A surface roughness detector and a detection method thereof

Abstract

The application relates to a surface roughness detector and a detection method thereof, and belongs to the field of surface roughness detection. The surface roughness detector comprises a fixing assembly, a probe assembly, a probe moving assembly and a controller. A data processing unit is arranged in the controller. The fixing assembly is used for positioning and fixing a measured piece. The probe moving assembly can drive the probe assembly to move along the X-axis, Y-axis and Z-axis directions. The probe assembly is carried on the probe moving assembly. The probe assembly is in contact with the surface of the measured piece and performs sliding, converts the surface profile of the measured piece into roughness values, simultaneously performs synchronous scanning on the sliding track, collects surface height information, visualizes data and thermal field distribution data, and controls the motion track of the probe moving assembly and the working state of the probe assembly. The data processing unit comprehensively processes the roughness values collected by the contact probe and the multiple types of data collected by the non-contact probe, and can comprehensively reflect the actual state of the surface of the measured piece.

Description

Technical Field

[0001] This application relates to the field of surface roughness testing, and in particular to a surface roughness testing instrument and its testing method. Background Technology

[0002] Surface roughness, as a core indicator for measuring the surface quality of a workpiece, directly affects the fitting accuracy, wear resistance, sealing performance, and service life of mechanical components. In industrial fields such as automobile manufacturing, aerospace, and precision instruments, the test results of workpiece surface roughness are a key basis for ensuring product performance and reliability.

[0003] In related technologies, the specific implementation process of the surface roughness detection scheme is as follows: the stylus is fixedly connected to the differential inductive sensor, and the sensor and stylus are driven to descend synchronously through the lifting device until the stylus contacts the workpiece. Subsequently, the horizontal displacement device drives the sensor and stylus to slide linearly along the surface of the workpiece. During the sliding process, the stylus makes full contact with the surface contour of the workpiece. The micro-undulations of the surface will cause the stylus to generate a corresponding vertical displacement. This vertical displacement will trigger a change in the inductance inside the differential inductive sensor. The sensor converts the inductance change signal into an electrical signal output. After subsequent signal processing and calculation, the surface roughness data of the workpiece is finally generated.

[0004] However, in complex industrial production conditions, such as surface deformation caused by high temperature, material fatigue damage caused by long-term service, and micro-defects that may accompany the processing, surface roughness data cannot fully reflect the actual state of the workpiece surface. It cannot provide multi-dimensional auxiliary judgment basis for subsequent failure analysis and quality traceability, thus limiting the application scenarios of the test results. Summary of the Invention

[0005] To address the aforementioned problems, this application provides a surface roughness tester and its testing method.

[0006] This application provides a surface roughness tester and its testing method, employing the following technical solution: It includes a housing, a fixing component, a probe assembly, a probe moving assembly, and a controller. The controller integrates a data processing unit and is located inside the housing. The fixing component is located in the lower region for positioning and fixing the workpiece under test. The probe moving assembly is located above the fixing component for driving the probe assembly to move along the X, Y, and Z axes. The probe assembly is mounted on the probe moving assembly. The probe assembly includes a contact probe and a non-contact probe. The contact probe is used for... The non-contact probe contacts the surface of the workpiece and moves along a preset trajectory to convert the surface contour of the workpiece into a roughness value. The non-contact probe scans the area corresponding to the trajectories of the contact probe and simultaneously collects surface height information, morphological visualization data, and thermal field distribution data. The controller is electrically connected to the probe moving component and the probe component. The controller is used to control the movement trajectory of the probe moving component and the working state of the probe component. The data processing unit performs comprehensive processing on the roughness values ​​collected by the contact probe and the surface height information, morphological visualization data, and thermal field distribution data collected by the non-contact probe.

[0007] By adopting the above technical solution, the contact probe moves along a preset trajectory to obtain the surface roughness value of the test piece, while the non-contact probe simultaneously scans the area of ​​the contact probe's trajectory to collect surface height information, morphological visualization data, and thermal field distribution data. Among them, the thermal field distribution data can intuitively reflect the surface temperature difference and corresponding deformation state of the test piece caused by the high temperature environment, and the morphological visualization data can clearly present the micro-cracks, dents, and other defects that may accompany the processing. The surface height information and roughness value corroborate each other to accurately determine the impact of material fatigue damage caused by long-term service on the surface micro-profile. Then, the data processing unit built into the controller integrates and analyzes the above multi-dimensional data to comprehensively reflect the actual state of the test piece surface. It can also provide multi-dimensional auxiliary judgment basis covering geometric features, morphological features, and thermal properties for failure analysis in scenarios such as high temperature deformation, material fatigue, and micro-defects, thus expanding the application scenarios of the test results.

[0008] Preferably, the non-contact probe includes a laser displacement scanner, a camera, and a thermal imaging acquisition device. The laser displacement scanner is used to scan the trajectories of the contact probe. The camera synchronously records the surface morphology images of the laser displacement scanner's scanning trajectory. The thermal imaging acquisition device synchronously acquires the thermal image data of the laser displacement scanner's scanning trajectory.

[0009] By adopting the above technical solutions, the laser displacement scanning component can capture the surface micro-contour and height changes of the trajectories of the contact probe, providing supplementary verification basis for roughness data; the surface morphology images recorded synchronously by the camera can intuitively present the micro-defects of the trajectories of the contact probe, and the thermal image data acquired synchronously by the thermal imaging component can reflect the temperature distribution differences of the trajectories of the contact probe, and determine the changes in thermal characteristics caused by surface deformation or material fatigue under high temperature conditions.

[0010] Preferably, the non-contact probe includes a test mounting base, the laser displacement scanning element is located at the center of the test mounting base, and the camera and the thermal imaging acquisition element are symmetrically distributed on both sides of the laser displacement scanning element.

[0011] By adopting the above technical solution, integrating the laser displacement scanner, camera, and thermal imaging acquisition device into a single test mounting base ensures that their relative positions remain fixed, ensuring that the acquisition range of the camera and thermal imaging acquisition device always coincides with the scanning trajectory of the laser displacement scanner, thus guaranteeing the synchronous matching of surface height information, morphological images, and thermal imaging data in both spatial and temporal dimensions.

[0012] Preferably, the data processing unit includes a filtering unit, which uses a Fourier transform-based algorithm to remove environmental interference and sensor noise from the data collected within the scanning trajectory of the laser displacement scanner.

[0013] By adopting the above technical solution, the filtering unit uses an algorithm based on Fourier transform to separate environmental interference and sensor noise in the data acquired by the laser displacement scanning component, effectively filtering out irrelevant interference components from affecting the surface height information, and significantly improving the purity and accuracy of the acquired data; the surface height information after filtering can truly reflect the micro-contour features within the scanning trajectory of the laser displacement scanning component of the tested part.

[0014] Preferably, the data processing unit further includes a roughness calculation unit, which calculates the surface roughness parameter Rz based on the height data of the scanning trajectory of the laser displacement scanning component. The Rz value is obtained by dividing the scanning trajectory of the laser displacement scanning component into multiple continuous segments, statistically analyzing the peak-valley differences of each segment, and calculating the average value.

[0015] By adopting the above technical solution, the roughness calculation unit in the data processing unit accurately calculates the surface roughness parameters Ra and Rz based on the scanning trajectory height data collected by the laser displacement scanning component. Specifically, by dividing the scanning trajectory into multiple continuous segments, statistically analyzing the peak-valley differences of each segment, and calculating the average value, the Rz value is obtained. This calculation method can more meticulously capture the surface micro-contour undulation features within the scanning trajectory of the laser displacement scanning component, reducing the interference of local extreme values ​​of the tested component on the overall roughness evaluation. At the same time, combined with the roughness values ​​of the contact probe, a multi-dimensional roughness evaluation index is formed.

[0016] Preferably, the data processing unit further includes a machine learning verification unit, which receives the preprocessed height data feature vector of the laser displacement scanning trajectory and outputs the roughness level to cross-validate the results of the traditional algorithm.

[0017] By adopting the above technical solution, the machine learning verification unit receives the feature vector of the height data of the scanning trajectory of the laser displacement scanning part and outputs the roughness level. It forms an effective cross-validation with the detection roughness parameters of the contact probe, which can identify possible deviations or misjudgments under extreme working conditions of the detection roughness parameters of the contact probe. This significantly improves the accuracy and robustness of the surface roughness detection results. At the same time, the machine learning model's ability to deeply mine the height data features can better adapt to the surface contour changes of the measured part under complex working conditions.

[0018] Preferably, the probe moving assembly includes a horizontal drive component and a vertical drive component. A portion of the horizontal drive component is disposed inside the housing, and a portion of the horizontal drive component extends to the outside of the housing for mounting the probe assembly. The vertical drive component is fixed to the fixing assembly, and the housing is disposed on the vertical drive component.

[0019] By adopting the above technical solution, the vertical drive unit drives the contact probe to move along the Z-axis to contact the surface of the workpiece, and simultaneously drives the non-contact probe to adjust to the preset scanning height along the Z-axis. On this basis, the horizontal drive unit simultaneously drives the contact probe to move along the XY-axis, so that the contact probe can move along the preset trajectory to obtain roughness data while maintaining contact with the surface of the workpiece, and drives the non-contact probe to move synchronously along the XY-axis to scan the trajectories of the contact probe. This ensures that the scanning range of the non-contact probe coincides with the trajectories of the contact probe, and achieves accurate spatial trajectory matching and temporal synchronization of multi-dimensional data acquisition by the contact probe and the non-contact probe.

[0020] Preferably, the fixing component includes a support platform and a clamping unit, the vertical drive component is fixed to the support platform, and the clamping unit is used to clamp the test piece.

[0021] By adopting the above technical solution, the fixing component provides an installation reference for the vertical drive component through the support platform, while the clamping unit can reliably clamp and fix the test piece, reducing displacement or shaking of the test piece during the testing process.

[0022] Preferably, the clamping unit includes a first clamping arm, a second clamping arm, a threaded rod, and a first driving member. The threaded rod is rotatably mounted on the support platform. The first driving member is coaxially fixed with the threaded rod. The threads at both ends of the threaded rod are reversed. The first clamping arm and the second clamping arm are respectively threaded with the two ends of the threaded rod.

[0023] By adopting the above technical solution, the first driving component drives the threaded rod to rotate. With the help of the threads set in opposite directions at both ends of the threaded rod, the first clamping arm and the second clamping arm can be moved relative to each other in opposite directions, thereby realizing the rapid clamping of the test piece and ensuring that the test piece is accurately positioned at the preset detection position of the support platform.

[0024] Preferably, a surface roughness detection method includes the following steps: S1: The clamping unit fixes the workpiece under test to the support platform; S2: The vertical drive unit drives the contact probe to contact the workpiece under test; S3: The horizontal drive unit drives the contact probe to perform roughness detection by swiping along a specific length of the surface of the workpiece under test and drives the non-contact probe to synchronously scan along the swiping trajectory of the contact probe to collect surface height information, morphology visualization data, and thermal field distribution data; S4: The data processing unit filters, calculates roughness parameters, and performs machine learning verification on the surface height information, morphology visualization data, and thermal field distribution data collected within the scanning trajectory of the non-contact probe.

[0025] By adopting the above technical solution, step S1 securely fixes the workpiece under test using a clamping unit. Step S2 uses a vertical drive component to ensure effective contact between the contact probe and the surface of the workpiece, guaranteeing the basic accuracy of roughness detection. Step S3 uses a horizontal drive component to move the contact probe along a specific length to acquire roughness data, while simultaneously driving a non-contact probe to scan along the trajectory of the contact probe. This achieves the matching of surface height information, morphology visualization data, and thermal field distribution data with the roughness data. Step S4 uses filtering, roughness parameter calculation, and machine learning verification by the data processing unit to effectively filter out data interference and improve data purity. Furthermore, dual verification enhances the accuracy and robustness of the detection results. The entire method provides comprehensive and reliable technical support for the accurate evaluation, quality traceability, and failure analysis of the surface quality of workpieces under complex working conditions.

[0026] In summary, this application includes at least one of the following beneficial technical effects: 1. The contact probe moves along a preset trajectory to collect roughness values ​​of the test piece. Simultaneously, the non-contact probe scans the area along the trajectory of the contact probe to collect surface height information, morphological visualization data, and thermal field distribution data. The thermal field distribution data reflects the surface temperature difference and deformation state of the test piece caused by the high-temperature environment. The morphological visualization data can present the micro-defects accompanying the processing of the test piece. The surface height information and roughness values ​​corroborate each other to determine the impact of material fatigue damage on the surface micro-profile. The data processing unit then integrates and analyzes the data to comprehensively reflect the actual surface state of the test piece. This provides multi-dimensional auxiliary judgment basis covering geometric features, morphological features, and thermal properties for failure analysis in scenarios such as high-temperature deformation, material fatigue, and micro-defects, effectively expanding the application scenarios of the test results. Attached Figure Description

[0027] Figure 1 This is a structural schematic diagram of an embodiment of this application.

[0028] Figure 2 This is a schematic diagram of the probe moving assembly, contact probe, and test mounting base in the embodiments of this application.

[0029] Figure 3 This is a schematic diagram of the structure of the housing, probe moving assembly, contact probe, and test mounting base in the embodiments of this application.

[0030] Figure 4 yes Figure 3 An enlarged diagram of A in the diagram.

[0031] Explanation of reference numerals in the attached drawings: 1. Housing; 11. Relief groove; 2. Support platform; 21. Support frame; 3. Clamping unit; 31. First clamping arm; 32. Second clamping arm; 33. Threaded rod; 34. First driving component; 4. Contact probe; 41. Probe; 42. Roughness detection component; 5. Non-contact probe; 51. Laser displacement scanning component; 52. Camera; 53. Thermal imaging acquisition component; 54. Test mounting base; 6. Probe moving assembly; 61. Horizontal driving component; 611. Connecting block; 62. Vertical driving component; 7. Controller; 8. Remote control device. Detailed Implementation

[0032] The following is in conjunction with the appendix Figure 1-4 This application will be described in further detail.

[0033] Example 1: This application discloses a surface roughness tester, including a housing 1, a fixing component, a probe component, a probe moving component 6, and a controller 7. The controller 7 is disposed inside the housing 1, the fixing component is disposed in the lower region of the housing 1, the probe moving component 6 is disposed above the fixing component, and the probe component is mounted on the probe moving component 6. The controller 7 is electrically connected to the probe moving component 6 and the probe component, thereby achieving the effect of positioning and fixing the workpiece under test, driving the probe component to move, and performing roughness detection to further collect and process data.

[0034] Reference Figure 1 Specifically, the fixing components include a support platform 2 and a clamping unit 3. The test piece is placed on the support platform 2, which provides stable support for the test piece. In this embodiment, the support platform 2 is made of marble. After precision processing, marble can form an extremely low surface roughness, which can minimize the interference of the surface texture of the support platform 2 itself on the roughness detection results of the test piece. At the same time, marble has excellent dimensional stability and rigidity, and is less affected by temperature and humidity changes, which can reduce the micro-deformation of the support platform 2 caused by environmental factors and ensure the flatness accuracy of the test piece when it is placed.

[0035] Furthermore, the clamping unit 3 is used to clamp the workpiece under test. The clamping unit 3 is fixed to the side wall of the support platform 2. The clamping unit 3 includes a first clamping arm 31, a second clamping arm 32, a threaded rod 33, and a first driving member 34. The side wall of the support platform 2 is provided with a support frame 21. The threaded rod 33 is rotatably mounted on the support frame 21. The first driving member 34 is coaxially fixed with the threaded rod 33. The first driving member 34 is configured as a drive motor. The output shaft of the drive motor is coaxially fixed with the threaded rod 33. The output shaft of the drive motor drives the threaded rod 33 to rotate. The threads at both ends of the threaded rod 33 are reversed. The first clamping arm 31 and the second clamping arm 32 are respectively engaged with the threads at both ends of the threaded rod 33. When the first driving member 34 drives the threaded rod 33 to rotate, since the threads at both ends of the threaded rod 33 are reversed, the first clamping arm 31 and the second clamping arm 32 will move towards or away from each other, thereby achieving clamping or loosening of the workpiece under test.

[0036] Reference Figure 2 and Figure 3Specifically, the probe moving assembly 6 includes a horizontal drive component 61 and a vertical drive component 62. The horizontal drive component 61 and the vertical drive component 62 are configured as a linear module. The vertical drive component 62 is vertically positioned, and one end of the vertical drive component 62 is fixed to the support platform 2. The housing 1 is assembled on the vertical drive component 62. Part of the structure of the horizontal drive component 61 is built into the housing 1. A connecting block 611 is provided on another part of the structure of the horizontal drive component 61, and the connecting block 611 is slidably positioned on the horizontal drive component 61. A clearance groove 11 extending along the length direction of the housing 1 is opened at the bottom of the housing 1. The thickness of the connecting block 611 is slightly smaller than the clearance groove 11. The connecting block 611 passes smoothly through the clearance groove 11 and extends to the outside of the housing 1 through the clearance groove 11, forming a fixed connection with the probe assembly.

[0037] Furthermore, the vertical drive unit 62 can drive the housing 1, the controller 7 inside the housing 1, the horizontal drive unit 61, and the probe assembly connected by the connecting block 611 to move as a whole along the Z-axis direction. At the same time, the horizontal drive unit 61 can drive the probe assembly fixed to the connecting block 611 to slide along the XY-axis direction by driving the sliding assembly of the connecting block 611.

[0038] Reference Figure 3 Furthermore, the probe assembly includes a contact probe 4 and a non-contact probe 5. The contact probe 4 is used to contact the surface of the workpiece and move along a preset trajectory to convert the surface contour of the workpiece into a roughness value. The contact probe 4 includes a probe 41 and a roughness detection element 42. The vertical drive element 62 drives the contact probe 4 to move in the vertical direction, so that the probe 41 establishes contact with the workpiece clamped and fixed by the clamping unit 3 on the support platform 2. After the probe 41 makes contact, the horizontal drive element 61 further drives the probe 41 to perform a swiping action in the horizontal direction, for example, controlling the swiping stroke to be 20mm. During this swiping process, the probe 41 produces a small displacement with the surface shape of the workpiece. The roughness detection element 42 simultaneously captures the 20mm displacement trajectory. Finally, the surface trajectory data within this 20mm swiping range is used as the basis to complete the roughness detection of the workpiece.

[0039] Meanwhile, in this embodiment, the sensor is an inductive displacement sensor. The probe 41 is electrically connected to the inductive displacement sensor. The inductive displacement sensor uses the small displacement of the probe 41 when it contacts and moves against the surface of the workpiece to drive the internal iron core of the inductive displacement sensor to move, thereby changing the electromagnetic induction parameters of the inductor coil of the inductive displacement sensor. Then, the signal processing circuit converts these electromagnetic induction parameters into an electrical signal that is proportional to the displacement. Finally, the system analyzes the electrical signal trajectory and calculates the roughness parameter Ra.

[0040] Reference Figure 4Furthermore, the non-contact probe 5 is used to scan the area corresponding to the trajectories of the contact probe 4 and simultaneously collect surface height information, morphological visualization data and thermal field distribution data. The non-contact probe 5 includes a laser displacement scanning element 51, a camera 52 and a thermal imaging acquisition element 53.

[0041] Furthermore, the laser displacement scanning element 51 is used to scan the trajectories of the contact probe 4 and measure the height information of the surface of the workpiece. The laser displacement scanning element 51 is set as a high-precision point laser displacement sensor, which can move synchronously with the probe 41 along the trajectories. It uses the laser triangulation principle to collect the displacement data of each point on the trajectories of the probe 41 in real time. The camera 52 synchronously records the surface morphology image of the scanning trajectory of the laser displacement scanning element 51. The camera 52 is a miniature industrial PTZ camera 52, which has a 355-degree horizontal rotation and a 90-degree vertical tilt capability. When the probe 41 moves along the horizontal direction of the workpiece, the camera 52 can adjust its posture in real time to ensure that the trajectories of the probe 41 are always in the center of the field of view. The thermal imaging acquisition element 53 synchronously collects the thermal image data of the scanning trajectory of the laser displacement scanning element 51. The thermal imaging acquisition element 53 is based on infrared thermal imaging technology and can capture the thermal field distribution on the surface of the workpiece. The thermal imaging acquisition element 53 adopts an industrial-grade miniature online infrared thermal imager.

[0042] This illustrates that the contact probe 4 moves along a preset trajectory to the surface of the workpiece, obtaining the surface roughness value. Simultaneously, the laser displacement scanner 51 moves synchronously along the trajectory, collecting displacement data of each point on the trajectory of the probe 41 in real time, thereby obtaining the height information of the workpiece surface. The camera 52 synchronously records the surface morphology image of the laser displacement scanner 51's scanning trajectory. The camera 52 is a miniature industrial PTZ camera with 355-degree horizontal rotation and 90-degree vertical tilt capability. When the probe 41 moves along the horizontal direction of the workpiece, it can adjust its posture in real time to ensure that the area of ​​the probe 41's scanning trajectory is always in the center of the field of view, clearly collecting surface morphology visualization data. As a thermal imaging acquisition device 53, it synchronously collects thermal image data of the laser displacement scanner 51's scanning trajectory, capturing the thermal field distribution on the surface of the workpiece.

[0043] Furthermore, the thermal field distribution data can intuitively reflect the surface temperature differences and corresponding deformation states of the tested part caused by the high-temperature environment. The morphology visualization data can clearly present the micro-cracks, dents and other defects that may accompany the processing. The surface height information and roughness value corroborate each other and can accurately determine the impact of material fatigue damage caused by long-term service on the surface micro-profile. Subsequently, the controller 7 integrates and analyzes the above roughness value, surface height information, morphology visualization data and thermal field distribution data to comprehensively reflect the actual state of the surface of the tested part. It can also provide multi-dimensional auxiliary judgment basis covering geometric features, morphological features and thermal properties for failure analysis in scenarios such as high-temperature deformation, material fatigue and micro-defects, effectively expanding the application scenarios of the test results.

[0044] Meanwhile, the non-contact probe 5 also includes a test mounting base 54. The laser displacement scanning element 51 is located at the center of the test mounting base 54. The camera 52 and the thermal imaging acquisition element 53 are symmetrically distributed on both sides of the laser displacement scanning element 51. Integrating the laser displacement scanning element 51, the camera 52 and the thermal imaging acquisition element 53 into a test mounting base 54 can ensure that their relative positions remain fixed, so that the acquisition range of the camera 52 and the thermal imaging acquisition element 53 always coincides with the scanning trajectory of the laser displacement scanning element 51, ensuring the synchronous matching of surface height information, morphological images and thermal imaging data in the spatial and temporal dimensions.

[0045] Furthermore, the controller 7 integrates a data processing unit, which integrates, analyzes, and comprehensively processes roughness values, surface height information, morphological visualization data, and thermal field distribution data. The data processing unit includes a filtering unit, which uses a Fourier transform-based algorithm to remove environmental interference and sensor noise from the data collected within the scanning trajectory of the laser displacement scanning component 51. This Fourier transform algorithm converts the time-domain signal into a frequency-domain signal, filters out high-frequency noise components, and then converts the signal back to the time domain to obtain clean collected data.

[0046] Meanwhile, the data processing unit also includes a roughness calculation unit. The roughness calculation unit calculates the surface roughness parameter Rz based on the height data of the scanning trajectory of the laser displacement scanning component 51. The Rz value is obtained by dividing the scanning trajectory of the laser displacement scanning component 51 into multiple continuous segments, statistically analyzing the peak-valley differences of each segment, and calculating the average value. Combined with the roughness value Ra of the contact probe 4, a multi-dimensional roughness evaluation index is formed.

[0047] In addition, the data processing unit also includes a machine learning verification unit. The machine learning verification unit receives the feature vector of the height data of the scanning trajectory of the laser displacement scanning part 51 after preprocessing and outputs the roughness level. It forms an effective cross-validation with the detection roughness parameters of the contact probe 4. It can identify possible deviations or misjudgments under extreme working conditions in the detection roughness parameters of the contact probe 4, which significantly improves the accuracy and robustness of the surface roughness detection results. At the same time, the machine learning model's ability to deeply mine the height data features can better adapt to the surface contour changes of the measured part under complex working conditions.

[0048] In addition, this application embodiment also includes a remote control device 8, which is electrically connected to the controller 7. The operator can send control commands to the controller 7 by controlling the remote control device 8. The controller 7 responds to the commands and drives the horizontal drive member 61 and the vertical drive member 62 to move, thereby accurately controlling the contact between the probe 41 and the workpiece being tested, as well as the length of the probe 41's trajectories.

[0049] The implementation principle of a surface roughness tester according to an embodiment of this application is as follows: the fixed component completes the stable positioning of the test piece, the support platform 2 provides a support foundation for the test piece, the clamping unit 3 drives the threaded rod 33 with reverse threads at both ends to rotate through the drive motor, so that the first clamping arm 31 and the second clamping arm 32 move towards or away from each other, so as to realize the reliable clamping and loosening of the test piece, the controller 7 drives the horizontal drive 61 and the vertical drive 62 of the probe moving assembly 6 to move the probe assembly in three-dimensional space, wherein the vertical drive 62 drives the controller 7, the horizontal drive 61 and the probe assembly in the housing 1 to move along the Z-axis direction, so that the probe 41 of the contact probe 4 contacts the test piece, and then the horizontal drive 61 drives the probe assembly to move along the XY-axis direction through the connecting block 611, driving the probe 41 to slide along the preset trajectory, the inductive displacement sensor of the contact probe 4 captures the small displacement of the probe 41 with the surface morphology of the test piece, and calculates the roughness parameter Ra.

[0050] During this process, the non-contact probe 5 works synchronously, the laser displacement scanning component 51 moves synchronously along the tracing trajectory with the probe 41 to collect the surface height information of the workpiece in real time, the camera 52 collects the topographic visualization data, and the thermal imaging acquisition component 53 captures the thermal field distribution data of the workpiece surface. All the collected roughness values, surface height information, topographic visualization data, and thermal field distribution data are transmitted to the data processing unit built into the controller 7. The filtering unit uses the Fourier transform algorithm to remove environmental interference and sensor noise. The roughness calculation unit calculates the surface roughness parameter Rz based on the height data and combines it with Ra to form a multi-dimensional evaluation index. The machine learning verification unit outputs the roughness level through the feature vector of the height data and cross-verifies it with the detection parameters of the contact probe 4. Finally, through integrated analysis, the actual state of the workpiece surface is fully reflected.

[0051] Example 2: A surface roughness detection method provided in this application includes the following steps: S1, the test piece is placed on the support platform 2, and the first drive component 34 is started. The first drive component 34 drives the threaded rod 33 to rotate. Since the threads at both ends of the threaded rod 33 are reversed, the first clamping arm 31 and the second clamping arm 32 move towards each other, thereby clamping the test piece on the support platform 2. The start and stop of the first drive component 34 are controlled by the controller 7.

[0052] S2, the vertical drive unit 62 is controlled by the controller 7 to drive the contact probe 4 to move downward until the probe 41 contacts the workpiece being measured.

[0053] S3, the controller 7 controls the horizontal drive unit 61 to drive the contact probe 4 and the non-contact probe 5 to move along a specific length on the surface of the workpiece for roughness detection. At the same time, the horizontal drive unit 61 drives the non-contact probe 5 to scan along the movement trajectory of the contact probe 4. The laser displacement scanner 51 scans this trajectory to collect surface height information, the camera 52 records the surface morphology image, and the thermal imaging acquisition unit 53 collects thermal image data simultaneously.

[0054] S4, the data processing unit filters, calculates roughness parameters, and performs machine learning verification on the surface height information, morphology visualization data, and thermal field distribution data collected within the scanning trajectory of the non-contact probe 5. The filtering unit uses a Fourier transform-based algorithm to remove environmental interference and sensor noise from the collected data. The roughness calculation unit calculates the surface roughness parameter Rz based on the height data of the laser displacement scanning component 51's scanning trajectory and combines it with Ra to form a multi-dimensional evaluation index. The machine learning verification unit receives the preprocessed height data feature vector and outputs the roughness level to cross-validate the results of the traditional algorithm.

[0055] The implementation principle of the surface roughness detection method in this embodiment is as follows: The surface roughness detection method sequentially completes the fixing of the workpiece, the contact of the probe 41, and the acquisition and processing of data. Through multi-dimensional data acquisition and comprehensive processing, it can comprehensively and accurately detect the actual state of the workpiece surface, providing a reliable basis for subsequent quality assessment and analysis, expanding the application scenarios of the detection results, and improving the accuracy and reliability of the detection.

[0056] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. A surface roughness tester, characterized in that: The device includes a housing (1), a fixing component, a probe assembly, a probe moving component (6), and a controller (7). The controller (7) integrates a data processing unit and is located inside the housing (1). The fixing component is located in the lower region and is used to position and fix the workpiece under test. The probe moving component (6) is located above the fixing component and is used to drive the probe assembly to move along the X-axis, Y-axis, and Z-axis. The probe assembly is mounted on the probe moving component (6). The probe assembly includes a contact probe (4) and a non-contact probe (5). The contact probe (4) is used to contact the surface of the workpiece under test and move along the X-axis, Y-axis, and Z-axis. The preset trajectory is used to convert the surface contour of the test piece into a roughness value. The non-contact probe (5) is used to scan the area corresponding to the trajectories of the contact probe (4) and simultaneously collect surface height information, morphology visualization data and thermal field distribution data. The controller (7) is electrically connected to the probe moving component (6) and the probe component. The controller (7) is used to control the movement trajectory of the probe moving component (6) and the working state of the probe component. The data processing unit performs comprehensive processing on the roughness value collected by the contact probe (4) and the surface height information, morphology visualization data and thermal field distribution data collected by the non-contact probe (5).

2. The surface roughness tester according to claim 1, characterized in that: The non-contact probe (5) includes a laser displacement scanner (51), a camera (52), and a thermal image acquisition device (53). The laser displacement scanner (51) is used to scan the trajectories of the contact probe (4). The camera (52) synchronously records the surface morphology images of the scanning trajectory of the laser displacement scanner (51). The thermal image acquisition device (53) synchronously acquires the thermal image data of the scanning trajectory of the laser displacement scanner (51).

3. The surface roughness tester according to claim 2, characterized in that: The non-contact probe (5) includes a test mounting base (54), the laser displacement scanning element (51) is located at the center of the test mounting base (54), and the camera (52) and the thermal imaging acquisition element (53) are symmetrically distributed on both sides of the laser displacement scanning element (51).

4. The surface roughness tester according to claim 2, characterized in that: The data processing unit includes a filtering unit, which uses a Fourier transform-based algorithm to remove environmental interference and sensor noise from the data collected within the scanning trajectory of the laser displacement scanning component (51).

5. The surface roughness tester according to claim 2, characterized in that: The data processing unit also includes a roughness calculation unit. The roughness calculation unit calculates the surface roughness parameter Rz based on the height data of the scanning trajectory of the laser displacement scanning component (51). The Rz value is obtained by dividing the scanning trajectory of the laser displacement scanning component (51) into multiple continuous segments, statistically analyzing the peak-valley differences of each segment, and calculating the average value.

6. The surface roughness tester according to claim 1, characterized in that: The data processing unit also includes a machine learning verification unit, which receives the height data feature vector of the preprocessed laser displacement scanning component (51) scanning trajectory and outputs the roughness level to cross-verify the results of the traditional algorithm.

7. The surface roughness tester according to claim 1, characterized in that: The probe moving assembly (6) includes a horizontal drive (61) and a vertical drive (62). Part of the structure of the horizontal drive (61) is disposed inside the housing (1), and part of the structure of the horizontal drive (61) extends to the outside of the housing (1) for mounting the probe assembly. The vertical drive (62) is fixed to the fixing assembly, and the housing (1) is disposed on the vertical drive (62).

8. The surface roughness tester according to claim 7, characterized in that: The fixing component includes a support platform (2) and a clamping unit (3). The vertical drive (62) is fixed on the support platform (2), and the clamping unit (3) is used to clamp the test piece.

9. The surface roughness tester according to claim 8, characterized in that: The clamping unit (3) includes a first clamping arm (31), a second clamping arm (32), a threaded rod (33), and a first driving member (34). The threaded rod (33) is rotatably mounted on the support platform (2). The first driving member (34) is coaxially fixed with the threaded rod (33). The threads at both ends of the threaded rod (33) are reversed. The first clamping arm (31) and the second clamping arm (32) are respectively threaded with the two ends of the threaded rod (33).

10. A surface roughness detection method, comprising the surface roughness detector according to claims 1 to 9, characterized in that, Includes the following steps: S1: The clamping unit (3) fixes the workpiece under test to the support platform (2). S2: The vertical drive unit (62) drives the contact probe (4) to contact the workpiece under test. S3: The horizontal drive unit (61) drives the contact probe (4) to make the surface of the workpiece under test move along a specific length for roughness detection and drives the non-contact probe (5) to scan along the movement trajectory of the contact probe (4) to collect surface height information, morphology visualization data and thermal field distribution data. S4: The data processing unit filters, calculates roughness parameters and performs machine learning verification on the surface height information, morphology visualization data and thermal field distribution data collected within the scanning trajectory of the non-contact probe (5).

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