CN110458822A - A non-contact three-dimensional matching detection method for complex surface parts - Google Patents

Abstract

The invention is applicable to the technical field of curved surface parts detection, and provides a non-contact three-dimensional matching detection method for complex curved surface parts, comprising the following steps: A. Performing three-dimensional fixed-point measurement on the detected parts; B. Drawing reference lines; C. Real-time area confirmation ; D. Obtain the overall surface profile of the free-form surface sample to be measured; E. Use the grid division form to perform a three-dimensional modeling of the workpiece to be processed for the overall surface profile of the obtained surface part. Thereby, the present invention can effectively realize accurate measurement, reduce measurement error, and improve measurement accuracy.

Description

A non-contact three-dimensional matching detection method for complex surface parts

technical field

The invention relates to the technical field of curved surface parts detection, in particular to a non-contact three-dimensional matching detection method for complex curved surface parts.

Background technique

At present, there are two main methods for the detection of high-precision complex surface parts: contact measurement method and non-contact measurement method. The contact measurement uses the traditional three-coordinate measuring machine to sample the parts point by point, and the measurement accuracy is high, but the measurement efficiency of this method is low, and there are special requirements for the material of the measured parts. With the continuous development of computer vision and pattern recognition technology, non-contact measurement technology has been more and more widely used in the field of complex surface parts inspection due to its high measurement speed and accuracy.

The non-contact measurement uses an optical scanner to obtain scanning point sets of different angles, and then combines these point sets to obtain a complete part scanning point set. The error information of the part is obtained by matching and analyzing the scanning point set and the CAD model point set. In the standard detection link, the processing error is generally considered, but the influence of the measurement error on the detection result is ignored; in fact, if the error of the matching itself does not reach the ideal order of magnitude, the wrong measurement result will be obtained, especially in high In the matching detection process of precision complex surface parts, the matching error should be minimized.

To sum up, the prior art obviously has inconvenience and defects in practical use, so it is necessary to improve it.

SUMMARY OF THE INVENTION

In view of the above-mentioned defects, the purpose of the present invention is to provide a non-contact three-dimensional matching detection method for complex curved surface parts, which can reduce the measurement error and improve the measurement accuracy.

In order to achieve the above purpose, the present invention provides a non-contact three-dimensional matching detection method for complex curved surface parts, comprising the following steps:

A. Three-dimensional fixed-point measurement of the detected parts:

First, measure the position of the reference line by the point measurement method, select and fix the section of the surface part to be measured during the measurement process, and then move it one by one on the same axis to measure the reference line. After the measurement is completed, move the specified distance on the vertical axis. Make successive movement measurements on another section to form the basic outline of the reference line;

B. Baseline drawing:

Draw the basic outline of the reference line formed in step A through the drawing software, and set the corresponding point distance. After the point distance is set, the surface of the part to be measured is scanned at a constant speed by the scanning instrument, and a complete light is formed during the scanning process. bar real-time area;

C. Real-time area confirmation:

Define the ith light strip image in the sequence light strip images {f'(x, y, t ₀ ), f'(x, y, t ₁ ), ..., f'(x, y, t _n-1 )} The position state of the light bar is X ⁱ , the light bar position relationship of adjacent light bar images is expressed by the following formula X ⁱ⁺¹ =X ⁱ +dω/f, i=0,1,2,...,n, where The minimum component in the horizontal direction of the light bar passing area after thresholding the image, is the maximum component, d is the average measurement distance from the scanning instrument to the surface of the part to be measured, ω 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 the displacement data measured by the laser interferometer, and the three-dimensional topography data of the free-form surface sample {D11(x, y, z), D12 (x, y, z), ..., D12(x, y, z), Dij(x, y, z), ..., DMN(x, y, z)} fitting, to obtain the whole of the measured free-form surface sample face contour;

E. On the basis of the baseline drawing in step B, the overall surface contour of the obtained surface part is divided into meshes to carry out a three-dimensional modeling of the workpiece to be processed, and a constrained triangular mesh is carried out according to the distribution of the feature points of the drawn contour. Divide, extract the skeleton of the 2D contour line, select the skeleton points and sampling points to project onto the 3D space ellipsoid surface, and introduce the dihedral angle principle to optimize the triangulation algorithm of discrete data points in space, and finally stitch the skeleton points to obtain a 3D mesh Surface representation.

According to the non-contact three-dimensional matching detection method of complex curved surface parts of the present invention, when the reference line is measured, the probe moves from point A to point B, returns to point C after measuring point B, and then moves to point D according to the specified step distance. Point, repeat the measurement of the next point E, during the measurement process, take the origin A as the angle fixed point, and draw the reference line of the surface part according to the measured data.

According to the non-contact three-dimensional matching detection method of complex curved surface parts of the present invention, in the step C, the connected area of the image light stripe segmented by the threshold is used to search the light stripe width value d row by row (column) from top to bottom to obtain the light stripe width value d. The bar width value sequence is as follows [d _i-λ ,...,d _i ,...,di _+λ ](λ≥1, i=k, k+1,...,k+n).

According to the non-contact three-dimensional matching detection method of complex curved surface parts of the present invention, the d _k is the light bar width value of the kth row, k is the first line of the light bar connected area, n is the total number of lines of the light bar connected area, and each The width value d _i of row i and its upper and lower λ row elements construct the calculation sequence [d _i-λ ,...,d _i ,...,di _+λ ](λ≥1,i=k,k+1,..., k+n), calculate the light bar width change rate ψ _i , define the light bar width in the form of discrete variance, and the change rate is as follows

Where: p _j is the probability of occurrence of the light bar width value d _j in the jth row (j∈[i-λ, i+λ]).

According to the non-contact three-dimensional matching detection method of complex curved surface parts of the present invention, the probability of the occurrence of p _j is p _j =1/(2λ+1), take λ=1, and μ is the average value of each width element of the calculation sequence , therefore, the change rate of the light bar width of the i-th row is obtained

Wherein, the width values d _k-1 and d _k+n+1 of the overflow portion at i=1 and i=n are processed as 0.

According to the non-contact three-dimensional matching detection method of complex curved surface parts of the present invention, the constrained triangular mesh division utilizes the spatial topology relationship of GIS to preprocess the input data of the algorithm, and realizes mesh refinement based on the unified data structure of triangles. , the reference line is drawn by two-dimensional contour line based on two-dimensional contour line and meta-sphere modeling technology, and the data processing is carried out by using the geometric characteristics of the central axis.

According to the non-contact three-dimensional matching detection method of complex curved surface parts of the present invention, the length deviation formula of the reference line: F=X2+Y2-R2, when the starting deviation is preset or the quadrant is changed during operation, according to the quadrant of the starting point and the direction is Carry out the deviation correction preset of F=F-X+Y or F=F-Y+X away from the X-axis or toward the X-axis, and the recursive calculation formula in the curve operation: when X±1: F=F±2 *X+1, when Y±1: F=F±2*Y+1, change to: when X±1: F=F±2*X+2, when Y±1: F=F± 2*Y+2, to make the correction amount to the reference R change from 0.8 to 0.6 to 1.5 in one quadrant, to remove the maximum deviation of the controlled point relative to the reference R on the coordinate axis, so that the two sides of the coordinate axis are removed. The trajectory is symmetrical, and the entire trajectory runs with R as the center.

The invention provides a non-contact three-dimensional matching detection method for complex curved surface parts, comprising the following steps:

A. Three-dimensional fixed-point measurement of the detected parts:

First, measure the position of the reference line by the point measurement method, select and fix the section of the surface part to be measured during the measurement process, and then move it one by one on the same axis to measure the reference line. After the measurement is completed, move the specified distance on the vertical axis. Make successive movement measurements on another section to form the basic outline of the reference line;

B. Baseline drawing:

Draw the basic outline of the reference line formed in step A through the drawing software, and set the corresponding point distance. After the point distance is set, the surface of the part to be measured is scanned at a constant speed by the scanning instrument, and a complete light is formed during the scanning process. bar real-time area;

C. Real-time area confirmation:

Define the ith light strip image in the sequence light strip images {f'(x, y, t ₀ ), f'(x, y, t ₁ ), ..., f'(x, y, t _n-1 )} The position state of the light bar is X ⁱ , the light bar position relationship of adjacent light bar images is expressed by the following formula X ⁱ⁺¹ =X ⁱ +dω/f, i=0,1,2,...,n, where The minimum component in the horizontal direction of the light bar passing area after thresholding the image, is the maximum component, d is the average measurement distance from the scanning instrument to the surface of the part to be measured, ω 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 the displacement data measured by the laser interferometer, and the three-dimensional topography data of the free-form surface sample {D11(x, y, z), D12 (x, y, z), ..., D12(x, y, z), Dij(x, y, z), ..., DMN(x, y, z)} fitting, to obtain the whole of the measured free-form surface sample face contour;

E. On the basis of the baseline drawing in step B, the overall surface contour of the obtained surface part is divided into meshes to carry out a three-dimensional modeling of the workpiece to be processed, and a constrained triangular mesh is carried out according to the distribution of the feature points of the drawn contour. Divide, extract the skeleton of the 2D contour line, select the skeleton points and sampling points to project onto the 3D space ellipsoid surface, and introduce the dihedral angle principle to optimize the triangulation algorithm of discrete data points in space, and finally stitch the skeleton points to obtain a 3D mesh Surface representation.

Beneficial effects of the invention: by designing the three-dimensional matching detection process of complex curved surface parts, the characteristics of fast convergence speed, good robustness and not easy to fall into local optimum can be fully utilized, and the test shows that high-precision and high-efficiency three-dimensional matching can be obtained. As a result, the non-contact measurement is adopted without damaging the processing surface of the component, and the image can be used to determine whether the processing is qualified or not, which can be used as an effective means for online rapid and batch inspection.

Detailed ways

In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be described in further detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not intended to limit the present invention. .

The invention provides a non-contact three-dimensional matching detection method for complex curved surface parts, comprising the following steps:

A. Three-dimensional fixed-point measurement of the detected parts:

First, measure the position of the reference line by the point measurement method, select and fix the section of the surface part to be measured during the measurement process, and then move it one by one on the same axis to measure the reference line. After the measurement is completed, move the specified distance on the vertical axis. Make successive movement measurements on another section to form the basic outline of the reference line;

B. Baseline drawing:

Draw the basic outline of the reference line formed in step A through the drawing software, and set the corresponding point distance. After the point distance is set, the surface of the part to be measured is scanned at a constant speed by the scanning instrument, and a complete light is formed during the scanning process. bar real-time area;

C. Real-time area confirmation:

Define the ith light strip image in the sequence light strip images {f'(x, y, t ₀ ), f'(x, y, t ₁ ), ..., f'(x, y, t _n-1 )} The position state of the light bar is X ⁱ , the light bar position relationship of adjacent light bar images is expressed by the following formula X ⁱ⁺¹ =X ⁱ +dω/f, i=0,1,2,...,n, where The minimum component in the horizontal direction of the light bar passing area after thresholding the image, is the maximum component, d is the average measurement distance from the scanning instrument to the surface of the part to be measured, ω 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 the displacement data measured by the laser interferometer, and the three-dimensional topography data of the free-form surface sample {D11(x, y, z), D12 (x, y, z), ..., D12(x, y, z), Dij(x, y, z), ..., DMN(x, y, z)} fitting, to obtain the whole of the measured free-form surface sample face contour;

E. On the basis of the baseline drawing in step B, the overall surface contour of the obtained surface part is divided into meshes to carry out a three-dimensional modeling of the workpiece to be processed, and a constrained triangular mesh is carried out according to the distribution of the feature points of the drawn contour. Divide, extract the skeleton of the 2D contour line, select the skeleton points and sampling points to project onto the 3D space ellipsoid surface, and introduce the dihedral angle principle to optimize the triangulation algorithm of discrete data points in space, and finally stitch the skeleton points to obtain a 3D mesh Surface representation.

Preferably, when measuring the reference line of the present invention, the probe moves from point A to point B, returns to point C after measuring at point B, and then moves to point D according to the specified step distance, repeats the measurement of the next point E, and measures In the process, the origin A is used as the angle fixed point, according to the measured data, the reference line of the surface part is drawn, and the effective point distance measurement of the reference line can be realized by moving multiple times based on the origin, which further improves the measurement accuracy.

In addition, the constrained triangular mesh division of the present invention utilizes the spatial topology relationship of GIS to preprocess the input data of the algorithm, realizes mesh refinement based on the unified data structure of triangles, and uses two-dimensional contour lines to draw the baseline based on two-dimensional The contour line and meta-sphere modeling technology uses the geometric characteristics of the central axis to process the data, and uses the constrained triangular mesh and the two-dimensional contour line and meta-sphere modeling technology to effectively measure the geometric line distance, so as to ensure the subsequent measurement process. accuracy in .

Further, in step C of the present invention, the connected area of the image light bar divided by the threshold is used to search the light bar width value d row by row (column) from top to bottom, and the sequence of light bar width values is obtained as follows [d _{i- λ} , ..., d _i , ... d _i+λ ] (λ≥1, i=k, k+1, ..., k+n), through the threshold segmentation method, the surface of the curved part is segmented and measured to ensure the accuracy of its subsequent measurements.

Preferably, the calculation formula of the length deviation of the reference line of the present invention: F=X2+Y2-R2, when the starting deviation is preset or the quadrant is changed during operation, F= is performed according to the quadrant where the starting point is located and the direction is away from the X-axis or toward the X-axis. The deviation correction preset of F-X+Y or F=F-Y+X, and the recursive calculation formula in the curve operation: when X±1: F=F±2*X+1, when Y±1 : F=F±2*Y+1, change to: when X±1: F=F±2*X+2, when Y±1: F=F±2*Y+2, to make the pair The correction amount of the reference R is changed from 0.8 to 0.6 to 1.5 in one quadrant, to remove the maximum deviation of the controlled point on the coordinate axis from the reference R, so that the trajectory on both sides of the coordinate axis is symmetrical, and the entire trajectory is centered on R Run, use the length deviation formula to effectively interpolate the position and point distance of the reference line, thereby ensuring the accuracy after measurement and improving the final drawing accuracy.

The invention provides a non-contact three-dimensional matching detection method for complex curved surface parts, comprising the following steps:

A. Three-dimensional fixed-point measurement of the detected parts:

First, measure the position of the reference line by the point measurement method, select and fix the section of the surface part to be measured during the measurement process, and then move it one by one on the same axis to measure the reference line. After the measurement is completed, move the specified distance on the vertical axis. Make successive movement measurements on another section to form the basic outline of the reference line;

B. Baseline drawing:

Draw the basic outline of the reference line formed in step A through the drawing software, and set the corresponding point distance. After the point distance is set, the surface of the part to be measured is scanned at a constant speed by the scanning instrument, and a complete light is formed during the scanning process. bar real-time area;

C. Real-time area confirmation:

Define the ith light strip image in the sequence light strip images {f'(x, y, t ₀ ), f'(x, y, t ₁ ), ..., f'(x, y, t _n-1 )} The position state of the light bar is X ⁱ , the light bar position relationship of adjacent light bar images is expressed by the following formula X ⁱ⁺¹ =X ⁱ +dω/f, i=0,1,2,...,n, where The minimum component in the horizontal direction of the light bar passing area after thresholding the image, is the maximum component, d is the average measurement distance from the scanning instrument to the surface of the part to be measured, ω 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 the displacement data measured by the laser interferometer, and the three-dimensional topography data of the free-form surface sample {D11(x, y, z), D12 (x, y, z), ..., D12(x, y, z), Dij(x, y, z), ..., DMN(x, y, z)} fitting, to obtain the whole of the measured free-form surface sample face contour;

E. On the basis of the baseline drawing in step B, the overall surface contour of the obtained surface part is divided into meshes to carry out a three-dimensional modeling of the workpiece to be processed, and a constrained triangular mesh is carried out according to the distribution of the feature points of the drawn contour. Divide, extract the skeleton of the 2D contour line, select the skeleton points and sampling points to project onto the 3D space ellipsoid surface, and introduce the dihedral angle principle to optimize the triangulation algorithm of discrete data points in space, and finally stitch the skeleton points to obtain a 3D mesh Surface representation.

When measuring the reference line, the probe moves from point A to point B, returns to point C after measuring at point B, and then moves to point D according to the specified step distance, and repeats the measurement of the next point E. During the measurement process, take the origin point. A is the fixed point of the angle, according to the measured data, draw the reference line of the surface part. In the step C, the connected area of the image light stripe segmented by the threshold is used to search for the light stripe width value d row by row (column) from top to bottom, and the number sequence of the light stripe width value is obtained as follows [d _i-λ , . . . , d _i ,...d _i+λ ] (λ≥1, i=k, k+1,...,k+n). The d _k is the light bar width value of the kth row, k is the first line of the light bar connected area, n is the total number of lines of the light bar connected area, and is constructed by the width value d _i of each line i and its upper and lower λ line elements. Calculate the sequence [d _{i- λ , .} Define the width of the light bar in the form of discrete variance, the rate of change is as follows

Where: p _j is the probability of occurrence of the light bar width value d _j in the jth row (j∈[i-λ, i+λ]).

The probability of the occurrence of p _j is p _j =1/(2λ+1), take λ = 1, and μ is the average value of each width element of the calculation sequence, therefore, the change rate of the light bar width in the i-th row is obtained.

Wherein, the width values d _k-1 and d _k+n+1 of the overflow portion at i=1 and i=n are processed as 0.

Constrained triangular meshing uses the spatial topological relationship of GIS to preprocess the input data of the algorithm, and realizes grid refinement based on the unified data structure of triangles. Modeling technology, using the geometric characteristics of the central axis to process data. The formula for the length deviation of the reference line: F=X2+Y2-R2, when the starting deviation is preset or the quadrant is changed during operation, according to the quadrant where the starting point is located and the direction is to leave the X-axis or toward the X-axis, perform F=F-X+Y or F =F-Y+X deviation correction preset, and recursive calculation formula in curve operation: when X±1: F=F±2*X+1, when Y±1: F=F±2* Y+1, change to: when X±1: F=F±2*X+2, when Y±1: F=F±2*Y+2, in order to make the correction amount to the reference R within one In the quadrant, the change from 0.8 to 0.6 to 1.5 is realized, and the maximum deviation of the controlled point on the coordinate axis relative to the reference R is removed, so that the trajectory on both sides of the coordinate axis is symmetrical, and the entire trajectory runs with R as the center.

To sum up, the present invention provides a non-contact three-dimensional matching detection method for complex curved surface parts, which includes the following steps:

A. Three-dimensional fixed-point measurement of the detected parts:

First, measure the position of the reference line by the point measurement method, select and fix the section of the surface part to be measured during the measurement process, and then move it one by one on the same axis to measure the reference line. After the measurement is completed, move the specified distance on the vertical axis. Make successive movement measurements on another section to form the basic outline of the reference line;

B. Baseline drawing:

Draw the basic outline of the reference line formed in step A through the drawing software, and set the corresponding point distance. After the point distance is set, the surface of the part to be measured is scanned at a constant speed by the scanning instrument, and a complete light is formed during the scanning process. bar real-time area;

C. Real-time area confirmation:

Define the ith light strip image in the sequence light strip images {f'(x, y, t ₀ ), f'(x, y, t ₁ ), ..., f'(x, y, t _n-1 )} The position state of the light bar is X ⁱ , the light bar position relationship of adjacent light bar images is expressed by the following formula X ⁱ⁺¹ =X ⁱ +dω/f, i=0,1,2,...,n, where The minimum component in the horizontal direction of the light bar passing area after thresholding the image, is the maximum component, d is the average measurement distance from the scanning instrument to the surface of the part to be measured, ω 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 the displacement data measured by the laser interferometer, and the three-dimensional topography data of the free-form surface sample {D11(x, y, z), D12 (x, y, z), ..., D12(x, y, z), Dij(x, y, z), ..., DMN(x, y, z)} fitting, to obtain the whole of the measured free-form surface sample face contour;

E. On the basis of the baseline drawing in step B, the overall surface contour of the obtained surface part is divided into meshes to carry out a three-dimensional modeling of the workpiece to be processed, and a constrained triangular mesh is carried out according to the distribution of the feature points of the drawn contour. Divide, extract the skeleton of the 2D contour line, select the skeleton points and sampling points to project onto the 3D space ellipsoid surface, and introduce the dihedral angle principle to optimize the triangulation algorithm of discrete data points in space, and finally stitch the skeleton points to obtain a 3D mesh Surface representation.

Beneficial effects of the invention: by designing the three-dimensional matching detection process of complex curved surface parts, the characteristics of fast convergence speed, good robustness and not easy to fall into local optimum can be fully utilized, and the test shows that high-precision and high-efficiency three-dimensional matching can be obtained. As a result, the non-contact measurement is adopted without damaging the processing surface of the component, and the image can be used to determine whether the processing is qualified or not, which can be used as an effective means for online rapid and batch inspection.

Of course, the present invention can also have other various embodiments, without departing from the spirit and essence of the present invention, those skilled in the art can make various corresponding changes and modifications according to the present invention, but these corresponding Changes and deformations should belong to the protection scope of the appended claims of the present invention.

Claims (7)

1. a non-contact three-dimensional matching detection method for complex curved surface parts, is characterized in that, comprises the following steps: A. Three-dimensional fixed-point measurement of the detected parts: First, measure the position of the reference line by the point measurement method, select and fix the section of the surface part to be measured during the measurement process, and then move it one by one on the same axis to measure the reference line. After the measurement is completed, move the specified distance on the vertical axis. Make successive movement measurements on another section to form the basic outline of the reference line; B. Baseline drawing: Draw the basic outline of the reference line formed in step A through the drawing software, and set the corresponding point distance. After the point distance is set, the surface of the part to be measured is scanned at a constant speed by the scanning instrument, and a complete light is formed during the scanning process. bar real-time area; C. Real-time area confirmation: Define the ith light strip image in the sequence light strip images {f'(x, y, t ₀ ), f'(x, y, t ₁ ), ..., f'(x, y, t _n-1 )} The position state of the light bar is X ⁱ , the light bar position relationship of adjacent light bar images is expressed by the following formula X ⁱ⁺¹ =X ⁱ +dω/f, i=0,1,2,...,n, where The minimum component in the horizontal direction of the light bar passing area after thresholding the image, is the maximum component, d is the average measurement distance from the scanning instrument to the surface of the part to be measured, ω 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 the displacement data measured by the laser interferometer, and the three-dimensional topography data of the free-form surface sample {D11(x, y, z), D12 (x, y, z), ..., D12(x, y, z), Dij(x, y, z), ..., DMN(x, y, z)} fit, get the measured freedom The overall surface profile of the curved sample; E. On the basis of the baseline drawing in step B, the overall surface contour of the obtained surface part is divided into meshes to carry out a three-dimensional modeling of the workpiece to be processed, and a constrained triangular mesh is carried out according to the distribution of the feature points of the drawn contour. Divide, extract the skeleton of the 2D contour line, select the skeleton points and sampling points to project onto the 3D space ellipsoid surface, and introduce the dihedral angle principle to optimize the triangulation algorithm of discrete data points in space, and finally stitch the skeleton points to obtain a 3D mesh Surface representation. 2. The non-contact three-dimensional matching detection method for complex curved surface parts according to claim 1, characterized in that, when the reference line is measured, the probe moves from point A to point B, and returns to point C after measuring at point B Point, and then according to the specified step distance to point D, repeat the measurement of the next point E, during the measurement process, take the origin A as the angle fixed point, according to the measured data, draw the surface part reference line. 3. The non-contact three-dimensional matching detection method for complex curved surface parts according to claim 1, characterized in that, in the step C, the connected region of the image light stripe segmented by the threshold is used, row by row (column) from top to bottom Search the light bar width value d, and get the light bar width value sequence as follows [d _i-λ ,...,d _i ,...d _i+λ ](λ≥1, i=k, k+1,...,k+ n). 4. The non-contact three-dimensional matching detection method for complex curved surface parts according to claim 3, wherein the d _k is the light bar width value of the kth row, k is the first row of the connected area of the light bar, and n is the light bar width value. The total number of rows in the connected region of the strip, the calculation sequence [d _i-λ , ..., d _i , ..., d _{i +λ} ] (λ≥1, i = _k , k+1, . Where: p _j is the probability of occurrence of the light bar width value d _j in the jth row (j∈[i-λ, i+λ]). 5. The non-contact three-dimensional matching detection method for complex curved surface parts according to claim 4, wherein the probability of the occurrence of p _j is p _j =1/(2λ+1), taking λ=1, and μ is This calculates the average value of each width element of the sequence, therefore, the change rate of the width of the light bar in the i-th row is obtained Wherein, the width values d _k-1 and d _k+n+1 of the overflow portion at i=1 and i=n are processed as 0. 6. The non-contact three-dimensional matching detection method for complex surface parts according to claim 1, wherein the constrained triangular mesh division utilizes the spatial topology relationship of GIS to preprocess the input data of the algorithm, based on triangular The unified data structure of the grid is used to refine the grid, and the reference line is drawn using two-dimensional contour lines based on two-dimensional contour lines and metaball modeling technology, and the geometric characteristics of the central axis are used for data processing. 7 . The non-contact three-dimensional matching detection method for complex curved surface parts according to claim 1 , wherein the length deviation formula of the reference line is: F=X2+Y2-R2, and the starting deviation is preset or the quadrant during operation. 8 . During the transformation, according to the quadrant of the starting point and whether the direction is away from the X-axis or towards the X-axis, the deviation correction preset of F=F-X+Y or F=F-Y+X, and the recursive calculation formula in the curve operation: when X When ±1: F＝F±2*X+1, when Y±1: F＝F±2*Y+1, change to: when X±1: F＝F±2*X+2, when When Y±1: F=F±2*Y+2, in order to make the correction to the reference R change from 0.8 to 0.6 to 1.5 in one quadrant, so as to remove the relative reference R of the controlled point on the coordinate axis The maximum deviation of , makes the trajectory on both sides of the coordinate axis symmetrical, and the entire trajectory runs with R as the center.