time and continuity, and the overall system can achieve an accuracy of dozens of micrometers.

[0037] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent replacement, improvement, 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 detecting abnormal workpiece clamping, characterized in that Including: Step 1: Scan to obtain multiple pieces of first side profile data of the sample workpiece, and generate a standard profile based on the multiple pieces of first side profile data; Step 2: Scan to obtain multiple pieces of second side profile data of the workpiece to be measured, calculate the 2D rigid body transformation between it and the standard profile, and obtain the rigid body transformation parameters: Tj = (ΔZj, ΔXj, ΔAj), where ΔZj represents the offset in the vertical direction of the j-th second profile, ΔXj represents the offset in the radial direction 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 abnormal workpiece clamping according to claim 1, wherein In the said Step 1, generating a standard profile based on multiple pieces of first side profile data specifically includes: performing fusion processing on the multiple pieces of first side profile data of the sample workpiece, and obtaining the standard profile after fusion; wherein, the fusion processing includes taking the median of the X coordinates of the same Z coordinate points of all first side profile data.

3. The method for detecting abnormal workpiece clamping according to claim 1, wherein In the said Step 2, the method for calculating the rigid body transformation parameters includes the Generalized Hough Transform, the Geometric Hashing Algorithm or the Iterative Closest Point Algorithm.

4. The method for detecting abnormal workpiece clamping according to claim 3, wherein, When the calculation method of the rigid body transformation parameters is the Generalized Hough Transform, it specifically includes: Establishing a reference model based on the standard profile; Matching each point of the profile of the workpiece to be measured with the reference model, and accumulating votes in the translation (ΔZ, ΔX) and rotation (ΔA) parameter spaces; Determining the optimal transformation parameters by detecting the vote peak to align the test profile with the standard profile.

5. The method for detecting abnormal workpiece clamping according to claim 1, wherein In the said Step 3, the method for determining whether the clamping posture of the workpiece is abnormal based on the rigid body transformation parameters includes: Regarding at least one of ΔZj, ΔXj, and ΔAj in the rigid body transformation parameters as a scalar sequence that changes with the scanning serial number j, and plotting a one-dimensional curve with the scanning serial 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; Performing filtering processing on the plotted ΔZ curve, ΔX curve, or / and ΔA curve, and judging whether the workpiece clamping is abnormal according to the fluctuation amplitude of the filtered ΔZ curve, ΔX curve, or / and ΔA curve.

6. The method for detecting abnormal workpiece clamping according to claim 5, wherein, Judging whether the workpiece clamping is abnormal according to the fluctuation amplitude of the filtered ΔZ curve, ΔX curve, or / and ΔA curve specifically includes: If the fluctuation amplitude of the ΔZ curve exceeds the preset threshold, it is determined that the workpiece has an abnormal vertical offset; If the fluctuation amplitude of the ΔX curve exceeds the preset threshold, it is determined that the workpiece has an abnormal radial offset; If the fluctuation amplitude of the ΔA curve exceeds the preset threshold, it is determined that the workpiece has an abnormal tilt.

7. The method for detecting abnormal workpiece clamping according to claim 5, wherein The said filtering processing includes median filtering, Gaussian filtering or mean filtering.

8. The method for detecting abnormal workpiece clamping according to claim 1, characterized in that, In the said Step 3, the method for determining whether the clamping posture of the workpiece is abnormal based on the rigid body transformation parameters includes: uniformly modeling the rigid body transformation parameters as a three-dimensional vector, and calculating the comprehensive offset; if the comprehensive offset exceeds the preset threshold, it is determined that the clamping is abnormal.

9. A device for detecting abnormal workpiece clamping, characterized in that, Including: A processing platform, which includes a turntable and clamping jaws arranged on the turntable, and the clamping jaws are used to clamp the workpiece to be measured; A laser scanning unit, which is used to scan and obtain the side profile data of the standard workpiece and the workpiece to be measured; A data processing unit, which is communicatively connected to the laser scanning unit and is configured to execute the method for detecting abnormal workpiece clamping according to any one of claims 1-8; A communication unit, which is configured to receive a scanning instruction from the processing platform and feed back the detection result to the processing platform to trigger an alarm or clamping adjustment.

10. The device for detecting abnormal workpiece clamping according to claim 9, characterized in that, The laser scanning unit is a laser profiler, the laser profiler 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 direction of the turntable rotation center.

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