CN117146720B - A rolling linear guide rail profile detection method and detection platform - Google Patents

Abstract

The invention discloses a rolling linear guide sub-rail profile detection method and a detection platform. The method includes: collecting point cloud data with a line laser measuring instrument; extracting the guide rail surface section based on the collected point cloud data; Extract the curvature inflection point; perform arc fitting and plane fitting on the guide rail to be tested; and solve the parameters of the guide rail profile. The present invention considers the detection of the guide rail profile parameters of the rolling linear guide rail pair more comprehensively. The detection range includes the guide rail raceway arc diameter of the rolling linear guide rail pair, the center position of the guide rail raceway arc, the base surface of the guide rail bottom surface and the side reference surface. flatness and parallelism. The detection method is fast and efficient, and the detection algorithm is accurate and reliable.

Description

A rolling linear guide rail profile detection method and detection platform

Technical field

The present invention relates to the field of precision detection of rolling linear guide rail pairs, and in particular to a method for detecting the profile of rolling linear guide rail pairs.

Background technique

The rolling linear guide pair is mainly composed of slide block, guide rail, ball or roller, reverser, retainer and end cover. The guide rail is the main component of the rolling linear guide, which directly affects the traveling accuracy and mechanical properties of the rolling linear guide. Ensuring the accuracy and quality of the guide rail profile in the rolling linear guide pair is a very important part of the production of the rolling linear guide pair.

The profile information of the guide rail includes the arc diameter of the raceway, the flatness of the side and bottom of the guide rail, the parallelism of the raceway center line relative to the plane, the distance between the left and right guide rail raceway center lines, etc.

Common non-contact rolling guide surface accuracy detection methods mainly include laser interference method, laser alignment measurement method, laser triangulation method, laser tracking method, etc. Among them, laser interference method has the advantages of high precision, high sensitivity, non-contact, etc., and has become one of the mainstream methods of guide rail profile accuracy detection technology.

At present, there is still no universal and efficient method for detecting guide rail profiles. There are few achievements in theoretical analysis and research devices for guide rail profiles. There are no market-oriented products. Moreover, there are still non-standard and inconsistent detection indicators. Problems such as low measurement accuracy and low detection efficiency.

The information disclosed in this Background section is merely intended to enhance an understanding of the general background of the invention and should not be construed as an admission or in any way implying that the information constitutes prior art that is already known to a person of ordinary skill in the art.

Contents of the invention

In order to achieve the above object, the present invention provides a rolling linear guide auxiliary guide rail profile detection method, which is characterized in that the method includes:

Point cloud data is collected by a line laser measuring instrument;

Extract the rail surface section based on the collected point cloud data;

Extract the inflection points of large curvature on the cross section;

Carry out arc fitting and plane fitting for the guide rail to be tested;

Solve the parameters of the guide rail profile.

In a preferred embodiment, extracting the straight-through filtering section of the guide rail surface specifically includes the following steps:

Extract sections along the movement direction of the slider, and set the filter field of the filter to "y";

Set the function limit range to the section thickness value;

Set the filter direction. Forward filtering means retaining cross-section data, and reverse filtering means removing cross-section information from the entire data;

Repeat N times, each time the input data is updated to the reverse filtered data of the previous section, and the two parameter values of the function limit range are continuously increased.

In a preferred embodiment, extracting the inflection point of large curvature on the cross-section specifically includes the following steps:

Use the nearestKSearch method of KD-Tree to traverse each point of the cross-section point cloud to find the nearest K points, and extract the point index and distance results obtained by the nearest neighbor search;

Use the principal component analysis method to calculate and extract the principal components of the point cloud, and obtain three feature vectors v1, v2 and v3;

Calculate the centroid coordinates of the extracted point cloud and fit a straight line based on the centroid and the direction of v1;

Calculate the mean, variance and standard deviation of the distance from each point in the point cloud set to the fitted straight line;

Determine whether the standard deviation is greater than the set threshold;

If the standard deviation is judged to be greater than the set threshold, the determined point is the inflection point of the arc segment of the guide rail section.

In a preferred embodiment, performing arc fitting and plane fitting on the guide rail to be measured includes the following steps:

Create a SACSegmentation object, set its model type to a three-dimensional circular model and a plane model, and perform fitting;

Each time the plane is fitted, the number of interior points of the model is recorded, the number of interior points is continuously extracted and compared, and the fitting results of the largest and second largest planes are updated and recorded.

In a preferred embodiment, solving the parameters of the guide rail profile includes the following steps:

Calculate the guide rail raceway radius. Calculating the guide rail raceway radius includes the following steps:

Assume that the radii of the fitting arcs of each section are: , where n is the number of sections, then the raceway arc radius value R is:/> ,

The standard deviation is: .

In a preferred embodiment, solving the parameters of the guide rail profile includes the following steps:

Calculate the raceway center distance Hr. Calculating the raceway center distance Hr includes the following steps:

Assume that the center coordinate of the left arc fitted to a certain section is , the center coordinate of the right arc is , then the distance between the centers of the two arcs/> for:

, the calculated center distance of each cross-section arc is , where n is the number of sections, then the raceway center distance Hr is: ,

The standard deviation is: .

In a preferred embodiment, solving the parameters of the guide rail profile includes the following steps:

Calculate the reference distance H from the raceway center to the bottom surface. Calculating the reference distance H from the raceway center to the bottom surface includes the following steps:

Assume that the center coordinate of a certain section fitting arc is , the plane equation fitting the bottom surface is , then the reference distance between the center of the circle and the bottom surface/> for:

, the calculated base distance of each cross-section arc to the bottom is , where n is the number of sections, then the raceway center distance H is:/> ,

The standard deviation is: .

In a preferred embodiment, solving the parameters of the guide rail profile includes the following steps:

Calculate the parallelism of the guide rail datum plane. Calculating the parallelism of the guide rail datum plane includes the following steps:

Let the direction vector of the line connecting the center lines of each section be the direction vector of the raceway center line , the normal vector of the guide rail side reference plane is/> , then the angle between it and the center line of the raceway/> For:/> ,

Suppose the normal vector of the base plane of the guide rail bottom is , then the angle between it and the center line of the raceway/> for: .

In a preferred embodiment, solving the parameters of the guide rail profile includes the following steps:

Calculate the flatness of the guide rail datum. Calculating the flatness of the guide rail datum includes the following steps:

First calculate the distance from each point to the plane ：/> , where i is the datum plane/> a little bit,

Assume that the datum plane has a total of n points, and calculate the average of all distances: , calculate the maximum value of all distances/> , according to the formula: flatness = maximum deviation/average deviation, the flatness of the reference plane can be obtained: .

The invention provides a guide rail profile detection platform. The platform includes a mounting flat plate. The mounting flat plate is equipped with a suspended motor base. A servo motor is installed on the motor base. The servo motor drives the left and right rotating ball wires through a diaphragm coupling. The left and right rotating ball screws are installed on the fixed unit and the support unit in a fixed support manner. The left and right rotating ball screws drive two nuts fixed on the suspension frame, which can perform synchronous and reverse adjustment movements. On the suspension frame It is equipped with a tension spring to connect the measuring instrument mounting plate. The mounting plate is used to fix the line laser measuring instrument. The fine-tuning bolt is installed on the suspension frame. The fine-tuning bolt is used to withstand the mounting plate. The fine-tuning line laser measuring instrument is fed by the screw of the fine-tuning bolt. In the position of Used to perform the method described above.

Compared with the existing technology, the present invention has the following advantages. The purpose of the invention is to provide a method for detecting the profile parameters of the rolling linear guide sub-guide rail to provide a non-contact guide rail profile error measurement solution. The invention uses a line laser measuring instrument to measure the profile characteristics of the guide rail, and designs an adjustment mechanism to meet the high-precision measurement task of multi-size guide rails. The invention can detect the profile characteristics of the guide rail including: the arc diameter of the guide rail raceway, the center position of the arc of the guide rail raceway, and the flatness and parallelism of the base surface of the guide rail and the side reference surface. The present invention considers the detection of the guide rail profile parameters of the rolling linear guide rail pair more comprehensively. The detection range includes the guide rail raceway arc diameter of the rolling linear guide rail pair, the guide rail raceway arc center position, the guide rail bottom reference surface and the side reference surface. flatness and parallelism. The detection method is fast and efficient, and the detection algorithm is accurate and reliable.

Description of drawings

Figure 1 is a front view of the guide rail profile detection platform of the present invention.

Figure 2 is a side view of the guide rail profile detection platform of the present invention.

Figure 3 is a flow chart of cross-section extraction in the present invention.

Figure 4 is a flow chart of large curvature inflection point extraction according to the present invention.

Figure 5 is a flow chart of arc fitting of the guide rail to be measured according to the present invention.

Figure 6 is a flow chart of plane fitting of the guide rail to be measured according to the present invention.

Implementation

The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings, but it should be understood that the protection scope of the present invention is not limited by the specific embodiments.

Unless expressly stated otherwise, throughout the specification and claims, the term "comprises" or its variations such as "comprises" or "comprising" will be understood to include the stated elements or components, and to Other elements or other components are not excluded.

Figure 1 is a front view of the guide rail profile detection platform of the present invention. Figure 2 is a side view of the guide rail profile detection platform of the present invention. As shown in the figure, the present invention provides a guide rail profile detection platform. Its main structure is: a mounting plate 1. The mounting plate 1 is equipped with a suspended motor base 2. The servo motor 3 is installed on the motor base 2. The servo motor 3. The diaphragm coupling 4 drives the left and right rotating ball screws 5. The left and right rotating ball screws 5 are installed on the fixed unit 6 and the support unit 7 in a fixed support manner. The left and right rotating ball screws 5 are equipped with two Two nuts 9 are respectively located on two sections of threads with opposite directions of rotation, and are assembled on the suspension frame 8, so that the two suspension frames 8 can perform synchronous and reverse adjustment movements. The bottom of the suspension frame 8 is equipped with a tension spring 10 connected to the measuring instrument mounting plate 11. The mounting plate 11 is used to fix the square line laser measuring instruments 12 on both sides. The fine-tuning bolt 13 is installed on the suspension frame 8. The fine-tuning bolt 13 is used to withstand the mounting plate 11, and the position and orientation of the fine-tuning line laser measuring instrument 12 is fed by the screw of the fine-tuning bolt 13. Each fine-tuning bolt 13 is equipped with a slotted self-locking nut. The suspension frame 8 is guided by a ball linear guide pair 14 fixed on the side of the mounting plate 1 . The measuring instrument mounting bracket 15 is installed in the middle of the installation plate 1 to install the second line laser measuring instrument 16 . The synchronous reverse motion axis is equipped with a travel switch 17 and an absolute grating system 18.

The invention proposes a guide rail profile detection method based on a line laser triangular displacement sensor. The invention is a non-contact detection method. The basic principle of the method of the present invention is to use a line laser displacement sensor to project laser onto the surface of the tested guide rail, the line laser measuring instrument 12 scans the raceway and side information of the tested guide rail, and the second line laser measuring instrument 16 scans the tested guide rail bottom information. The data collected by the displacement sensor are transferred to the computer for point cloud processing, and the corresponding algorithm is developed to complete the guide rail profile detection. The measurement principle is shown in the figure. For larger guide rail models, divide the side of the guide rail into areas and scan multiple times to complete the measurement. When the line laser measuring instrument (which is also called a line laser displacement sensor or a line laser triangular displacement sensor in the present invention) is running, it emits a line of laser light to hit the measured guide rail. When the three line laser measuring instruments collect data synchronously, it can be seen as continuously detecting the "section profile" of the measured guide rail along the movement direction of the slider. Among them, the distance between adjacent sections is adjustable by the triggering method and collection frequency of the sensor. When the measured guide rail is scanned, the cross-sectional information is spliced together to obtain the entire three-dimensional profile information of the measured guide rail.

The invention provides a rolling linear guide rail sub-rail profile detection method, which is characterized in that the method includes:

Point cloud data is collected by a line laser measuring instrument;

As shown in Figure 3, in a preferred embodiment, the method for extracting the guide rail surface section of the present invention is specifically:

The data collected by the line laser displacement sensor has the following characteristics: In the PCD file, the point cloud data is saved in the form of groups. In each set of data, the first column of data represents the X-axis coordinate value of the point cloud, and the difference between each point value is fixed, which is the contour data interval of the line laser sensor. The second column of data represents the actual displacement in the direction of laser movement during the acquisition process. The third column of data represents the height value of each point, where negative numbers mean that the point is below the reference zero.

In one embodiment, a method based on a straight-through filter is used to extract rail surface sections. First, set the filter field of the filter to "y", that is, perform section extraction along the direction of slider movement. Set the function limit range (min_limit, max_limit). The difference between min_limit and max_limit represents the cross-section thickness value. Set the filter direction. Forward filtering means retaining cross-section data, and reverse filtering means removing cross-section information from the entire data. The above steps are repeated N times. Each time the input data is updated to the reverse filtered data of the previous section, and the function limit range is increased by a value section_interval, N sections can be extracted. Among them, section_interval represents the distance between two sections.

As shown in Figure 4, in a preferred embodiment, extracting the inflection point of large curvature on the cross-section specifically includes the following steps:

Use the nearestKSearch method of KD-Tree to traverse each point of the cross-section point cloud to find the nearest K points, and save the index and distance results of the points obtained by the nearest neighbor search. Extract the index value separately;

Use the principal component analysis method to calculate and extract the principal components of the point cloud, and obtain three feature vectors v1, v2 and v3;

Calculate the centroid coordinates of the extracted point cloud and fit a straight line based on the centroid and the direction of v1;

Calculate the mean, variance and standard deviation of the distance from each point in the point cloud set to the fitted straight line;

Determine whether the standard deviation is greater than the set threshold;

If the standard deviation is judged to be greater than the set threshold, the determined point is the inflection point of the arc segment of the guide rail section. Point cloud data of sharp points and non-sharp points are extracted from the original point cloud object and clustered and stored separately.

As shown in Figures 5 and 6, in a preferred embodiment, performing arc fitting and plane fitting on the guide rail to be measured includes the following steps:

Arc and plane fitting based on Random Sampling Consensus Algorithm (RANSAC). Create a SACSegmentation object, set its model type to a three-dimensional circle model (that is, fitting an arc) and a plane model, set the method type to RANSAC, and perform fitting.

In plane fitting, the bottom datum plane of the guide rail to be measured corresponds to the largest plane of the collected point cloud, while the side datum plane corresponds to the second largest plane of the collected point cloud. Each time the plane is fitted, the number of interior points of the model is recorded, the number of interior points is continuously extracted and compared, and the fitting results of the largest and second largest planes are updated and recorded.

In a preferred embodiment, solving the parameters of the guide rail profile includes the following steps:

Calculate the guide rail raceway radius. Calculating the guide rail raceway radius includes the following steps:

Assume that the radii of the fitting arcs of each section are: , where n is the number of sections, then the raceway arc radius value R is:/> ,

The standard deviation is: .

In a preferred embodiment, solving the parameters of the guide rail profile includes the following steps:

Calculate the raceway center distance Hr. Calculating the raceway center distance Hr includes the following steps:

Assume that the center coordinate of the left arc fitted to a certain section is , the center coordinate of the right arc is , then the distance between the centers of the two arcs/> for:

, the calculated center distance of each cross-section arc is , where n is the number of sections, then the raceway center distance Hr is:/> ,

The standard deviation is: .

In a preferred embodiment, solving the parameters of the guide rail profile includes the following steps:

Calculate the reference distance H from the raceway center to the bottom surface. Calculating the reference distance H from the raceway center to the bottom surface includes the following steps:

Assume that the center coordinate of a certain section fitting arc is , the plane equation fitting the bottom surface is , then the reference distance between the center of the circle and the bottom surface/> for:

, the calculated base distance of each cross-section arc to the bottom is , where n is the number of sections, then the raceway center distance H is:/> ,

The standard deviation is: .

In a preferred embodiment, solving the parameters of the guide rail profile includes the following steps:

Calculate the parallelism of the guide rail datum plane. Calculating the parallelism of the guide rail datum plane includes the following steps:

Let the direction vector of the line connecting the center lines of each section be the direction vector of the raceway center line , the normal vector of the guide rail side reference plane is/> , then the angle between it and the center line of the raceway/> For:/> ,

Suppose the normal vector of the base plane of the guide rail bottom is , then the angle between it and the center line of the raceway/> for: .

In a preferred embodiment, solving the parameters of the guide rail profile includes the following steps:

Calculate the flatness of the guide rail datum. Calculating the flatness of the guide rail datum includes the following steps:

First calculate the distance from each point to the plane ：/> , where i is the datum plane/> a little bit,

Assume that the datum plane has a total of n points, and calculate the average of all distances: , calculate the maximum value of all distances/> , according to the formula: flatness = maximum deviation/average deviation, the flatness of the reference plane can be obtained: .

The foregoing descriptions of specific exemplary embodiments of the present invention have been presented for purposes of illustration and illustration. These descriptions are not intended to limit the invention to the precise form disclosed, and obviously many modifications and variations are possible in light of the above teachings. The exemplary embodiments were chosen and described in order to explain certain principles of the invention and its practical applications, thereby enabling others skilled in the art to make and utilize various exemplary embodiments of the invention and various different applications. Choice and change. The scope of the invention is intended to be defined by the claims and their equivalents.

Claims (8)

1. A rolling linear guide auxiliary guide rail profile detection method, characterized in that the method includes: Point cloud data is collected by a line laser measuring instrument; Based on the collected point cloud data, the guide rail surface through-filter section is extracted; Extract the inflection points of large curvature on the cross section; Carry out arc fitting and plane fitting for the guide rail to be tested; Solve the parameters of the guide rail profile; Among them, the extraction of large curvature inflection points on the cross-section specifically includes the following steps: Use the nearestKSearch method of KD-Tree to traverse each point of the cross-section point cloud to find the nearest K points, and extract the point index and distance results obtained by the nearest neighbor search; Use the principal component analysis method to calculate and extract the principal components of the point cloud, and obtain three feature vectors v1, v2 and v3; Calculate the centroid coordinates of the extracted point cloud and fit a straight line based on the centroid and the direction of v1; Calculate the mean, variance and standard deviation of the distance from each point in the point cloud set to the fitted straight line; Determine whether the standard deviation is greater than the set threshold; If the standard deviation is judged to be greater than the set threshold, it is determined that the point is the inflection point of the arc segment of the guide rail section; Among them, solving the parameters of the guide rail profile includes the following steps: Calculate the guide rail raceway radius. Calculating the guide rail raceway radius includes the following steps: Assume that the radii of the fitting arcs of each section are: , where n is the number of sections, then the raceway arc radius value R is:/> , The standard deviation is: . 2. The method according to claim 1, wherein extracting the straight-through filtering section of the guide rail surface specifically includes the following steps: Extract sections along the movement direction of the slider, and set the filter field of the filter to "y"; Set the function limit range to the section thickness value; Set the filter direction. Forward filtering means retaining cross-section data, and reverse filtering means removing cross-section information from the entire data; Repeat N times, each time the input data is updated to the reverse filtered data of the previous section, and the two parameter values of the function limit range are continuously increased. 3. The method according to claim 2, wherein performing arc fitting and plane fitting on the guide rail to be measured includes the following steps: Create a SACSegmentation object, set its model type to a three-dimensional circular model and a plane model, and perform fitting; Each time the plane is fitted, the number of interior points of the model is recorded, the number of interior points is continuously extracted and compared, and the fitting results of the largest and second largest planes are updated and recorded. 4. The method of claim 3, wherein solving the parameters of the guide rail profile includes the following steps: Calculate the raceway center distance Hr. Calculating the raceway center distance Hr includes the following steps: Assume that the center coordinate of the left arc fitted to a certain section is , the center coordinate of the right arc is/> , then the distance between the centers of the two arcs/> for: , the calculated center distance of each cross-section arc is , where n is the number of sections, then the raceway center distance Hr is:/> , The standard deviation is: . 5. The method of claim 1, wherein solving the parameters of the guide rail profile includes the following steps: Calculate the reference distance H from the raceway center to the bottom surface. Calculating the reference distance H from the raceway center to the bottom surface includes the following steps: Assume that the center coordinate of a certain section fitting arc is , the plane equation fitting the bottom surface is , then the reference distance between the center of the circle and the bottom surface/> for: , the calculated base distance of each cross-section arc to the bottom is , where n is the number of sections, then the raceway center distance H is:/> , The standard deviation is: . 6. The method of claim 4, wherein solving the parameters of the guide rail profile includes the following steps: Calculate the parallelism of the guide rail datum plane. Calculating the parallelism of the guide rail datum plane includes the following steps: Let the direction vector of the line connecting the center lines of each section be the direction vector of the raceway center line , the normal vector of the guide rail side reference plane is , then the angle between it and the center line of the raceway/> for:/> , Suppose the normal vector of the base plane of the guide rail bottom is , then the angle between it and the center line of the raceway/> for: . 7. The method of claim 5, wherein solving the parameters of the guide rail profile includes the following steps: Calculate the flatness of the guide rail datum. Calculating the flatness of the guide rail datum includes the following steps: First calculate the distance from each point to the plane ：/> , where i is the datum plane/> a little bit, Assume that the datum plane has a total of n points, and calculate the average of all distances: , calculate the maximum value of all distances/> , according to the formula: flatness = maximum deviation/average deviation, the flatness of the reference plane can be obtained: . 8. A guide rail profile detection platform, characterized in that the platform includes a mounting flat plate equipped with a suspended motor base, a servo motor is installed on the motor base, and the servo motor drives the left and right sides through a diaphragm coupling. The left and right rotating ball screws are installed on the fixed unit and the support unit in a fixed support manner. The left and right rotating ball screws drive two nuts fixed on the suspension frame, which can perform synchronous and reverse adjustment movements. , the suspension frame is equipped with a tension spring to connect the measuring instrument mounting plate. The mounting plate is used to fix the line laser measuring instrument. The fine-tuning bolts are installed on the suspension frame. The fine-tuning bolts are used to withstand the mounting plate. The fine-tuning bolts are used for fine-tuning through the spiral feed. For the position and posture of the line laser measuring instrument, each fine-tuning bolt is equipped with a slotted self-locking nut. The suspension frame is guided by a ball screw fixed to the side of the mounting plate. The measuring instrument mounting bracket is installed in the middle of the mounting plate to install the second line laser measuring instrument. Wherein, the platform is used to perform the method according to one of claims 1-7.