Roller laser cladding repair method and system based on wear performance mapping

Abstract

This application discloses a method and system for laser cladding repair of rollers based on wear performance mapping, belonging to the field of roller repair technology. The method includes: acquiring three-dimensional morphological data of the roller surface to be repaired, identifying each wear area and extracting wear characteristic parameters; establishing a wear-performance mapping by combining historical forming data and wear characteristic parameters, and calculating the contribution weight of each wear area to forming performance; determining a first target compensation amount based on the contribution weight, and generating a laser cladding path and first process parameters; formulating a gradient cladding scheme using the laser cladding path and process parameters, controlling the laser cladding equipment to clad each wear area, using high-precision cold work die steel powder as the material, achieving precise repair and performance optimization of the roller surface. This scheme achieves precise gradient repair of wear areas, ensuring the restoration of roller surface geometry and forming performance, while allocating repair amount according to contribution weight, improving material utilization, reducing stress concentration, and enhancing repair efficiency and lifespan.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of roller repair, and particularly relates to a roller laser cladding repair method and system based on wear performance mapping. BACKGROUND

[0002] In industrial production, the roller as a key forming component, its surface state directly affects the precision and quality of the forming product. With the extension of service time, the roller surface changes in appearance due to wear, causing the forming performance to decline, so it is necessary to restore its geometric precision and surface performance through repair technology. The traditional repair method is difficult to accurately match the correlation between the wear area and the forming performance, resulting in insufficient performance recovery or over-repair of the roller after repair, and an accurate repair technology based on three-dimensional topographic data and performance mapping is urgently needed.

[0003] The existing roller repair technology usually detects the wear area manually, sets fixed cladding paths and process parameters based on experience, and realizes surface reconstruction through single-layer uniform cladding. The specific steps include: manually measuring the wear depth and range, selecting the cladding material according to the measurement results, setting process parameters such as laser power and scanning speed, and finally depositing the repair layer through a laser cladding device.

[0004] The existing technology does not establish a quantitative mapping relationship between wear characteristics and forming performance, which makes it difficult to distinguish the influence of different wear areas on the forming performance during repair, and it is easy to appear the problems of insufficient compensation in key areas or excessive cladding in non-key areas. At the same time, fixed process parameters are difficult to adapt to the gradient changes of the wear area, and the uniformity of the repair layer performance is poor, which affects the service life of the roller and the stability of the forming product. SUMMARY

[0005] In order to overcome the above-mentioned defects, the present application is proposed to solve or at least partially solve the technical problems that the existing technology does not establish a quantitative mapping relationship between wear characteristics and forming performance, which makes it difficult to distinguish the influence of different wear areas on the forming performance during repair, and it is easy to appear the problems of insufficient compensation in key areas or excessive cladding in non-key areas. At the same time, fixed process parameters are difficult to adapt to the gradient changes of the wear area, and the uniformity of the repair layer performance is poor, which affects the service life of the roller and the stability of the forming product.

[0006] In a first aspect, the present application provides a roller laser cladding repair method based on wear performance mapping, the method comprising: Obtaining three-dimensional topographic data of the surface of the roller to be repaired, identifying each wear area based on the three-dimensional topographic data and extracting corresponding wear characteristic parameters; Historical forming data of the roller to be repaired is obtained. Based on the three-dimensional morphology data, historical forming data and wear characteristic parameters, wear and performance mapping of each wear area is established, and the contribution weight of each wear area to forming performance is calculated based on the wear and performance mapping. The first target compensation amount for each wear area is determined based on the contribution weight of each wear area, and the laser cladding path and first process parameters for each wear area are generated based on the first target compensation amount. Based on the laser cladding path and the first process parameters, a gradient cladding scheme is determined for each wear area, and the laser cladding equipment is controlled to perform laser cladding on each wear area based on the gradient cladding scheme; wherein, the material used for laser cladding is high-precision cold work die steel powder.

[0007] In a second aspect, the present invention provides a roller laser cladding repair system based on wear performance mapping, the system comprising: The wear area identification module is used to acquire three-dimensional morphological data of the surface of the roller to be repaired, identify each wear area based on the three-dimensional morphological data, and extract the corresponding wear feature parameters. The weight determination module is used to acquire historical molding data of the roller to be repaired, establish wear and performance mapping of each wear area based on the three-dimensional morphology data, historical molding data and wear characteristic parameters, and calculate the contribution weight of each wear area to molding performance based on the wear and performance mapping. The cladding parameter determination module is used to determine the first target compensation amount of each wear area based on the contribution weight of each wear area, and to generate the laser cladding path and the first process parameters of each wear area based on the first target compensation amount. The laser cladding module is used to determine the gradient cladding scheme for each wear area based on the laser cladding path and the first process parameters, and to control the laser cladding equipment to perform laser cladding on each wear area based on the gradient cladding scheme; wherein, the material used for laser cladding is high-precision cold work die steel powder.

[0008] In a third aspect, an electronic device is provided, comprising a processor, a memory, and a program or instructions stored in the memory and executable on the processor, the program or instructions being loaded and run by the processor to perform the steps of the aforementioned roller laser cladding repair method based on wear performance mapping.

[0009] In a fourth aspect, a computer-readable storage medium is provided, wherein a plurality of program codes are stored therein, the program codes being adapted to be loaded and run by a processor to perform the steps of the above-described roller laser cladding repair method based on wear performance mapping.

[0010] The above-described technical solutions of the present invention have at least one or more of the following beneficial effects: In implementing the technical solution of this invention, precise compensation and gradient repair of the worn area can be achieved, ensuring uniform deposition of the cladding material, continuous wheel surface profile, and restoration of the roller's original geometric accuracy and forming performance. Simultaneously, the repair amount can be allocated according to the actual contribution weight of each worn area, improving material utilization, reducing excessive cladding and localized stress concentration, and enhancing repair efficiency and service life. Attached Figure Description

[0011] The disclosure of this invention will become more readily understood with reference to the accompanying drawings. It will be readily understood by those skilled in the art that these drawings are for illustrative purposes only and are not intended to limit the scope of protection of this invention. Furthermore, similar numbers in the drawings are used to denote similar components, wherein: Figure 1 This is a schematic diagram of the main steps of a roller laser cladding repair method based on wear performance mapping according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the main steps of a roller laser cladding repair method based on wear performance mapping according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the main structure of a roller laser cladding repair system based on wear performance mapping according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0012] Some embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0013] In the description of this invention, "module" and "processor" can include hardware, software, or a combination of both. A module can include hardware circuitry, various suitable sensors, communication ports, memory, and may also include software components, such as program code, or a combination of software and hardware. A processor can be a central processing unit, microprocessor, image processor, digital signal processor, or any other suitable processor. The processor has data and / or signal processing capabilities. The processor can be implemented in software, in hardware, or a combination of both. Non-transitory computer-readable storage media include any suitable medium capable of storing program code, such as magnetic disks, hard disks, optical disks, flash memory, read-only memory, random access memory, etc. The term "A and / or B" means all possible combinations of A and B, such as only A, only B, or A and B. The terms "at least one A or B" or "at least one of A and B" have a similar meaning to "A and / or B" and can include only A, only B, or A and B. The singular terms "a" or "this" can also include plural forms.

[0014] See appendix Figure 1 , Figure 1 This is a schematic flowchart illustrating the main steps of a roller laser cladding repair method based on wear performance mapping according to an embodiment of the present invention. Figure 1 As shown, a roller laser cladding repair method based on wear performance mapping in an embodiment of the present invention mainly includes the following steps S101-S104.

[0015] Step S101: Obtain three-dimensional morphological data of the surface of the roller to be repaired, identify each wear area based on the three-dimensional morphological data and extract the corresponding wear feature parameters.

[0016] Rollers to be repaired are roller components that have worn out after long-term service in roll forming operations. These components need to be repaired using processes such as laser cladding to restore their original working contour accuracy.

[0017] Three-dimensional topography data is the three-dimensional geometric information of the roller surface acquired by measuring equipment such as three-dimensional laser scanners, optical profilometers, or structured light sensors.

[0018] Wear areas are localized areas on the roller surface where there is obvious wear, dents, or material loss. These areas significantly affect the forming performance of the roller and are the key areas for repair work.

[0019] Wear characteristic parameters are specific indicators used to quantitatively characterize the morphological features of wear areas, including height deviation, indentation depth, and surface curvature.

[0020] High-precision 3D scanning is performed on the surface of the roller to be repaired. Elevation data from different angles of the wheel surface are collected using structured light scanning or laser contour scanning equipment, forming 3D topographic data covering the entire wheel surface. Simultaneously, the spatial coordinates and surface height information of each measuring point on the wheel surface are recorded. Subsequently, noise filtering and smoothing are performed on the original 3D topographic data to eliminate outliers and random measurement errors. Coordinate unification and spatial registration are also performed on data from different scanning perspectives to ensure the continuity and consistency of the overall wheel surface morphology. Based on this, by comparing the current 3D topographic data of the wheel surface with the ideal design contour or a preset reference contour, the local height deviation of each measuring point is calculated. The wheel surface is then divided into regions based on the height deviation threshold, and continuous regions with heights significantly lower than the design contour are identified as wear areas. Further local depression analysis is performed on the identified preliminary wear areas, calculating the depression depth and area distribution of each region. Simultaneously, the curvature of the surface is calculated to obtain the principal curvature and higher-order curvature changes, thereby reflecting the local morphological undulations of the wheel surface. For each wear area, specific wear characteristic indicators are further extracted: first, the height deviation indicator, which quantifies the degree of material loss by calculating the average and maximum deviations of each measuring point within the area; second, the indentation depth indicator, which calculates the indentation depth distribution by the height difference between local depressions and the surrounding area, reflecting the severity of local indentations on the wheel surface; and third, the surface curvature indicator, which characterizes the undulation features of the wheel surface by fitting the local curved surfaces of measuring points within the area and calculating the principal curvature and curvature changes. Finally, the height deviation, indentation depth, and curvature indicators of each wear area are integrated to generate wear characteristic parameters corresponding to each wear area.

[0021] Based on the above technical solution, optionally, the identification of each wear region and extraction of corresponding wear feature parameters based on the three-dimensional topography data includes: Point cloud preprocessing is performed on the three-dimensional topography data to obtain the point cloud data of the first surface of the roller to be repaired; Based on point cloud segmentation and surface fitting, wear regions are identified from the first surface point cloud data of the roller to be repaired, and the boundary information of each wear region is obtained. Each wear region is then determined based on the boundary information. Height deviations of each wear zone are calculated by point cloud fitting and local analysis. Based on point cloud depression recognition and depth analysis, the depression depth of the boundary information is calculated to obtain the depression depth data of each wear area; Surface curvature is calculated based on surface fitting and curvature analysis to obtain surface curvature data for each wear region; Wear characteristic parameters are determined based on the height deviation data, indentation depth data, and surface curvature data.

[0022] In this scheme, the first surface point cloud data is a set of points obtained after performing a three-dimensional scan or measurement on the surface of the roller to be repaired. These point clouds contain the three-dimensional spatial coordinate information of each sampling point on the roller surface, namely the X, Y, and Z coordinates.

[0023] Boundary information is derived from the point cloud data of the first surface through point cloud segmentation and surface fitting, identifying the boundary contours of each wear region. This includes the spatial location of each wear region on the wheel surface, its contour coordinates, and the boundary lines with adjacent regions, primarily used to define the spatial extent and specific shape of each wear region.

[0024] Height deviation data is the difference between the actual wheel surface height and the reference or target wheel surface height in each wear area. It is usually measured in micrometers or millimeters and can visually reflect the extent of bulges or depressions on the wheel surface caused by wear or long-term use.

[0025] Indentation depth data is the numerical value of the depth of a localized indentation within a worn area; specifically, it is the maximum vertical distance between the wheel surface and the surrounding unworn area. It is primarily used to describe the specific characteristics of localized pits or grooves within a worn area, helping to determine the severity of localized wear in that area.

[0026] Surface curvature data reflects the curvature characteristics of each wear area surface in three-dimensional space, including core parameters such as principal curvature, mean curvature, or Gaussian curvature. It is used to accurately represent the degree of curvature and the trend of change of the wheel surface shape.

[0027] To acquire the three-dimensional topography of the roller surface to be repaired, spatial coordinate data of the roller surface can be obtained through methods such as laser scanning, structured light measurement, or high-precision three-dimensional probe scanning. The acquired discrete point set is then preprocessed, primarily including removing measurement noise, filling in missing points, smoothing local outliers, and unifying the coordinate system. This generates complete, continuous, and usable first surface point cloud data for subsequent calculations. This point cloud data not only contains the three-dimensional position information of each sampling point on the roller surface but also clearly reflects the surface's microscopic unevenness and wear characteristics, laying the foundation for subsequent wear area identification.

[0028] Based on the first surface point cloud data, and combining point cloud segmentation and surface fitting techniques, the wheel surface is locally partitioned to accurately identify areas that may be worn. Specifically, by detecting changes in surface normal vectors, local curvature anomalies, or point cloud density variations, the changes in wheel surface morphology are determined, and the contour range of potential wear areas is identified. Then, through three-dimensional surface fitting calculations, smooth boundary lines for each region are obtained, thus acquiring the boundary information of each wear area. This boundary information clarifies the spatial location and extent of each wear area on the wheel surface and provides a reliable reference for subsequent fine feature extraction.

[0029] For wheel surface points within the boundary information range, height deviation analysis is conducted to calculate the difference between the actual wheel surface height and the height of the reference geometric surface or target wheel surface, generating height deviation data for each wear area. In this process, by combining local surface fitting and neighborhood point difference calculation, the vertical deviation of each sampling point is quantified, thereby accurately characterizing the overall wear fluctuations of the wheel surface and providing solid data for assessing the severity of wheel surface wear.

[0030] Based on this, the focus is on identifying and analyzing the depth of depressions within the wear area. By extracting points below the horizontal plane of the surrounding surface within the boundary range, the maximum vertical depth and average depression depth of these points are calculated to obtain depression depth data for each wear area. This data can clearly depict the depth and distribution characteristics of local pits or grooves, helping to determine the degree of local wear concentration and clarify specific repair needs.

[0031] Curvature analysis was performed on the wheel surface within the boundary area. By fitting a local three-dimensional surface, key parameters such as principal curvature, average curvature, or Gaussian curvature were calculated to obtain surface curvature data for each wear region. Curvature data can intuitively reflect the degree of bending and unevenness patterns of the wheel surface morphology, effectively distinguishing different types of wear, such as uniform wear, grooved wear, or localized bulges, providing strong support for subsequent optimization of repair paths and adjustment of compensation amounts. Finally, the height deviation data, indentation depth data, and surface curvature data were comprehensively processed to generate wear characteristic parameters for each wear region.

[0032] This solution enables precise identification and quantitative characterization of roller wear areas, providing a high-precision data foundation for subsequent compensation calculations and cladding path planning. It effectively reduces misjudgments and over-repair, improves repair consistency and surface quality, and extends the service life of the rollers.

[0033] Step S102: Obtain historical molding data of the roller to be repaired, establish wear and performance mapping of each wear area based on the three-dimensional morphology data, historical molding data and wear characteristic parameters, and calculate the contribution weight of each wear area to molding performance based on the wear and performance mapping.

[0034] Historical forming data refers to the forming process data recorded during the past production and use of the roller to be repaired. This data covers key information such as rolling process conditions, applied pressure and torque, roller displacement trajectory, sheet deformation response, springback, and sheet stress distribution.

[0035] Wear-performance mapping establishes a correlation or functional relationship between quantified wear characteristics of various wear regions of the roller, such as height deviation, indentation depth, and surface curvature, and corresponding forming performance deviations, such as local thickness deviation, springback deviation, or trajectory deviation. This mapping can be used to predict the specific impact of each wear region on the forming result.

[0036] Contribution weight refers to the relative influence of each wear area on the overall molding performance deviation, and the numerical value reflects the contribution of the wear in that area to the molding quality.

[0037] Historical molding data can be retrieved from the database. The raw data is then filtered and smoothed to remove noise and abnormal measurement points from the sensors, ensuring data accuracy. Following this, the processed historical molding data is spatially registered with the roller's 3D morphology data, mapping each molding measurement point to the wheel surface's 3D coordinates. This ensures a precise match between the historical performance information and geometric features of each region of the wheel surface.

[0038] Based on this, wear characteristic parameters such as height deviation, indentation depth, and surface curvature of each wear area on the wheel surface are integrated at the regional level with historical forming performance data of the corresponding locations to form a local performance deviation sequence and wear feature vector specific to each wear area. By analyzing the numerical correlation between the wear feature vector of each wear area and the local performance deviation sequence, a mapping relationship between changes in wear indicators and changes in performance deviation is established, that is, wear-performance mapping. This mapping can quantitatively characterize the impact of each wear area on forming performance under the current wear state.

[0039] Using the established wear-performance mapping, performance response calculations are performed for each wear region. Local performance impact values ​​are weighted and aggregated based on region area or historical usage frequency, while also considering the spatial coupling effect of adjacent wear regions to correct for local interactive effects. Finally, the contribution weight of each wear region to the overall molding performance is obtained.

[0040] Based on the above technical solution, optionally, a wear-performance mapping for each wear region can be established based on the three-dimensional morphology data, historical molding data, and wear characteristic parameters, including: Based on the historical molding data, pressure, displacement and trajectory analysis are performed to obtain the pressure deviation sequence, displacement deviation sequence and trajectory deviation sequence of the overall surface area of ​​the roller to be repaired, and a comprehensive performance deviation sequence is generated based on the pressure deviation sequence, displacement deviation sequence and trajectory deviation sequence. Based on wear characteristic parameters, geometric analysis, local depression analysis and curvature analysis are performed to obtain the height deviation index, depression depth index and surface curvature index of each wear area. Based on the height deviation index, depression depth index and surface curvature index, a multidimensional wear feature vector of each wear area is generated. Based on the spatial location of the first surface point cloud data, the comprehensive performance deviation sequence is assigned to each wear region to obtain the local performance deviation sequence of each wear region; The wear-performance mapping is obtained by performing feature association and mapping modeling on the local performance deviation sequence of each wear region and the multidimensional wear feature vector.

[0041] In this solution, the overall surface area refers to the complete working surface range of the roller to be repaired during the forming operation.

[0042] The pressure deviation sequence is a numerical sequence formed by arranging the difference between the actual molding pressure and the corresponding process reference pressure recorded in the historical molding process, according to the molding time or molding position, to reflect the deviation of the overall stress state of the roller surface.

[0043] The displacement deviation sequence is a sequence of displacement deviations formed by organizing the differences between the actual displacement trajectory and the theoretical displacement trajectory of the roller or workpiece in the historical forming process according to time or space order. It is used to characterize the offset characteristics of the roller forming accuracy as the process changes.

[0044] The trajectory deviation sequence is a sequence of deviations formed by the spatial offset of the roller running trajectory or workpiece forming trajectory relative to the preset trajectory during the forming process, according to the order of the forming path. It is used to reflect the stability and geometric consistency of the roller movement path.

[0045] The comprehensive performance deviation sequence is a unified performance deviation sequence generated by first aligning the pressure deviation sequence, displacement deviation sequence, and trajectory deviation sequence in time or space, and then according to a preset fusion rule. It is used to characterize the degree of deviation of the comprehensive performance of the roller during the forming process.

[0046] The height deviation index is the average or extreme deviation of the actual surface height of the roller relative to a reference surface or ideal profile within a single wear area. It is used to quantify the height variation characteristics of that area caused by wear.

[0047] The pit depth index is the vertical distance of a local lowest point in a wear area relative to the periphery of that area or a reference surface. It is used to describe the severity of local pits or grooves within the wear area.

[0048] The surface curvature index is a curvature characteristic parameter obtained by fitting the surface of the wear area. It is used to reflect the degree of surface curvature and the trend of morphological change in the area.

[0049] Multidimensional wear feature vectors are vectorized data that combine height deviation index, indentation depth index, and surface curvature index according to a unified dimensional structure to form a comprehensive wear state of a single wear area.

[0050] Spatial location refers to the spatial coordinate range or geometric location identifier of the wear area in the point cloud data of the first surface, which is used to establish the spatial correspondence between the wear area and the forming performance data.

[0051] The local performance deviation sequence is a performance deviation subsequence assigned to the corresponding wear area after dividing the comprehensive performance deviation sequence according to the spatial location of the wear area. It is used to characterize the local influence characteristics of a single wear area on the molding performance deviation.

[0052] Collect molding record data corresponding to multiple historical molding processes of the roller to be repaired. This historical molding data includes molding pressure data, roller displacement data, and actual running trajectory data of the roller recorded in the molding sequence. Each data item has corresponding molding position or molding time identification information to facilitate subsequent data alignment and matching.

[0053] Based on this, the first step is to perform working condition alignment processing on these historical molding data, matching the data in the same molding stage or the same molding position in different molding batches one by one, to ensure that the pressure data, displacement data and trajectory data are consistent on the time axis or spatial axis, laying the foundation for subsequent deviation calculation.

[0054] Using preset standard forming parameters as a benchmark, the difference between the actual pressure value and the benchmark pressure value is calculated for each forming position to obtain the pressure deviation corresponding to that forming position. All pressure deviations are then arranged according to the forming sequence to generate a pressure deviation sequence acting on the entire surface area of ​​the roller to be repaired. Simultaneously, deviation calculation is performed: for each forming position, the actual displacement value is compared with the theoretical displacement value, and the displacement offset is calculated and arranged according to the forming sequence to form a displacement deviation sequence. At the same time, the actual running trajectory is spatially compared with the preset forming trajectory to calculate the trajectory offset at each forming position, generating a trajectory deviation sequence.

[0055] After obtaining the pressure deviation sequence, displacement deviation sequence, and trajectory deviation sequence, the three types of sequences are synchronously aligned according to the forming position. The pressure deviation, displacement deviation, and trajectory deviation corresponding to the same forming position are then fused and calculated to obtain a comprehensive performance deviation sequence that characterizes the degree of deviation in forming performance of the overall surface area of ​​the roller. Within each determined wear area, the surface morphology data of the corresponding area is extracted, and the spatial height distribution of the wear area surface is calculated and analyzed point by point.

[0056] After obtaining the height deviation data corresponding to the wheel surface sampling points in each wear area, a regional-level summary processing is carried out for all height deviation values ​​within the same wear area. Specifically, this involves statistically calculating the height deviation of all sampling points within the wear area, extracting the maximum height deviation, minimum height deviation, and the average or root mean square value of the height deviation. These parameters are used to characterize the overall lifting of the wheel surface relative to the reference geometric surface or the degree of wear in that area. By summarizing the distribution range and statistical characteristics of the height deviation, the discrete height deviation data is transformed into a height deviation index that reflects the overall geometric deviation of the wear area, allowing this index to serve as a quantitative basis for subsequent wear assessment and compensation calculations.

[0057] After obtaining the indentation depth data for each wear area, multiple indentation points or sub-regions identified within the same wear area are centrally analyzed and processed. Statistical analysis is performed on the indentation depth data within this wear area to calculate the maximum indentation depth, average indentation depth, and indentation depth distribution density. These data are used to describe the severity and concentration of localized pit or groove wear. By integrating the above statistical results, the indentation depth data is transformed into an indentation depth index reflecting the degree of localized material loss in the wear area, allowing this index to intuitively demonstrate the potential impact of localized wear on the molding contact state.

[0058] Based on the obtained surface curvature data of the wear area, the curvature values ​​of each sampling point within the same wear area are summarized and organized at the regional level. Specifically, statistical analysis is performed on the principal curvature, average curvature, or Gaussian curvature data within the wear area to extract the average level and fluctuation range of curvature changes within the area. This information is used to measure the degree of bending and morphological stability of the wheel surface in that area. By comprehensively organizing the curvature distribution characteristics, the discrete curvature data is transformed into surface curvature indices reflecting the surface morphological changes of the wear area, thus providing a reliable basis for distinguishing different wear patterns and for the continuous design of subsequent cladding paths.

[0059] Through the above series of processes, the height deviation data, indentation depth data, and surface curvature data within each wear region are transformed into corresponding height deviation indices, indentation depth indices, and surface curvature indices, respectively. What were originally scattered, point-level, distribution-level data are transformed into region-level, directly comparable wear characteristic parameters after processing. After obtaining the height deviation indices, indentation depth indices, and surface curvature indices, the height deviation sub-features, indentation depth sub-features, and surface curvature sub-features corresponding to the same wear region are spliced ​​or mapped according to a preset order to construct a multidimensional wear feature vector for that wear region.

[0060] Based on the spatial location range of each wear region in the first surface point cloud data, the coordinate interval corresponding to each wear region in the overall surface region of the roller is determined, realizing the spatial association between the local region and the overall surface. On this basis, the performance deviation data corresponding to each forming position in the comprehensive performance deviation sequence is matched with the spatial coordinates in the first surface point cloud data to determine whether the surface position corresponding to the forming position falls within the spatial location range of a certain wear region.

[0061] For performance deviation data falling within the spatial range of the same wear area, the data is extracted from the comprehensive performance deviation sequence and then arranged according to the molding sequence to form a local performance deviation sequence corresponding to that wear area. Through the above processing, each wear area corresponds to a set of local performance deviation sequences, which can reflect the impact of that area on the overall molding performance during the historical molding process.

[0062] For each wear region, its corresponding multidimensional wear feature vector is mapped to a local performance deviation sequence to ensure that the wear feature parameters and performance deviations are consistent in spatial location and forming sequence, providing accurate data support for subsequent correlation analysis. Based on this, the correspondence between the changes in parameters of each dimension in the multidimensional wear feature vector and the changes in deviations in the local performance deviation sequence is compared to clarify the influence of different wear feature changes on local forming performance deviations. By fitting and summarizing the above correspondence, a correlation between changes in wear feature parameters and changes in forming performance deviations is established, forming a wear-performance mapping for each wear region.

[0063] In this scheme, the overall molding performance deviation and the local wear geometric characteristics are established in a corresponding relationship on the same spatial scale, so that wear is no longer just a morphological description, but is directly related to the actual molding pressure, displacement and trajectory performance, thereby improving the engineering effectiveness and pertinence of wear assessment.

[0064] Based on the above technical solution, optionally, the contribution weight of each wear region to the molding performance can be calculated based on the wear-performance mapping, including: Based on the wear and performance mapping, the performance response of the multidimensional wear feature vector of each wear region is calculated to obtain the predicted performance deviation value of each wear region under the current wear state. Based on the predicted performance deviation values, normalization is performed to obtain the relative performance impact of each wear region. The historical usage frequency of each wear area is obtained, and the relative performance impact is weighted and summarized based on the historical usage frequency to obtain the preliminary contribution value corresponding to each wear area. Based on the point cloud data of the first surface, the spatial proximity relationship of each wear region is determined. Based on the spatial proximity relationship, the initial contribution value is coupled and corrected to obtain the contribution weight of each wear region to the forming performance.

[0065] In this scheme, the performance deviation prediction value is the predicted deviation of a specific wear area from the molding performance under the current wear state, including molding performance dimensions such as pressure distribution, molding displacement stability, and motion trajectory consistency.

[0066] The relative performance impact is the predicted performance deviation of a specific wear area, and its relative impact across all wear areas.

[0067] Historical usage frequency refers to the number or percentage of times that molding load, contact pressure, and motion trajectory actually act on a specific wear area during past molding production processes.

[0068] The preliminary contribution value is the weighted influence of a specific wear area on the overall molding performance degradation without considering the effects of spatial coupling.

[0069] After obtaining the multidimensional wear feature vectors corresponding to each wear region, for each wear region, its multidimensional wear feature vector is first used as an input variable and substituted into the pre-established mapping relationship between wear and molding performance. This wear-performance mapping relationship is obtained by performing correlation modeling on the molding pressure distribution, molding displacement response, and molding stability index under different wear modes during historical molding processes, which can accurately characterize the response law of changes in wear feature parameters to changes in molding performance.

[0070] In practice, for each wear area, its corresponding height deviation characteristics, indentation depth characteristics, and surface curvature characteristics are combined according to a preset input order in the mapping relationship, and then substituted into the wear-performance mapping function to calculate the molding performance response result caused by the wear area under the current wear state. This response result is presented in the form of deviation from the ideal molding performance benchmark value, reflecting the degree of deviation caused by the wear area on the molding performance under the current wear conditions, thus obtaining the corresponding performance deviation prediction value. The performance deviation prediction value can be reflected in at least one of the following: molding force fluctuation amplitude, molding displacement offset, and degree of decrease in molding uniformity.

[0071] After obtaining the predicted performance deviation values ​​for all wear regions, in order to eliminate the incomparability caused by differences in dimensions and numerical ranges among different wear regions, it is necessary to perform uniform scaling on the predicted performance deviation values ​​for each wear region. In practice, a set containing the predicted performance deviation values ​​for all wear regions is first constructed, and then the maximum and minimum ranges of the predicted performance deviation values ​​are determined within this set.

[0072] Subsequently, using the maximum and minimum values ​​as normalization benchmarks, the predicted performance deviation values ​​for each wear region are proportionally mapped, converting the predicted performance deviation value for each wear region into a relative quantity within the same numerical range, forming the relative performance influence quantity corresponding to each wear region. The relative performance influence quantity can characterize the relative strength of the influence of different wear regions in the overall molding performance degradation process. After obtaining the relative performance influence quantity of each wear region, the importance of the wear region is further corrected by introducing historical usage frequency. Historical usage frequency is derived from the distribution of molding load, contact trajectory, and contact sequence on the mold surface in historical molding records. By statistically analyzing the number of times and duration of molding load actually applied to each surface region in different molding cycles, the historical usage frequency corresponding to each wear region can be obtained.

[0073] In the specific calculation, the relative performance impact of each wear area is weighted and summarized with its corresponding historical usage frequency. This allows the performance impact of the wear area to be considered in conjunction with its usage intensity in actual production, resulting in the preliminary contribution value for each wear area. The preliminary contribution value reflects the individual contribution of each wear area to the degradation of molding performance without considering inter-area interactions. After obtaining the preliminary contribution value for each wear area, the spatial distribution characteristics of the wear areas on the mold surface are further combined to perform a coupling correction. Specifically, the spatial coordinates of the mold surface are reconstructed based on the first surface point cloud data. Then, the spatial proximity relationships between different wear areas are determined according to the spatial positional relationships of the corresponding point sets of each wear area in the point cloud.

[0074] Based on this, for wear areas that are spatially adjacent or close together, the potential load superposition effect and local deformation coupling effect during the forming process are considered, and the corresponding preliminary contribution values ​​are jointly corrected. This correction process introduces a spatial proximity weight, allowing adjacent wear areas to influence each other in the contribution assessment, thus obtaining a corrected result that reflects the spatial coupling characteristics. Finally, based on the results after coupling correction, the contribution weight of each wear area to the overall forming performance is determined.

[0075] This solution can quantify the specific impact of each wear area on the overall forming performance, making the repair priority and compensation strategy more scientific and precise.

[0076] Step S103: Determine the first target compensation amount for each wear area based on the contribution weight of each wear area, and generate the laser cladding path and first process parameters for each wear area based on the first target compensation amount.

[0077] The primary target compensation amount is the initial laser cladding repair thickness or volume increment determined for each worn area based on its contribution weight to the overall forming performance. This compensation amount is used to compensate for performance deviations caused by wear in that area. This quantitative value guides the design of the deposition amount and layer thickness of the laser cladding material, ensuring that the repaired wheel surface accurately restores the preset geometric contour and forming performance.

[0078] The laser cladding path is the specific trajectory of the laser cladding equipment moving along the roller surface during repair operations. It includes core elements such as path spatial coordinates, scanning sequence, and directional planning. This path must fully cover the target wear area or its layered repair area to ensure uniform deposition of the cladding material and achieve precise filling of the wear area.

[0079] The first process parameter is the process setting item that needs to be strictly controlled when carrying out laser cladding operations. It covers key aspects such as laser power, scanning speed, powder feeding amount, cladding layer thickness, and interlayer spacing. It is used to ensure that the material is fully melted, firmly adhered, and the repair layer is uniform and dense during the cladding process, while meeting the expected contour accuracy and surface quality requirements of the wheel surface.

[0080] The contribution weight data of each wear area is obtained, and then the preliminary compensation thickness of each area is calculated based on the weight. Specifically, the contribution weight of a single wear area is multiplied by the overall wheel surface repair thickness or the designed compensation amount to obtain the first target compensation amount for that area. For areas with high contribution weights and severe wear, the first target compensation amount needs to be processed in layers, decomposing the total thickness into several gradient layers. The thickness of each layer is fine-tuned based on the height deviation and curvature index of the area to ensure that the compensation thickness is compatible with the continuity of the wheel surface geometry.

[0081] Based on the initial target compensation amount for each wear area, a laser cladding path can be further generated. The specific implementation steps are as follows: map the compensation thickness of a single wear area to the three-dimensional coordinates of the wheel surface, and plan the starting point, ending point, and path sequence of the laser scan based on the wheel surface curvature and the distribution of the compensation layer; determine the path interval and scanning overlap rate according to the compensation layer thickness to ensure uniform material deposition by the laser in the working area; for high curvature or concave areas, appropriately adjust the path density and scanning direction to avoid material accumulation or repair defects, and ensure uniform filling of the cladding material.

[0082] After path planning is completed, the first process parameters for each wear area are determined by combining the first target compensation amount and the laser cladding path. Specifically, the laser power is calculated based on the compensation layer thickness and wheel surface material characteristics to ensure sufficient melting of the substrate and cladding material; the powder feed rate is matched according to the path length, scanning speed, and laser power to achieve uniform adhesion of the cladding material; and the scanning speed and power distribution are fine-tuned based on the wheel surface curvature, gradient layer thickness, and area size to optimize the cladding temperature field, avoid local overheating or warping deformation, and ensure a tight bond between the cladding layer and the wheel surface substrate. Finally, the first target compensation amount, laser cladding path, and first process parameters for each wear area are output.

[0083] Based on the above technical solution, optionally, the laser cladding path and first process parameters for each wear area are generated based on the first target compensation amount, including: Based on the first surface point cloud data and the first target compensation amount, the local cladding range of each wear area is determined; Based on the local cladding range, path planning is performed to obtain the laser cladding path for each wear area; Based on the first target compensation amount, a layered calculation is performed to obtain the number of cladding layers in each wear area and the thickness distribution data of each layer. The corresponding laser power is calculated based on the thickness distribution data of each layer, and the power setting value of each layer is obtained. The scanning speed is calculated based on the thickness distribution data and power settings of each layer, and the scanning speed settings for each layer are obtained. The powder feeding amount is calculated based on the thickness distribution data of each layer, the power setting value, and the scanning speed setting value, and the powder feeding amount setting value of each layer is obtained. The power setting, scanning speed setting, and powder feed rate setting are integrated into the first process parameter for each wear zone.

[0084] In this scheme, the local cladding range is the surface of the roller to be repaired. For each wear area, the actual laser cladding coverage area is determined based on the target compensation amount, which is the spatial range of the surface area to be clad and repaired.

[0085] The laser cladding path is a specific movement trajectory planned for the laser cladding equipment within the local cladding area, used to guide the cladding head to evenly cover the wear area along a designated route.

[0086] The number of cladding layers refers to the number of times laser cladding is performed in a layered manner for each wear area to achieve the target compensation amount. Each cladding layer will form a cladding metal of corresponding thickness.

[0087] Thickness distribution data is the actual thickness information of each cladding layer distributed along the cladding path within the wear area, used to accurately control the amount of cladding material accumulated in each layer.

[0088] The power setting value is the laser output power value calculated based on the thickness distribution of each layer, which can ensure that the cladding material is fully melted and that the cladding layers are well bonded together.

[0089] The scanning speed setting is the speed at which the laser cladding head moves along each cladding path. Combined with the cladding layer thickness and laser power parameters, it ensures uniform deposition of the cladding material.

[0090] The powder feeding setting value is the required powder spraying rate and powder supply amount on each cladding path during the laser cladding process, ensuring that the thickness and forming quality of the cladding layer meet the design requirements.

[0091] After acquiring the first surface point cloud data of the roller to be repaired and the first target compensation amount for each wear area, the compensation amount is mapped along the wheel surface contour to the corresponding surface points based on the spatial range of each wear area in the point cloud, thereby determining the local cladding range of each wear area. During the mapping process, the wheel surface curvature and boundary extension range are calculated using the spatial coordinates of the point cloud. Simultaneously, the coverage area is expanded along the wheel surface normal in conjunction with the magnitude of the compensation amount, thus generating the actual surface area requiring cladding repair for each wear area. The data of the local cladding range is represented by the set of points or patches to be clad within each wear area, enabling precise marking of the spatial boundaries of the cladding operation.

[0092] After determining the local cladding range, path planning is performed for each wear area to obtain the laser cladding path. Path planning discretizes the local cladding range into continuous cladding trajectory points, and optimizes the path spacing based on the wheel surface curvature and boundary shape to ensure that the molten pool can uniformly cover the entire wear area during laser cladding. During path planning, the starting point, ending point, and direction of movement for each path are calculated by combining the wheel surface normal, curvature change, and flow characteristics of the cladding material, generating continuous laser trajectory data that covers all target areas. This data will be used to guide the laser cladding equipment to complete the movement along the predetermined route.

[0093] Based on the initial target compensation amount, layered calculations are performed on each wear area to obtain the number of cladding layers and the thickness distribution data of each layer. The layered calculation divides each wear area into several achievable uniform thickness layers along the wheel surface normal, according to the target compensation amount. The thickness distribution data of each layer is adjusted based on local depression depth and curvature variations to ensure the uniformity of cladding material deposition in different areas of the wheel surface. The thickness distribution data records the specific thickness value of each layer on the wheel surface, providing data support for subsequent calculations of laser power, scanning speed, and powder feed rate.

[0094] Based on the thickness distribution data of each layer, the corresponding laser power is calculated to obtain the power setting value for each layer. During the calculation process, the melting point, thermal conductivity, and molten pool size requirements of the laser cladding material are comprehensively considered. The laser output power is dynamically adjusted according to the thickness and area of ​​each layer to ensure that the molten pool can be fully melted and the bonding between cladding layers is stable. The power setting value is expressed as a continuous power value sequence along the path for each layer, which can be directly used as the input parameter for the laser controller.

[0095] The scanning speed is calculated by combining the thickness distribution data and power settings for each layer, resulting in the scanning speed setting value for each layer. The calculation of the scanning speed focuses on matching the required heat input of the molten pool with the laser power, while also considering the material deposition amount and surface flatness requirements. By adjusting the movement speed in different areas of the wheel surface, precise control of the uniformity of the cladding layer is achieved. The scanning speed settings form a continuous speed sequence along the path, which is used to actually control the movement state of the laser cladding head.

[0096] The powder feed rate is then calculated based on the thickness distribution data, power settings, and scanning speed settings for each layer, resulting in the powder feed rate setting for each layer. The powder feed rate calculation comprehensively considers laser power, molten pool heat capacity, and scanning speed to ensure that the powder supply matches the molten pool melting rate, thereby accurately achieving the target thickness for each layer. The powder feed rate setting is expressed as a sequence of powder spray rates along the cladding path, providing precise parameters for the accurate control of the cladding equipment. Finally, the power settings, scanning speed settings, and powder feed rate settings for each layer are integrated into the primary process parameters for each wear zone.

[0097] In this solution, the amount of material compensation and the cladding path of each wear area can be precisely controlled to ensure that the height and shape of the repaired wheel surface are uniform.

[0098] Step S104: Determine the gradient cladding scheme for each wear area based on the laser cladding path and the first process parameters, and control the laser cladding equipment to perform laser cladding on each wear area based on the gradient cladding scheme; wherein, the material used for laser cladding is high-precision cold work die steel powder.

[0099] The gradient cladding scheme needs to be planned separately for each wear area. The core is to combine the first target compensation amount, wheel surface curvature, and wear depth to formulate a specific execution process for layered laser cladding. The scheme must clearly define the thickness distribution, scanning sequence, path arrangement, and material deposition order of each cladding layer. The ultimate goal is to achieve a gradient distribution of thickness and heat input.

[0100] Laser cladding equipment is used for material deposition and melting on the surface of worn areas, and belongs to high-precision processing equipment. It includes a laser emission system, a laser scanning and positioning mechanism, a powder feeding device, and a motion control system.

[0101] High-precision cold work die steel powder is a special material for laser cladding repair. Its composition strictly follows the relevant standards and specifications for cold work die steel, and its particle size distribution is uniform and its purity meets the standards.

[0102] For the laser cladding paths already determined for each wear area, each path must first be segmented in the three-dimensional wheel surface coordinate system. Then, combined with the first target compensation amount, the layer thickness distribution of each wear area is calculated one by one. In practice, along the path direction, combined with the wheel surface curvature and local wear depth, the target compensation amount is divided into several gradient layers. The thickness of each layer is finely adjusted according to local height deviations and curvature changes. This ensures that the wheel surface profile is continuous and smooth after material deposition, and also effectively prevents excessive local thickness or depressions.

[0103] Based on layer thickness data and path segmentation information, a customized gradient cladding scheme is developed for each wear area. The scheme clearly defines the laser scanning sequence, path interval, and scanning overlap rate for each layer. Simultaneously, by considering the wheel surface curvature and gradient layer height, the scanning speed and powder feed rate are flexibly adjusted to ensure uniform deposition of the cladding material. For areas with significant curvature or local depressions, the path density is appropriately increased to ensure precise matching between the scanning direction and the contour normal direction, guaranteeing uniform coverage of the compensation layer and full fusion of the cladding material.

[0104] Operating the laser cladding equipment according to the gradient cladding scheme, the equipment strictly follows the path set in the scheme, controls the laser switch, and precisely feeds and melts high-precision cold-working die steel powder according to the scanning speed and power parameters of each layer, ensuring full fusion of the cladding material with the metal substrate of the wheel surface. During the cladding process, the laser power, scanning speed, and powder flow rate are continuously monitored in real time. If local curvature changes or thickness deviations are detected, the equipment parameters are finely adjusted in a timely manner to ensure that the thickness and surface quality of the cladding layer meet the design requirements. After each cladding layer is completed, the wheel surface undergoes temperature equalization and cooling operations to ensure tight bonding between each gradient layer, control thermal stress within a reasonable range, and effectively avoid quality problems such as cracking and warping.

[0105] Based on steps S101-S104 above, precise compensation and gradient repair of the worn area can be achieved, ensuring uniform deposition of the cladding material, continuous wheel surface profile, and restoration of the roller's original geometric accuracy and forming performance. Simultaneously, the repair amount can be allocated according to the actual contribution weight of each worn area, improving material utilization, reducing excessive cladding and localized stress concentration, and enhancing repair efficiency and service life.

[0106] See appendix Figure 2 , Figure 2 This is a schematic flowchart illustrating the main steps of a roller laser cladding repair method based on wear performance mapping according to an embodiment of the present invention. Figure 2As shown, a roller laser cladding repair method based on wear performance mapping in an embodiment of the present invention mainly includes the following steps S201-S208.

[0107] Step S201: Obtain three-dimensional morphological data of the surface of the roller to be repaired, identify each wear area based on the three-dimensional morphological data and extract the corresponding wear feature parameters.

[0108] Step S202: Obtain historical molding data of the roller to be repaired, establish wear and performance mapping of each wear area based on the three-dimensional morphology data, historical molding data and wear characteristic parameters, and calculate the contribution weight of each wear area to molding performance based on the wear and performance mapping.

[0109] Step S203: Determine the first target compensation amount for each wear area based on the contribution weight of each wear area, and generate the laser cladding path and first process parameters for each wear area based on the first target compensation amount.

[0110] Step S204: Determine the gradient cladding scheme for each wear area based on the laser cladding path and the first process parameters, and control the laser cladding equipment to perform laser cladding on each wear area based on the gradient cladding scheme; wherein, the material used for laser cladding is high-precision cold work die steel powder.

[0111] Step S205: Obtain the second surface point cloud data of the repaired roller, and extract the contour point cloud data corresponding to the working contour of the roller based on the second surface point cloud data.

[0112] Step S206: Based on the contour point cloud data, perform spatial registration with the preset target contour, calculate the radial contour offset and axial contour offset of the repaired roller, and generate contour deviation distribution data based on the radial contour offset and axial contour offset.

[0113] Step S207: Obtain the molding performance data of the repaired roller under standard molding conditions, and perform process response calculation based on the molding performance data to obtain the molding performance deviation result of the repaired roller.

[0114] Step S208: Map the contour deviation distribution data and molding performance deviation to the existing wear area, analyze the repair effect of each wear area, and obtain the performance verification results of each wear area.

[0115] In this embodiment, the second surface point cloud data is a set of spatial coordinates obtained by three-dimensional scanning of the roller surface after the first laser cladding repair is completed. It is used to reflect the actual shape and height change of the wheel surface after repair.

[0116] The working profile of a roller is the surface profile area of ​​the roller that actually participates in material processing during the forming process. It is a key contact area that directly affects the forming accuracy and quality of the product.

[0117] Contour point cloud data is a set of spatial coordinates extracted from the second surface point cloud data and matched with the working contour of the roller, used to characterize the actual shape features of the working contour.

[0118] The preset target profile is a roller profile reference determined in advance based on design requirements or ideal forming standards. It is used to compare with the actual profile after repair and to calculate the deviation.

[0119] Radial profile offset is the deviation of the repaired profile in the radial direction, that is, along the roller radius, from the preset target profile.

[0120] Axial profile offset is the deviation of the repaired profile in the axial direction, that is, along the length of the roller, from the preset target profile.

[0121] Contour deviation distribution data is spatial distribution data of contour deviation across the entire working contour range, formed by integrating radial and axial contour offsets.

[0122] Standard forming conditions refer to the operating state of the rollers performing forming operations according to specified production parameters and process conditions. This includes key conditions such as load, speed, and temperature, thereby ensuring that the measured performance data are comparable and representative.

[0123] The molding performance data is the roller processing result data collected under standard molding conditions, which includes relevant information such as pressure, displacement, finished product geometry, and surface quality.

[0124] The molding performance deviation result is obtained by comparing and analyzing the molding performance data of the repaired roller with the design value or target value, and obtaining relevant deviation information.

[0125] The performance verification results are the repair effect evaluation results obtained by mapping the contour deviation distribution data and molding performance deviation results to each wear area.

[0126] A surface scanning operation was performed on the rollers that had undergone the first laser cladding repair. High-precision 3D measuring equipment was used to collect data point-by-point across the entire roller surface, obtaining the spatial coordinate set of the repaired roller, i.e., the second surface point cloud data. This second surface point cloud data accurately reflects the actual morphology of the roller surface after laser cladding, including key information such as height changes, unevenness, and local flatness, providing fundamental data support for subsequent contour extraction and accuracy analysis. The second surface point cloud data was then filtered and smoothed to remove noise and outliers generated during the measurement process, resulting in clear, continuous, and accurate information about the roller surface morphology.

[0127] After acquiring the point cloud data of the second surface, based on the established definition of the roller processing area, contour point cloud data corresponding to the roller working contour is extracted from the point cloud. The roller working contour is the key area where the wheel surface comes into contact with the material during the actual forming process and directly determines the shape of the finished product. During the extraction process, key sampling points located in the center area of ​​the wheel surface and along the length direction are selected from the point cloud. At the same time, the local curved surface contour is fitted to accurately determine the spatial boundary and geometric features of the roller working contour, and finally a complete contour point cloud data set is formed.

[0128] Spatially register the contour point cloud data with the preset target contour to clarify the positional relationship of the actual contour relative to the preset target contour in three-dimensional space. During the registration process, the iterative nearest point algorithm or local least squares fitting method is used to accurately align the contour point cloud data with the ideally designed preset target contour. After alignment, the radial and axial contour offsets of each sampling point are calculated. These radial and axial contour offsets are then meshed or interpolated over the entire working contour range of the roller to generate contour deviation distribution data. This data can intuitively reflect local bulges and depressions on the wheel surface and the overall repair accuracy, facilitating the rapid identification of areas where repair deficiencies still exist.

[0129] Performance verification of the repaired rollers was conducted under standard forming conditions. This involved performing forming operations under specified loads, speeds, and processing conditions, while simultaneously collecting various forming performance data, including contact pressure, roller surface displacement, processing trajectory deviation, and relevant information such as finished product dimensions and surface quality. After signal processing, filtering, and numerical fitting of these forming performance data, process response calculations were performed. The actual feedback data from the roller surface was compared with the ideal or design targets to determine the forming performance deviation for each sampling point or contour segment. This resulted in the final forming performance deviation result of the repaired roller, quantifying the impact of the roller surface repair operation on the actual forming effect.

[0130] The contour deviation distribution data and molding performance deviation results are mapped to the identified wear area. By using spatial location matching and numerical classification, the contour error and performance deviation in each wear area are comprehensively statistically analyzed. This allows for a comprehensive evaluation of the actual repair effect of each wear area, and the analysis results are compiled into the performance verification results for each wear area.

[0131] Based on the above steps S201-S208, the deviation of the roller profile and forming performance after repair can be accurately quantified, and the geometric accuracy and actual forming effect can be correlated to each wear area. This provides a reliable basis for judging the repair quality and whether to perform secondary local cladding, while improving the pertinence and accuracy of the repair plan.

[0132] Based on the above technical solution, optionally, after obtaining the performance verification results of each wear area, the method further includes: If a performance verification result that does not meet the preset performance standard is identified, the corresponding wear area is taken as the target wear area, and the second target compensation amount for local compensation is calculated based on the contour deviation distribution data of the target wear area and the molding performance deviation. The secondary laser cladding path and second process parameters for the target wear area are generated based on the second target compensation amount. Based on the secondary laser cladding path and the second process parameters, a local cladding scheme for the target wear area is determined, and the laser cladding equipment is controlled to perform local laser cladding on the target wear area based on the local cladding scheme; Re-evaluate whether the performance verification results of the target wear area meet the preset performance standards. If they still do not meet the preset performance standards, repeat the above steps until the performance verification results of the target wear area meet the preset performance standards.

[0133] In this scheme, the preset performance standard is the allowable deviation range of the repaired roller profile accuracy, forming performance and other key indicators, which is used to determine whether the repair effect of the wear area meets the predetermined requirements.

[0134] The target wear area is the wear area that did not meet the preset performance standard during the performance verification process. It is a specific area on the roller surface that requires secondary local compensation cladding.

[0135] The second target compensation amount is a secondary compensation height or compensation volume calculated for the target wear area, combining contour deviation distribution data and forming performance deviation results, and is used to guide subsequent local laser cladding repair operations.

[0136] The secondary laser cladding path is a laser cladding movement trajectory planned based on the second target compensation amount, which accurately covers the target wear area and ensures the precise implementation of local compensation operations.

[0137] The second process parameter is the value of process parameters such as laser power, scanning speed, and powder feeding amount set for the secondary laser cladding path.

[0138] The local cladding scheme is a specific execution plan that combines the secondary laser cladding path and the second process parameters. It includes the operation sequence of local cladding, the distribution of the number of cladding layers, and the configuration of various process parameters, and is used to guide the laser cladding equipment to carry out precise local repair operations.

[0139] First, a performance standard compliance check is performed on the repaired rollers. The contour deviation distribution data and forming performance deviation results are comprehensively compared and analyzed to accurately identify wear areas that do not meet the preset performance standards. These areas are marked as target wear areas and used for secondary local cladding repair. During the identification process, the contour deviation values ​​of each wear area are mapped to the local mesh and sampling points on the wheel surface. Simultaneously, combined with the mechanical and trajectory deviations generated during the forming process, a set of local performance failure points is constructed to clarify the specific range of the wheel surface requiring additional compensation.

[0140] Subsequently, based on the contour deviation distribution data and forming performance deviation of the target wear area, local compensation is calculated. The contour deviation distribution data accurately provides the height difference between the actual contour and the target contour at each sampling point, while the forming performance deviation directly reflects the actual impact of this area on the final forming result. These two types of data are processed comprehensively, and the required local compensation height for each sampling point and grid point is calculated using weighted superposition or mathematical fitting methods. This generates a second target compensation amount, reflecting the material thickness distribution that needs to be filled during the secondary cladding operation.

[0141] Based on the second target compensation amount, a secondary laser cladding path is planned to fully cover the target wear area. During path planning, the laser scanning trajectory is segmented according to the wheel surface geometry, the compensation height variation pattern, and the laser processing requirements, generating a continuous movement trajectory. Simultaneously, the movement direction, path spacing, and layer sequence of each segment are calculated to ensure the laser beam can uniformly cover the entire target wear area. Furthermore, based on the thickness requirements of the secondary compensation, the local curvature of the wheel surface, and the characteristics of the cladding material, matching second process parameters are calculated, covering core parameters such as laser power, scanning speed, and powder feed rate. This ensures that each cladding path achieves precise cladding thickness and that the forming quality meets process requirements.

[0142] The secondary laser cladding path is integrated with the second process parameters to form a local cladding scheme. This scheme clearly defines the cladding sequence, the distribution of cladding layers, and the specific configuration of each process parameter. The control system will operate the laser cladding equipment to carry out local cladding operations according to the local cladding scheme. During the cladding process, the real-time changes in laser power, scanning speed, and powder feed rate are monitored throughout the process, and dynamic fine-tuning is performed based on the actual geometry of the wheel surface and the material cladding response to ensure the accuracy of secondary compensation and the forming quality of the cladding layer.

[0143] After the secondary cladding operation is completed, the contour point data and forming performance data of the target wear area are collected again, and the performance verification work is carried out again. The newly measured contour deviation and forming deviation are compared with the preset performance standards. If the standard requirements are still not met, the cycle of target wear area identification, second target compensation calculation, secondary laser cladding path and second process parameter generation, local cladding execution and performance verification is repeated until the performance verification results of the target wear area meet the preset performance standards.

[0144] This solution can accurately compensate for local wear on the roller surface, improving the forming accuracy and performance consistency of the repaired roller; at the same time, through iterative optimization, it can achieve efficient and controllable secondary laser cladding, reducing material waste and the risk of rework.

[0145] It should be noted that although the steps in the above embodiments are described in a specific order, those skilled in the art will understand that in order to achieve the effects of the present invention, different steps do not necessarily have to be executed in such an order. They can be executed simultaneously (in parallel) or in other orders, and these variations are all within the scope of protection of the present invention.

[0146] Furthermore, the present invention also provides a roller laser cladding repair system based on wear performance mapping.

[0147] See appendix Figure 3 , Figure 3 This is a main structural block diagram of a roller laser cladding repair system based on wear performance mapping according to an embodiment of the present invention. Figure 3 As shown, it specifically includes: Wear area identification module 301 is used to acquire three-dimensional morphological data of the surface of the roller to be repaired, identify each wear area based on the three-dimensional morphological data and extract the corresponding wear feature parameters; The weight determination module 302 is used to acquire historical molding data of the roller to be repaired, establish wear and performance mapping of each wear area based on the three-dimensional morphology data, historical molding data and wear characteristic parameters, and calculate the contribution weight of each wear area to molding performance based on the wear and performance mapping. The cladding parameter determination module 303 is used to determine the first target compensation amount of each wear area based on the contribution weight of each wear area, and generate the laser cladding path and the first process parameters of each wear area based on the first target compensation amount. The laser cladding module 304 is used to determine the gradient cladding scheme for each wear area based on the laser cladding path and the first process parameters, and to control the laser cladding equipment to perform laser cladding on each wear area based on the gradient cladding scheme; wherein, the material used for laser cladding is high-precision cold work die steel powder.

[0148] The roller laser cladding repair system based on wear performance mapping provided in this application embodiment can achieve... Figure 1 The various processes implemented in the method implementation examples will not be described again here to avoid repetition.

[0149] Those skilled in the art will understand that all or part of the processes in the method of the above embodiment of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable storage medium can include any entity or device capable of carrying the computer program code, a medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory, a random access memory, an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc. It should be noted that the content included in the computer-readable storage medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable storage medium does not include electrical carrier signals and telecommunication signals.

[0150] Furthermore, the present invention also provides an electronic device 400, including a processor 401, a memory 402, and a program or instructions stored in the memory 402 and executable on the processor 401. When the program or instructions are executed by the processor 401, they implement the various processes of the above-described embodiment of a roller laser cladding repair method based on wear performance mapping and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0151] It should be noted that the electronic devices in the embodiments of this application include the mobile electronic devices and non-mobile electronic devices described above.

[0152] Furthermore, the present invention also provides a computer-readable storage medium. In one embodiment of the computer-readable storage medium according to the present invention, the computer-readable storage medium can be configured to store a program for performing a roller laser cladding repair method based on wear performance mapping according to the above-described method embodiments. This program can be loaded and run by a processor to implement the above-described roller laser cladding repair method based on wear performance mapping. For ease of explanation, only the parts related to the embodiments of the present invention are shown; for specific technical details not disclosed, please refer to the method section of the embodiments of the present invention. The computer-readable storage medium can be a storage device comprising various electronic devices. Optionally, in the embodiments of the present invention, the computer-readable storage medium is a non-transitory computer-readable storage medium.

[0153] Furthermore, it should be understood that since the various modules are only provided to illustrate the functional units of the device of the present invention, the physical devices corresponding to these modules may be the processor itself, or a part of the processor's software, hardware, or a combination of software and hardware. Therefore, the number of modules shown in the figures is merely illustrative.

[0154] Those skilled in the art will understand that the various modules in the device can be adaptively split or combined. Such splitting or combining of specific modules will not cause the technical solution to deviate from the principles of the present invention; therefore, the technical solutions after splitting or combining will fall within the protection scope of the present invention.

[0155] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A roller laser cladding repair method based on wear performance mapping, characterized in that, The method includes: Acquire three-dimensional topographic data of the surface of the roller to be repaired, identify each wear area based on the three-dimensional topographic data and extract the corresponding wear feature parameters; Historical forming data of the roller to be repaired is obtained. Based on the three-dimensional morphology data, historical forming data and wear characteristic parameters, wear and performance mapping of each wear area is established, and the contribution weight of each wear area to forming performance is calculated based on the wear and performance mapping. The first target compensation amount for each wear area is determined based on the contribution weight of each wear area, and the laser cladding path and first process parameters for each wear area are generated based on the first target compensation amount. Based on the laser cladding path and the first process parameters, a gradient cladding scheme is determined for each wear area, and the laser cladding equipment is controlled to perform laser cladding on each wear area based on the gradient cladding scheme; wherein, the material used for laser cladding is high-precision cold work die steel powder.

2. The roller laser cladding repair method based on wear performance mapping according to claim 1, characterized in that, in, Based on the three-dimensional topographic data, each wear region is identified and the corresponding wear feature parameters are extracted, including: Point cloud preprocessing is performed on the three-dimensional topography data to obtain the point cloud data of the first surface of the roller to be repaired; Based on point cloud segmentation and surface fitting, wear regions are identified from the first surface point cloud data of the roller to be repaired, and the boundary information of each wear region is obtained. Each wear region is then determined based on the boundary information. Height deviations of each wear zone are calculated by point cloud fitting and local analysis. Based on point cloud depression recognition and depth analysis, the depression depth of the boundary information is calculated to obtain the depression depth data of each wear area; Surface curvature is calculated based on surface fitting and curvature analysis to obtain surface curvature data for each wear region; Wear characteristic parameters are determined based on the height deviation data, indentation depth data, and surface curvature data.

3. The roller laser cladding repair method based on wear performance mapping according to claim 2, characterized in that, in, Based on the aforementioned three-dimensional morphology data, historical forming data, and wear characteristic parameters, a wear-performance mapping for each wear region is established, including: Based on the historical molding data, pressure, displacement and trajectory analysis are performed to obtain the pressure deviation sequence, displacement deviation sequence and trajectory deviation sequence of the overall surface area of ​​the roller to be repaired, and a comprehensive performance deviation sequence is generated based on the pressure deviation sequence, displacement deviation sequence and trajectory deviation sequence. Based on wear characteristic parameters, geometric analysis, local depression analysis and curvature analysis are performed to obtain the height deviation index, depression depth index and surface curvature index of each wear area. Based on the height deviation index, depression depth index and surface curvature index, a multidimensional wear feature vector of each wear area is generated. Based on the spatial location of the first surface point cloud data, the comprehensive performance deviation sequence is assigned to each wear region to obtain the local performance deviation sequence of each wear region; The wear-performance mapping is obtained by performing feature association and mapping modeling on the local performance deviation sequence of each wear region and the multidimensional wear feature vector.

4. The roller laser cladding repair method based on wear performance mapping according to claim 3, characterized in that, in, The contribution weight of each wear region to molding performance is calculated based on the wear-performance mapping, including: Based on the wear and performance mapping, the performance response of the multidimensional wear feature vector of each wear region is calculated to obtain the predicted performance deviation value of each wear region under the current wear state. Based on the predicted performance deviation values, normalization is performed to obtain the relative performance impact of each wear region. The historical usage frequency of each wear area is obtained, and the relative performance impact is weighted and summarized based on the historical usage frequency to obtain the preliminary contribution value corresponding to each wear area. Based on the point cloud data of the first surface, the spatial proximity relationship of each wear region is determined. Based on the spatial proximity relationship, the initial contribution value is coupled and corrected to obtain the contribution weight of each wear region to the forming performance.

5. The roller laser cladding repair method based on wear performance mapping according to claim 2, characterized in that, in, Based on the first target compensation amount, laser cladding paths and first process parameters are generated for each wear region, including: Based on the first surface point cloud data and the first target compensation amount, the local cladding range of each wear area is determined; Based on the local cladding range, path planning is performed to obtain the laser cladding path for each wear area; Based on the first target compensation amount, a layered calculation is performed to obtain the number of cladding layers in each wear area and the thickness distribution data of each layer. The corresponding laser power is calculated based on the thickness distribution data of each layer, and the power setting value of each layer is obtained. The scanning speed is calculated based on the thickness distribution data and power settings of each layer, and the scanning speed settings for each layer are obtained. The powder feeding amount is calculated based on the thickness distribution data of each layer, the power setting value, and the scanning speed setting value, and the powder feeding amount setting value of each layer is obtained. The power setting, scanning speed setting, and powder feed rate setting are integrated into the first process parameter for each wear zone.

6. The roller laser cladding repair method based on wear performance mapping according to claim 1, characterized in that, in, After controlling the laser cladding equipment based on the gradient cladding scheme to perform laser cladding on each wear area, the method further includes: Acquire the point cloud data of the second surface of the repaired roller, and extract the contour point cloud data corresponding to the working contour of the roller based on the second surface point cloud data; Spatial registration is performed between the contour point cloud data and the preset target contour. The radial contour offset and axial contour offset of the repaired roller are calculated, and contour deviation distribution data are generated based on the radial contour offset and axial contour offset. Obtain molding performance data of the repaired roller under standard molding conditions, perform process response calculation based on the molding performance data, and obtain the molding performance deviation result of the repaired roller; The contour deviation distribution data and molding performance deviation are mapped to the existing wear area, the repair effect of each wear area is analyzed, and the performance verification results of each wear area are obtained.

7. The roller laser cladding repair method based on wear performance mapping according to claim 6, characterized in that, in, After obtaining the performance verification results for each wear region, the method further includes: If a performance verification result that does not meet the preset performance standard is identified, the corresponding wear area is taken as the target wear area, and the second target compensation amount for local compensation is calculated based on the contour deviation distribution data of the target wear area and the molding performance deviation. The secondary laser cladding path and second process parameters for the target wear area are generated based on the second target compensation amount. Based on the secondary laser cladding path and the second process parameters, a local cladding scheme for the target wear area is determined, and the laser cladding equipment is controlled to perform local laser cladding on the target wear area based on the local cladding scheme; Re-evaluate whether the performance verification results of the target wear area meet the preset performance standards. If they still do not meet the preset performance standards, repeat the above steps until the performance verification results of the target wear area meet the preset performance standards.

8. A roller laser cladding repair system based on wear performance mapping, characterized in that, The system includes: The wear area identification module is used to acquire three-dimensional morphological data of the surface of the roller to be repaired, identify each wear area based on the three-dimensional morphological data, and extract the corresponding wear feature parameters. The weight determination module is used to acquire historical molding data of the roller to be repaired, establish wear and performance mapping of each wear area based on the three-dimensional morphology data, historical molding data and wear characteristic parameters, and calculate the contribution weight of each wear area to molding performance based on the wear and performance mapping. The cladding parameter determination module is used to determine the first target compensation amount of each wear area based on the contribution weight of each wear area, and to generate the laser cladding path and the first process parameters of each wear area based on the first target compensation amount. The laser cladding module is used to determine the gradient cladding scheme for each wear area based on the laser cladding path and the first process parameters, and to control the laser cladding equipment to perform laser cladding on each wear area based on the gradient cladding scheme; wherein, the material used for laser cladding is high-precision cold work die steel powder.

9. An electronic device comprising a processor, a memory, and a program or instructions stored in the memory and executable on the processor, characterized in that, The program or instructions are adapted to be loaded and run by the processor to perform a roller laser cladding repair method based on wear performance mapping as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a plurality of program codes, characterized in that, The program code is adapted to be loaded and run by a processor to perform a roller laser cladding repair method based on wear performance mapping as described in any one of claims 1 to 7.

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