CN110458822B - Non-contact three-dimensional matching detection method for complex curved surface part - Google Patents

Non-contact three-dimensional matching detection method for complex curved surface part Download PDF

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CN110458822B
CN110458822B CN201910724278.6A CN201910724278A CN110458822B CN 110458822 B CN110458822 B CN 110458822B CN 201910724278 A CN201910724278 A CN 201910724278A CN 110458822 B CN110458822 B CN 110458822B
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郭渊
王俊
许泽银
秦强
蒋克荣
袁永壮
夏小虎
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Hefei University
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Abstract

The invention is suitable for the technical field of curved surface part detection, and provides a non-contact three-dimensional matching detection method for a complex curved surface part, which comprises the following steps: A. carrying out three-dimensional fixed-point measurement on the detected part; B. drawing a reference line; C. confirming a real-time area; D. obtaining the overall surface profile of the measured free-form surface sample; E. and carrying out three-dimensional modeling on the workpiece to be processed by adopting a mesh segmentation form on the obtained integral surface profile of the curved surface part. Therefore, the invention can effectively realize accurate measurement, reduce measurement errors and improve measurement precision.

Description

Non-contact three-dimensional matching detection method for complex curved surface part
Technical Field
The invention relates to the technical field of curved surface part detection, in particular to a non-contact three-dimensional matching detection method for a complex curved surface part.
Background
At present, two types of methods are mainly used for detecting complex curved surface parts with higher precision: contact measurement and non-contact measurement. The contact measurement adopts the traditional three-coordinate measuring machine to sample the parts point by point, the measurement precision is higher, but the method has low measurement efficiency and has special requirements on the material of the parts to be measured. With the continuous development of computer vision and pattern recognition technology, the non-contact measurement technology is more and more widely applied in the field of complex curved surface part detection with higher measurement speed and precision.
The non-contact measurement utilizes an optical scanner to obtain scanning point sets with different angles, then the point sets are spliced to obtain a complete part scanning point set, and error information of the part is obtained through matching analysis of the scanning point set and a CAD model point set. In a standard detection link, machining errors are generally mainly considered, but the influence of measurement errors on a detection result is ignored; in fact, if the error of the matching itself does not reach the ideal order of magnitude, a wrong measurement result is obtained, and particularly, the matching error is reduced to the minimum in the matching detection process of the high-precision complex curved surface part.
In view of the foregoing, it is apparent that the prior art has inconvenience and disadvantages in practical use, and thus, needs to be improved.
Disclosure of Invention
In view of the above-mentioned drawbacks, the present invention provides a non-contact three-dimensional matching detection method for a complex curved surface part, which can reduce measurement errors and improve measurement accuracy.
In order to achieve the purpose, the invention provides a non-contact three-dimensional matching detection method for a complex curved surface part, which comprises the following steps:
A. carrying out three-dimensional fixed-point measurement on the detected part:
firstly, measuring the position of a reference line by a point location measurement method, selecting and fixing the section of a curved surface part to be measured in the measurement process, then moving the curved surface part to be measured successively on the same axis to measure the reference line, moving the curved surface part on a vertical axis for a specified distance after the measurement is finished, and then measuring the other section by moving the curved surface part successively to form a basic profile of the reference line;
B. drawing a reference line:
drawing the basic profile of the datum line formed in the step A through drawing software, setting corresponding point distances, after the point distances are set, scanning the surface of the part to be detected through a scanning instrument at a constant speed, and forming a complete light strip real-time area in the scanning process;
C. real-time zone confirmation:
defining a sequence of lightsBar image { f' (x, y, t) 0 )，f′(x，y，t 1 )，…，f′(x，y，t n-1 ) Stripe position state of the ith stripe image in (j) is X i The relationship between the positions of adjacent light bars is expressed by following formula i+1 ＝X i + d ω/f, i =0,1,2, \ 8230;, n, wherein
Figure BDA0002158368440000021
Figure BDA0002158368440000022
The minimum component of the light stripe passing region in the horizontal direction after the thresholding for the image,
Figure BDA0002158368440000023
d is the maximum component, d is the average measurement distance from the scanning instrument to the surface of the part to be measured, omega is the scanning angular velocity of the scanning instrument, and f is the acquisition frame frequency of the scanning instrument;
D. the linear motion error of the tested curved surface part during X-direction and Y-direction scanning detection is compensated by displacement data obtained by measurement of a laser interferometer, and three-dimensional shape data { D11 (X, Y, z), D12 (X, Y, z) \ 8230 } of a free-form surface sample, D12 (X, Y, z) } of a free-form surface sample is fitted to obtain the overall surface profile of the tested free-form surface sample;
E. and B, on the basis of drawing the reference line in the step B, carrying out three-dimensional modeling on the workpiece to be processed by adopting a mesh segmentation form on the obtained integral surface profile of the curved surface part, carrying out constrained triangulation mesh subdivision according to the distribution of the characteristic points of the drawn contour line, extracting a skeleton of the two-dimensional contour line, selecting skeleton points and sampling points, projecting the skeleton points and the sampling points to the three-dimensional space ellipsoid curved surface, introducing a dihedral angle principle, optimizing a triangularization algorithm of the spatial discrete data points, and finally stitching the skeleton points to obtain three-dimensional mesh curved surface representation.
According to the non-contact three-dimensional matching detection method for the complex curved surface part, during baseline measurement, the measuring head moves from the point A to the point B, the measuring head retreats to the point C after the point B is measured, then the measuring head moves to the point D according to the specified step pitch, the measurement of the next point E is repeated, and during the measurement process, the original point A is used as an angle fixed point, and the baseline of the complex curved surface part is drawn according to the measured data.
According to the non-contact three-dimensional matching detection method for the complex curved surface part, in the step C, the light strip width value d is searched line by line (column) from top to bottom by adopting the image light strip communication area divided by the threshold value, and the light strip width value sequence is obtained as shown in the following [ d i-λ ，…，d i ，…，d i+λ ](λ≥1，i＝k，k+1，…，k+n)。
According to the non-contact three-dimensional matching detection method of the complex curved surface part, d k The width value of the light strip of the kth row, k is the first row of the light strip communication area, n is the total row number of the light strip communication area, and the width value d of each row i is taken as i And the upper and lower lambda lines construct the calculation sequence [ d ] i-λ ，…，d i ，…，d i+λ ](lambda is more than or equal to 1,i =1 k, k +1, \ 8230;, k + n), and the rate of change of the optical stripe width psi is calculated i The width of the light bar is defined in the form of discrete variance, and the change rate is as follows
Figure BDA0002158368440000031
Wherein: p is a radical of j Is the jth row (j is epsilon [ i-lambda, i + lambda)]) Width d of light strip j Probability of occurrence.
According to the non-contact three-dimensional matching detection method of the complex curved surface part, p j Probability of occurrence is p j λ = 1/(2 λ + 1), and μ is an average value of each width element in the calculated number series, so that the rate of change in the width of the optical stripe in the i-th row is obtained as
Figure BDA0002158368440000032
Wherein the width value d of the overflow part at i =1 and i = n k-1 And d k+n+1 The treatment was performed as 0.
According to the non-contact three-dimensional matching detection method for the complex curved surface part, the constrained triangular mesh generation utilizes the spatial topological relation of a GIS to preprocess algorithm input data, mesh refinement is realized based on a uniform data structure of a triangle, a two-dimensional contour line is adopted for reference line drawing, and data processing is carried out on the reference line drawing by utilizing the geometric characteristics of a central axis line based on the two-dimensional contour line and a metasphere modeling technology.
According to the non-contact three-dimensional matching detection method for the complex curved surface part, the length deviation of the datum line is calculated as follows: f = X2+ Y2-R2, performing deviation correction presetting of F = F-X + Y or F = F-Y + X according to the starting point in the quadrant and the deviation of the starting point away from the X axis or towards the X axis when starting deviation presetting or quadrant conversion in operation is performed, and performing recursion calculation on a curve operation: when X + -1: f = F ± 2X +1, when Y ± 1: f = F ± 2 × Y +1, and is changed into: when X + -1: f = F ± 2 x +2, when Y ± 1: f = F +/-2 + Y +2 is used for enabling the correction quantity of the reference R to be changed from 0.8 to 1.5 in one quadrant, so that the maximum deviation of the controlled point on the coordinate axis relative to the reference R is removed, tracks on two sides of the coordinate axis are symmetrical, and the whole track runs by taking the R as the center.
The invention provides a non-contact three-dimensional matching detection method for a complex curved surface part, which comprises the following steps:
A. carrying out three-dimensional fixed-point measurement on the detected part:
firstly, measuring the position of a datum line by a point location measurement method, selecting and fixing the section of a curved surface part to be measured in the measurement process, then moving the curved surface part to be measured on the same axis successively to measure the datum line, and moving the curved surface part on a vertical axis for a specified distance after the measurement is finished to measure another section successively to form a basic contour of the datum line;
B. drawing a reference line:
b, drawing the basic contour of the datum line formed in the step A through drawing software, setting corresponding point distances, after the point distances are set, scanning the surface of the part to be detected through a scanning instrument at a constant speed, and forming a complete light strip real-time area in the scanning process;
C. real-time zone confirmation:
a sequential light bar image f' (x,y，t 0 )，f′(x，y，t 1 )，…，f′(x，y，t n-1 ) The light bar position state of the ith light bar image in the previous step is X i The relationship between the positions of adjacent light bars is expressed by following formula i+1 ＝X i + d ω/f, i =0,1,2, \8230;, n, where
Figure BDA0002158368440000051
Figure BDA0002158368440000052
The minimum component of the light stripe passing region in the horizontal direction after the thresholding for the image,
Figure BDA0002158368440000053
d is the maximum component, d is the average measurement distance from the scanning instrument to the surface of the part to be measured, omega is the scanning angular velocity of the scanning instrument, and f is the acquisition frame frequency of the scanning instrument;
D. the linear motion error of the measured curved surface part during X-direction and Y-direction scanning detection is compensated by displacement data obtained by measurement of a laser interferometer, and three-dimensional shape data { D11 (X, Y, z), D12 (X, Y, z) \8230, D12 (X, Y, z), dij (X, Y, z) \8230, DMN (X, Y, z) } of a free curved surface sample is fitted to obtain the overall surface profile of the measured free curved surface sample;
E. and B, on the basis of drawing the reference line in the step B, carrying out three-dimensional modeling on the workpiece to be processed by adopting a mesh segmentation form on the obtained integral surface profile of the curved surface part, carrying out constrained triangulation mesh subdivision according to the distribution of the characteristic points of the drawn contour line, extracting a skeleton of the two-dimensional contour line, selecting skeleton points and sampling points, projecting the skeleton points and the sampling points to the three-dimensional space ellipsoid curved surface, introducing a dihedral angle principle, optimizing a triangularization algorithm of the spatial discrete data points, and finally stitching the skeleton points to obtain three-dimensional mesh curved surface representation.
The invention has the beneficial effects that: by designing the three-dimensional matching detection process of the complex curved surface part, the characteristics of high convergence rate, good robustness and difficulty in falling into local optimum can be fully utilized, tests show that a high-precision and high-efficiency three-dimensional matching result can be obtained, non-contact measurement is adopted, the machined surface of an element is not damaged, whether machining is qualified or not can be judged through images, and the three-dimensional matching detection process can be used as an effective means for online rapid and batch detection.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to examples, and it should be understood that the specific examples described herein are only for the purpose of explaining the present invention and are not intended to limit the present invention.
The invention provides a non-contact three-dimensional matching detection method for a complex curved surface part, which comprises the following steps:
A. carrying out three-dimensional fixed-point measurement on the detected part:
firstly, measuring the position of a datum line by a point location measurement method, selecting and fixing the section of a curved surface part to be measured in the measurement process, then moving the curved surface part to be measured on the same axis successively to measure the datum line, and moving the curved surface part on a vertical axis for a specified distance after the measurement is finished to measure another section successively to form a basic contour of the datum line;
B. drawing a reference line:
drawing the basic profile of the datum line formed in the step A through drawing software, setting corresponding point distances, after the point distances are set, scanning the surface of the part to be detected through a scanning instrument at a constant speed, and forming a complete light strip real-time area in the scanning process;
C. real-time zone confirmation:
defining sequential bar images { f' (x, y, t) 0 )，f′(x，y，t 1 )，…，f′(x，y，t n-1 ) The light bar position state of the ith light bar image in the previous step is X i The relationship between the positions of adjacent light bars is expressed by following formula i+1 ＝X i + d ω/f, i =0,1,2, \ 8230;, n, wherein
Figure BDA0002158368440000061
Figure BDA0002158368440000062
The minimum component of the light stripe passing region in the horizontal direction after the thresholding for the image,
Figure BDA0002158368440000063
d is the maximum component, d is the average measurement distance from the scanning instrument to the surface of the part to be measured, omega is the scanning angular velocity of the scanning instrument, and f is the acquisition frame frequency of the scanning instrument;
D. the linear motion error of the tested curved surface part during X-direction and Y-direction scanning detection is compensated by displacement data obtained by measurement of a laser interferometer, and three-dimensional shape data { D11 (X, Y, z), D12 (X, Y, z) \ 8230 } of a free-form surface sample, D12 (X, Y, z) } of a free-form surface sample is fitted to obtain the overall surface profile of the tested free-form surface sample;
E. and B, on the basis of drawing the reference line in the step B, carrying out three-dimensional modeling on the workpiece to be processed by adopting a mesh segmentation form on the obtained integral surface profile of the curved surface part, carrying out constrained triangulation mesh subdivision according to the distribution of the characteristic points of the drawn contour line, extracting a skeleton of the two-dimensional contour line, selecting skeleton points and sampling points, projecting the skeleton points and the sampling points to the three-dimensional space ellipsoid curved surface, introducing a dihedral angle principle, optimizing a triangularization algorithm of the spatial discrete data points, and finally stitching the skeleton points to obtain three-dimensional mesh curved surface representation.
Preferably, when the datum line is measured, the measuring head moves from the point A to the point B, the measuring head retreats to the point C after the measurement of the point B, then the measuring head moves to the point D according to the specified step distance, the measurement of the next point E is repeated, the datum line of the curved surface part is drawn by taking the original point A as an angle fixed point in the measuring process, the datum line is moved for multiple times based on the original point, the effective point distance measurement of the datum line is achieved, and the measuring accuracy is further improved.
In addition, the constrained triangular mesh subdivision utilizes the spatial topological relation of a GIS to preprocess algorithm input data, realizes mesh refinement based on a triangular unified data structure, adopts a two-dimensional contour line based on a two-dimensional contour line and a metasphere modeling technology for drawing a reference line, utilizes the geometric characteristics of a central axis to process data, and utilizes the constrained triangular mesh, the two-dimensional contour line and the metasphere modeling technology to effectively measure geometric line distance, thereby ensuring the accuracy in the subsequent measuring process.
Further, in step C of the present invention, the light bar width value d of the image divided by the threshold is searched from top to bottom row by row (column) to obtain the light bar width value sequence as shown in [ d i-λ ，…，d i ，…d i+λ ](lambda is more than or equal to 1,i=k +1, 8230; k + n), and the surface of the curved surface part is segmented and distance-measured by a threshold segmentation method, so that the accuracy of subsequent measurement is ensured.
Preferably, the length deviation of the reference line of the present invention is calculated by the following equation: f = X2+ Y2-R2, performing deviation correction presetting of F = F-X + Y or F = F-Y + X according to the starting point in the quadrant and the deviation of the starting point away from the X axis or towards the X axis when starting deviation presetting or quadrant conversion in operation is performed, and performing recursion calculation on a curve operation: when X + -1: f = F ± 2X +1, when Y ± 1: f = F ± 2+ Y +1, instead: when X + -1: f = F ± 2 x +2, when Y ± 1: f = F +/-2 + Y +2 is used for enabling the correction amount of the reference R to be changed from 0.8 to 1.5 in a quadrant, so that the maximum deviation of a controlled point on a coordinate axis relative to the reference R is removed, tracks on two sides of the coordinate axis are symmetrical, the whole track runs by taking the R as the center, effective interpolation is carried out on the position and the point distance of the reference line by using a length deviation formula, the accuracy after measurement is further ensured, and the final drawing accuracy is improved.
The invention provides a non-contact three-dimensional matching detection method for a complex curved surface part, which comprises the following steps:
A. carrying out three-dimensional fixed-point measurement on the detected part:
firstly, measuring the position of a datum line by a point location measurement method, selecting and fixing the section of a curved surface part to be measured in the measurement process, then moving the curved surface part to be measured on the same axis successively to measure the datum line, and moving the curved surface part on a vertical axis for a specified distance after the measurement is finished to measure another section successively to form a basic contour of the datum line;
B. drawing a reference line:
drawing the basic profile of the datum line formed in the step A through drawing software, setting corresponding point distances, after the point distances are set, scanning the surface of the part to be detected through a scanning instrument at a constant speed, and forming a complete light strip real-time area in the scanning process;
C. real-time zone confirmation:
defining sequential bar images { f' (x, y, t) 0 )，f′(x，y，t 1 )，…，f′(x，y，t n-1 ) The light bar position state of the ith light bar image in the previous step is X i The relationship between the positions of adjacent light bars is expressed by following formula i+1 ＝X i + d ω/f, i =0,1,2, \ 8230;, n, wherein
Figure BDA0002158368440000081
Figure BDA0002158368440000082
The minimum component of the light stripe passing region in the horizontal direction after the thresholding for the image,
Figure BDA0002158368440000083
d is the maximum component, d is the average measurement distance from the scanning instrument to the surface of the part to be measured, omega is the scanning angular velocity of the scanning instrument, and f is the acquisition frame frequency of the scanning instrument;
D. the linear motion error of the tested curved surface part during X-direction and Y-direction scanning detection is compensated by displacement data obtained by measurement of a laser interferometer, and three-dimensional shape data { D11 (X, Y, z), D12 (X, Y, z) \ 8230 } of a free-form surface sample, D12 (X, Y, z) } of a free-form surface sample is fitted to obtain the overall surface profile of the tested free-form surface sample;
E. and B, on the basis of drawing the reference line in the step B, carrying out three-dimensional modeling on the workpiece to be processed by adopting a mesh segmentation form on the obtained integral surface profile of the curved surface part, carrying out constrained triangulation mesh subdivision according to the distribution of the characteristic points of the drawn contour line, extracting a skeleton of the two-dimensional contour line, selecting skeleton points and sampling points, projecting the skeleton points and the sampling points to the three-dimensional space ellipsoid curved surface, introducing a dihedral angle principle, optimizing a triangularization algorithm of the spatial discrete data points, and finally stitching the skeleton points to obtain three-dimensional mesh curved surface representation.
And during the measurement of the datum line, the measuring head moves from the point A to the point B, moves back to the point C after the measurement of the datum line is finished through the point B, then moves to the point D according to the specified step pitch, repeats the measurement of the next point E, and draws the datum line of the curved surface part by taking the original point A as an angle to fix the point in the measurement process according to the measured data. In the step C, the light strip width value d of the image divided by the threshold is searched from top to bottom row by row (column), and the light strip width value array is obtained as shown in the following [ d ] i-λ ，…，d i ，…d i+λ ](lambda is more than or equal to 1,i =1 k, k +1, \ 8230;, k + n). D is k The width value of the light strip of the kth row, k is the first row of the light strip communication area, n is the total row number of the light strip communication area, and the width value d of each row i is taken as i And the upper and lower lambda row elements construct the calculation sequence [ d ] i-λ ，…，d i ，…，d i+λ ](lambda is more than or equal to 1,i =1 k, k +1, \ 8230;, k + n), and the rate of change of the optical stripe width psi is calculated i The width of the light bar is defined in the form of a discrete variance with a rate of change as follows
Figure BDA0002158368440000091
Wherein: p is a radical of j Is the jth row (j is epsilon [ i-lambda, i + lambda)]) Width d of light strip j The probability of occurrence.
Said p is j Probability of occurrence is p j λ = 1/(2 λ + 1), and μ is an average value of each width element of the calculated number series, and therefore, the rate of change in the optical stripe width of the i-th row is obtained as
Figure BDA0002158368440000092
Wherein the width value d of the overflow part at i =1 and i = n k-1 And d k+n+1 The treatment was carried out as 0.
The constrained triangulation network utilizes the spatial topological relation of a GIS to preprocess algorithm input data, the network refinement is realized based on a triangular unified data structure, a two-dimensional contour line is adopted for reference line drawing, and the data processing is carried out on the two-dimensional contour line based on a two-dimensional contour line and a metasphere modeling technology by utilizing the geometric characteristics of a central axis. Length deviation of the reference line: f = X2+ Y2-R2, performing deviation correction presetting of F = F-X + Y or F = F-Y + X according to the starting point in the quadrant and the deviation of the starting point away from the X axis or towards the X axis when starting deviation presetting or quadrant conversion in operation is performed, and performing recursion calculation on a curve operation: when X + -1: f = F ± 2X +1, when Y ± 1: f = F ± 2+ Y +1, instead: when X + -1: f = F ± 2 x +2, when Y ± 1: f = F +/-2 + Y +2, so that the correction of the reference R is changed from 0.8 to 1.5 in a quadrant, the maximum deviation of the controlled point on the coordinate axis relative to the reference R is removed, tracks on two sides of the coordinate axis are symmetrical, and the whole track runs by taking the R as the center.
In summary, the invention provides a non-contact three-dimensional matching detection method for a complex curved surface part, which comprises the following steps:
A. carrying out three-dimensional fixed-point measurement on the detected part:
firstly, measuring the position of a datum line by a point location measurement method, selecting and fixing the section of a curved surface part to be measured in the measurement process, then moving the curved surface part to be measured on the same axis successively to measure the datum line, and moving the curved surface part on a vertical axis for a specified distance after the measurement is finished to measure another section successively to form a basic contour of the datum line;
B. drawing a reference line:
drawing the basic profile of the datum line formed in the step A through drawing software, setting corresponding point distances, after the point distances are set, scanning the surface of the part to be detected through a scanning instrument at a constant speed, and forming a complete light strip real-time area in the scanning process;
C. real-time zone confirmation:
define sequential bar images { f' (x, y, t) 0 )，f′(x，y，t 1 )，…，f′(x，y，t n-1 ) Stripe position state of the ith stripe image in (j) is X i The relationship between the positions of adjacent light bars is deduced by the following formulaShow X i+1 ＝X i + d ω/f, i =0,1,2, \8230;, n, where
Figure BDA0002158368440000101
Figure BDA0002158368440000102
The minimum component of the light stripe passing region in the horizontal direction after the thresholding for the image,
Figure BDA0002158368440000103
d is the maximum component, d is the average measurement distance from the scanning instrument to the surface of the part to be measured, omega is the scanning angular velocity of the scanning instrument, and f is the acquisition frame frequency of the scanning instrument;
D. the linear motion error of the measured curved surface part during X-direction and Y-direction scanning detection is compensated by displacement data obtained by measurement of a laser interferometer, and three-dimensional shape data { D11 (X, Y, z), D12 (X, Y, z) \8230, D12 (X, Y, z), dij (X, Y, z) \8230, DMN (X, Y, z) } of a free curved surface sample is fitted to obtain the overall surface profile of the measured free curved surface sample;
E. and B, on the basis of drawing the reference line in the step B, carrying out three-dimensional modeling on the obtained integral surface profile of the curved surface part on the workpiece to be processed in a grid segmentation mode, carrying out constrained triangular grid subdivision according to the distribution of characteristic points of the drawn contour line, extracting a framework of the two-dimensional contour line, selecting framework points and sampling points, projecting the framework points and the sampling points to a three-dimensional space ellipsoid curved surface, introducing a dihedral angle principle, optimizing a triangularization algorithm of space discrete data points, and finally stitching the framework points to obtain three-dimensional grid curved surface representation.
The invention has the beneficial effects that: by designing the three-dimensional matching detection process of the complex curved surface part, the characteristics of high convergence rate, good robustness and difficulty in falling into local optimum can be fully utilized, tests show that a high-precision and high-efficiency three-dimensional matching result can be obtained, non-contact measurement is adopted, the machined surface of an element is not damaged, whether machining is qualified or not can be judged through images, and the three-dimensional matching detection process can be used as an effective means for online rapid and batch detection.
The present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof, and it should be understood that various changes and modifications can be effected therein by one skilled in the art without departing from the spirit and scope of the invention as defined in the appended claims.

Claims (7)

1. A non-contact three-dimensional matching detection method for a complex curved surface part is characterized by comprising the following steps:
A. carrying out three-dimensional fixed-point measurement on the detected part:
firstly, measuring the position of a datum line by a point location measurement method, selecting and fixing the section of a curved surface part to be measured in the measurement process, then moving the curved surface part to be measured on the same axis successively to measure the datum line, and moving the curved surface part on a vertical axis for a specified distance after the measurement is finished to measure another section successively to form a basic contour of the datum line;
B. drawing a reference line:
drawing the basic profile of the datum line formed in the step A through drawing software, setting corresponding point distances, after the point distances are set, scanning the surface of the part to be detected through a scanning instrument at a constant speed, and forming a complete light strip real-time area in the scanning process;
C. real-time zone confirmation:
define sequential bar images { f' (x, y, t) 0 )，f′(x，y，t 1 )，…，f′(x，y，t n-1 ) The light bar position state of the ith light bar image in the previous step is X i The relationship between the positions of adjacent light bars is expressed by following formula i+1 ＝X i + d ω/f, i =0,1,2, \8230;, n, where
Figure FDA0002158368430000011
Figure FDA0002158368430000012
The minimum component of the light stripe passing region in the horizontal direction after the thresholding for the image,
Figure FDA0002158368430000013
d is the maximum component, d is the average measurement distance from the scanning instrument to the surface of the part to be measured, omega is the scanning angular velocity of the scanning instrument, and f is the acquisition frame frequency of the scanning instrument;
D. compensating linear motion errors of the measured curved surface part during X-direction and Y-direction scanning detection by displacement data obtained by measurement of a laser interferometer, and fitting three-dimensional shape data { D11 (X, Y, z), D12 (X, Y, z),. } of a free-form surface sample, D12 (X, Y, z), dij (X, Y, z),. } of DMN (X, Y, z) } to obtain an integral surface profile of the measured free-form surface sample;
E. and B, on the basis of drawing the reference line in the step B, carrying out three-dimensional modeling on the workpiece to be processed by adopting a mesh segmentation form on the obtained integral surface profile of the curved surface part, carrying out constrained triangulation mesh subdivision according to the distribution of the characteristic points of the drawn contour line, extracting a skeleton of the two-dimensional contour line, selecting skeleton points and sampling points, projecting the skeleton points and the sampling points to the three-dimensional space ellipsoid curved surface, introducing a dihedral angle principle, optimizing a triangularization algorithm of the spatial discrete data points, and finally stitching the skeleton points to obtain three-dimensional mesh curved surface representation.
2. The non-contact three-dimensional matching detection method for the complex curved surface part according to claim 1, characterized in that when the datum line is measured, the measuring head moves from a point A to a point B, the measuring head moves back to a point C after the measurement of the point B, the measuring head moves to a point D according to a specified step distance, the measurement of the next point E is repeated, and during the measurement, the datum line of the complex curved surface part is drawn according to the measured data by taking an original point A as an angle fixed point.
3. The method for detecting non-contact three-dimensional matching of a complex curved surface part as claimed in claim 1, wherein in step C, the light strip width value d is searched from top to bottom row by row (column) by using the image light strip connected region divided by the threshold value, and the light strip width value is obtained as the following sequence [ d [ i-λ ，…，d i ，…d i+λ ](λ≥1，i＝k，k+1，…，k+n)。
4. The method for detecting the non-contact three-dimensional matching of the complex curved surface part according to claim 3, wherein d is the same as d k The width value of the light strip of the kth row, k is the first row of the light strip communication area, n is the total row number of the light strip communication area, and the width value d of each row i is taken as i And the upper and lower lambda row elements construct the calculation sequence [ d ] i-λ ，…，d i ，…，d i+λ ](lambda is more than or equal to 1,i =1, k +1, 8230; k + n), and the change rate psi of the width of the light stripe is calculated i The width of the light bar is defined in the form of discrete variance, and the change rate is as follows
Figure FDA0002158368430000021
Wherein: p is a radical of j Is the jth row (j is epsilon [ i-lambda, i + lambda)]) Width value d of light strip j The probability of occurrence.
5. The non-contact three-dimensional matching detection method for complex curved surface parts, according to claim 4, characterized in that p is j Probability of occurrence is p j λ = 1/(2 λ + 1), and μ is an average value of each width element of the calculated number series, and therefore, the rate of change in the optical stripe width of the i-th row is obtained as
Figure FDA0002158368430000022
Wherein the width value d of the overflow part at i =1 and i = n k-1 And d k+n+1 The treatment was performed as 0.
6. The non-contact three-dimensional matching detection method for the complex curved surface part as claimed in claim 1, wherein the constrained triangulation mesh generation utilizes a spatial topological relation of a GIS to preprocess algorithm input data, mesh refinement is realized based on a uniform data structure of triangles, a two-dimensional contour line is adopted for reference line drawing, and a two-dimensional contour line and a metasphere modeling technology are adopted, and data processing is carried out on the reference line drawing by utilizing geometric characteristics of a central axis.
7. The non-contact three-dimensional matching detection method for the complex curved surface part according to claim 1, characterized in that the length deviation of the datum line is calculated by the following formula: f = X2+ Y2-R2, performing deviation correction presetting of F = F-X + Y or F = F-Y + X according to the starting point in the quadrant and the deviation of the starting point away from the X axis or towards the X axis when starting deviation presetting or quadrant conversion in operation is performed, and performing recursion calculation on a curve operation: when X + -1: f = F ± 2 x +1, when Y ± 1: f = F ± 2+ Y +1, instead: when X + -1: f = F ± 2 x +2, when Y ± 1: f = F +/-2 + Y +2 is used for enabling the correction quantity of the reference R to be changed from 0.8 to 1.5 in one quadrant, so that the maximum deviation of the controlled point on the coordinate axis relative to the reference R is removed, tracks on two sides of the coordinate axis are symmetrical, and the whole track runs by taking the R as the center.
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