A Method and System for Optimizing Laser Cladding Parameters of Hydraulic Supports Based on Adaptive Partitioning

Abstract

This application discloses a method and system for optimizing laser cladding parameters of hydraulic supports based on adaptive partitioning, belonging to the field of automatic control technology. The method includes: acquiring three-dimensional model data of the part to be processed and identifying geometric feature change points; generating temporary partitions with uniform geometric features using a region growing algorithm; merging and dividing the temporary partitions according to working conditions to form a final partition containing high-stress areas and easily worn areas; for each partition, matching a basic parameter set from a parameter library based on its geometric attributes and working conditions, and dynamically adjusting it based on specific geometric features to generate a matching processing parameter set; finally generating a partition control command set for controlling the processing equipment. This application achieves precise adaptive optimization and automated control of processing parameters, improving processing quality and efficiency.

Description

Technical Field

[0001] This application relates to the field of automatic control technology, and in particular to a method and system for optimizing the laser cladding parameters of hydraulic supports based on adaptive partitioning. Background Technology

[0002] Hydraulic supports, as a key support structure in fully mechanized coal mining equipment, are prone to wear, corrosion, and fatigue damage in their critical components under complex underground working conditions. Laser cladding technology, due to its advantages such as high heat input and low dilution rate, is widely used in the remanufacturing and strengthening of critical components of hydraulic supports.

[0003] However, existing machining parameters are mostly set based on manual experience, lacking a systematic consideration of the surface geometry of the parts and the distribution of working loads. Traditional methods usually use uniform parameters for machining, which is difficult to adapt to the different requirements of wear resistance and fatigue resistance in different areas, resulting in uneven performance of the machined layer and easy local failure. At the same time, machining path planning and parameter switching rely on manual operation, which is inefficient and makes it difficult to achieve high-quality and high-efficiency adaptive machining. Summary of the Invention

[0004] This application provides a method and system for optimizing laser cladding parameters of hydraulic supports based on adaptive partitioning. Its main purpose is to solve the problem that parameter setting in traditional processing relies on manual experience, making it difficult to adaptively adjust the parameters according to the geometric features and working conditions of different areas of complex components, resulting in low processing efficiency and poor processing quality consistency.

[0005] To achieve the above objectives, this application provides a method for optimizing laser cladding parameters of hydraulic supports based on adaptive partitioning, comprising:

[0006] Obtain the three-dimensional model data of the hydraulic support component to be processed, and identify the geometric feature change points on the surface of the component to be processed based on the three-dimensional model data;

[0007] An initial set of boundary points is defined using the geometric feature change points. Based on the region growing algorithm, surface regions with continuous curvature and spatial adjacency are aggregated to generate a first temporary partition with multiple geometric features evenly distributed.

[0008] The first temporary partition is merged or divided according to the working conditions of the part to be processed to form a second final partition, which includes a high stress concentration area and a wear-prone area.

[0009] For each of the second final partitions, a set of basic parameters is matched from a preset parameter library based on the geometric feature attributes of the second final partition and the operating condition requirements;

[0010] Based on the specific geometric features of the second final partition, the energy beam incident angle, processing path, material delivery rate and energy source power in the basic parameter set are dynamically adjusted to generate a processing parameter set that matches the geometric features of each partition.

[0011] Based on the set of processing parameters, an adaptive partition control instruction set for controlling the processing equipment is generated.

[0012] To address the aforementioned issues, this application also provides an adaptive partitioning-based hydraulic support laser cladding parameter optimization system, the system comprising:

[0013] The geometric feature change point recognition module is used to acquire the three-dimensional model data of the hydraulic support component to be processed, and to identify the geometric feature change points on the surface of the component to be processed based on the three-dimensional model data.

[0014] The temporary partition generation module is used to define an initial boundary point set based on the geometric feature change points, and aggregate surface regions with continuous curvature and spatial adjacency based on the region growth algorithm to generate a first temporary partition with multiple geometric features evenly distributed.

[0015] The final partitioning determination module is used to merge or divide the first temporary partition according to the working conditions of the part to be processed, forming a second final partition, which includes a high stress concentration area and a wear-prone area.

[0016] The basic parameter set matching module is used to match a basic parameter set from a preset parameter library for each of the second final partitions based on the geometric feature attributes of the second final partition and the working condition requirements.

[0017] The parameter dynamic adjustment module is used to dynamically adjust the energy beam incident angle, processing path, material delivery rate and energy source power in the basic parameter set according to the specific geometric features of the second final partition, so as to generate a processing parameter set that matches the geometric features of each partition.

[0018] The partition control instruction set generation module is used to generate an adaptive partition control instruction set for controlling the processing equipment based on the processing parameter set.

[0019] Compared with the prior art, this application has the following beneficial effects:

[0020] This application achieves precise optimization of laser processing parameters and automatic generation of control commands for hydraulic supports through an adaptive partitioning method based on the geometric features of a 3D model and operating condition requirements. First, by identifying geometric feature change points and combining them with a region growing algorithm, uniform partitioning of the component surface's geometric features is achieved, providing a basis for parameter customization in different regions. Second, by fusing finite element analysis stress cloud maps and historical wear data, operating condition-driven merging and segmentation of the partitions ensures the integrity of high-stress and wear-prone areas, providing a partitioning basis for differentiated performance requirements.

[0021] This application effectively solves the problems of poor parameter adaptability and reliance on manual experience in traditional processing, realizing full-process automation and intelligence from 3D model to processing instructions. Through dual-drive zoning of geometry and working conditions, parameter library matching and dynamic adjustment, and automatic processing path planning, it significantly improves the uniformity, wear resistance, and fatigue resistance of the processed layer, reduces processing defects, improves the remanufacturing quality and service life of hydraulic supports, while reducing the intensity of manual intervention and improving processing efficiency and consistency. Attached Figure Description

[0022] Figure 1 A flowchart illustrating a method for optimizing laser cladding parameters of a hydraulic support based on adaptive partitioning, provided in an embodiment of this application;

[0023] Figure 2 A functional block diagram of a hydraulic support laser cladding parameter optimization system based on adaptive partitioning provided in an embodiment of this application;

[0024] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0025] It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit this application.

[0026] This application provides a method for optimizing laser cladding parameters of hydraulic supports based on adaptive partitioning. The execution entity of this method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the method for optimizing laser cladding parameters of hydraulic supports based on adaptive partitioning can be executed by software or hardware installed on a terminal device or a server device, and the software or hardware constitutes the core of an adaptive control system. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks, and big data and artificial intelligence platforms.

[0027] This embodiment details the application of the adaptive partitioning-based machining parameter optimization control method provided by the present invention in the specific scenario of laser cladding manufacturing of key components of hydraulic supports. It should be noted that this embodiment uses laser cladding as an example, but this control method is also applicable to other types of additive manufacturing or surface processing processes.

[0028] Reference Figure 1 The diagram shown is a flowchart illustrating a method for optimizing laser cladding parameters of a hydraulic support based on adaptive partitioning, according to an embodiment of this application. In this embodiment, the method includes:

[0029] S1. Obtain the three-dimensional model data of the hydraulic support component to be processed, and identify the geometric feature change points on the surface of the component to be processed based on the three-dimensional model data.

[0030] In this embodiment of the application, the component to be processed may be the component to be clad in a hydraulic support.

[0031] In this embodiment, the hydraulic support component to be processed is a key component of the hydraulic support that needs to be repaired or its performance enhanced through remanufacturing technology (laser cladding technology in this embodiment) due to wear, corrosion, or fatigue damage during long-term use. Common components include the outer cylinder of the column, the jack piston, and the cylinder of the push jack. The three-dimensional model data is a digital model data that can completely reflect the surface shape, size, and spatial position of the component to be processed. This data includes the three-dimensional coordinates, normal direction, and curvature of each point on the surface of the component, which can be used for subsequent geometric feature analysis and partitioning. The geometric feature change point is the point where the curvature value of the surface of the component to be processed changes significantly. These points usually correspond to the geometric shape transition points of the component surface, such as the junction of the arc transition surface and the cylindrical surface, the edge of the step surface, etc., which are important boundary references for subsequent adaptive partitioning.

[0032] In some embodiments, acquiring the three-dimensional model data of the hydraulic support component to be processed, and identifying geometric feature change points on the surface of the component to be processed based on the three-dimensional model data, includes:

[0033] The surface point cloud data of the part to be processed is acquired using a three-dimensional measurement device;

[0034] The surface point cloud data is denoised and smoothed to generate preprocessed 3D model data;

[0035] The surface curvature distribution of the part to be processed is calculated by processing the preprocessed three-dimensional model data based on the curvature change algorithm.

[0036] Points in the surface curvature distribution whose curvature values ​​exceed a preset curvature threshold are identified as points of geometric feature change.

[0037] In this embodiment, the three-dimensional measuring device is a high-precision measuring device that generates surface point cloud data by emitting an energy beam toward the surface of the part to be processed and receiving the reflected signal, thereby collecting a large number of three-dimensional coordinate points on the surface of the part in real time.

[0038] In this embodiment of the application, the surface point cloud data is the original data set consisting of a large number of discrete three-dimensional coordinate points obtained after the three-dimensional measuring device scans the surface of the part to be processed. These points together constitute the shape contour of the part surface, but the original data may contain noise points caused by environmental interference.

[0039] In this embodiment, denoising and smoothing are preprocessing operations performed on the acquired surface point cloud raw data. The denoising operation aims to remove isolated noise points (such as points caused by ambient light reflection interference) from the point cloud data, while the smoothing operation optimizes the distribution uniformity of the point cloud data and reduces data fluctuations while preserving the key geometric features of the component surface. The preprocessed 3D model data is 3D model data that has been denoised and smoothed, eliminating noise interference and optimizing data quality. This data can more accurately reflect the true geometric shape of the component to be processed, providing a reliable foundation for subsequent curvature calculation and feature recognition.

[0040] In this embodiment, the curvature change algorithm is an algorithm used to calculate the curvature values ​​of each point on the surface of a three-dimensional model and analyze the curvature distribution law. Through this algorithm, the curvature magnitude at different positions on the surface of the part to be processed can be obtained, thereby identifying geometric feature change points where curvature changes abruptly. Commonly used curvature change algorithms include principal curvature calculation algorithms based on the covariance matrix. The surface curvature distribution is the overall distribution of curvature values ​​of each point on the surface of the part to be processed after the three-dimensional model data is preprocessed by the curvature change algorithm. This distribution can intuitively reflect the geometric smoothness of different areas on the surface of the part. For example, the curvature distribution of the cylindrical surface area is relatively uniform, while the curvature of the transition surface area will show obvious changes. The preset curvature threshold is a curvature critical value pre-set to determine whether it is a geometric feature change point based on the material characteristics of the part to be processed (such as the mechanical properties of Q345 steel), processing requirements, and a large amount of previous experimental data. When the curvature value of a certain point on the surface exceeds the threshold, the point can be determined as a geometric feature change point.

[0041] In this embodiment, the surface point cloud data of the component to be processed is collected using a three-dimensional measuring device. This includes: First, determining the placement position of the component to be processed and fixing it (taking the outer cylinder of the column as an example) on the scanning table to ensure no displacement during scanning; second, collecting the surface point cloud data of the component to be processed (i.e., the component to be clad) using a three-dimensional measuring device (in this embodiment, a FARO Focus S70 three-dimensional laser scanning device), with the scanning range covering the entire surface of the outer cylinder of the column; then, setting the scanning parameters, based on the dimensions of the outer cylinder of the column (diameter 300mm, length 1500mm), setting the scanning resolution to 0.1mm and adjusting the scanning distance to 1.5m, which ensures scanning accuracy while avoiding blind spots; finally, starting the three-dimensional measuring device, which performs a comprehensive scan of the surface of the outer cylinder of the column according to a preset processing path (using a spiral processing path to ensure no missed scanning areas). During the scanning process, the device records the three-dimensional coordinates of each laser reflection point in real time, ultimately generating surface point cloud data of the outer cylinder of the column containing 1.2 million discrete points.

[0042] In this embodiment, the surface point cloud data is denoised and smoothed to generate preprocessed 3D model data. This includes: processing the collected point cloud data of the outer cylinder surface using a statistical filtering algorithm. The core of this algorithm is to calculate the mean and standard deviation of the distance between each point and other points in its neighborhood, setting the standard deviation multiple to 3 (i.e., the 3σ criterion), and identifying points with a mean distance exceeding 3 times the standard deviation as isolated noise points and removing them; secondly, smoothing optimization is performed on the denoised point cloud data using the moving least squares method. This method constructs a quadratic polynomial fitting surface in the neighborhood of each point (the fitting window size is set to 5×). The point cloud data is 5mm thick, which matches the scanning resolution to ensure a smooth effect while preserving surface details. The coordinates of each point are adjusted according to the weight of neighboring points (the closer the point, the greater the weight) to make the distribution of the point cloud data more uniform. Finally, the point cloud data after noise reduction and smoothing is imported into 3D modeling software. Through point cloud stitching (if there are multiple segments of scanning data), mesh generation (using triangular mesh with a mesh side length of 0.2mm), and surface fitting, a preprocessed 3D model data that can fully reflect the geometry of the outer cylinder surface of the column is generated. The geometric error of this model data is controlled within 0.03mm.

[0043] In this embodiment, the preprocessed 3D model data is processed based on a curvature change algorithm to calculate the surface curvature distribution of the part to be processed. This includes: selecting a principal curvature calculation algorithm based on the covariance matrix as the curvature change algorithm for this step. This algorithm is a classic algorithm in the field of geometric shape analysis and can accurately calculate the principal curvature values ​​at each point on the 3D surface; performing meshing processing on the preprocessed 3D model data of the column outer cylinder, dividing the model surface into triangular mesh units with a side length of 0.3mm (the mesh unit size is set according to the model's accuracy requirements to ensure the accuracy of the curvature calculation), with each mesh unit's vertex being the curvature calculation point; calculating the curvature value of each vertex, and for each vertex, selecting... A local coordinate system is constructed using 30 neighboring vertices (this neighborhood covers the main geometric information around the vertex, ensuring the stability of curvature calculation). The covariance matrix of all points within this neighborhood is calculated, and the eigenvalues ​​and eigenvectors of the covariance matrix are obtained. The square root of each eigenvalue represents the principal curvature values ​​of the vertex in the two perpendicular directions (denoted as k1 and k2, respectively). The average of the two principal curvature values ​​is taken as the average curvature value of the vertex (k = (k1 + k2) / 2). The average curvature values ​​of all vertices are associated with their corresponding three-dimensional coordinates to generate a curvature distribution cloud map of the outer cylinder surface of the column. This cloud map allows for a direct observation that the average curvature value of the cylindrical surface region of the outer cylinder surface remains stable at a certain value. Around the same time, the average curvature of the transition area between the arc-shaped surface and the cylindrical surface gradually increases, reaching a maximum of [missing value]. The average curvature value at the edge of the step surface also shows a significant abrupt change.

[0044] In this embodiment, points in the surface curvature distribution whose curvature values ​​exceed a preset curvature threshold are identified as points of geometric feature change. This includes: first, determining the value of the preset curvature threshold, and combining it with the material of the outer cylinder of the column (Q345 steel), processing requirements (the processing layer thickness needs to reach 1.5mm, and special adjustments to processing parameters are needed for curvature abrupt change areas), and 15 sets of preliminary experimental data (testing the processing effect of different curvature areas, and finding that curvature values ​​exceeding...). When the uniformity of the processed layer begins to decrease significantly, the preset curvature threshold is set to... Secondly, a comprehensive analysis is performed on the calculated surface curvature distribution of the column's outer cylinder block, comparing the average curvature value of each vertex with a preset curvature threshold. Finally, values ​​exceeding the preset curvature threshold are considered. The vertices are marked as points of geometric feature change. Analysis reveals that these points are mainly concentrated in the junction area between the arc transition surface and the cylindrical surface of the outer cylinder block (average curvature value). ) and the edge region of the stepped surface (mean curvature value) A total of 1,800 geometric feature change points were identified, and the three-dimensional coordinates of these points were stored as a boundary point set file for subsequent adaptive partitioning operations.

[0045] In this embodiment of the application, the surface point cloud data of the part to be processed is collected by a three-dimensional measuring device, which solves the problems of low measurement efficiency, limited measurement range and inability to obtain complete shape data of complex curved surfaces when measuring the surface shape of the part to be processed by traditional manual measurement (such as using calipers or micrometers). This achieves fast, comprehensive and non-destructive digital acquisition of the surface shape of the part to be processed.

[0046] In this embodiment, the surface curvature distribution of the part to be processed is calculated based on the curvature change algorithm after preprocessing the three-dimensional model data. This solves the problem that traditional partitioning methods (such as dividing the part equally according to the axial length of the part) cannot quantify the differences in the geometric features of the surface of the part to be processed, resulting in a mismatch between the partitioning and the actual geometry. The surface curvature distribution calculated by the curvature change algorithm can convert the geometric smoothness of the part surface into a quantifiable curvature value, which intuitively reflects the differences in the geometric features of different regions (such as the smooth areas of the cylindrical surface and the abrupt areas of the transition surface).

[0047] S2. Define an initial set of boundary points based on the geometric feature change points, and aggregate surface regions with continuous curvature and spatial adjacency based on the region growth algorithm to generate a first temporary partition with multiple geometric features evenly distributed.

[0048] In this embodiment, the initial boundary point set is a collection of all geometric feature change points on the surface of the part to be processed identified in the preceding steps. These points can clearly define the locations where the geometric shape of the part surface changes abruptly, providing a clear boundary constraint basis for subsequent region division. The region growth algorithm is an algorithm for region aggregation based on the neighborhood characteristics of the point cloud on the surface of a 3D model. This algorithm gradually aggregates discrete points that meet the conditions into continuous regions by setting specific similarity criteria and constraints, and is often used for the geometric partitioning of 3D surfaces.

[0049] In this embodiment, curvature continuity means that the difference in curvature values ​​between two adjacent points on the surface of the part to be processed is within a preset allowable range. This state indicates that the geometric shape of the surface regions where the two points are located transitions smoothly without obvious abrupt changes and can be classified into the same geometric feature region. Spatial adjacency means that the straight-line distance between two points on the surface of the part to be processed in three-dimensional space is less than a preset distance threshold. This condition is used to determine whether the two points have the basic spatial correlation to be classified into the same region. Surface region aggregation refers to the process of gradually merging discrete points on the surface of the part to be processed that meet the conditions of curvature continuity and spatial adjacency through a region growth algorithm to form a continuous and complete geometric region.

[0050] In this embodiment, the first temporary partition is a preliminary partition on the surface of the part to be processed, which is obtained by aggregation and boundary smoothing using a region growing algorithm. This partition is the basis for subsequent adjustment to the final partition based on working conditions.

[0051] In some embodiments, defining an initial set of boundary points based on the geometric feature change points, and aggregating surface regions with continuous curvature and spatial adjacency based on a region growing algorithm to generate a first temporary partition with multiple uniformly distributed geometric features includes:

[0052] Define an initial set of boundary points based on the geometric feature change points, and execute a region growing algorithm based on the initial set of boundary points as constraints.

[0053] The region growing algorithm aggregates surface regions with continuous curvature based on curvature similarity criteria and spatial adjacency criteria, generating several initial regions separated by the initial boundary point set;

[0054] The boundaries between the initial regions are smoothed to generate a first temporary partition with multiple geometric features evenly distributed.

[0055] In this embodiment, the curvature similarity criterion is one of the core criteria in the region growing algorithm for determining whether adjacent points can be aggregated. This criterion determines whether two points belong to the same geometric feature region by comparing whether the difference in curvature values ​​between two adjacent points is less than a preset curvature difference threshold. The spatial adjacency criterion is another core criterion in the region growing algorithm for determining whether adjacent points can be aggregated. This criterion determines whether two points have the conditions for spatial aggregation by judging whether the straight-line distance between two adjacent points in three-dimensional space is less than a preset distance threshold.

[0056] In this embodiment, the initial region is a set of multiple discontinuous regions separated by the initial boundary point set, generated by the region growing algorithm after aggregating surface points that satisfy the curvature similarity criterion and the spatial adjacency criterion under the constraint of the initial boundary point set. These regions have not yet undergone boundary optimization processing. Boundary smoothing processing is an operation to optimize the boundaries between the initial regions. By using a specific mathematical algorithm to adjust the coordinates of the boundary points, the region boundaries are transformed from a polyline or angular state to a smooth curve state, avoiding abrupt boundary changes that may affect subsequent processing path planning.

[0057] In this embodiment, geometric feature change points are defined as the initial boundary point set. Using the initial boundary point set as a constraint, a region growing algorithm is executed, including: First, acquiring 2000 geometric feature change points on the surface of the part to be processed (taking a jack piston as an example, made of 27SiMn steel) identified in the previous steps. The three-dimensional coordinates of these points (e.g., X-axis range 50-800mm, Y-axis range 80-120mm, Z-axis range 100-1500mm) are organized into the initial boundary point set and stored as a TXT format file. This file contains a unique number and three... First, the initial boundary point set is imported into the processing module of the region growing algorithm (developed on the MATLAB platform, which has powerful matrix operation and point cloud processing capabilities, meeting the computational requirements of 3D geometric partitioning). Constraints are set for the algorithm, ensuring that the regions generated during region growing do not cross the initial boundary point set, thus effectively separating each region. Then, initial seed points are selected from the non-initial boundary point set on the surface of the part to be processed, prioritizing regions with relatively gentle geometric features (such as the central region of the cylindrical segment of a jack, where the curvature value is stable at a certain value). Five seed points are selected as initial seed points, with a spatial distance of no less than 50mm between each seed point to avoid overly concentrated seed point distribution leading to region overlap. Finally, the region growing algorithm is started. Starting from the initial seed point, the algorithm traverses and judges the points around the seed point according to the preset search order (using a spiral search, expanding the search range layer by layer from the seed point outward), initially screening out points that may meet the aggregation conditions, preparing for subsequent criterion-based precise aggregation.

[0058] This step is based on the "seed point expansion" principle of the region growing algorithm. This principle can start from known feature flat points and gradually expand outwards to form continuous regions. At the same time, the constraint effect of the initial boundary point set can prevent the region from crossing geometric abrupt changes, ensuring the consistency between partitioning and geometric features, which meets the core requirement of adaptive partitioning to be "divided according to geometric features".

[0059] In this embodiment, the region growing algorithm aggregates surface regions with continuous curvature based on curvature similarity criteria and spatial adjacency criteria, generating several initial regions separated by an initial set of boundary points. This includes: first, setting the judgment parameters for the curvature similarity criterion, and combining the material characteristics of the jack's piston (the processing technology of 27SiMn steel has high requirements for geometric uniformity) with 12 sets of experimental data from the previous stage (testing the uniformity of the processed layer under different curvature differences, revealing the curvature difference...). When the uniformity of the processing layer meets the requirements, the curvature difference threshold is set to [value]. That is, when the curvature values ​​of two adjacent points differ First, the curvature similarity criterion is satisfied. Second, the judgment parameters for the spatial adjacency criterion are set. Referring to the scanning accuracy of the 3D measuring equipment mentioned earlier (0.05mm), the spatial distance threshold is set to 0.1mm (twice the scanning accuracy, which ensures the spatial correlation of adjacent points and avoids missing effective adjacent points). That is, when the straight-line distance between two adjacent points in 3D space is ≤0.1mm, the spatial adjacency criterion is satisfied. Then, the region aggregation operation is performed. The region growing algorithm judges the points around the initial seed point one by one. First, the 3D spatial distance between the point to be judged and the seed point (or the points in the aggregated area) is calculated. If the distance is ≤0.1mm, the spatial adjacency criterion is satisfied. Then, the curvature difference between the two points is calculated. If the difference is ≤0.1mm, the spatial adjacency criterion is satisfied. The curvature similarity criterion is satisfied, and only points that satisfy both criteria are included in the current aggregation region. During the aggregation process, if the point to be judged belongs to the initial boundary point set, the region expansion in that direction is stopped to ensure that the region is separated by the initial boundary point set. Finally, the above aggregation process is repeated until all non-initial boundary points are assigned to their corresponding regions, generating 6 initial regions, namely the upper cylindrical segment region of the jack cylinder (curvature similarity). ), upper circular arc transition section region (curvature) ), the middle cylindrical section region (curvature) ), lower circular arc transition region (curvature) ), Lower cylindrical segment region (curvature) ) and stepped surface area (curvature) Each initial region is clearly separated by an initial set of boundary points, and the curvature values ​​within the regions are all... .

[0060] In this step, the curvature similarity criterion ensures uniform geometric features within the region, while the spatial adjacency criterion ensures spatial continuity. The combination of the two can effectively avoid the problem of "geometrically abrupt regions being classified into the same partition" caused by traditional single criteria (such as dividing by spatial distance alone), laying the foundation for accurate adaptation of subsequent processing parameters.

[0061] In this embodiment, the boundaries between initial regions are smoothed to generate multiple first temporary partitions with uniformly distributed geometric features. This includes: First, extracting boundary points between initial regions. By comparing the point cloud data of each initial region, boundary points located at the region edges are selected. The initial boundaries formed by these boundary points are mostly polylines or line segments with sharp angles, such as the initial boundary between the arc transition segment and the upper cylinder segment on the jack's piston, which exhibits a clear polyline transition. Second, the B-spline interpolation algorithm is selected as the boundary smoothing algorithm. This algorithm is a commonly used curve smoothing algorithm in computer graphics, capable of constructing smooth curves by controlling vertices without changing the overall direction of the boundary. To meet the requirement of smoothing the region boundaries, the parameters of the B-spline interpolation algorithm are set. For each initial boundary, 15 feature points on the boundary are selected as control vertices of the B-spline (the number of control vertices is determined experimentally; 15 can accurately preserve the geometric trend of the boundary while ensuring smoothness). The three-dimensional coordinates of these control vertices are input into the B-spline interpolation formula, which calculates 100 discrete points on the smoothed boundary curve. Finally, the smoothed boundary points replace the initial boundary points, and the extent of each region is redefined, generating six first temporary partitions with uniformly distributed geometric features. The boundary of each partition is a smooth curve, and the curvature difference between any two points within the partition is... It is spatially continuous without any breaks, such as the first temporary section of the arc transition segment on the jack column. After the boundary is smoothed, there are no sharp corners, which can better adapt to the movement trajectory of the subsequent processing head.

[0062] In this embodiment, geometric feature change points are defined as the initial boundary point set. Using the initial boundary point set as a constraint, a region growth algorithm is executed. This solves the problem that traditional partitioning methods (such as dividing by part length) do not consider geometric feature boundaries, resulting in partitions crossing geometric abrupt changes (such as the junction of an arc transition surface and a cylindrical surface), which leads to large differences in geometric features within the same partition. By constraining the initial boundary point set, it is ensured that the region growth process does not cross geometric abrupt changes, enabling the subsequently generated regions to accurately match the geometric feature boundaries. This avoids the situation where the same partition contains both smooth regions and abrupt change regions, providing a geometric basis for subsequent processing parameters to be adapted to the region.

[0063] In the embodiments of this application, this application solves the problem that traditional single-criterion partitioning (such as based solely on spatial distance) cannot guarantee the uniformity of geometric features within a region. By using the curvature similarity criterion, it ensures that the curvature value difference within each initial region is within a small range, thereby achieving uniformity of regional geometric features. At the same time, the spatial adjacency criterion ensures the spatial continuity of the region, avoiding the appearance of discrete points or small regions, so that each initial region has a complete geometric shape.

[0064] In this embodiment, the present application solves the problem that the existence of sharp corners and broken lines at the boundary of the initial region causes abrupt changes in the trajectory of the subsequent processing head at the boundary, which in turn leads to defects such as uneven processing layer thickness and increased porosity. The smoothed boundary curve enables the trajectory of the processing head to transition continuously and avoids abrupt changes in trajectory. At the same time, the geometric uniformity of the first temporary partition is further improved, ensuring that the processing conditions (such as energy beam incident angle and processing path) in each partition are consistent.

[0065] S3. According to the working conditions of the parts to be processed, the first temporary partition is merged or divided to form a second final partition, which includes a high stress concentration area and a wear-prone area.

[0066] In this embodiment, the working condition requirements are the load conditions, motion frequency, environmental wear intensity, and other usage requirements that the component to be processed needs to withstand during actual operation. These requirements directly determine the differences in the performance requirements of the processing layer (such as wear resistance and fatigue resistance) for different areas of the component. The second final partition is a partition that is precisely matched with the actual performance requirements after merging or dividing the first temporary partition with the working condition requirements of the component to be processed. This partition clearly includes high stress concentration areas and easily worn areas, which is the core basis for subsequent matching of processing parameters.

[0067] In this embodiment, the high stress concentration area is the area where the surface stress value of the component to be processed is significantly higher than that of the surrounding area and exceeds a certain proportion of the material's yield strength when it is in operation. This area is prone to fatigue cracks during use and has high requirements for the fatigue resistance of the processed layer. The wear-prone area is the part of the component to be processed that has significantly higher wear than other areas due to friction between the surface and other components or contact with impurities during long-term operation. This area has high requirements for the hardness and wear resistance of the processed layer.

[0068] In some embodiments, merging or dividing the first temporary partition according to the working conditions of the component to be processed to form a second final partition includes:

[0069] Obtain the finite element analysis stress cloud diagram and historical wear data of the part to be processed under working conditions;

[0070] Based on the stress cloud diagram identified by the finite element analysis, if a first temporary partition spans multiple high stress concentration regions, then the first temporary partition is divided; if multiple first temporary partitions are located in the same high stress concentration region, then the first temporary partitions are merged.

[0071] Based on the historical wear data, easily worn areas are identified, and the boundaries of adjacent partitions are adjusted so that each easily worn area is completely covered within a partition.

[0072] In this embodiment, the finite element analysis stress cloud map is a result file that simulates the stress distribution of the part to be processed under actual working load using finite element analysis software. It visually displays the stress magnitude in different areas in the form of a color cloud map, which can quickly locate the location and range of high stress concentration areas. The historical wear data is a collection of data such as wear amount and wear rate in different areas of the part to be processed, recorded by periodic measurements (such as laser thickness measurement and vernier caliper measurement) during the past use cycle. These data can reflect the actual wear of each area of ​​the part and provide a basis for identifying easily worn areas.

[0073] In some embodiments, adjusting the boundaries of adjacent partitions to ensure that each wear-prone area is fully covered within a partition includes:

[0074] If a wear-prone area is divided by a temporary boundary, the boundary is redefined to ensure that the wear-prone area is merged into a single partition.

[0075] In this embodiment, the temporary boundary is the initial boundary between the first temporary partitions that has not yet been adapted to the operating conditions. These boundaries are divided only based on geometric features, and there may be cases where the same wear-prone area is separated.

[0076] In this embodiment, obtaining the finite element analysis stress cloud map and historical wear data of the component to be processed under working conditions includes: First, obtaining the basic parameters of the component to be processed. Taking the component to be processed as the cylinder of a hydraulic support push jack (made of Q460 steel, outer diameter 200mm, inner diameter 180mm, length 1200mm) as an example, clarifying its actual working load (pushing force 300kN, pulling force 250kN, these parameters are from the hydraulic support industry standard MT / T1097-2008), working temperature (-20℃~60℃), and other working conditions; Second, generating the finite element analysis stress cloud map. Using finite element analysis software, importing the three-dimensional model of the push jack cylinder (from the pre-processed three-dimensional model data mentioned above), and dividing the mesh (high stress potential areas, such as the flange transition at both ends of the cylinder, use a hexahedral mesh with a mesh size of 2mm, while other areas use...) Using a 5mm grid to ensure both calculation accuracy and efficiency, a working load (a 300kN pushing force is applied to one end of the cylinder, while the other end is fixed and constrained) and boundary conditions (the temperature load is set to 25℃, a normal temperature state) are applied. After solving, a stress cloud map is generated. This cloud map uses different colors to indicate the stress magnitude, with red areas representing stress concentration areas. The stress values ​​of each area can be directly read. Finally, historical wear data is collected. The usage records of this type of push jack cylinder in a coal mine from 2021 to 2023 are retrieved. These records contain wear measurement data every 6 months (using a Keyence laser thickness gauge with a measurement accuracy of 0.01mm). Measurement points are set every 50mm along the cylinder axis, for a total of 24 measurement points. The initial thickness and the thickness after each measurement are recorded at each measurement point. The cumulative wear amount and annual wear rate of each measurement point are calculated to form a complete historical wear data table.

[0077] In this embodiment, high stress concentration regions are identified based on the stress cloud map obtained from finite element analysis. If a first temporary partition spans multiple high stress concentration regions, the first temporary partition is divided; if multiple first temporary partitions are located in the same high stress concentration region, the first temporary partitions are merged. This includes: First, determining the criteria for identifying high stress concentration regions. Based on the yield strength of Q460 steel (460MPa) and combined with the fatigue resistance design requirements of the processing layer (the processing layer must withstand stress not less than 80% of the material's yield strength), regions with stress values ​​≥368MPa (460MPa×80%) are identified as high stress concentration regions. Second, extracting high stress concentration regions from the stress cloud map obtained from the finite element analysis. The three-dimensional coordinate range of the stress concentration area is determined. The high stress concentration areas of the jack cylinder are mainly concentrated at the transition points between the two end flanges and the cylinder body, totaling two locations. The axial range of each location is 100mm (e.g., the X-coordinate of the left end flange transition is 50-150mm, and the X-coordinate of the right end flange transition is 1050-1150mm), and the radial range is 180-200mm. Then, the range of the high stress concentration area is spatially matched with the first temporary partition (a total of 5, namely the left flange area, left transition area, middle cylinder area, right transition area, and right flange area). The spatial intersection calculation method (using the Intersect function of MATLAB software) is used to determine the position of the two. Relationship: It was found that the first temporary zone of the "left transition zone" (X coordinate 80-120mm) is completely located within the high stress concentration area on the left (X coordinate 50-150mm), and the first temporary zone of the "right transition zone" (X coordinate 1080-1120mm) is completely located within the high stress concentration area on the right (X coordinate 1050-1150mm), with no first temporary zone spanning multiple high stress concentration areas. However, it was found that the high stress concentration area on the left also includes a portion of the first temporary zone of the "left flange zone" (X coordinate 50-80mm), and the stress value of this portion is also ≥368MPa, belonging to the same high stress concentration area. Therefore, the "left flange zone" (X coordinate 80-120mm) is considered to be within the same high stress concentration area. The two temporary zones, "50-80mm" and "Left Transition Zone" (X coordinate 80-120mm), are merged. The merged zone, with X coordinate 50-150mm, completely covers the high stress concentration area on the left. Similarly, the "Right Flange Zone" (X coordinate 1120-1150mm) and "Right Transition Zone" (X coordinate 1080-1120mm) are merged. The merged zone, with X coordinate 1050-1150mm, completely covers the high stress concentration area on the right. The stress values ​​in the intermediate cylinder zone (X coordinate 150-1050mm) are all ≤200MPa, with no high stress concentration, so the original zones remain unchanged. Finally, three transition zones containing high stress concentration areas are formed.

[0078] In this embodiment, wear-prone areas are identified based on historical wear data, and the boundaries of adjacent zones are adjusted to ensure that each wear-prone area is completely covered within a zone. This includes: First, determining the criteria for identifying wear-prone areas, and combining this with the usage requirements of the jack cylinder (maximum allowable wear of 0.3mm during normal use, annual wear rate ≤0.15mm / year), areas with an annual wear rate >0.15mm / year in the historical wear data are identified as wear-prone areas; Second, analyzing the historical wear data, among the 24 measurement points of the jack cylinder, the X-coordinate 300-400mm (corresponding to the guide sleeve contact area where the cylinder connects to the pushing beam) and The annual wear rates at the measurement points at X-coordinate 800-900mm (corresponding to the sealing area where the cylinder barrel contacts the base) are 0.18mm / year and 0.17mm / year, respectively, both greater than 0.15mm / year. Therefore, these two areas are marked as easily worn areas, with their three-dimensional coordinate ranges being X-coordinate 300-400mm (radial 180-200mm) and X-coordinate 800-900mm (radial 180-200mm), respectively. Then, the easily worn area ranges are matched with the current transition zones (left high-stress zone 50-150mm, middle cylinder barrel zone 150-1050mm, right high-stress zone 1050-1150mm), and it is found that... Both wear-prone areas are located within the transition zone of the "intermediate cylinder barrel area," and the temporary boundaries (150mm and 1050mm) of this transition zone do not divide the wear-prone areas. However, further inspection revealed that the wear-prone area at X coordinate 300-400mm is adjacent to the internal temporary sub-boundary of the intermediate cylinder barrel area (X coordinate 350mm, which is a subdivision boundary left over from the first temporary zone that was not completely eliminated). This sub-boundary divides the wear-prone area into two parts: X300-350mm and X350-400mm. Finally, the boundaries of the adjacent zones were adjusted, the internal temporary sub-boundary at X coordinate 350mm was deleted, and the internal range of the intermediate cylinder barrel area was redefined. The X300-400mm wear-prone area is completely contained within the same partition, while ensuring that the X800-900mm wear-prone area is also undivided, ultimately forming 5 second final partitions: the left high-stress area (50-150mm), the first wear-prone area (300-400mm), the middle normal area (150-300mm, 400-800mm, and 900-1050mm are combined, this area has no high stress and high wear), the second wear-prone area (800-900mm), and the right high-stress area (1050-1150mm). Each high-stress concentration area and wear-prone area is completely covered within an independent partition.

[0079] In this embodiment, if a wear-prone area is divided by a temporary boundary, the boundary is redefined to ensure that the wear-prone area is merged into a single partition. This includes, for example, taking historical wear data from another batch of jack cylinders as an example, assuming that in this batch of data, the area with an X-coordinate of 600-700mm is identified as a wear-prone area (annual wear rate 0.19mm / year), but this area is divided into two parts, X600-650mm and X650-700mm, by a temporary boundary with an X-coordinate of 650mm left over from the first temporary partition. These two parts belong to two temporary partitions, "Intermediate Cylinder Area 1" (X400-650mm) and "Intermediate Cylinder Area 2" (X650-900mm), respectively. First, the complete three-dimensional coordinate range (X600-700mm, radial 180-200mm) of the wear-prone area and the coordinates of the temporary boundary (X650mm) are obtained. Second, the partition attributes on both sides of the temporary boundary are analyzed, specifically "Intermediate Cylinder Area 1" and "Intermediate Cylinder Area 2". Zone 2 consists entirely of conventional areas (without high stress concentration), except for the X600-700mm area, which is prone to wear. Then, a boundary re-division algorithm is used, with the center coordinates of the prone wear area (X650mm, which is the geometric center of the prone wear area, ensuring symmetry of the re-division boundary) as the benchmark. The original temporary boundary at X650mm is adjusted to X700mm, so that the X600-700mm prone wear area is completely incorporated into "Intermediate Cylinder Zone 1". The adjusted "Intermediate Cylinder Zone 1" ranges from X400-700mm, and "Intermediate Cylinder Zone 2" ranges from X700-900mm. Finally, it is verified whether the re-divided boundary completely covers the prone wear area. Spatial coordinate comparison confirms that the X600-700mm prone wear area has no boundary divisions, and the adjusted partition does not affect the integrity of other areas (such as high stress concentration areas), ensuring that the prone wear area is merged into one partition. Subsequently, uniform high wear-resistant processing parameters can be matched to this partition.

[0080] In this embodiment, the present application solves the problem that traditional geometric partitioning may lead to the fragmentation of high-stress areas or the merging of different stress areas, resulting in insufficient or excessive fatigue resistance of the processed layer. By merging temporary partitions of the same high-stress area, the present application ensures that the area receives a uniform fatigue resistance strengthening parameter. By dividing partitions across multiple high-stress areas, the present application avoids the inability of a single parameter to adapt to different stress requirements, thereby improving the fatigue life of the processed layer in high-stress areas and reducing the probability of fatigue crack formation.

[0081] In this embodiment, the present application solves the problem that traditional geometric partitioning may divide the wear-prone areas, resulting in large differences in processing parameters between different partitions and premature failure of local wear-prone areas. By adjusting the boundary, the wear-prone areas are ensured to be completely included in one partition. A uniform high wear resistance parameter can be matched to the partition, thereby improving the hardness and wear resistance of the processed layer in the wear-prone areas and extending the overall service life of the component.

[0082] In this embodiment, if a wear-prone area is divided by a temporary boundary, the boundary is redefined to ensure that the wear-prone area is merged into a single partition. This solves the problem of wear-prone area segmentation caused by residual temporary boundaries. By redefined the boundary in a targeted manner, the segmentation is completely eliminated, ensuring that the wear-prone area receives continuous and uniform wear-resistant reinforcement. This avoids premature scrapping of components due to insufficient local reinforcement and further guarantees the overall effectiveness of the processing technology.

[0083] S4. For each of the second final partitions, match the basic parameter set from the preset parameter library according to the geometric feature attributes of the second final partition and the working condition requirements.

[0084] In the embodiments of this application, geometric feature attributes are a set of parameters that can quantitatively describe the surface geometry of the second final partition. These parameters directly affect the interaction between the energy beam and the workpiece surface during processing, as well as the forming effect of the processing layer.

[0085] In some embodiments, matching a basic parameter set from a preset parameter library for each of the second final partitions based on the geometric feature attributes of the second final partition and the operating condition requirements includes:

[0086] Extract the geometric feature attributes of the second final partition, including surface curvature, tilt angle, and partition area;

[0087] Obtain the working condition requirement attributes corresponding to the second final partition, wherein the working condition requirement attributes include wear resistance level and fatigue resistance level;

[0088] The geometric feature attributes and working condition requirement attributes are used as joint query conditions to match the optimal set of basic parameters in the preset parameter library.

[0089] In this embodiment, surface curvature is a quantitative indicator of the degree of curvature of the second final partition surface. This indicator can be used to determine whether the partition surface is a plane, a cylinder, or a complex curved surface. Different degrees of curvature correspond to different laser energy distribution requirements. The tilt angle is the angle between the second final partition surface and the horizontal plane. This angle affects the accumulation state of the processing powder on the workpiece surface and the energy reflectivity of the energy beam, requiring targeted adjustment of processing parameters. The partition area is the surface area occupied by the second final partition in three-dimensional space. The area size determines the planning method of the processing path and the processing efficiency, thereby affecting the parameter selection.

[0090] In this embodiment, the working condition requirement attribute is a specific requirement index for the performance of the processed layer derived from the load, wear, and other conditions borne by the second final partition during the operation of the hydraulic support. It is one of the core bases for matching processing parameters. The wear resistance level is a grading index that measures the wear resistance of the processed layer of the second final partition. It is set according to historical wear data and usage requirements. The higher the level, the higher the requirements for the hardness and density of the processed layer. The fatigue resistance level is a grading index that measures the ability of the processed layer of the second final partition to resist the generation and propagation of fatigue cracks. It is set according to the stress value of finite element analysis. The higher the level, the higher the requirements for the uniformity of the processed layer structure and the bonding strength.

[0091] In this embodiment of the application, the preset parameter library is a set of processing parameters that is pre-built and stored. This set contains a large number of experimentally verified mapping relationships of "geometric feature attributes + working condition requirement attributes - processing parameters", which provides data support for rapid parameter matching.

[0092] In this embodiment of the application, the joint query condition is a query basis formed by combining the geometric feature attributes of the second final partition with the working condition requirement attributes. Through the combination of multi-dimensional attributes, the optimal parameters in the preset parameter library can be accurately located.

[0093] In this embodiment of the application, the basic parameter set is a combination of processing parameters matched from the preset parameter library and initially adapted to the geometry and working conditions of the second final partition. It includes the initial values ​​of core parameters such as energy beam incident angle, processing path, material delivery rate, and energy source power.

[0094] In this embodiment, the geometric feature attributes of the second final partition are extracted. These geometric feature attributes include surface curvature, tilt angle, and partition area. The process involves: First, determining the second final partition from which the geometric feature attributes are to be extracted. Taking the second final partition of a hydraulic support column as an example (containing a left high-stress area, a first easily worn area, a middle conventional area, a second easily worn area, and a right high-stress area, made of Q345 steel), the left high-stress area is selected as the target partition for attribute extraction. Second, extracting the surface curvature, the three-dimensional model data of the left high-stress area (from the preprocessed three-dimensional model described above) is imported into GeomagicControlX software. Using a principal curvature calculation method based on the covariance matrix, 100 uniformly distributed sampling points within the partition are selected (the number of sampling points is determined experimentally; 100 points balance computational accuracy and efficiency). The principal curvature value of each sampling point is calculated and averaged to obtain the surface curvature of the left high-stress area. This value indicates that the surface of the partition is a circular arc transition surface. Then, the tilt angle is extracted by measuring the angle between the surface normal of the left high-stress zone and the vertical direction using software (the tilt angle is defined as the angle between the surface and the horizontal plane, which can be converted from the normal angle). Twenty evenly distributed measurement points are selected, and the average tilt angle is calculated to be 30°, reflecting the degree of tilt of the partition surface. Finally, the partition area is extracted using the area measurement function in the software. The surface within the boundary of the left high-stress zone is meshed (mesh size set to 0.5mm, matching the scanning accuracy), and the area of ​​all mesh units is calculated and summed to obtain the partition area of ​​the left high-stress zone. Similarly, the surface curvature, tilt angle, and area of ​​other second final partitions are extracted using the same method, such as the surface curvature of the first easily worn area. Inclination angle , area of ​​each zone .

[0095] In this embodiment, the working condition requirement attributes corresponding to the second final partition are obtained. These attributes include wear resistance level and fatigue resistance level. The process involves: First, determining the grading standards for the working condition requirement attributes. Referring to the industry standard for laser processing of hydraulic supports and 10 sets of preliminary experimental data (testing the usage effect of different performance processing layers), grading rules for wear resistance and fatigue resistance levels are established: Wear resistance is divided into 5 levels, with level 1 corresponding to an annual wear rate ≤ 0.05 mm / year, level 2 corresponding to 0.05-0.1 mm / year, level 3 corresponding to 0.1-0.15 mm / year, level 4 corresponding to 0.15-0.2 mm / year, and level 5 corresponding to > 0.2 mm / year; Fatigue resistance is divided into 5 levels, with level 1 corresponding to stress ≤ 50% of the material's yield strength, level 2 corresponding to 50%-60%, level 3 corresponding to 60%-70%, level 4 corresponding to 70%-80%, and level 5 corresponding to > 80%; Second, obtaining the working condition requirement attributes for the high-stress zone on the left... Based on the data, the average stress value of the high-stress zone in the left area is 280 MPa, and the yield strength of Q345 steel is 345 MPa. The calculated stress-to-yield strength ratio is 81% (280 ÷ 345 ≈ 0.81). According to the fatigue resistance grading rules, this ratio falls within the range of >80%, therefore the fatigue resistance grade of the high-stress zone in the left area is grade 5. The annual wear rate of the high-stress zone in the left area is 0.12 mm / year, which falls within the range of 0.1-0.15 mm / year according to the wear resistance grading rules, therefore the wear resistance grade of the high-stress zone in the left area is grade 3. Finally, the working condition requirements attributes of other second final zones are obtained using the same method. For example, the annual wear rate of the first easily worn zone is 0.18 mm / year (wear resistance grade 4), and the stress value is 180 MPa (fatigue resistance grade 2), ensuring that the working condition requirements attributes of each zone have clear quantitative basis.

[0096] In this embodiment, the geometric feature attributes and working condition requirement attributes are used as joint query conditions to match the optimal set of basic parameters in a preset parameter library. This includes: First, constructing a preset parameter library based on 1200 sets of processing experimental data (experimental materials cover commonly used hydraulic support materials such as Q345 steel and 27SiMn steel, and experimental variables include surface curvature). Inclination angle , area of ​​each zone The system is constructed using wear resistance grades 1-5 and fatigue resistance grades 1-5, and stored in a MySQL database. Secondly, the joint query conditions are determined; taking the high-stress area on the left as an example, the joint query condition is "surface curvature". +Tilting Angle +zone area +Abrasion resistance level 3 +Fatigue resistance level 5; Then, query matching is performed, using the K-nearest neighbor (KNN) algorithm as the query matching algorithm (K value set to 5, experimental verification shows that this K value can ensure matching accuracy while avoiding overfitting). The algorithm calculates the similarity between the query conditions and each data record in the preset parameter library. The similarity calculation is based on the Euclidean distance formula (the smaller the Euclidean distance, the higher the similarity). Each attribute value in the query conditions is standardized (such as surface curvature). Normalized to 0.6, based on curvature range After conversion, the distance to the records in the database is calculated using the Euclidean distance formula. Finally, the five records with the smallest Euclidean distances are selected, and the average value of each parameter in these five records is calculated as the optimal basic parameter set. The basic parameter set obtained by matching the left high-stress zone is: energy beam incident angle. (Initially set as a vertical surface), serpentine processing path (suitable for medium-sized area partitions), material delivery rate 8g / min, energy source power 1800W; similarly, the first easily worn zone is based on "surface curvature". +Tilting Angle +zone area The query condition "+wear resistance level 4+fatigue resistance level 2" yields the following basic parameter set: energy beam incident angle. Processing path is spiral (suitable for small area partitions), material conveying rate is 7g / min, and energy source power is 1600W.

[0097] In the embodiments of this application, this application solves the problem that traditional parameter selection cannot accurately match the working condition requirements, resulting in excessive or insufficient performance of the processing layer. By converting the working condition into quantifiable level indicators, parameter matching can be directly based on performance requirements, ensuring that the wear resistance and fatigue resistance of the processing layer are in line with the actual use requirements of the partition, avoiding premature component failure due to insufficient performance or cost waste due to excessive performance.

[0098] S5. Based on the specific geometric features of the second final partition, dynamically adjust the energy beam incident angle, processing path, material delivery rate and energy source power in the basic parameter set to generate a processing parameter set that matches the geometric features of each partition.

[0099] In this embodiment, the specific geometric features are the unique geometric parameters that distinguish the second final partition from other partitions. These parameters have a more significant impact on the processing and require targeted adjustment of the basic parameters to ensure processing quality. The energy beam incident angle adjustment is the angle value that needs to be adjusted from the initial energy beam incident angle in the basic parameter set to keep the energy beam perpendicular to the surface of the processing point in the second final partition. This value is calculated from the curvature of the partition surface. The processing parameter set is a combination of processing parameters that, after dynamic adjustment, are fully adapted to the specific geometric features of the second final partition. It includes the adjusted energy beam incident angle, processing path, material delivery rate, and energy source power. This parameter set serves as the output of the control system and can be directly used to control the processing equipment.

[0100] In some embodiments, the dynamic adjustment of the energy beam incident angle, processing path, material delivery rate, and energy source power in the basic parameter set includes:

[0101] The adjustment amount of the energy beam incident angle is calculated based on the surface curvature to ensure that the energy beam is always perpendicular to the surface of the processing point;

[0102] The processing path is determined based on the area of ​​the partition;

[0103] As the tilt angle increases, the ratio between the material delivery rate and the energy source power increases.

[0104] In this embodiment, the constants related to the processed material are fixed values ​​determined through numerous experiments based on the thermophysical properties of the processed material (such as Fe-Cr-B-Si alloy powder), such as melting point, specific heat capacity, and heat of fusion. These values ​​ensure that the ratio of energy source power to material delivery rate meets the material melting requirements. The increasing function that increases with the tilt angle is a function obtained by fitting processing experimental data at different tilt angles. The output value of this function increases with the increase of the tilt angle of the second final partition, which is used to compensate for the energy loss and powder accumulation changes caused by the tilted surface.

[0105] In some embodiments, the ratio of the material delivery rate to the energy source power is as follows:

[0106]

[0107] in, It is the power of the energy source (in the embodiments of this application, it is the laser power). It is the material conveying rate (in the embodiments of this application, it is the powder feeding rate). It is a constant related to the processed material. It is an increasing function that increases with the angle of inclination. It is the tilt angle.

[0108] Furthermore, in the laser cladding scenario of this embodiment, the control system makes dynamic adjustments based on this formula. When the control system detects that the tilt angle of a certain section is 30°, it calls the formula to calculate a new power value and adjusts the control signals output to the processing equipment (laser and powder feeder).

[0109] In the embodiments of this application, the ratio of material delivery rate to energy source power describes the quantitative correlation between energy source power and material delivery rate. This relationship is adjusted with the change of the tilt angle of the second final partition to ensure that the processing layer energy matches the powder amount.

[0110] In this embodiment, the adjustment amount of the energy beam incident angle is calculated based on the surface curvature to ensure that the energy beam is always perpendicular to the surface of the processing point. This includes: First, clarifying the adjustment target of the energy beam incident angle. The energy beam being perpendicular to the surface of the processing point means that the energy beam incident angle (the angle between the energy beam and the normal to the surface of the processing point) is... When the surface of the second final partition has curvature, the normal direction of the processing point will change with the surface curvature. The adjustment amount needs to be calculated to maintain the incident angle of the energy beam. Secondly, the adjustment calculation method is determined, using the formula "incident angle adjustment = arcsin(surface curvature × neighborhood radius)", where the neighborhood radius is the point cloud range around the processing point used to calculate the normal direction. Based on the scanning accuracy of the 3D measuring equipment mentioned above (0.05mm), the neighborhood radius is set to 1mm (this size can cover enough point cloud normals without causing normal deviation due to excessive range); then, the high stress area on the left side of the hydraulic support column (the second final zone, surface curvature) is used as the basis for the adjustment. Taking the surface curvature as an example, the calculation is performed. Substituting the neighborhood radius of 1mm into the formula, we obtain the incident angle adjustment amount as follows: Finally, the incident angle was adjusted, and the initial energy beam incident angle in the high-stress region on the left side of the basic parameter set was... Based on the calculated adjustment amount Adjust the incident angle of the energy beam to Furthermore, the laser head posture is controlled in real time through the five-axis linkage system of the processing equipment (such as the THK five-axis processing platform) to ensure that the energy beam incident angle at each processing point is the adjusted angle and that the energy beam is always perpendicular to the surface.

[0111] In this embodiment of the application, based on the partition area Determining the processing path includes: First, dividing the area into zones, based on the area range of the second final zone mentioned above ( ) and 50 sets of processing experimental data for different area zones (comparing the processing uniformity of three processing paths: serpentine, spiral, and parallel lines), to determine the correspondence between area zones and processing paths: zone area A serpentine machining path is used (the serpentine path for small-area partitions has no obvious idle stroke, resulting in excellent machining uniformity). Parallel line processing paths are used (parallel line path planning is simple and efficient for medium-sized zones), and the zone area is... A spiral processing path is adopted (for large-area partitions, the spiral path can expand from the center outwards to avoid edge accumulation); secondly, the partition area of ​​the target partition is determined. Taking the second final partition of the hydraulic support column as an example, the partition area of ​​the left high-stress zone is... The area of ​​the first easily worn zone is The area of ​​the middle regular zone is Then, match the machining path, left high stress area ( ) and the first wear zone ( All belong to Therefore, a serpentine processing path was chosen for the specified range, with the intermediate regular area ( )belong Therefore, a spiral machining path was chosen for the given range. Finally, the machining path parameters were refined. The path spacing (distance between adjacent scan lines) of the serpentine machining path was set to 0.8 mm (based on a machining layer width of 1 mm to ensure 20% overlap between adjacent machining paths and avoid gaps where fusion does not occur). The starting radius of the spiral machining path was set to 5 mm (starting from the center of the partition to ensure sufficient machining in the central area). The scanning speed was set to 5 mm / s (based on the material delivery rate and energy source power matching in the previous basic parameter set to avoid insufficient machining due to excessive speed).

[0112] Furthermore, in the laser cladding scenario applied to this embodiment, when the tilt angle increases, the ratio of material delivery rate to energy source power is increased, including: First, clarifying the values ​​of each parameter in the mathematical expression of the ratio; selecting Fe-Cr-B-Si alloy powder commonly used in hydraulic supports as the processing material; conducting 20 sets of matching experiments with different material delivery rates and energy source power (material delivery rate 5-15 g / min, energy source power 1500-2500 W); determining the constant K=225 related to the processing material (unit: W•min / g; this value ensures that the density of the processed layer is ≥98% when the powder delivery and power are matched); and fitting an increasing function based on the processing experimental data at different tilt angles (0°-60°). ( (Unit: °), experiments have verified that this function can compensate for energy and powder changes at tilt angles of 0°-60°, such as... =0° f(0)=1, α=30° f(30)=1+0.0067×30=1.2, α=60° f(60)=1+0.0067×60=1.4; then, taking the left high stress zone (tilt angle 30°, material conveying rate v=8g / min in the basic parameter set) as an example, the calculation is performed with K=225, v=8g / min, Substituting 30° (f(30)=1.2) into the formula, we get the energy source power P=225×8×1.2=2160W; Finally, we adjust the material conveying rate and energy source power. The energy source power of the high stress zone on the left side of the basic parameter set is 1800W. Based on the calculation results, we adjust the energy source power to 2160W, and keep the material conveying rate unchanged at 8g / min. This adjusts the ratio of the two from 1800W / 8g / min to 2160W / 8g / min, thus increasing the ratio when the tilt angle increases. For the first wear-prone zone with a tilt angle of 0° (material conveying rate of 7g / min in the basic parameter set), we substitute... =0°(f(0)=1), we get P=225×7×1=1575W, and adjust the 1600W in the basic parameter set to 1575W to ensure that the ratio of different tilt angle zones is appropriate.

[0113] In this embodiment, generating a set of processing parameters matching the geometric features of each partition includes: First, integrating the adjustment results of each parameter. For each second final partition, the energy beam incident angle, processing path, material delivery rate, and energy source power are dynamically adjusted, and all adjusted parameters are collected. Second, taking the left high-stress zone as an example, the parameters are integrated. The adjusted energy beam incident angle is 1.7°, the processing path is serpentine (path spacing 0.8mm, scanning speed 5mm / s), the material delivery rate is 8g / min, and the energy source power is 2160W. These parameters are combined into the processing parameter set for the left high-stress zone. Then, the parameters of other partitions are integrated in the same way, such as the first easily worn zone (tilt angle 0°, surface curvature). The adjusted parameters are as follows: energy beam incident angle 0.6° (calculated as arcsin(0.01×1)=0.6°), serpentine processing path (path spacing 0.8mm), material delivery rate 7g / min, and energy source power 1575W. These parameters are combined to form the processing parameter set for this partition. Finally, the consistency of the parameter set is verified by checking whether the values ​​of parameters with the same meaning (such as scanning speed and path spacing) are consistent across all partitions to ensure that the parameters are consistent throughout the document. At the same time, the parameter set is simulated using virtual simulation software (such as SimufactWelding) to verify whether the processing layer thickness and density meet the requirements. After the simulation is successful, the final processing parameter set is determined.

[0114] In the embodiments of this application, this application solves the problem that the traditional fixed incident angle cannot be adapted to curved surface processing, resulting in low laser energy utilization and uneven processing layer thickness. After adjustment, the laser energy utilization is significantly improved, the processing layer thickness deviation is greatly reduced, and defects such as incomplete fusion or over-fusion in curved surface areas are avoided, providing energy guarantee for subsequent processing quality.

[0115] In the embodiments of this application, this application solves the problem that the traditional single processing path cannot adapt to different area partitions, resulting in many empty strokes in small area partitions and uneven processing in large area partitions. After matching the corresponding path to different area partitions, the processing efficiency is improved, the uniformity of the processing layer is significantly improved, and the performance difference of the processing layer caused by improper path is avoided.

[0116] In the embodiments of this application, this application solves the problem of low density and insufficient thickness of the processing layer caused by powder slippage and laser reflection in the processing of inclined surfaces. By adjusting the ratio, the quality of the processing layer of the inclined surface is made to be the same as that of the horizontal surface, ensuring that the processing performance of different inclined angle zones is consistent and meeting the requirements of working conditions.

[0117] S6. Generate an adaptive partition control instruction set for controlling the processing equipment based on the processing parameter set.

[0118] In this embodiment, the adaptive partition control instruction set is a set of instructions that can drive the processing equipment to automatically switch processing parameters and adjust motion trajectory according to the geometric and working conditions of different second final partitions, and can be directly recognized and executed by the equipment control system.

[0119] In some embodiments, generating an adaptive partition control instruction set for controlling the processing equipment based on the processing parameter set includes:

[0120] The processing parameter set is converted into control commands for the processing equipment;

[0121] Based on the position of the second final partition in three-dimensional space, plan the processing path sequence of the processing equipment;

[0122] A set of control instructions is generated to move the machining platform and machining head to the second final partition according to the machining path sequence, and the corresponding set of machining parameters is configured.

[0123] In this embodiment, the control command is to convert parameters such as energy source power, material delivery rate, and motion requirements in the processing parameter set into code that conforms to the communication protocol of the processing equipment, and is the direct basis for the equipment to perform processing operations; the position in three-dimensional space is the three-dimensional coordinate range of the second final partition in the equipment coordinate system, which clarifies the specific location of the partition in the equipment processing space and provides a spatial reference for planning the processing path; the processing path sequence is the order in which the processing equipment processes each partition and the laser head movement trajectory within the partition, determined according to the three-dimensional position and working condition importance of the second final partition, taking into account both processing efficiency and quality.

[0124] In this embodiment, the processing platform is a mechanical structure used to fix the part to be processed and can realize multi-axis movement and attitude adjustment according to control commands. The motion accuracy affects the accuracy of the processing position. The processing head is the core execution component in the processing equipment that emits energy beams and transports processing powder. Its attitude and position need to be adjusted synchronously to ensure that the parameters are applied accurately.

[0125] In this embodiment, converting the processing parameter set into control instructions for the processing equipment includes: First, determining that the processing equipment adopts the ISO6983 standard G / M code protocol, which is a universal protocol for CNC equipment, ensuring instruction compatibility; Second, establishing a mapping relationship between parameters and instructions based on the equipment manual and 80 sets of parameter-instruction matching experiments, where the energy source power (P) corresponds to the M code "M03S×××" (S followed by the power value in W), and the material conveying rate (V) corresponds to the M code "M08F×××" (F followed by the material conveying rate in g / min), and scanning... The speed corresponds to the G-code "G01F×××" (F after the scan speed, in mm / s); then, taking the processing parameter set for the high-stress zone on the left (energy source power 2160W, material delivery rate 8g / min, scan speed 5mm / s) as an example, the energy source power 2160W is converted to "M03S2160", the material delivery rate 8g / min is converted to "M08F8", and the scan speed 5mm / s is converted to "G01F5"; finally, the converted instructions are imported into the equipment simulation system for verification to confirm that there are no syntax errors and the parameters are transmitted accurately, thus avoiding abnormal equipment execution.

[0126] In this embodiment, the processing path sequence of the processing equipment is planned according to the position of the second final partition in three-dimensional space, including: First, extracting the three-dimensional coordinate range of the second final partition, such as the high-stress area (X50-150mm, Y80-120mm, Z100-200mm) and the first easily worn area (X300-400mm, Y80-120mm, Z100-200mm); Second, setting the processing priority, with a priority coefficient of 1.5 for the high-stress area, 1.2 for the easily worn area, and 1.0 for the normal area, with higher coefficients indicating higher priorities. The earlier the processing begins, the more advanced the processing becomes. Then, the A* algorithm is used to plan the sequence, starting from the initial position of the equipment (X0Y0Z0), and a cost function is constructed (cost = idle travel distance / priority coefficient). The cost of the left high-stress zone is calculated to be 100, the first wear-prone zone to be 291.7, etc. The sequence is determined according to the cost from smallest to largest as "left high-stress zone → first wear-prone zone → middle normal zone → second wear-prone zone → right high-stress zone". Finally, the trajectory within the partition is refined. The left high-stress zone follows a serpentine path, generating trajectory points within the coordinate range, with an adjacent point spacing of 0.8mm to ensure coverage of the entire partition.

[0127] In this embodiment, generating a set of control instructions to move the machining platform and machining head to the second final partition according to the machining path sequence, and configuring the corresponding machining parameter set, includes: First, generating a machining platform movement instruction from the initial position (X0Y0Z0) to the starting point of the left high-stress zone (X50Y80Z150) using the rapid movement instruction "G00X50Y80Z150F500" (F500 is the movement speed, in mm / min); Second, generating a machining head posture instruction, with the energy beam incident angle of the left high-stress zone at 1.7°, ensuring accurate posture through the A-axis adjustment instruction "G68.2X50Y80Z150A1.7"; Then, combining the parameter instructions with... Movement and attitude commands are used to form the command segment for the left high-stress zone: “G00X50Y80Z150F500; G68.2X50Y80Z150A1.7; M03S2160; M08F8; G01X50Y120Z150F5; ……”. Then, other partition command segments are generated according to the same logic, and parameter switching commands are added between adjacent partitions (such as “M05; M09;” to turn off the laser and powder feeding, and then load new parameters). Finally, all command segments are integrated, with an initialization command “G21G90;” added at the beginning and a reset command “G00X0Y0Z0; M30;” added at the end, forming a complete adaptive partition control command set. The simulation system is then used to verify that there is no interference risk.

[0128] In the embodiments of this application, this application solves the problems of low efficiency and error-proneness of traditional manual instruction writing, ensuring that parameters are accurately converted into executable code for the device, and avoiding processing defects caused by instruction errors.

[0129] In this embodiment of the application, the final integration step is to generate a set of control instructions for the control processing platform and the processing head to move to the second final partition according to the processing path sequence and to configure the corresponding set of processing parameters. The outputs of the first two steps are integrated to form a set of instructions that can directly control the equipment. This step is closely connected with the set of processing parameters output in step S5 above, and together they complete the closed loop of "parameter-instruction-equipment control".

[0130] like Figure 2 The diagram shown is a functional block diagram of a hydraulic support laser cladding parameter optimization system based on adaptive partitioning provided in an embodiment of this application.

[0131] The adaptive partitioning-based hydraulic support laser cladding parameter optimization system 100 described in this application can be installed in an electronic device. Depending on the functions implemented, the adaptive partitioning-based hydraulic support laser cladding parameter optimization system 100 may include a geometric feature change point identification module 101, a temporary partition generation module 102, a final partition determination module 103, a basic parameter set matching module 104, a parameter dynamic adjustment module 105, and a partition control instruction set generation module 106. The module described in this application can also be called a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, and is stored in the memory of the electronic device.

[0132] In this embodiment, the functions of each module / unit are as follows:

[0133] The geometric feature change point recognition module 101 is used to acquire the three-dimensional model data of the hydraulic support component to be processed, and to identify the geometric feature change points on the surface of the component to be processed based on the three-dimensional model data.

[0134] The temporary partition generation module 102 is used to define an initial boundary point set based on the geometric feature change points, and aggregate surface regions with continuous curvature and spatial adjacency based on the region growth algorithm to generate a first temporary partition with multiple geometric features evenly distributed.

[0135] The final partition determination module 103 is used to merge or divide the first temporary partition according to the working conditions of the part to be processed to form a second final partition, the second final partition including a high stress concentration area and a wear-prone area;

[0136] The basic parameter set matching module 104 is used to match a basic parameter set from a preset parameter library for each of the second final partitions based on the geometric feature attributes of the second final partition and the working condition requirements.

[0137] The parameter dynamic adjustment module 105 is used to dynamically adjust the energy beam incident angle, processing path, material delivery rate and energy source power in the basic parameter set according to the specific geometric features of the second final partition, and generate a processing parameter set that matches the geometric features of each partition.

[0138] The partition control instruction set generation module 106 is used to generate an adaptive partition control instruction set for controlling the processing equipment based on the processing parameter set.

[0139] In this embodiment, the system is integrated into an industrial control computer or a cloud control platform, enabling real-time data interaction and control command issuance with the laser cladding equipment.

[0140] In the embodiments provided in this application, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0141] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0142] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0143] It will be apparent to those skilled in the art that this application is not limited to the details of the exemplary embodiments described above, and that this application can be implemented in other specific forms without departing from the spirit or essential characteristics of this application.

[0144] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0145] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application and are not intended to limit it. Although this application has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of this application without departing from the spirit and scope of the technical solutions of this application.

Claims

1. A method for optimizing laser cladding parameters of hydraulic supports based on adaptive partitioning, characterized in that, The method includes: Obtain the three-dimensional model data of the hydraulic support component to be processed, and identify the geometric feature change points on the surface of the component to be processed based on the three-dimensional model data; An initial set of boundary points is defined using the geometric feature change points. Based on the region growing algorithm, surface regions with continuous curvature and spatial adjacency are aggregated to generate a first temporary partition with multiple geometric features evenly distributed. The first temporary partition is merged or divided according to the working conditions of the part to be processed to form a second final partition. The second final partition includes a high stress concentration area and a wear-prone area, including: Obtain the finite element analysis stress cloud diagram and historical wear data of the part to be processed under working conditions; Based on the stress cloud diagram identified by the finite element analysis, if a first temporary partition spans multiple high stress concentration regions, then the first temporary partition is divided; if multiple first temporary partitions are located in the same high stress concentration region, then the first temporary partitions are merged. Based on the historical wear data, wear-prone areas are identified, and the boundaries of adjacent partitions are adjusted so that each wear-prone area is completely covered within a partition. If a wear-prone area is divided by a temporary boundary, the boundary is redrawn to ensure that the wear-prone area is merged into a partition. For each of the second final partitions, a basic parameter set is matched from a preset parameter library based on the geometric feature attributes of the second final partition and the operating condition requirements, including: Extract the geometric feature attributes of the second final partition, including surface curvature, tilt angle, and partition area; Obtain the working condition requirement attributes corresponding to the second final partition, wherein the working condition requirement attributes include wear resistance level and fatigue resistance level; The geometric feature attributes and working condition requirement attributes are used as joint query conditions to match the optimal set of basic parameters in the preset parameter library; Based on the specific geometric features of the second final partition, the energy beam incident angle, processing path, material delivery rate, and energy source power in the basic parameter set are dynamically adjusted to generate a processing parameter set that matches the geometric features of each partition. The dynamic adjustment includes: The adjustment amount of the energy beam incident angle is calculated based on the surface curvature to ensure that the energy beam is always perpendicular to the surface of the processing point; The processing path is determined based on the area of ​​the partition; As the tilt angle increases, the ratio of material conveying rate to energy source power increases, and the ratio of material conveying rate to energy source power is as follows: in, It is the power of the energy source. It is the material delivery rate. It is a constant related to the processed material. It is an increasing function that increases with the angle of inclination. It is the tilt angle; Based on the set of processing parameters, an adaptive partition control instruction set for controlling the processing equipment is generated.

2. The method for optimizing laser cladding parameters of hydraulic supports based on adaptive partitioning as described in claim 1, characterized in that, The process of acquiring the three-dimensional model data of the hydraulic support component to be processed, and identifying geometric feature change points on the surface of the component to be processed based on the three-dimensional model data, includes: The surface point cloud data of the part to be processed is acquired using a three-dimensional measurement device; The surface point cloud data is denoised and smoothed to generate preprocessed 3D model data; The surface curvature distribution of the part to be processed is calculated by processing the preprocessed three-dimensional model data based on the curvature change algorithm. Points in the surface curvature distribution whose curvature values ​​exceed a preset curvature threshold are identified as points of geometric feature change.

3. The method for optimizing laser cladding parameters of hydraulic supports based on adaptive partitioning as described in claim 1, characterized in that, The process involves defining an initial set of boundary points based on the geometric feature change points, aggregating surface regions with continuous curvature and spatial adjacency using a region growing algorithm, and generating multiple first temporary partitions with uniformly distributed geometric features, including: Define an initial set of boundary points based on the geometric feature change points, and execute a region growing algorithm based on the initial set of boundary points as constraints. The region growing algorithm aggregates surface regions with continuous curvature based on curvature similarity criteria and spatial adjacency criteria, generating several initial regions separated by the initial boundary point set; The boundaries between the initial regions are smoothed to generate a first temporary partition with multiple geometric features evenly distributed.

4. The method for optimizing laser cladding parameters of hydraulic supports based on adaptive partitioning as described in claim 1, characterized in that, The adjustment of the boundaries of adjacent partitions to ensure that each wear-prone area is fully covered within a partition includes: If a wear-prone area is divided by a temporary boundary, the boundary is redefined to ensure that the wear-prone area is merged into a single partition.

5. The method for optimizing laser cladding parameters of hydraulic supports based on adaptive partitioning as described in claim 1, characterized in that, The step of generating an adaptive partition control instruction set for controlling the processing equipment based on the processing parameter set includes: The processing parameter set is converted into control commands for the processing equipment; Based on the position of the second final partition in three-dimensional space, plan the processing path sequence of the processing equipment; A set of control instructions is generated to move the machining platform and machining head to the second final partition according to the machining path sequence, and the corresponding set of machining parameters is configured.

6. A system for optimizing laser cladding parameters of hydraulic supports based on adaptive partitioning, characterized in that, The system includes: The geometric feature change point recognition module is used to acquire the three-dimensional model data of the hydraulic support component to be processed, and to identify the geometric feature change points on the surface of the component to be processed based on the three-dimensional model data. The temporary partition generation module is used to define an initial boundary point set based on the geometric feature change points, and aggregate surface regions with continuous curvature and spatial adjacency based on the region growth algorithm to generate a first temporary partition with multiple geometric features evenly distributed. The final partitioning module is used to merge or divide the first temporary partitions according to the working conditions of the parts to be processed, forming a second final partition. The second final partition includes high stress concentration areas and wear-prone areas, including: Obtain the finite element analysis stress cloud diagram and historical wear data of the part to be processed under working conditions; Based on the stress cloud diagram identified by the finite element analysis, if a first temporary partition spans multiple high stress concentration regions, then the first temporary partition is divided; if multiple first temporary partitions are located in the same high stress concentration region, then the first temporary partitions are merged. Based on the historical wear data, wear-prone areas are identified, and the boundaries of adjacent partitions are adjusted so that each wear-prone area is completely covered within a partition. If a wear-prone area is divided by a temporary boundary, the boundary is redrawn to ensure that the wear-prone area is merged into a partition. A basic parameter set matching module is used to match a basic parameter set from a preset parameter library for each of the second final partitions based on the geometric feature attributes of the second final partition and the operating condition requirements, including: Extract the geometric feature attributes of the second final partition, including surface curvature, tilt angle, and partition area; Obtain the working condition requirement attributes corresponding to the second final partition, wherein the working condition requirement attributes include wear resistance level and fatigue resistance level; The geometric feature attributes and working condition requirement attributes are used as joint query conditions to match the optimal set of basic parameters in the preset parameter library; A parameter dynamic adjustment module is used to dynamically adjust the energy beam incident angle, processing path, material delivery rate, and energy source power in the basic parameter set according to the specific geometric features of the second final partition, generating a processing parameter set that matches the geometric features of each partition. The dynamic adjustment includes: The adjustment amount of the energy beam incident angle is calculated based on the surface curvature to ensure that the energy beam is always perpendicular to the surface of the processing point; The processing path is determined based on the area of ​​the partition; As the tilt angle increases, the ratio of material conveying rate to energy source power increases, and the ratio of material conveying rate to energy source power is as follows: in, It is the power of the energy source. It is the material delivery rate. It is a constant related to the processed material. It is an increasing function that increases with the angle of inclination. It is the tilt angle; The partition control instruction set generation module is used to generate an adaptive partition control instruction set for controlling the processing equipment based on the processing parameter set.

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