Impeller probe trajectory planning method based on visual cone discretization

Abstract

The impeller probe trajectory planning method based on visual cone discretization comprises the following steps: two-dimensional projection of the three-dimensional model of the impeller; coloring of the two-dimensional model of the impeller; obtaining each measuring point reachable cone by occlusion query and one-dimension, and the one-dimensional vector set is recorded as a single point reachable cone vector group; grouping of the measuring points to obtain a continuous measuring point group and a single measuring point group; in-group path planning; inter-group path planning; path export; and completion of the impeller probe trajectory planning. The method has high work efficiency, reduces the calculation amount, and has similar turning angles and translational distances of the overall trajectory to global planning, and is good in adaptability.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of in-machine measurement of numerical control machine tools, and particularly relates to a blade head trajectory planning method based on visual cone discretization. BACKGROUND

[0002] The application field of numerical control machine tools is also more and more extensive. At present, it is involved in the use in a series of high-precision manufacturing fields such as equipment manufacturing, automobiles, aerospace, energy, medical devices and the like.

[0003] Three-coordinate measurement is widely used due to its high precision and high universality, but in the machining of precision parts, three-coordinate measurement is offline measurement, and the installation error introduced thereby is difficult to eliminate. In this background, in-machine measurement (OMM) technology begins to be applied to numerical control machine tools. At present, in-machine measurement technology has been widely applied to the machining and detection of various numerical control machine tools. The whole blade and its blade belong to thin-walled complex curved surfaces, and the machining difficulty is high, and the cost is high, and it is usually machined on a five-axis numerical control machine tool. In the blade machining process, the use of in-machine measurement technology can reduce the installation error and improve the blade precision.

[0004] Due to the complex surface characteristics of the blade, the measurement point trajectory of the complex curved surface of the blade has a great influence on the measurement efficiency and measurement precision, and further influences the machining precision of the whole blade and its blade. At present, the distribution of the blade measurement points and the trajectory planning of the probe mainly rely on the experience of the machinists, and the efficiency is low and lacks universality, and these problems are urgent to be solved. SUMMARY

[0005] The application is provided to overcome the deficiencies of the prior art, and provides a blade probe trajectory planning method based on visual cone discretization. The method completes the grouping of the measurement points according to the one-dimensional vector group discretized from the reachable cone at the selected measurement points, completes the selection of the probe direction at each measurement point in and between the groups by the rotation angle and the translation distance of the probe, connects the probe directions at each measurement point, realizes the measurement point grouping trajectory planning of the blade, and has good universality.

[0006] The blade probe trajectory planning method based on visual cone discretization comprises the following steps:

[0007] S1: two-dimensional projection of a three-dimensional model of a blade;

[0008] S2: coloring of a two-dimensional model of a blade;

[0009] S3: obtain the reachable cone of each measurement point by occlusion query and one-dimension, and the one-dimensional vector set is recorded as a single-point reachable cone vector group;

[0010] S4: measurement point grouping, to obtain a continuous measurement point group and a single measurement point group;

[0011] S5: intra-group path planning;

[0012] S6: inter-group path planning, path derivation, complete impeller probe trajectory planning.

[0013] Further, the specific content of step S1 is that, first, the model is converted from a local space to a three-dimensional space through model matrix transformation;

[0014] Secondly, the model is converted from the three-dimensional space to the perspective of the camera through rotation and translation by using an observation matrix according to the direction of the camera observation, to generate an observation space;

[0015] Then, a perspective projection matrix is adopted to select a suitable range in each dimension, and the observation space is cropped to a cropped space within the standardized device coordinate range.

[0016] Finally, the model coordinate system is set to the coordinate range defined in advance through a viewport transformation, to generate a screen space and complete the projection conversion of the coordinate system.

[0017] Further, the specific content of step S4 is that: the intersection of the one-dimensional vector sets of the reachable cones of two adjacent measuring points is sequentially calculated, if the intersection of the two measuring points is not a zero vector, the two measuring points are connected as a group, and the intersection is sequentially calculated downward until the intersection with the next measuring point is a zero vector, and the above continuously connected measuring points are a group, which is recorded as a continuous measuring point group; if the intersection of a single point with the previous and next two measuring points is a zero vector, the single point is grouped, which is recorded as a single measuring point group, and the grouping of all measuring points is sequentially completed.

[0018] Further, the specific content of step S6 is that: starting from the first group, for the next group being a continuous measuring point group, the last measuring point of the current group and the first measuring point of the next group are selected, and the inter-group path planning calculation is completed through a path smoothing algorithm, minimum moving time optimization and minimum turning angle optimization algorithm; for the next group or several groups being single measuring point groups, the last measuring point of the current group, the measuring points contained in the single measuring point groups of the next several groups and the first measuring point of the first continuous measuring point group downward are selected, and the inter-group path planning calculation is completed through the path smoothing algorithm, the minimum moving time optimization and the minimum turning angle optimization algorithm, so as to sequentially complete the inter-group path planning calculation.

[0019] The beneficial effects of the present application compared with the prior art are:

[0020] The present application expresses the probe direction at each measuring point by using the reachable cone, and discretizes the reachable cone into a one-dimensional vector by using the triangular meshing method, so that the subsequent trajectory planning is facilitated and the work efficiency is high.

[0021] The one-dimensional vector is used to complete the grouping of the measuring points, and the local trajectory planning combining the groups and the inter-groups can greatly reduce the calculation amount compared with the traditional global trajectory planning. Moreover, due to the continuity of the measuring points, the turning angle and the translational distance of the overall trajectory are similar to those of the global planning, and the adaptability is good.

[0022] The technical solutions of the present application will be further described below in combination with the drawings and embodiments. BRIEF DESCRIPTION OF DRAWINGS

[0023] Figure 1 A process diagram for impeller accessibility detection;

[0024] Figure 2 A diagram of an accessible cone;

[0025] Figure 3 A process diagram for converting three-dimensional coordinates of an impeller model into screen coordinates;

[0026] Figure 4 A process diagram for graphic rendering pipeline processing;

[0027] Figure 5 A single-point accessible cone diagram;

[0028] Figure 6 An octahedron triangulation diagram;

[0029] Figure 7 An accessible vector set diagram;

[0030] Figure 8 An example diagram for measuring point grouping. DETAILED DESCRIPTION

[0031] The embodiments of the technical solutions of the present application will be described in detail below in combination with the drawings. Unless otherwise specified, the technical terms or scientific terms used in this application should be understood as the usual meanings understood by those skilled in the art to which the present application belongs.

[0032] The impeller probe trajectory planning method based on visual cone discretization comprises the following steps:

[0033] S1: Two-dimensional projection of the three-dimensional model of the impeller;

[0034] S2: Coloring of the two-dimensional model of the impeller;

[0035] S3: Obtain the accessible cone of each measuring point by occlusion query and one-dimensionalization, and the one-dimensional vector set is denoted as the single-point accessible cone vector group;

[0036] S4: Grouping of measuring points, obtaining continuous measuring point groups and single measuring point groups;

[0037] S5: In-group path planning;

[0038] S6: Inter-group path planning, path derivation, and completion of impeller probe trajectory planning.

[0039] Analysis of the above-mentioned implementation solutions of visual cones and accessible cones:

[0040] The accessible posture of the measuring rod in the process of blade surface detection is as follows Figure 1As shown, the probe starts from the initial point q t Along the measurement point p t surface normal vector v t The probe is detected in the opposite direction, and the probe direction vector is... To ensure the line segment during blade inspection Take office a little bit p λ The probe at the location does not interfere with or collide with the impeller model S.

[0041] In three-dimensional space, the measuring rod revolves around the point p to be measured. t The direction vector of the measuring rod can be changed arbitrarily. This results in an infinite number of possible directions for the measuring rod's direction vector. The set of all measuring rod direction vectors forms a sphere S. 2 The unit sphere is considered to be a Gaussian sphere. At the point p to be measured... t At a given location, the mapping relationship of the direction vectors reachable by the measuring rod is called the Gaussian mapping, and the set formed by these direction vectors is called the reachability cone, the result of which is as follows: Figure 2 As shown.

[0042] During the detection process of impeller measuring points, the following reachable cones are defined: the single-point reachable cone of the impeller, and the set of direction vectors that the probe can contact the impeller measuring points.

[0043] Furthermore, in S1, the three-dimensional model of the impeller is projected into two dimensions. First, the model is transformed from local space to three-dimensional space through model matrix transformation.

[0044] Secondly, according to the direction of the camera's observation, the model is transformed from three-dimensional space to the camera's viewpoint through rotation and translation using the observation matrix, thus generating the observation space;

[0045] Then, using a perspective projection matrix, a suitable range is selected in each dimension to clip the observation space into a clipping space with a standardized device coordinate range;

[0046] Finally, by transforming the viewport, the model coordinate system is set to a pre-defined coordinate range, generating screen space and completing the projection transformation of the coordinate system.

[0047] The specific process of 2D model projection is as follows: Figure 3 As shown.

[0048] Furthermore, the specific content of step S2 is as follows:

[0049] After the 3D model is pixelated into 2D pixels using the vertex shading, primitive assembly, and geometry shading processes in the OpenGL graphics rendering pipeline, 2D shading and rendering are completed using the fragment shader. Specific operations are as follows: Figure 4 As shown.

[0050] Further, the specific content of step S3 is: for each measuring point, rendering the probe rod and the probe barrel model respectively, judging whether there is an occlusion relationship with the impeller model at different viewing angles through the occlusion query of OpenGL, and the specific steps of the occlusion query of OpenGL are as follows:

[0051] (1) calling glGenQueries(), generating query object IDs for the impeller, the probe rod and the probe barrel model respectively;

[0052] (2) rendering the obstacle impeller model;

[0053] (3) calling glBeginQuery(), starting the occlusion query;

[0054] (4) rendering the probe rod and the probe barrel model;

[0055] (5) calling glEndQuery(), ending the occlusion query;

[0056] (6) calling glGetQueryObjectiv(), extracting the result of the occlusion query according to the ID;

[0057] (7) calling glDeleteQueries(), deleting the ID and recycling the resource.

[0058] The occlusion query calculates the fully reachable cone range of the probe rod and the probe barrel at the measuring point on the blade, and obtains the intersection range of the two, and finally obtains the single-point reachable cone, as shown in Figure 5 ; then through the octahedron triangulation method, as shown in Figure 6 , the reachable cone is discretized into a one-dimensional vector set with a dimension of 1026, the reachable direction is the direction vector, and the unreachable direction is the zero vector, and the one-dimensional vector set is recorded as the single-point reachable cone vector group, as shown in Figure 7 .

[0059] Further, the specific content of step S4 is: sequentially intersecting the one-dimensional vector sets of the reachable cones of adjacent two measuring points, if the intersection of the two measuring points is not a zero vector, then connecting the two measuring points as a group, sequentially intersecting down to the zero vector of the intersection with the next measuring point, and the above continuously connected measuring points are a group, recorded as a continuous measuring point group; if the single point intersects with the front and rear two measuring points to be zero vectors, then the single point is grouped, recorded as a single measuring point group, and the grouping of all measuring points is sequentially completed. The grouping is shown in Figure 8 .

[0060] Based on the above implementation scheme,

[0061] The specific content of step S5 of the group path planning is:

[0062] For single measurement point group, no planning is made; for continuous measurement point group, the minimum moving time optimization and minimum angle optimization algorithm is used, that is:

[0063] min∑(t1,t2,...,t n ), minΣ(θ1,θ2,...,θ n )

[0064] In which t is the ratio of the distance between the two measurement points and the moving speed of the probe, and θ is the angle between the two measurement point vectors, and the path planning calculation in the group is completed.

[0065] In which the minimum moving time optimization and minimum angle optimization algorithm is to sequentially extract non-zero vectors from the single point reachable cone vector group of each measurement point in the selected measurement point group, calculate the sum of the vector rotation angle and the sum of the vector translation time between the measurement points, set the weight ratio to add the sum of the rotation angle and the sum of the translation distance, and record it as the group planning value In.

[0066] In = Ina x min∑(t1,t2,...,t n )+Inb x min∑(θ1,θ2,...,θ n )

[0067] In which Ina and Inb are normalization parameters, and the sum of the two is equal to 1, and the vector of each measurement point corresponding to the minimum group planning value In is the planning vector of the group probe path.

[0068] Based on the above implementation scheme,

[0069] The specific content of the inter-group path planning of step S6 is:

[0070] Starting from the first group, for the next group being a continuous measurement point group, the last measurement point of the current group and the first measurement point of the next group are selected, and the path smoothing algorithm, the minimum moving time optimization and the minimum angle optimization algorithm are used to complete the inter-group path planning calculation; for the next group or the next few groups being single measurement point groups, the last measurement point of the current group, the measurement points contained in the next few single measurement point groups and the first measurement point of the first continuous measurement point group are selected, and the path smoothing algorithm, the minimum moving time optimization and the minimum angle optimization algorithm are used to complete the inter-group path planning calculation, so as to sequentially complete the inter-group path planning calculation.

[0071] In which the minimum moving time optimization and minimum angle optimization algorithm is consistent with the calculation of the group planning value in step S5, and the smoothing algorithm is to add a transition measurement point vector v n+0.5 =(v n +v n+1 ) / 2 to the planning vector obtained by the minimum moving time optimization and minimum angle optimization algorithm for adjacent measurement points with an angle rotation of more than 15°, in which v nThe vector value of n measuring points is measured, and the obtained vector of each point is the planning vector of the path of the measuring head between groups. The trajectory planning of the impeller measuring head is completed.

[0072] Finally, the paths between groups and within groups are spliced and verified for integrity, and the path is derived as NC code, so that the NC code can be run in the machine tool to complete the in-machine measurement of the blade.

[0073] The present application has been disclosed in the preferred embodiments as above, however, is not intended to limit the present application, any skilled person in the art, without departing from the technical solution range of the present application, can make some changes or modifications to the above disclosed structure and technical content for equivalent embodiments of equivalent changes, which still belong to the technical solution range of the present application.

Claims

1. A method for planning the trajectory of an impeller probe based on visual cone discretization, characterized in that: The method includes the following steps: S1: Two-dimensional projection of the three-dimensional model of the impeller; S2: Coloring of the two-dimensional impeller model; S3: Obstruction query obtains the reachable cones of each measuring point and transforms them into one dimension. The one-dimensional vector set is denoted as the single-point reachable cone vector group. For each measurement point, the probe rod and probe cylinder models are rendered separately. Using OpenGL occlusion lookup, the presence of occlusion with the impeller model is determined from different perspectives. The occlusion lookup calculates the fully reachable cone range of the probe rod and probe cylinder at the measurement point on the blade, and calculates the range of their intersection. Finally, the single-point reachable cone is obtained. Then, using the regular octahedral triangulation method, the reachable cone is discretized into a one-dimensional vector set with dimension 1026. The reachable direction is the vector of that direction, and the unreachable direction is the zero vector. The one-dimensional vector set is denoted as the single-point reachable cone vector set. The specific steps for OpenGL occlusion lookup are as follows: (1) Call glGenQueries() to generate query object IDs for the impeller, probe rod and probe cylinder models respectively; (2) Render the obstacle impeller model; (3) Call glBeginQuery() to begin the occlusion query; (4) Render the probe rod and probe cylinder models; (5) Call glEndQuery() to end the occlusion query; (6) Call glGetQueryObjectiv() to extract the results of the occlusion query based on the ID; (7) Call glDeleteQueries() to delete the ID and reclaim resources; S4: Grouping measurement points to obtain continuous measurement point groups and single electrical measurement groups; The intersection of the reachable cone one-dimensional vector sets of adjacent measurement points is calculated sequentially. If the intersection of the two measurement points is not a zero vector, the two measurement points are connected to form the same group. The intersection is calculated downwards sequentially until the intersection with the next measurement point is a zero vector. The above-mentioned continuously connected measurement points form a group, which is called a continuous measurement point group. If the intersection of a single point with the two measurement points before and after it is a zero vector, the single point is grouped, which is called a single measurement point group. The grouping of all measurement points is completed in this way. S5: Intra-group path planning; S6: Inter-group path planning, path export, and completion of impeller probe trajectory planning.

2. The impeller probe trajectory planning method based on visual cone discretization according to claim 1, characterized in that: The specific content of step S1 is as follows: First, the model is transformed from local space to three-dimensional space through model matrix transformation; Secondly, according to the direction of the camera's observation, the model is transformed from three-dimensional space to the camera's viewpoint through rotation and translation using the observation matrix, thus generating the observation space; Then, using a perspective projection matrix, a suitable range is selected in each dimension to clip the observation space into a clipping space with a standardized device coordinate range; Finally, by transforming the viewport, the model coordinate system is set to a pre-defined coordinate range, generating screen space and completing the projection transformation of the coordinate system.

3. The impeller probe trajectory planning method based on visual cone discretization according to claim 1, characterized in that: The specific content of step S2 is as follows: After completing the 2D pixelation of the 3D model in the first step through vertex shading, primitive assembly, and geometry shading in the OpenGL graphics rendering pipeline, the 2D shading rendering is completed through the fragment shader.

4. The impeller probe trajectory planning method based on visual cone discretization according to claim 1, characterized in that: The specific content of step S5 is as follows: No planning is performed for single measurement point groups; for continuous measurement point groups, optimization algorithms are used based on the minimum probe travel time and minimum turning angle, i.e.: min∑(t1,t2,...,t n ),min∑(θ1,θ2,...,θ n ) In the formula, t is the ratio of the distance between the two measuring points to the moving speed of the probe, and θ is the angle between the vectors of the two measuring points. This completes the path planning calculation within the group.

5. The impeller probe trajectory planning method based on visual cone discretization according to claim 4, characterized in that: In step S5, the optimization algorithms for minimum probe movement time and minimum turning angle are as follows: for each single-point reachable cone vector group in the selected measurement point group, non-zero vectors are sequentially extracted, the sum of vector turning angles and vector translation time between measurement points are calculated, and the sum of the turning angles and translation distances are added together by setting a weight ratio, which is recorded as the planning value In within the group. In=Ina×min∑(t1,t2,...,t n )+Inb×min∑(θ1,θ2,...,θ n ) In the formula, Ina and Inb are normalization parameters, and their sum is equal to 1. The vector of each measuring point corresponding to the minimum planning value In within the group is the planning vector of the probe path within the group.

6. The impeller probe trajectory planning method based on visual cone discretization according to claim 1, characterized in that: The specific content of step S6 is as follows: Starting from the first group, for the next group of continuous measurement points, select the last measurement point of the current group and the first measurement point of the next group, and complete the inter-group path planning calculation through the path smoothing algorithm, minimum movement time optimization, and minimum turning angle optimization algorithm. For the next group or several groups of single measurement points, select the last measurement point of the current group, the measurement points contained in the next few groups of single measurement points, and the first measurement point of the first continuous measurement point group below, and complete the inter-group path planning calculation through the path smoothing algorithm, minimum movement time optimization, and minimum turning angle optimization algorithm, thus completing the inter-group path planning calculation in sequence.

7. The impeller probe trajectory planning method based on visual cone discretization according to claim 6, characterized in that: In step S6, the minimum movement time optimization and minimum turning angle optimization algorithms are consistent with the intra-group planning values ​​calculated in step S5. The smoothing algorithm adds a transition measuring point vector v to the planning vector obtained from the minimum movement time optimization and minimum turning angle optimization algorithms for adjacent measuring points with an angle rotation exceeding 15°. n+0.5 =(v n +v n+1 ) / 2, where v n Given the vector values ​​at n measurement points, the resulting vectors at each point are the planning vectors for the probe paths between groups.

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