CN117934760A - Cutter curved surface three-dimensional reconstruction method based on non-contact scanning measurement - Google Patents
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Abstract
The invention discloses a cutter curved surface three-dimensional reconstruction method based on non-contact scanning measurement, which comprises the following steps: step one: cutter point cloud data acquisition and pretreatment: 11 Gathering tool point cloud data: the line laser scanner is controlled by a machine tool servo system to perform measurement movement, and tool point cloud data of multiple positions and angles are collected; 12 Cutter point cloud data preprocessing: the three-dimensional point cloud data are regarded as two-dimensional data, and missing values, simplification and abnormal value processing are sequentially carried out on the three-dimensional point cloud data so as to optimize the quality of the point cloud and improve the usability of the data; step two: rotating and splicing tool point cloud data: based on cutter processing characteristics and rotation measurement movement, splicing a plurality of groups of point cloud data to obtain complete and accurate point cloud data; step three: three-dimensional reconstruction of a cutter curved surface: and carrying out three-dimensional reconstruction of the curved surface of the cutter based on a poisson curved surface method. The three-dimensional reconstruction method of the curved surface of the cutter based on non-contact scanning measurement has the advantages of high measurement efficiency, high integrity of measurement information and the like.
Description
Technical Field
The invention belongs to the technical field of three-dimensional reconstruction, and particularly relates to a cutter curved surface three-dimensional reconstruction method based on non-contact scanning measurement.
Background
In contemporary manufacturing, the function of the tool is critical, with precision directly related to the quality and efficiency of the machining. Along with the continuous development of technology, how to quickly and accurately acquire complete three-dimensional information of a curved surface of a cutter in the production process of the cutter provides reliable data support for online compensation of machining, so that the machining precision of the cutter is ensured, and the method is always a great technical problem.
Traditional measurement methods include non-contact off-line measurement and contact on-machine measurement. The offline measurement needs to take down the processing cutter from the machine tool for detection, so that the problems of secondary clamping errors, processing reference changes and the like are easily caused, and the measuring precision and efficiency of the cutter are reduced; the contact type on-machine measurement mostly needs to adopt probe point-by-point measurement, the measurement efficiency is low, and the requirement of high-precision measurement of a cutter microstructure is often difficult to meet due to the size of the probe. In general, conventional measurement methods have low measurement efficiency and limited measurement accuracy.
Disclosure of Invention
In view of the above, the invention aims to provide a cutter curved surface three-dimensional reconstruction method based on non-contact scanning measurement, which has the advantages of high measurement efficiency, high measurement information integrity and the like.
In order to achieve the above purpose, the present invention provides the following technical solutions:
a three-dimensional reconstruction method of a cutter curved surface based on non-contact scanning measurement comprises the following steps:
Step one: tool point cloud data acquisition and preprocessing
11 Gathering tool point cloud data: the line laser scanner is controlled by a machine tool servo system to perform measurement movement, and tool point cloud data of multiple positions and angles are collected;
12 Cutter point cloud data preprocessing: the three-dimensional point cloud data are regarded as two-dimensional data, and missing values, simplification and abnormal value processing are sequentially carried out on the three-dimensional point cloud data so as to optimize the quality of the point cloud and improve the usability of the data;
step two: tool point cloud data rotation splicing
Based on cutter processing characteristics and rotation measurement movement, splicing a plurality of groups of point cloud data to obtain complete and accurate point cloud data;
Step three: three-dimensional reconstruction of tool curved surface
And carrying out three-dimensional reconstruction of the curved surface of the cutter based on a poisson curved surface method.
Further, in the step 12), the method for preprocessing the tool point cloud data includes the following steps:
121 Carrying out missing value processing on the tool point cloud data;
122 Simplifying the tool point cloud data;
123 Performing outlier processing on the tool point cloud data.
Further, in the step 121), the method for performing missing value processing on the tool point cloud data includes:
1211 Using a 'minimum' bounding box method to reject invalid data points irrelevant to the tested tool;
1212 Calculating the number of invalid points of the ith scanning line;
1213 Determining whether a ratio between the number of invalid data points deleted in the ith scan line and the total number of data points in the scan line exceeds a set first threshold: if yes, go to step 1214); if not, go to step 1215
1214 Deleting the ith scan line, performing step 1216)
1215 Using cubic spline interpolation to complement the data points of the ith scan line, performing 1216);
1216 Determine if the value of i is equal to the total number of scan lines n: if yes, finishing the processing of the missing value of the point cloud data of the cutter; if not, let i=i+1, go to step 1212).
Further, in the step 122), the method for simplifying the tool point cloud data includes:
1221 Dividing the point cloud data into three-dimensional cube grids, each grid being called a voxel;
1222 Calculating the centroid of each voxel and finding the closest data point to it instead of the centroid;
1223 Deleting other data points except the data point serving as the center of gravity in the voxel to obtain the simplified point cloud data.
Further, in the step 123), the method for performing outlier processing on the tool point cloud data includes the steps of:
1231 Traversing the ith scanning line, and respectively calculating data residual errors for the data of the ith scanning line by adopting a Gaussian filter;
1232 Judging whether the data residual exceeds a set second threshold value: if yes, the corresponding data point is an outlier, execute step 1233); if not, go to step 1234);
1233 Removing abnormal points;
1234 Adopting cubic spline interpolation to complement data points in the ith scanning line to obtain data processed by the t-th abnormal point;
1235 Judging whether the current iteration number T is equal to the set maximum iteration number T max: if yes, go to step 1236); if not, let t=t+1, execute step 1231);
1236 Determine if the value of i is equal to the total number of scan lines n: if yes, completing the processing of the abnormal value of the tool point cloud data, and executing step 1237); if not, let i=i+1, t=1, execute step 1231);
1237 Outputting the data.
In the second step, the method for performing rotation splicing on the tool point cloud data comprises the following steps:
21 Calibration of the measurement system: mapping the scanning data into a workpiece coordinate system to obtain actual three-dimensional information;
22 Point cloud rotation stitching): to obtain complete and accurate point cloud data.
Further, in the step 21), the method for calibrating the measurement system includes the following steps:
211 Taking a standard cylindrical bar as a calibration piece, considering that the inclination angle is smaller, regarding elliptical column-shaped data obtained by measuring the installation error of a scanner as a column shape, and fitting an extraction axis to the elliptical column-shaped data by adopting a RANSAC algorithm;
212 Respectively calculating expression equations of the axes under the workpiece coordinate system and the measurement coordinate system to obtain a transformation matrix M from the measurement coordinate system to the workpiece coordinate system;
213 The transformation matrix M is applied to the tool point cloud data, so that actual tool three-dimensional information is obtained.
Further, in the step 22), the method of the rotational splicing of the point cloud includes the following steps:
221 Sequentially rotating n sets of point cloud data (n-1) a around the X-axis according to the measurement order, wherein a is a rotation angle at each measurement, and nα=2pi;
222 Combining the rotated sets of point cloud data, and performing weighted fusion on the combined point cloud based on the density of the voxel grid and the points to process an overlapping area under multiple angles;
223 A consistent and complete tool point cloud data is obtained.
Further, in the third step, the poisson curve method represents the boundary of the object surface by an indication function, where the indication function is:
wherein M represents a cutter; p represents a point in the tool point cloud data;
Introducing vector fields Indirect solution of the indication function due to indication gradient/>Approximately equal to vector field/>Applying a divergence operator/>Conversion to poisson's equation:
Where Δ is denoted as Laplacian;
solving a poisson equation by adopting a finite element method to obtain an indication function χ M;
Performing contour surface extraction by using a Marching Cure, setting an equivalent r as an average value of χ M of all tool point cloud data points, and ensuring that the extracted contour surface is attached to the tool point cloud data; and extracting an isosurface from the three-dimensional grids of the cutter point cloud based on χ M and r, outputting a triangular grid, and completing the three-dimensional reconstruction of the cutter curved surface.
The invention has the beneficial effects that:
The invention relates to a three-dimensional reconstruction method of a cutter curved surface based on non-contact scanning measurement, which comprises the steps of firstly, utilizing a machine tool servo system to control a line laser scanner to perform measurement movement, and collecting multi-position and multi-angle cutter point cloud data; then, on the basis of carrying out noise and incompleteness processing on the original scanning data, realizing accurate point cloud registration, thereby obtaining more complete and accurate cutter point cloud data; finally, realizing the omnibearing three-dimensional reconstruction of the cutter based on the poisson curved surface, improving the detection integrity of three-dimensional information of the cutter in the production process, providing a new measurement technical means for the processing quality regulation and control of the cutter, and providing data support for the cutter performance analysis and the optimal design; the method has the advantages of high measurement efficiency, high integrity of measurement information and the like.
Drawings
In order to make the objects, technical solutions and advantageous effects of the present invention more clear, the present invention provides the following drawings for description:
FIG. 1 is a flow chart of a three-dimensional reconstruction method of a curved surface of a tool based on non-contact scanning measurement;
FIG. 2 is a calibration theoretical model of a measurement system;
FIG. 3 is a basic functional relationship of a Poisson reconstruction; (a) Vector field (B) Indicate gradient/>(C) An indication function χ M; (d) Tap surface/>
FIG. 4 is a view of a tap data acquisition site experiment;
FIG. 5 is a comparison of the point cloud data preprocessing effect of tap points; (a) raw measurement data; (b) after data preprocessing;
FIG. 6 is a three-dimensional splice model of the full point cloud of a tap tip;
fig. 7 is a three-dimensional reconstruction model of a tap tip.
Detailed Description
The present invention will be further described with reference to the accompanying drawings and specific examples, which are not intended to limit the invention, so that those skilled in the art may better understand the invention and practice it.
As shown in fig. 1, the method for reconstructing a curved surface of a tool according to the present embodiment includes the following steps.
Step one: tool point cloud data acquisition and preprocessing
11 Gathering tool point cloud data: and controlling the line laser scanner to measure by using a machine tool servo system, and collecting multi-position and multi-angle tool point cloud data. In this embodiment, the line laser scanner is installed in situ by the fixture, and the tool is controlled by the machine tool servo system to perform a measurement motion. Considering that the line laser scanner is limited by the measuring range, the measurement of a single angle and position cannot reflect the information of the complete cutter, therefore, the cutter is driven to do equiangular rotation through the axis A of the machine tool, the multi-angle multi-position measurement is realized on the cutter, and a plurality of groups of cutter point cloud data are obtained.
12 Cutter point cloud data preprocessing: and according to the scanning characteristics of the line laser scanner, the three-dimensional point cloud data are regarded as two-dimensional data, and missing values, simplification and abnormal value processing are sequentially carried out on the three-dimensional point cloud data so as to optimize the point cloud quality and improve the data availability.
Specifically, the method for preprocessing the cutter point cloud data comprises the following steps:
121 Processing missing value of tool point cloud data
1211 Using a 'minimum' bounding box method to reject invalid data points irrelevant to the tested tool;
1212 Calculating the number of invalid points of the ith scanning line;
1213 Determining whether a ratio between the number of invalid data points deleted in the ith scan line and the total number of data points in the scan line exceeds a set first threshold: if yes, go to step 1214); if not, go to step 1215
1214 Deleting the ith scan line, performing step 1216)
1215 Using cubic spline interpolation to complement the data points of the ith scan line, performing 1216);
1216 Determine if the value of i is equal to the total number of scan lines n: if yes, finishing the processing of the missing value of the point cloud data of the cutter; if not, let i=i+1, go to step 1212).
122 Simplified tool point cloud data
1221 Dividing the point cloud data into three-dimensional cube grids, each grid being called a voxel;
1222 Calculating the centroid of each voxel and finding the closest data point to it instead of the centroid;
1224 Deleting other data points except the data point serving as the center of gravity in the voxel to obtain the simplified point cloud data.
123 Performing outlier processing on tool point cloud data
1231 Traversing the ith scanning line, and respectively calculating data residual errors for the data of the ith scanning line by adopting a Gaussian filter;
1232 Judging whether the data residual exceeds a set second threshold value: if yes, the corresponding data point is an outlier, execute step 1233); if not, go to step 1234);
1233 Removing abnormal points;
1234 Adopting cubic spline interpolation to complement data points in the ith scanning line to obtain data processed by the t-th abnormal point;
1235 Judging whether the current iteration number T is equal to the set maximum iteration number T max: if yes, go to step 1236); if not, let t=t+1, execute step 1231);
1236 Determine if the value of i is equal to the total number of scan lines n: if yes, completing the processing of the abnormal value of the tool point cloud data, and executing step 1237); if not, let i=i+1, t=1, execute step 1231);
1237 Outputting the data.
Step two: tool point cloud data rotation splicing
And based on the cutter processing characteristics and the rotation measurement movement, splicing a plurality of groups of point cloud data to obtain complete and accurate point cloud data. Specifically, the method for performing rotary splicing on the tool point cloud data comprises the following steps:
21 Calibration of the measurement system: the scan data is mapped into the workpiece coordinate system to obtain the actual three-dimensional information.
The calibration of the line laser scanner, that is, mapping the scanning data into the workpiece coordinate system to ensure accurate three-dimensional information, and the calibration theoretical model of the measuring system is shown in fig. 2, wherein O w—XwYwZw is the workpiece coordinate system, O c—XcYcZc is the measuring coordinate system, and the calibration piece is a standard cylindrical bar. Specifically, in this embodiment, the method for calibrating the measurement system includes the following steps:
211 Taking a standard cylindrical bar as a calibration piece, considering that the inclination angle is smaller, regarding elliptical column-shaped data obtained by measuring the installation error of a scanner as a column shape, and fitting an extraction axis to the elliptical column-shaped data by adopting a RANSAC algorithm;
212 Respectively calculating expression equations of the axes under the workpiece coordinate system O w—XwYwZw and the measurement coordinate system O c—XcYcZc to obtain a transformation matrix M from the measurement coordinate system to the workpiece coordinate system;
214 The transformation matrix M is applied to the tool point cloud data, so that actual tool three-dimensional information is obtained.
22 Point cloud rotation stitching): to obtain complete and accurate point cloud data.
Specifically, in this embodiment, the method for rotational splicing of the point cloud includes the following steps:
221 Sequentially rotating n sets of point cloud data (n-1) a around the X-axis according to the measurement order, wherein a is a rotation angle at each measurement, and nα=2pi;
222 Combining the rotated sets of point cloud data, and performing weighted fusion on the combined point cloud based on the density of the voxel grid and the points to process an overlapping area under multiple angles;
223 A consistent and complete tool point cloud data is obtained.
Step three: three-dimensional reconstruction of tool curved surface
And carrying out three-dimensional reconstruction of the curved surface of the cutter based on a poisson curved surface method.
The poisson surface method is to reconstruct a surface by using an implicit function, and the core idea is to represent the boundary of the surface of an object by an indication function (1 in the surface and 0 out the surface), wherein the indication function is as follows:
Wherein: m represents a tool, and p represents a point in the tool point cloud data.
Because of the discontinuity of χ M, which cannot be directly solved, a vector field is introducedAnd solving for the intermediate. The relationship between the tool point cloud normal vector and the indicator function is shown in fig. 3. According to the divergence theorem, the gradient/>, is indicatedMay be approximately equal to vector field/>And then apply a divergence operator/>, to both sides thereofConversion to poisson's equation:
where Δ is denoted as the Laplacian. And solving a poisson equation by adopting a finite element method to obtain an exponential function χ M.
In order to reconstruct the curved surface of the tool, the contour surface is extracted by adopting a Maring Cure, and meanwhile, the contour r is set to be the average value of χ M of all the point cloud data points of the tool, so that the extracted contour surface is ensured to be attached to the point cloud data of the tool. On the basis, on the basis of χ M and r, an isosurface is extracted from the three-dimensional meshes of the point cloud of the cutter, a triangular mesh is output, and the three-dimensional reconstruction of the curved surface of the cutter is completed.
For a better understanding of the present invention by those skilled in the art, the following description of the present invention will be provided in connection with examples of tap scanning.
Step one: tool point cloud data acquisition and preprocessing
Referring to step one, data acquisition is performed on the pointed tap as shown in fig. 4.
Then, preprocessing is performed on the measured data, point cloud data is simplified, and abnormal points in the data are removed, as shown in fig. 5.
Step two: tool point cloud rotation splicing
Referring to the second step, the measured multiple sets of point cloud data of the tap are spliced to obtain complete point cloud data, as shown in fig. 6.
Step three: three-dimensional reconstruction of tool curved surface
According to the reference step three, a poisson surface method is used for three-dimensional reconstruction, and a final three-dimensional model is generated, as shown in fig. 6.
The above-described embodiments are merely preferred embodiments for fully explaining the present invention, and the scope of the present invention is not limited thereto. Equivalent substitutions and modifications will occur to those skilled in the art based on the present invention, and are intended to be within the scope of the present invention. The protection scope of the invention is subject to the claims.
Claims (9)
1. A three-dimensional reconstruction method of a cutter curved surface based on non-contact scanning measurement is characterized by comprising the following steps of: the method comprises the following steps:
Step one: tool point cloud data acquisition and preprocessing
11 Gathering tool point cloud data: the line laser scanner is controlled by a machine tool servo system to perform measurement movement, and tool point cloud data of multiple positions and angles are collected;
12 Cutter point cloud data preprocessing: the three-dimensional point cloud data are regarded as two-dimensional data, and missing values, simplification and abnormal value processing are sequentially carried out on the three-dimensional point cloud data so as to optimize the quality of the point cloud and improve the usability of the data;
step two: tool point cloud data rotation splicing
Based on cutter processing characteristics and rotation measurement movement, splicing a plurality of groups of point cloud data to obtain complete and accurate point cloud data;
Step three: three-dimensional reconstruction of tool curved surface
And carrying out three-dimensional reconstruction of the curved surface of the cutter based on a poisson curved surface method.
2. The three-dimensional reconstruction method of a curved surface of a tool based on non-contact scanning measurement according to claim 1, wherein the method comprises the following steps: in the step 12), the method for preprocessing the tool point cloud data comprises the following steps:
121 Carrying out missing value processing on the tool point cloud data;
122 Simplifying the tool point cloud data;
123 Performing outlier processing on the tool point cloud data.
3. The three-dimensional reconstruction method of the curved surface of the cutter based on non-contact scanning measurement according to claim 2, wherein the method comprises the following steps: in the step 121), the method for performing missing value processing on the tool point cloud data includes:
1211 Using a 'minimum' bounding box method to reject invalid data points irrelevant to the tested tool;
1212 Calculating the number of invalid points of the ith scanning line;
1213 Determining whether a ratio between the number of invalid data points deleted in the ith scan line and the total number of data points in the scan line exceeds a set first threshold: if yes, go to step 1214); if not, go to step 1215
1214 Deleting the ith scan line, performing step 1216)
1215 Using cubic spline interpolation to complement the data points of the ith scan line, performing 1216);
1216 Determine if the value of i is equal to the total number of scan lines n: if yes, finishing the processing of the missing value of the point cloud data of the cutter; if not, let i=i+1, go to step 1212).
4. The three-dimensional reconstruction method of the curved surface of the cutter based on non-contact scanning measurement according to claim 2, wherein the method comprises the following steps: in the step 122), the method for simplifying the tool point cloud data includes:
1221 Dividing the point cloud data into three-dimensional cube grids, each grid being called a voxel;
1222 Calculating the centroid of each voxel and finding the closest data point to it instead of the centroid;
1223 Deleting other data points except the data point serving as the center of gravity in the voxel to obtain the simplified point cloud data.
5. The three-dimensional reconstruction method of the curved surface of the cutter based on non-contact scanning measurement according to claim 2, wherein the method comprises the following steps: in the step 123), the method for performing outlier processing on the tool point cloud data includes the steps of:
1231 Traversing the ith scanning line, and respectively calculating data residual errors for the data of the ith scanning line by adopting a Gaussian filter;
1232 Judging whether the data residual exceeds a set second threshold value: if yes, the corresponding data point is an outlier, execute step 1233); if not, go to step 1234);
1233 Removing abnormal points;
1234 Adopting cubic spline interpolation to complement data points in the ith scanning line to obtain data processed by the t-th abnormal point;
1235 Judging whether the current iteration number T is equal to the set maximum iteration number T max: if yes, go to step 1236); if not, let t=t+1, execute step 1231);
1236 Determine if the value of i is equal to the total number of scan lines n: if yes, completing the processing of the abnormal value of the tool point cloud data, and executing step 1237); if not, let i=i+1, t=1, execute step 1231);
1237 Outputting the data.
6. The three-dimensional reconstruction method of a curved surface of a tool based on non-contact scanning measurement according to claim 1, wherein the method comprises the following steps: in the second step, the method for performing rotary splicing on the tool point cloud data comprises the following steps:
21 Calibration of the measurement system: mapping the scanning data into a workpiece coordinate system to obtain actual three-dimensional information;
22 Point cloud rotation stitching): to obtain complete and accurate point cloud data.
7. The three-dimensional reconstruction method of a curved surface of a tool based on non-contact scanning measurement according to claim 6, wherein the method comprises the following steps: in the step 21), the method for calibrating the measurement system comprises the following steps:
211 Taking a standard cylindrical bar as a calibration piece, considering that the inclination angle is smaller, regarding elliptical column-shaped data obtained by measuring the installation error of a scanner as a column shape, and fitting an extraction axis to the elliptical column-shaped data by adopting a RANSAC algorithm;
212 Respectively calculating expression equations of the axes under the workpiece coordinate system and the measurement coordinate system to obtain a transformation matrix M from the measurement coordinate system to the workpiece coordinate system;
213 The transformation matrix M is applied to the tool point cloud data, so that actual tool three-dimensional information is obtained.
8. The three-dimensional reconstruction method of a curved surface of a tool based on non-contact scanning measurement according to claim 6, wherein the method comprises the following steps: in the step 22), the method for the point cloud rotation splicing comprises the following steps:
221 Sequentially rotating n sets of point cloud data (n-1) a around the X-axis according to the measurement order, wherein a is a rotation angle at each measurement, and nα=2pi;
222 Combining the rotated sets of point cloud data, and performing weighted fusion on the combined point cloud based on the density of the voxel grid and the points to process an overlapping area under multiple angles;
223 A consistent and complete tool point cloud data is obtained.
9. The three-dimensional reconstruction method of a curved surface of a tool based on non-contact scanning measurement according to claim 1, wherein the method comprises the following steps: in the third step, the poisson curve method represents the boundary of the object surface through an indication function, wherein the indication function is as follows:
wherein M represents a cutter; p represents a point in the tool point cloud data;
Introducing vector fields Indirect solution of the indication function due to indication gradient/>Approximately equal to vector field/>Applying a divergence operator/>Conversion to poisson's equation:
Where Δ is denoted as Laplacian;
solving a poisson equation by adopting a finite element method to obtain an indication function χ M;
Performing contour surface extraction by using a Marching Cure, setting an equivalent r as an average value of χ M of all tool point cloud data points, and ensuring that the extracted contour surface is attached to the tool point cloud data; and extracting an isosurface from the three-dimensional grids of the cutter point cloud based on χ M and r, outputting a triangular grid, and completing the three-dimensional reconstruction of the cutter curved surface.
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