Geometric feature-based filling angle adaptive optimization and minimum partition path planning method

Abstract

The invention provides a geometric feature-based filling angle adaptive optimization and minimum partition path planning method, which comprises the following steps of: 1, reading a part contour sequence, calculating concavity and convexity of points, obtaining a concave point set, and finally calculating a tangent angle range; 2, discretizing the angle based on the tangent angle range in the step 1, generating a filling line family, calculating the number of contour intersection points, and finally selecting an angle interval with the least intersection points; step 3, based on the angle interval in the step 2, performing subdivision search in the candidate interval, and calculating the number of times of arc starting and arc extinguishing under each angle; selecting an angle which enables the number of times of arc starting and arc extinguishing to be minimum as an optimal filling angle; generating a partition scheme and a processing path sequence based on the optimal filling angle; step 4, optimizing a processing path sequence; and step 5, processing the partition transition area. According to the method, the optimal filling direction is analyzed and determined through the concave point tangent angle from the geometrical characteristics of the part contour, and path planning with the minimum arc starting and extinguishing times is achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of intelligent manufacturing, and particularly relates to computer-aided process planning technology in additive manufacturing, and more particularly to an adaptive filling angle optimization and minimum partition path planning method based on geometric features and process parameters. Background Art

[0002] In the fields of additive manufacturing and numerical control machining, the reasonable planning of the workpiece machining path is a key factor affecting machining quality and efficiency. In the prior art, path planning strategies such as equidistant offset method and reciprocating parallel method are generally adopted, and these methods usually generate paths based on preset fixed filling angles and deterministic partition schemes. However, with the continuous development of manufacturing technology and the increasing industrial demands, the workpiece structure shows an obvious trend of complexity, and many limitations of traditional path planning methods are exposed in practical applications.

[0003] During the machining process of complex-shaped workpieces, the fixed filling angle strategy often leads to over-partitioning, which not only increases the idle travel and the number of arc starting and extinguishing times during the machining process, but also significantly reduces the machining efficiency due to the frequent switching of tool paths. Especially in the machining of multi-connected regions, an unreasonable filling angle selection may lead to a sharp increase in the number of partitions, resulting in a large amount of idle travel loss.

[0004] In addition, the existing partition optimization methods mainly rely on simple geometric feature recognition or predetermined partition rules, lacking in-depth consideration of the correlation between filling angles and partition effects. This technical route has the following problems: First, due to the failure to establish an effective coupling mechanism between filling angles and partition boundaries, it is difficult to optimize the number of partitions; second, the path planning at the partition seams lacks a reasonable transition strategy, which is likely to form potential machining quality hazards; finally, the traditional methods lack a scientific basis for filling angle selection and often rely on empirical judgment, making it difficult to meet the machining requirements of complex-shaped workpieces. Summary of the Invention

[0005] The present invention provides a method for adaptive optimization of filling angles based on geometric features and minimum partition path planning. Starting from the geometric features of the part contour, this method determines the optimal filling direction through the analysis of the tangent angles of concave points, realizes path planning with the least number of arc starting and extinguishing times, and solves the problem of excessive arc starting and extinguishing times during the machining of complex-shaped parts in the prior art.

[0006] To achieve the above technical features, the object of the present invention is achieved as follows: A method for adaptive optimization of filling angles based on geometric features and minimum partition path planning, comprising the following steps: Step 1, read the part contour sequence, calculate the concavity and convexity of points, then obtain the set of concave points, and finally calculate the tangent angle range; Step 2: Based on the tangent angle range in Step 1, perform angle discretization processing to generate a family of filling lines, calculate the number of contour intersection points, and finally select the angle interval with the fewest intersection points. Step 3: Based on the angle interval in Step 2, perform a refined search within the candidate interval, calculate the number of starting and extinguishing arcs at each angle; select the angle with the fewest number of starting and extinguishing arcs as the optimal filling angle; generate a zoning plan and a machining path sequence based on the optimal filling angle. Step 4: Optimization of the machining path sequence. Step 5: Treatment of the transition area between zones.

[0007] Preferably, the specific steps of Step 1 are as follows: Read the discrete point sequence of the part contour, calculate the direction vectors of adjacent points, judge the concavity and convexity of points through the vector cross product, obtain all concave points and establish a set of concave points; for each concave point, calculate the angle between its adjacent side vectors and the x-axis to determine the tangent angle range.

[0008] Preferably, the method for judging concave points in Step 1 is as follows: Denote a certain point as P, and the direction vectors of adjacent points as v k and v k+1 , judge the concavity and convexity of the point by calculating the sign of (v k ×v k+1 )·dz. When the result is less than zero, it is determined as a concave point, where dz is the unit vector in the positive direction of the Z-axis.

[0009] Preferably, the method for calculating the tangent angle range in Step 1 is as follows: For any concave point, obtain the angles α and β between its adjacent side vectors v1 and v2 and the x-axis. When β is less than or equal to 180 degrees, the tangent angle range Ψ is [α, β]; when α is greater than or equal to 180 degrees, Ψ is [α - 180, β - 180]; when α is less than or equal to 180 degrees and β is greater than or equal to 180 degrees, let α' = α, β' = β - 180. If α' is less than β', then Ψ is [0, α'] ∪ [β', 180].

[0010] Preferably, the specific steps of Step 2 are as follows: In the 0 - 180 degree coordinate system, perform angle discretization processing with a step of 0.1 degree. For each discrete angle, first determine the filling line spacing, then generate a series of equally spaced filling lines parallel to this angle, and select the angle interval with the fewest intersection points between the filling lines and the part contour as the candidate interval by calculating the number of intersection points at each angle.

[0011] Preferably, the specific steps of Step 3 are as follows: Within the candidate range, for each angle, the multi-connected region is divided into several simply-connected sub-regions by using the cutting line at the concave point; the minimum number of arc starting and extinguishing times is calculated through the formula N steps = Np - 1, where Np is the number of simply-connected regions; the angle that minimizes the number of arc starting and extinguishing times is selected as the optimal filling angle; during partitioning, ensure that the cutting line passes through the concave point and is perpendicular to the filling direction, ensuring that each sub-region contains only one filling line segment at any scanning height.

[0012] Preferably, the specific steps of step 4 are as follows: Implement the "Z"-shaped filling strategy within the determined partition, generate filling lines that meet the preset filling spacing requirements, trim the endpoints of the filling lines to ensure that the filling lines do not exceed the workpiece boundary, determine the connection order of the filling line segments through an optimization algorithm, and generate a continuous path sequence to ensure that the connection order of the filling line segments reaches the optimal state.

[0013] Preferably, the specific steps of step 5 are as follows: When processing the partition transition region, first identify the boundary regions of adjacent partitions, determine the range of the transition region according to the geometric characteristics of the boundary, adopt an adaptive connection strategy, and dynamically adjust the filling path of the transition region according to the specific characteristics of the partition boundary to ensure smooth connection with the paths of adjacent partitions, realize the continuity of the processing process, and reduce the number of arc starting and extinguishing times.

[0014] The present invention has the following beneficial effects: 1. The present invention determines the optimal filling angle through the analysis of the concave point tangent angle, provides a scientific theoretical basis, avoids the blindness of filling angle selection in traditional methods, and effectively improves the rationality of path planning.

[0015] 2. The partition strategy based on the optimal filling angle of the present invention realizes the minimization of the number of arc starting and extinguishing times, significantly improves the processing efficiency; at the same time, through the smooth transition design between partitions, the processing quality is guaranteed.

[0016] 3. The present invention adopts an adaptive partition and path generation strategy, making the method have strong robustness, capable of adapting to the processing requirements of various complex-shaped parts, and having good engineering application value.

[0017] 4. The method of the present invention is simple to implement, has high computational efficiency, and is easy to apply in actual processing; through a reasonable mathematical model and optimization algorithm, it provides a new solution for the processing path planning of complex-shaped parts. Description of the Drawings

[0018] The following further illustrates the present invention in conjunction with the drawings and embodiments.

[0019] Figure 1 The overall flowchart of the method of the present invention.

[0020] Figure 2 The present invention generates a machining path with a filling angle of 0° within the single-layer slicing plane of the model based on this optimization algorithm.

[0021] Figure 3 The present invention generates a machining path with a filling angle of 50° within the single-layer slicing plane of the model based on this optimization algorithm.

[0022] Figure 4 The present invention generates a machining path with a filling angle of 90° within the single-layer slicing plane of the model based on this optimization algorithm. Detailed implementation manners

[0023] The following will describe in detail the technical solutions in the embodiments of the present invention. The described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Without departing from the design concept of the present invention, various improvements made by those of ordinary skill in the art to the technical solutions of the present invention shall fall within the protection scope of the present invention.

[0024] Embodiment 1: As Figure 1 shown, a method for adaptive optimization of filling angle and minimum partition path planning based on geometric features includes the following steps: Step 1: Read the discrete point sequence of the part contour, calculate the direction vectors of adjacent points, judge the concavity and convexity of the points through the vector cross product, obtain all concave points and establish a concave point set; for each concave point, calculate the angle between its adjacent side vector and the X-axis to determine the tangent angle range; Step 2: Based on the obtained tangent angle range, perform angle discretization processing in the 0-180 degree coordinate system, and set the step size to 0.1 degree; for each discrete angle, generate a family of filling lines and calculate the number of intersection points with the contour; select the angle interval with the fewest intersection points as the candidate interval; Step 3: Perform a subdivision search within the candidate interval, calculate the start arc and end arc times at each angle; select the angle with the fewest start arc and end arc times as the optimal filling angle; generate a partition plan and a machining path sequence based on the optimal filling angle; Step 4: Adopt a "Z"-shaped filling strategy to generate an initial path within each partition, while ensuring that the distance between the filling line segments meets the preset requirements, and perform boundary trimming on the endpoints of the filling lines to ensure that the path does not exceed the workpiece boundary. The system will generate a continuous path sequence through the optimization algorithm to ensure that the connection order of the filling line segments reaches the optimal state.

[0025] Step 5: When processing the partition transition region, first identify the boundary regions of adjacent partitions, and calculate the appropriate width of the transition region according to the geometric features of the boundary. By adopting an adaptive connection strategy, the system can dynamically adjust the filling path of the transition region to ensure smooth connection with the paths of adjacent partitions, effectively reducing the number of arc starting and extinguishing times during the processing and improving the processing efficiency.

[0026] Step 1 of the present invention is specifically as follows: Denote a certain point on the slice as P. The direction vectors of adjacent points are v k and v k+1 . By calculating the sign of (v k ×v k+1 )·dz to judge the concavity and convexity of the point. When the result is less than zero, it is determined as a concave point and saved separately into a set, where dz is the unit vector in the positive Z-axis direction.

[0027] Further, for any concave point, obtain the included angles α and β between its adjacent side vectors v1 and v2 and the X-axis. When β is less than or equal to 180 degrees, Ψ is [α, β]; when α is greater than or equal to 180 degrees, Ψ is [α - 180, β - 180]; when α is less than or equal to 180 degrees and β is greater than or equal to 180 degrees, let α' = α, β' = β - 180. If α' is less than β', then Ψ is [0, α'] ∪ [β', 180]. Where Ψ is the tangent angle range.

[0028] Step 2 of the present invention is specifically as follows: In the 0 - 180 degree coordinate system, perform angle discretization with a step of 0.1 degree. For each discrete angle, first determine the filling line spacing, and then generate a series of equally spaced filling lines parallel to this angle. By calculating the number of intersection points between the filling lines and the part contour at each angle, select the angle interval with the fewest intersection points as the candidate interval.

[0029] Step 3 of the present invention is specifically as follows: Within the candidate interval, for each angle, use the splitting line at the concave point to divide the multi-connected region into several single-connected sub-regions. Calculate the minimum number of arc starting and extinguishing times through the formula Nj = Np - 1, where Nj is the number of arc starting and extinguishing times and Np is the number of single-connected regions. Select the angle with the fewest arc starting and extinguishing times as the optimal filling angle. When partitioning, ensure that the splitting line passes through the concave point and is perpendicular to the filling direction, ensuring that each sub-region contains only one filling line segment at any scanning height.

[0030] Step 4 of the present invention is specifically as follows: Implement a "Z"-shaped filling strategy within a defined partition to generate filling lines that meet the requirements of a preset filling spacing. Trim the endpoints of the filling lines to ensure that the filling lines do not exceed the workpiece boundary. Determine the connection order of the filling line segments through an optimization algorithm to generate a continuous path sequence.

[0031] Step 5 of the present invention is specifically as follows: Identify the boundary regions of adjacent partitions and determine the scope of the transition region based on the geometric features of the boundaries. Adopt an adaptive connection strategy to dynamically adjust the filling path of the transition region according to the specific features of the partition boundaries, ensuring smooth connection with the paths of adjacent partitions, achieving the continuity of the machining process, and reducing the number of arc starting and extinguishing times.

[0032] Embodiment 2: Refer to Figures 2 - 4 The feasibility of a machining path planning method for complex-shaped parts based on filling angle optimization provided by the present invention has been verified through experiments. The specific experiments include: Taking the Pikachu model as the test object, obtain the number of partitions and paths at different filling angles on a certain layer of the model. Finally, obtain the optimal filling angle, the minimum number of partitions, and paths. The specific data is shown in Table 1. The actual slicing path generation is as Figures 2 - 4 shown.

[0033] Table 1 Statistics of the number of partitions of the Pikachu model at the 15th layer slicing contour under different filling angles

[0034] The experimental data in Table 1 and Figures 2 - 4 The test results verify the technical advantages of the filling angle adaptive optimization algorithm based on geometric features proposed by the present invention in the field of complex-shaped part machining. Through systematic analysis of the filling angles in the range of 0° - 180°, the research confirms the adaptive path planning ability of the algorithm. Data analysis shows that under the filling angle conditions of 0° and 160°, when the model has 13 concave point features and the theoretical number of partitions is 27, the algorithm optimizes the number of generated paths to 12, reaching the optimal solution level; under the filling angle condition of 70°, the number of concave points of the workpiece increases to 23 and the theoretical number of partitions reaches 47, and the algorithm still maintains stable optimization performance, controlling the number of generated paths to 19. Figures 2 - 4 The visualization results of

[0035] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than limiting the present invention; although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that any modification or replacement does not make the essence of the corresponding technical solution deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included within the protection scope of the present application.

Claims

1. A method for adaptive optimization of filling angle and minimum partition path planning based on geometric features, characterized in that: The following steps are involved: Step 1: read the part contour sequence, calculate the concavity of the point, obtain the concave point set, and finally calculate the tangent angle range; Step 2: Based on the tangent angle range in step 1, discretize the angle, generate a fill line family, calculate the number of contour intersections, and finally select the angle interval with the least intersections; Step 3: Based on the angle interval in step 2, perform a subdivision search in the candidate interval to calculate the number of arcing and arcing at each angle; select the angle with the least number of arcing and arcing as the optimal filling angle; generate a partitioning scheme and a processing path sequence based on the optimal filling angle; Step 4, optimization of processing path sequence; Step 5: Processing of partition transition area.

2. According to claim 1, a method for adaptive optimization of filling angle and minimum partition path planning based on geometric features, characterized in that: Step 1 The specific steps are: Read the discrete point sequence of the part contour, calculate the direction vectors of adjacent points, determine the concavity of the points through vector cross product, obtain all concave points and establish a concave point set; for each concave point, calculate the angle between its adjacent edge vector and the x-axis, and determine the tangent angle range.

3. According to claim 2, a method for adaptive optimization of filling angle and minimum partition path planning based on geometric features, characterized in that: The method for determining the concave point in step 1 is: Let a point be P and the direction vector of the adjacent point be v k and v k+1 , by calculating (v k ×v k+1 The sign of )·dz determines the concavity of the point. When the result is less than zero, it is judged as a concave point, where dz is the positive unit vector of the Z axis.

4. According to claim 3, a method for adaptive optimization of filling angle and minimum partition path planning based on geometric features, characterized in that: The method for calculating the tangent angle range in step 1 is: For any concave point, obtain the angles α and β between its adjacent edge vectors v1 and v2 and the x-axis. When β is less than or equal to 180 degrees, the tangent angle range Ψ is [α, β]; when α is greater than or equal to 180 degrees, Ψ is [α-180, β-180]; When α is less than or equal to 180 degrees and β is greater than or equal to 180 degrees, let α'=α, β'=β-180. If α' is less than β', then Ψ is [0, α']∪[β', 180].

5. According to claim 4, a method for adaptive optimization of filling angle and minimum partition path planning based on geometric features, characterized in that: Step 2 The specific steps are: In the 0-180 degree coordinate system, the angle is discretized with a step size of 0.1 degree. For each discrete angle, the fill line spacing is first determined, and then a series of equidistant fill lines parallel to the angle are generated. By calculating the number of intersections between the fill line and the part contour at each angle, the angle interval with the least number of intersections is selected as the candidate interval.

6. The method for adaptive optimization of filling angle and minimum partition path planning based on geometric features according to claim 5, characterized in that: Step 3 The specific steps are: In the candidate interval, for each angle, the dividing line at the concave point is used to divide the multi-connected region into several simply connected sub-regions; the minimum number of arcing and arcing extinction is calculated by the formula N steps = Np-1, where Np is the number of simply connected regions; the angle with the least number of arcing and arcing extinction is selected as the optimal filling angle; when partitioning, ensure that the dividing line passes through the concave point and is perpendicular to the filling direction, so that each sub-region contains only one filling line segment at any scanning height.

7. The method for adaptive optimization of filling angle and minimum partition path planning based on geometric features according to claim 6, characterized in that: Step 4 The specific steps are: A "Z"-shaped filling strategy is implemented within the determined partition to generate filling lines that meet the preset filling spacing requirements. The filling line endpoints are trimmed to ensure that the filling lines do not exceed the workpiece boundaries. The connection order of the filling line segments is determined through the optimization algorithm, and a continuous path sequence is generated to ensure that the connection order of the filling line segments reaches the optimal state.

8. The method for adaptive optimization of filling angle and minimum partition path planning based on geometric features according to claim 7, characterized in that: Step 5 The specific steps are: When processing the partition transition area, first identify the boundary area of ​​the adjacent partitions, determine the range of the transition area according to the geometric characteristics of the boundary, and use an adaptive connection strategy to dynamically adjust the filling path of the transition area according to the specific characteristics of the partition boundary to ensure smooth connection with the adjacent partition path, achieve continuity of the processing process, and reduce the number of arcing and arcing.

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