CN117146720B - Rolling linear guide rail pair guide rail profile detection method and detection platform - Google Patents
Rolling linear guide rail pair guide rail profile detection method and detection platform Download PDFInfo
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Abstract
The invention discloses a method and a platform for detecting the profile of a rolling linear guide rail pair guide rail, wherein the method comprises the following steps: collecting point cloud data by a line laser measuring instrument; extracting a guide rail surface section based on the acquired point cloud data; extracting a large curvature inflection point on the section; performing arc fitting and plane fitting on the guide rail to be tested; and solving parameters of the profile of the guide rail. The invention has more comprehensive detection consideration on the profile parameters of the rolling linear guide rail pair, and the detection range comprises the diameter of the arc of the guide rail raceway of the raceway linear guide rail pair, the center position of the arc of the guide rail raceway, and the planeness and parallelism of the reference surface of the bottom surface and the reference surface of the side surface of the guide rail. The detection method is fast and efficient, and the detection algorithm is accurate and reliable.
Description
Technical Field
The invention relates to the field of precise detection of rolling linear guide rail pairs, in particular to a method for detecting the profile of a rolling linear guide rail pair.
Background
The rolling linear guide rail pair mainly comprises a sliding block, a guide rail, a ball or roller, a reverser, a retainer, an end cover and the like. The guide rail is a main body part of the rolling linear guide rail pair, and the running precision, mechanical properties and the like of the rolling linear guide rail are directly affected. The precision and the quality of the profile of the guide rail in the rolling linear guide rail pair are ensured, and the rolling linear guide rail pair is an important ring in the production of the rolling linear guide rail pair.
The profile information of the guide rail comprises the arc diameter of the roller path, the planeness of the side surface and the bottom surface of the guide rail, the parallelism of the center line of the roller path relative to the plane, the distance between the center lines of the left guide rail and the right guide rail, and the like.
Common non-contact type rolling guide rail profile precision detection methods mainly comprise a laser interferometry method, a laser collimation measurement method, a laser triangulation method, a laser tracking method and the like. The laser interferometry has the advantages of high precision, high sensitivity, non-contact and the like, and is one of the mainstream methods of the guide rail profile precision detection technology.
At present, a general and efficient guide rail profile detection method is not available, the theoretical analysis and research device of the guide rail profile has less results, products facing the market are not formed, and the problems of non-uniform detection indexes, low measurement precision, low detection efficiency and the like exist.
The information disclosed in this background section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person of ordinary skill in the art.
Disclosure of Invention
In order to achieve the above purpose, the invention provides a method for detecting the profile of a rolling linear guide rail pair guide rail, which is characterized by comprising the following steps:
collecting point cloud data by a line laser measuring instrument;
extracting a guide rail surface section based on the acquired point cloud data;
extracting a large curvature inflection point on the section;
performing arc fitting and plane fitting on the guide rail to be tested;
and solving parameters of the profile of the guide rail.
In a preferred embodiment, the extraction of the guide surface straight-through filtering section comprises the following steps:
extracting a section along the moving direction of the sliding block, and setting a filtering field of a filter as y;
setting a function limiting range as a section thickness value;
setting the filtering direction of a filter, forward filtering to keep section data, and reverse filtering to remove section information of the whole data;
the method is repeatedly executed for N times, and each time the input data is updated to the reverse filtering data of the last section, the function limiting range is continuously increased by two parameter values.
In a preferred embodiment, the extraction of the inflection point of large curvature on the cross section specifically comprises the following steps:
traversing each point of the cross-section point cloud by using a nearest-neighbor KSearch method of KD-Tree to find the nearest K points, and extracting a point index and a distance result obtained by nearest neighbor searching;
calculating and extracting principal components of the point cloud by using a principal component analysis method to obtain three feature vectors v1, v2 and v3;
calculating the centroid coordinates of the extracted point cloud, and fitting a straight line according to the directions of the centroid and v 1;
calculating the average value, variance and standard deviation of the distances from each point in the point cloud set to the fitting straight line;
judging whether the standard deviation is larger than a set threshold value or not;
if the standard deviation is larger than the set threshold value, the determination point is an inflection point of the arc section of the guide rail section.
In a preferred embodiment, performing arc fitting and plane fitting on the guide rail to be tested comprises the following steps:
creating a SACsegment object, respectively setting model types of the SACsegment object as a three-dimensional circular model and a planar model, and executing fitting;
and when the planes are fitted each time, recording the number of the inner points of the model, continuously extracting and comparing the number of the inner points, and updating the fitting results of the largest and second largest planes.
In a preferred embodiment, the solving of the parameters of the rail profile comprises the steps of:
calculating the radius of the guide rail raceway, wherein the calculating of the radius of the guide rail raceway comprises the following steps:
let the radius of each section fitting arc be:wherein n is the number of sections, and the radius value R of the circular arc of the rollaway nest is: />,
The standard deviation is:。
in a preferred embodiment, the solving of the parameters of the rail profile comprises the steps of:
calculating a raceway center distance Hr, wherein the raceway center distance Hr is calculated by the following steps:
a certain section is fitted with a left circular arc circleThe heart coordinates areThe center coordinates of the right circular arc areThe center distance of the two circular arcs is->The method comprises the following steps:
calculating the center distance of the circular arcs of each section asWherein n is the number of sections, and the center distance Hr of the rollaway nest is:,
the standard deviation is:。
in a preferred embodiment, the solving of the parameters of the rail profile comprises the steps of:
calculating a raceway center-to-bottom surface reference distance H, the raceway center-to-bottom surface reference distance H comprising the steps of:
setting the circle center coordinates of a certain section fitting circular arc asThe plane equation of the fitted bottom surface isThe reference distance of the circle center to the bottom surface>The method comprises the following steps:
calculating the reference distance from each section arc to the bottom surface asWherein n is the number of sections, and the center distance H of the rollaway nest is: />,
The standard deviation is:。
in a preferred embodiment, the solving of the parameters of the rail profile comprises the steps of:
calculating the parallelism of the guide rail reference surface, wherein the calculating of the parallelism of the guide rail reference surface comprises the following steps:
the direction vector of the connecting line of the circle centers of all sections is taken as the direction vector of the central line of the rollaway nestThe normal vector of the reference plane of the side surface of the guide rail is +.>The included angle between the ball and the central line of the roller path is +.>The method comprises the following steps: />,
Let the normal vector of the reference plane of the bottom surface of the guide rail beThe included angle between the ball and the central line of the roller path is +.>The method comprises the following steps:。
in a preferred embodiment, the solving of the parameters of the rail profile comprises the steps of:
calculating the flatness of the guide rail reference surface, wherein the calculating of the flatness of the guide rail reference surface comprises the following steps:
first calculate the distance of each point to the plane:/>Wherein i is the reference plane +.>In (a) is provided,
let the reference plane have n total points, calculate the average of all distances:calculate the maximum value of all distances +.>The formula is: flatness = maximum deviation/average deviation, resulting in flatness of the reference plane:。
the invention provides a guide rail profile detection platform, which comprises a mounting flat plate, wherein a suspension type motor seat is arranged on the mounting flat plate, a servo motor is arranged on the motor seat, the servo motor drives a left-right rotation ball screw through a diaphragm coupler, the left-right rotation ball screw is arranged on a fixing unit and a supporting unit in a fixed supporting mode, the left-right rotation ball screw drives two nuts fixed on a suspension bracket, synchronous and reverse adjustment movement can be carried out, the suspension bracket is provided with an extension spring connected with a measuring instrument mounting plate, the mounting plate is used for fixing a line laser measuring instrument, a fine adjustment bolt is arranged on the suspension bracket and is used for supporting the mounting plate, each fine adjustment bolt is provided with a slotted self-locking nut through screw feeding of the fine adjustment bolt, the suspension bracket is guided by a ball screw pair fixed on the side surface of the mounting flat plate, and a measuring instrument mounting frame is arranged in the middle of the mounting flat plate for mounting a second line laser measuring instrument, wherein the platform is used for executing the method as described above.
Compared with the prior art, the invention has the following advantages, and the invention aims to provide a method for detecting the profile parameters of the rolling linear guide rail pair guide rail so as to provide a non-contact type guide rail profile error measurement scheme. The invention adopts the linear laser measuring instrument to measure the profile characteristics of the guide rail, and designs the adjusting mechanism to meet the high-precision measuring task of the guide rail with multiple dimensions. The invention can detect the profile characteristics of the guide rail, comprising: the diameter of the guide rail raceway arc, the center position of the guide rail raceway arc, the planeness and parallelism of the guide rail bottom surface datum plane and the side surface datum plane. The invention has more comprehensive detection consideration on the profile parameters of the rolling linear guide rail pair, and the detection range comprises the diameter of the arc of the guide rail raceway of the raceway linear guide rail pair, the center position of the arc of the guide rail raceway, and the planeness and parallelism of the reference surface of the bottom surface and the reference surface of the side surface of the guide rail. The detection method is fast and efficient, and the detection algorithm is accurate and reliable.
Drawings
Fig. 1 is a front view of a rail profile inspection platform of the present invention.
Fig. 2 is a side view of the rail profile inspection platform of the present invention.
FIG. 3 is a flow chart of a section extraction of the present invention.
Fig. 4 is a flow chart of the large curvature inflection point extraction of the present invention.
Fig. 5 is a flow chart of the present invention for performing arc fitting on a rail to be tested.
Fig. 6 is a flow chart of the present invention for performing a plane fit to a rail under test.
Description of the embodiments
The following detailed description of embodiments of the invention is, therefore, to be taken in conjunction with the accompanying drawings, and it is to be understood that the scope of the invention is not limited to the specific embodiments.
Throughout the specification and claims, unless explicitly stated otherwise, the term "comprise" or variations thereof such as "comprises" or "comprising", etc. will be understood to include the stated element or component without excluding other elements or components.
Fig. 1 is a front view of a rail profile inspection platform of the present invention. Fig. 2 is a side view of the rail profile inspection platform of the present invention. As shown in the figure, the invention provides a guide rail profile detection platform, which has the main structure that: the installation flat board 1 is provided with a suspended motor base 2 on the installation flat board 1, a servo motor 3 is arranged on the motor base 2, the servo motor 3 drives a left-right rotation ball screw 5 through a diaphragm type coupler 4, the left-right rotation ball screw 5 is arranged on a fixed unit 6 and a supporting unit 7 in a fixed supporting mode, the left-right rotation ball screw 5 is provided with two nuts 9, the two nuts 9 are respectively arranged on two sections of threads with opposite rotation directions and are assembled on a hanging frame 8, and then the two hanging frames 8 can carry out synchronous and opposite adjusting motions. The bottom of the suspension bracket 8 is provided with an extension spring 10 which is connected with a measuring instrument mounting plate 11, and the mounting plate 11 is used for fixing a two-side line laser measuring instrument 12. The trimming bolt 13 is installed on the suspension bracket 8, and the trimming bolt 13 is used for supporting the mounting plate 11, and the pose of the trimming line laser measuring instrument 12 is trimmed through the screw feeding of the trimming bolt 13. Each of the fine tuning bolts 13 is equipped with a slotted self-locking nut. The hanger 8 is guided by a pair of linear ball guides 14 fixed to the side of the mounting plate 1. The second line laser measuring instrument 16 is mounted by mounting the measuring instrument mounting bracket 15 in the middle of the mounting plate 1. The synchronous counter-motion axis is equipped with a travel switch 17 and an absolute grating system 18.
The invention provides a guide rail profile detection method based on a line laser triangle displacement sensor, which is a non-contact detection method. The basic principle of the method of the invention is that: the laser is projected onto the surface of the rail to be inspected using a line laser displacement sensor, the line laser gauge 12 scans the raceway and side information of the rail to be inspected, and the second line laser gauge 16 scans the bottom information of the rail to be inspected. And (3) transmitting data acquired by the displacement sensor into a computer for point cloud processing, developing a corresponding algorithm to finish the detection of the profile of the guide rail, and measuring the principle as shown in the figure. For the guide rail model with larger size, the side surface of the guide rail is divided into areas, and the measurement is completed through multiple scans. When the linear laser measuring instrument (which is also called a linear laser displacement sensor in the invention) operates, a linear laser is emitted to strike a guide rail to be measured. When three line laser measuring instruments collect synchronously, the detection of the section profile is continuously carried out on the guide rail to be measured along the moving direction of the sliding block. The distance between adjacent sections is adjustable by the triggering mode and the acquisition frequency of the sensor. And when the scanning of the guide rail to be detected is finished, splicing the section information to obtain the whole three-dimensional profile information of the guide rail to be detected.
The invention provides a method for detecting the profile of a rolling linear guide rail pair guide rail, which is characterized by comprising the following steps:
collecting point cloud data by a line laser measuring instrument;
as shown in fig. 3, in a preferred embodiment, the method for extracting the section of the guide surface of the present invention specifically includes:
the data collected by the linear laser displacement sensor has the following characteristics: in the PCD file, the point cloud data is stored 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 value of each point value is fixed, namely the outline data interval of the line laser sensor. The second column data represents the actual displacement in the direction of movement of the laser during acquisition. The third column of data represents the height value of each point, where a negative number means that the point is below the reference zero.
In one embodiment, the guide plane cross section extraction is performed based on a straight-through filter method. The filter field of the filter is first set to "y", i.e. the cross-section extraction is performed along the direction of movement of the slider. The function limit ranges (min_limit, max_limit) are set, and the difference between min_limit and max_limit represents the section thickness value. Setting the filtering direction of the filter, forward filtering, namely reserving section data, and reverse filtering, namely removing section information from the whole data. The steps are repeatedly executed for N times, the input data is updated to the reverse filtering data of the last section every time, and the function limiting range is increased by one value section_interval, so that N sections can be extracted. Wherein section_interval represents the distance between two sections.
As shown in fig. 4, in a preferred embodiment, the extraction of the inflection point of the large curvature on the cross section specifically includes the following steps:
traversing each point of the cross-section point cloud by using a nearest-neighbor KSearch method of KD-Tree to search the nearest K points, and storing indexes and distance results of the points obtained by nearest neighbor searching. Extracting index values independently;
calculating and extracting principal components of the point cloud by using a principal component analysis method to obtain three feature vectors v1, v2 and v3;
calculating the centroid coordinates of the extracted point cloud, and fitting a straight line according to the directions of the centroid and v 1;
calculating the average value, variance and standard deviation of the distances from each point in the point cloud set to the fitting straight line;
judging whether the standard deviation is larger than a set threshold value or not;
if the standard deviation is larger than the set threshold value, the determination point is an inflection point of the arc section of the guide rail section. And extracting point cloud data of sharp points and non-sharp points from the original point cloud object, and respectively clustering and storing the point cloud data.
As shown in fig. 5 and 6, in a preferred embodiment, performing arc fitting and plane fitting on the guide rail to be tested includes the steps of:
circular arc and plane fitting based on random sample consensus algorithm (RANSAC). Creating a SACCsegment object, setting model types of the SACCsegment object to be a three-dimensional circular model (namely a fitting circular arc) and a plane model respectively, setting a method type to be RANSAC, and executing fitting.
In the plane fitting, the bottom surface reference surface of the guide rail to be measured corresponds to the largest plane of the acquisition point cloud, and the side surface reference surface corresponds to the second largest plane of the acquisition point cloud. And when the planes are fitted each time, recording the number of the inner points of the model, continuously extracting and comparing the number of the inner points, and updating the fitting results of the largest and second largest planes.
In a preferred embodiment, the solving of the parameters of the rail profile comprises the steps of:
calculating the radius of the guide rail raceway, wherein the calculating of the radius of the guide rail raceway comprises the following steps:
let the radius of each section fitting arc be:wherein n is the number of sections, the arc of the racewayThe radius value R is: />,
The standard deviation is:。
in a preferred embodiment, the solving of the parameters of the rail profile comprises the steps of:
calculating a raceway center distance Hr, wherein the raceway center distance Hr is calculated by the following steps:
let the center coordinates of the left arc fitted with a certain section beThe center coordinates of the right circular arc areThe center distance of the two circular arcs is->The method comprises the following steps:
calculating the center distance of the circular arcs of each section asWherein n is the number of sections, and the center distance Hr of the rollaway nest is: />,
The standard deviation is:。
in a preferred embodiment, the solving of the parameters of the rail profile comprises the steps of:
calculating a raceway center-to-bottom surface reference distance H, the raceway center-to-bottom surface reference distance H comprising the steps of:
setting the circle center coordinates of a certain section fitting circular arc asThe plane equation of the fitted bottom surface isThe reference distance of the circle center to the bottom surface>The method comprises the following steps:
calculating the reference distance from each section arc to the bottom surface asWherein n is the number of sections, and the center distance H of the rollaway nest is: />,
The standard deviation is:。
in a preferred embodiment, the solving of the parameters of the rail profile comprises the steps of:
calculating the parallelism of the guide rail reference surface, wherein the calculating of the parallelism of the guide rail reference surface comprises the following steps:
the direction vector of the connecting line of the circle centers of all sections is taken as the direction vector of the central line of the rollaway nestThe normal vector of the reference plane of the side surface of the guide rail is +.>The included angle between the ball and the central line of the roller path is +.>The method comprises the following steps: />,
Is provided with a bottom surface of the guide railThe normal vector of the reference plane isThe included angle between the ball and the central line of the roller path is +.>The method comprises the following steps:。
in a preferred embodiment, the solving of the parameters of the rail profile comprises the steps of:
calculating the flatness of the guide rail reference surface, wherein the calculating of the flatness of the guide rail reference surface comprises the following steps:
first calculate the distance of each point to the plane:/>Wherein i is the reference plane +.>In (a) is provided,
let the reference plane have n total points, calculate the average of all distances:calculate the maximum value of all distances +.>The formula is: flatness = maximum deviation/average deviation, resulting in flatness of the reference plane:。
the foregoing descriptions of specific exemplary embodiments of the present invention are presented for purposes of illustration and description. It is not intended to limit the invention to the precise form disclosed, and obviously many modifications and variations are possible in light of the above teaching. The exemplary embodiments were chosen and described in order to explain the specific principles of the invention and its practical application to thereby enable one skilled in the art to make and utilize the invention in various exemplary embodiments and with various modifications as are suited to the particular use contemplated. It is intended that the scope of the invention be defined by the claims and their equivalents.
Claims (8)
1. The method for detecting the profile of the rolling linear guide rail pair guide rail is characterized by comprising the following steps of:
collecting point cloud data by a line laser measuring instrument;
carrying out direct-pass filtering section extraction of the guide rail surface based on the acquired point cloud data;
extracting a large curvature inflection point on the section;
performing arc fitting and plane fitting on the guide rail to be tested;
solving parameters of the profile of the guide rail;
the method for extracting the inflection point with the large curvature on the section specifically comprises the following steps:
traversing each point of the cross-section point cloud by using a nearest-neighbor KSearch method of KD-Tree to find the nearest K points, and extracting a point index and a distance result obtained by nearest neighbor searching;
calculating and extracting principal components of the point cloud by using a principal component analysis method to obtain three feature vectors v1, v2 and v3;
calculating the centroid coordinates of the extracted point cloud, and fitting a straight line according to the directions of the centroid and v 1;
calculating the average value, variance and standard deviation of the distances from each point in the point cloud set to the fitting straight line;
judging whether the standard deviation is larger than a set threshold value or not;
if the standard deviation is larger than the set threshold value, determining that the point is an inflection point of the arc section of the cross section of the guide rail;
the method for solving the parameters of the profile of the guide rail comprises the following steps:
calculating the radius of the guide rail raceway, wherein the calculating of the radius of the guide rail raceway comprises the following steps:
fitting circular arcs on each sectionThe radii of (2) are respectively as follows:wherein n is the number of sections, and the radius value R of the circular arc of the rollaway nest is: />,
The standard deviation is:。
2. the method according to claim 1, wherein the extraction of the guide surface straight-through filtering section comprises the steps of:
extracting a section along the moving direction of the sliding block, and setting a filtering field of a filter as y;
setting a function limiting range as a section thickness value;
setting the filtering direction of a filter, forward filtering to keep section data, and reverse filtering to remove section information of the whole data;
the method is repeatedly executed for N times, and each time the input data is updated to the reverse filtering data of the last section, the function limiting range is continuously increased by two parameter values.
3. The method of claim 2, wherein performing an arc fit and a plane fit on the rail under test comprises the steps of:
creating a SACsegment object, respectively setting model types of the SACsegment object as a three-dimensional circular model and a planar model, and executing fitting;
and when the planes are fitted each time, recording the number of the inner points of the model, continuously extracting and comparing the number of the inner points, and updating the fitting results of the largest and second largest planes.
4. A method according to claim 3, wherein solving parameters of the rail profile comprises the steps of:
calculating a raceway center distance Hr, wherein the raceway center distance Hr is calculated by the following steps:
let the center coordinates of the left arc fitted with a certain section beThe center coordinates of the right circular arc are +.>The center distance of the two circular arcs is->The method comprises the following steps:
calculating the center distance of the circular arcs of each section asWherein n is the number of sections, and the center distance Hr of the rollaway nest is: />,
The standard deviation is:。
5. the method of claim 1, wherein solving parameters of the rail profile comprises the steps of:
calculating a raceway center-to-bottom surface reference distance H, the raceway center-to-bottom surface reference distance H comprising the steps of:
setting the circle center coordinates of a certain section fitting circular arc asThe plane equation of the fitted bottom surface isThe reference distance of the circle center to the bottom surface>The method comprises the following steps:
calculating the reference distance from each section arc to the bottom surface asWherein n is the number of sections, and the center distance H of the rollaway nest is: />,
The standard deviation is:。
6. the method of claim 4, wherein solving parameters of the rail profile comprises the steps of:
calculating the parallelism of the guide rail reference surface, wherein the calculating of the parallelism of the guide rail reference surface comprises the following steps:
the direction vector of the connecting line of the circle centers of all sections is taken as the direction vector of the central line of the rollaway nestThe normal vector of the reference surface of the side surface of the guide rail isThe included angle between the ball and the central line of the roller path is +.>The method comprises the following steps: />,
Let the normal vector of the reference plane of the bottom surface of the guide rail beThe included angle between the ball and the central line of the roller path is +.>The method comprises the following steps:。
7. the method of claim 5, wherein solving parameters of the rail profile comprises the steps of:
calculating the flatness of the guide rail reference surface, wherein the calculating of the flatness of the guide rail reference surface comprises the following steps:
first calculate the distance of each point to the plane:/>Wherein i is the reference plane +.>In (a) is provided,
let the reference plane have n total points, calculate the average of all distances:calculate the maximum value of all distances +.>The formula is: flatness = maximum deviation/average deviation, resulting in flatness of the reference plane:。
8. the guide rail profile detection platform is characterized by comprising a mounting plate, wherein a suspension type motor seat is arranged on the mounting plate, a servo motor is arranged on the motor seat, the servo motor drives a left-right rotation direction ball screw through a diaphragm type coupler, the left-right rotation direction ball screw is arranged on a fixing unit and a supporting unit in a fixed supporting mode, the left-right rotation direction ball screw drives two nuts fixed on a suspension bracket, synchronous and reverse adjustment movement can be carried out, an extension spring is arranged on the suspension bracket to be connected with a measuring instrument mounting plate, the mounting plate is used for fixing a line laser measuring instrument, a fine tuning bolt is arranged on the suspension bracket and used for supporting the mounting plate, each fine tuning bolt is provided with a slotted self-locking nut through screw feeding of the fine tuning bolt, the suspension bracket is guided by a ball screw pair fixed on the side surface of the mounting plate, and a second line laser measuring instrument is arranged on the mounting bracket in the middle of the mounting plate, and the platform is used for executing the method according to one of claims 1-7.
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Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP3088130A1 (en) * | 2015-04-30 | 2016-11-02 | Brodmann Technologies GmbH | Method for contactless evaluation of the surface properties of a ball raceway of a ball screw drive |
CN106441168A (en) * | 2016-08-30 | 2017-02-22 | 南京理工大学 | Rolling linear guide rail pair slider profile accuracy measurement method |
CN108195321A (en) * | 2018-01-31 | 2018-06-22 | 闽台龙玛直线科技股份有限公司 | A kind of ball line slideway auxiliary raceway depth of parallelism On-line Measuring Method |
CN108871229A (en) * | 2018-06-11 | 2018-11-23 | 南京理工大学 | A kind of measurement method of ball nut spiral interior rollaway nest curved surface and outer diameter |
CN109035153A (en) * | 2018-06-06 | 2018-12-18 | 链家网(北京)科技有限公司 | A kind of modification method and device of point cloud data |
CN111272088A (en) * | 2020-03-09 | 2020-06-12 | 南京理工大学 | Measuring algorithm for profile pitch diameter of sliding block of rolling linear guide rail pair |
CN112504146A (en) * | 2020-07-20 | 2021-03-16 | 南京理工大学 | Method for detecting rolling path pitch diameter of rolling linear guide rail pair |
CN116255930A (en) * | 2022-12-06 | 2023-06-13 | 桂林量具刃具有限责任公司 | Cross section extraction and measurement method and system based on point cloud slice |
Family Cites Families (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
AU2016385541B2 (en) * | 2016-01-15 | 2019-07-11 | Wuhan Optics Valley Zoyon Science And Technology Co., Ltd. | Object surface deformation feature extraction method based on line scanning three-dimensional point Cloud |
CN111993159B (en) * | 2020-08-27 | 2022-02-11 | 江苏科技大学 | In-place non-contact detection method for shaft workpieces |
-
2023
- 2023-11-01 CN CN202311432523.9A patent/CN117146720B/en active Active
Patent Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP3088130A1 (en) * | 2015-04-30 | 2016-11-02 | Brodmann Technologies GmbH | Method for contactless evaluation of the surface properties of a ball raceway of a ball screw drive |
CN106441168A (en) * | 2016-08-30 | 2017-02-22 | 南京理工大学 | Rolling linear guide rail pair slider profile accuracy measurement method |
CN108195321A (en) * | 2018-01-31 | 2018-06-22 | 闽台龙玛直线科技股份有限公司 | A kind of ball line slideway auxiliary raceway depth of parallelism On-line Measuring Method |
CN109035153A (en) * | 2018-06-06 | 2018-12-18 | 链家网(北京)科技有限公司 | A kind of modification method and device of point cloud data |
CN108871229A (en) * | 2018-06-11 | 2018-11-23 | 南京理工大学 | A kind of measurement method of ball nut spiral interior rollaway nest curved surface and outer diameter |
CN111272088A (en) * | 2020-03-09 | 2020-06-12 | 南京理工大学 | Measuring algorithm for profile pitch diameter of sliding block of rolling linear guide rail pair |
CN112504146A (en) * | 2020-07-20 | 2021-03-16 | 南京理工大学 | Method for detecting rolling path pitch diameter of rolling linear guide rail pair |
CN116255930A (en) * | 2022-12-06 | 2023-06-13 | 桂林量具刃具有限责任公司 | Cross section extraction and measurement method and system based on point cloud slice |
Non-Patent Citations (1)
Title |
---|
基于二维截面筛选标记的点云简化方法研究;刘菲菲;杨铎;;机电工程;第37卷(第05期);第582-586页 * |
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