Graphical calibration system and method for CNC mold machining

Abstract

This invention discloses a graphic calibration system and method for CNC mold machining. The system includes: a data acquisition module configured to receive CNC machining tasks and acquire graphic data and measurement data of the mold to be machined based on the machining tasks; a data calibration module configured to perform geometric feature calibration on the graphic data based on preset calibration data, generate calibrated calibrated graphic data, and spatially register the measurement data and calibrated graphic data to obtain deviation data; a data processing module configured to map the deviation data to a machining parameter library in the machining task, calculate the correction values ​​of each machining parameter to obtain calibration parameters; and a data feedback module configured to feed back the calibrated graphic data and / or calibration parameters to the system, and perform the remaining graphic data input and machining parameter input for the machining task. This invention significantly improves mold machining accuracy and production efficiency, providing a high-confidence graphic input benchmark for CNC mold machining.

Description

Technical Field

[0001] This invention relates to the field of numerical control technology, specifically to a graphic calibration system and method for CNC mold processing. Background Technology

[0002] In the field of CNC mold machining, mold graphic data (usually CAD models) serves as the source of machining instructions, and its geometric accuracy directly determines the final molding quality. However, in actual machining, due to the coupling effects of multiple physical fields such as material thermal expansion, cutting vibration, and tool wear, the measured contour of the machined part often deviates systematically from the original graphic data.

[0003] Existing technologies struggle to adapt to the spatial distribution characteristics of deviations under different mold structures, material properties, and process conditions, resulting in insufficient feature capture capabilities in key areas. Deviation discrimination generally relies on fixed threshold mechanisms, failing to effectively distinguish between reasonable fluctuations caused by process disturbances (such as thermal deformation and cutting vibration) and geometric distortions requiring correction, easily leading to false rejections or missed judgments. The calibration process is weakly correlated with machining parameters, and calibration results are mostly limited to graphic geometric corrections, lacking the ability to trace the process origin of deviations and failing to support targeted optimization of machining parameters. When deviations caused by multiple process factors are spatially superimposed, existing methods lack effective coupling deviation separation mechanisms, making calibration correction prone to mutual interference and affecting overall calibration reliability.

[0004] Therefore, there is an urgent need for a graphic calibration system and method for CNC mold machining that can configure calibration strategies based on the type of machining parameter deviation, accurately identify the deviation characteristics of interference and non-interference intervals, and achieve synergistic optimization of graphic data and machining parameters, so as to provide a high-confidence graphic input benchmark for CNC mold machining. Summary of the Invention

[0005] To address the aforementioned problems, this invention provides a graphic calibration system and method for CNC mold processing, providing a high-confidence graphic input benchmark for CNC mold processing.

[0006] A first aspect of the present invention provides a graphic calibration system for CNC mold machining, comprising: The data acquisition module is configured to receive CNC machining tasks and acquire graphic data and measurement data of the mold to be processed based on the machining tasks. The data calibration module is configured to perform geometric feature calibration on the graphic data based on preset calibration data, generate calibrated calibration graphic data, and spatially register the measurement data and the calibration graphic data to obtain deviation data. The data processing module is configured to map the deviation data to the processing parameter library in the processing task, and calculate the correction value of each processing parameter to obtain the calibration parameter. The data feedback module is configured to feed back the calibration graphic data and / or the calibration parameters to the system, and to input the remaining graphic data and processing parameters for the processing task.

[0007] As a preferred embodiment, the data calibration module performs the following steps: The preset calibration data is obtained, which includes a theoretical dimension library of standard gauge blocks or a benchmark measurement dataset of historical qualified molds; Extract key geometric feature points from the graphic data as standard points; According to the preset processing parameter deviation type in the processing parameter library, the corresponding set of discrete points is called from the discrete point configuration library. Each set of discrete points has a specific size density for that deviation type. ICP registration is performed based on the standard points and the corresponding feature points in the preset calibration data to calculate the initial scale deviation and rotation deviation. During spatial registration, each set of discrete points is assigned a registration size change threshold that matches the type of deviation of the processing parameters. The registration size change threshold is greater than the conventional registration threshold. When the actual deviation of a discrete point exceeds the conventional registration threshold but does not exceed the registration size change threshold, the discrete point is retained to participate in the registration calculation. Based on the initial scale deviation and rotation deviation, an affine transformation correction is performed on the graphic data to generate the calibrated graphic data; The measurement data is preprocessed, and the preprocessed measurement data is spatially registered with the calibration graphic data. The Euclidean distance between each measurement point and the theoretical profile is calculated to generate an initial deviation vector. Based on the topological relationship of the spatial distribution of discrete points of different groups, interference intervals and non-interference intervals are divided. The interference interval is the overlapping part of the spatial coverage area of ​​two groups of discrete points, and the non-interference interval is the coverage area of ​​a single group of discrete points.

[0008] As a preferred embodiment, the discrete point configuration library pre-stores thermal deformation deviation groups, vibration displacement deviation groups, and composite deviation groups.

[0009] As a preferred embodiment, the data calibration module further performs the following steps: Within the interference range, a comprehensive allowable threshold Ti is set. Ti = α × Th + β × Tv Where Th is the registration size change threshold of the discrete points of the thermal deformation deviation group, Tv is the registration size change threshold of the discrete points of the vibration displacement deviation group, and the weighting coefficients α and β are determined according to the point density ratio of the two groups of discrete points in the interference interval, and α+β=1. When the measurement point is within the interference range and its deviation is less than Ti, it is determined to be an allowable deviation and retained for registration; when the deviation is greater than or equal to Ti, it is determined to be a deviation that needs to be calibrated and marked. Within the first non-interference zone, a first-group-specific allowable threshold Th is set; when the deviation of the measurement point is less than Th, it is determined to be an allowable deviation, and when the deviation is greater than or equal to Th, it is determined to be a deviation that needs to be calibrated. Within the second non-interference zone, a second group-specific allowable threshold Tv is set; when the deviation of the measurement point is less than Tv, it is determined to be an allowable deviation, and when the deviation is greater than or equal to Tv, it is determined to be a deviation that needs to be calibrated. The first non-interference interval and the second non-interference interval are non-interference intervals of different groups; Generate the deviation data, which includes the interval identifier of each measurement point, the deviation value, and the deviation judgment result identifier; The calibration offset is bound to a key calibration point, and differential processing is performed based on the deviation determination result: Within the non-interference range, the compensation logic for the corresponding group is triggered only when a deviation is determined to require calibration. Within the interference range, when a deviation is determined to require calibration, a weighting coefficient is calculated based on the proportion of the triggering states of the discrete points of the thermal deformation deviation group and the vibration displacement deviation group. The thermal deformation compensation amount and the vibration displacement compensation amount are then weighted and fused to generate a comprehensive compensation amount.

[0010] As a preferred embodiment, the data processing module performs the following steps: Extract the global deviation vector set corresponding to the standard point in the deviation data, the local deviation vector set marked as the deviation to be calibrated in each non-interference interval, and the coupled deviation vector set marked as the deviation to be calibrated in the interference interval, respectively. The overall consistency of graphic registration is evaluated based on the global deviation vector set: when the mean magnitude of the global deviation vector exceeds a first preset threshold, it is determined that there is a systematic deviation in the graphic registration. Based on the local deviation vector set and its corresponding interval identifier, the following deviation source tracing diagnosis is performed: When the local deviation vector of the deviation point to be calibrated in the first non-interference interval shows a gradient accumulation distribution and the gradient value exceeds the third preset threshold, it is determined that there is a deviation in the thermal deformation related parameters. When the local deviation vector of the deviation point to be calibrated within the second non-interference interval exhibits periodic fluctuations and the fluctuation amplitude exceeds the second preset threshold, it is determined that there is a deviation in the vibration-related parameters. When the coupled deviation vector of the deviation point to be calibrated within the interference interval simultaneously satisfies the characteristics of gradient accumulation and periodic fluctuation, it is determined that there is thermal vibration coupling deviation, and the dominant deviation type is determined according to the weighting coefficient. The deviation types identified through traceability diagnosis are matched with a pre-set deviation parameter mapping database to determine the associated processing parameter categories; Based on the associated processing parameter category, the calibration parameters are calculated, the graphic compensation value is calculated, and the calibration graphic data is corrected according to the graphic compensation value. When the graphic compensation value causes the margin adjustment value to be less than the preset safety threshold, the preset upper limit of the calibration offset is adjusted.

[0011] As a preferred embodiment, the machining parameter categories include toolpath offset, spindle speed setting, feed rate, and clamping and positioning parameters; The calibration parameters include tool radius compensation correction value, feed rate adjustment coefficient, and clamping reference offset.

[0012] As a preferred embodiment, the data feedback module is further configured as follows: When multiple consecutive measurement points within the first non-interference interval are determined to have a deviation that requires calibration and the deviation amount continuously exceeds Th, the calibration graphic data is fed back to the system to replace the remaining graphic data input in the processing task. When the displacement fluctuation of the deviation point to be calibrated in the second non-interference interval exceeds the critical value and triggers the compensation strategy of the corresponding group, the calibration parameters are fed back to the system to adjust the input of the remaining processing parameters in the processing task. When the proportion of deviation points requiring calibration within the interference range exceeds a preset ratio, and the coupled deviation vector simultaneously satisfies the threshold values ​​for thermal deformation and vibration characteristics, the calibration graphic data and the calibration parameters are synchronously fed back to the system to collaboratively perform joint correction of the graphic data and processing parameters.

[0013] A second aspect of the present invention provides a graphic calibration method for CNC mold processing, comprising the following steps: Receive CNC machining tasks and acquire graphic data and measurement data of the mold to be machined based on the machining tasks; Based on preset calibration data, the graphic data is geometrically calibrated to generate calibrated graphic data. The measurement data and the calibrated graphic data are then spatially registered to obtain deviation data. Based on the deviation data, the calibration parameters are obtained by mapping the data to the processing parameter library in the processing task and calculating the correction value of each processing parameter. The calibration graphic data and / or the calibration parameters are fed back to the system, and the remaining graphic data and processing parameters for the processing task are input.

[0014] As a preferred method, the step of performing geometric feature calibration on the graphic data based on preset calibration data includes: Extract key geometric feature points from the graphic data as standard points; Based on the preset processing parameter deviation type in the processing parameter library, the discrete points of the corresponding group are called from the discrete point configuration library; Based on the standard points and the preset calibration data, perform ICP registration to calculate the initial deviation; Based on the initial deviation, the graphic data is corrected by affine transformation, and the out-of-tolerance contour region is refitted by NURBS. After preprocessing the measurement data, spatial registration is performed between the data and the corrected graphic data. The interference and non-interference intervals are divided based on the spatial topological relationship between the discrete points of the thermal deformation deviation group and the discrete points of the vibration displacement deviation group. Within the interference interval, a comprehensive allowable threshold Ti = α × Th + β × Tv is set, where α and β are weighting coefficients, α + β = 1, and α and β are determined based on the point density ratio of the two sets of discrete points within the interference interval; Th and Tv are set separately within the non-interference interval. Based on the comparison results between the deviation of the measurement points in each interval and the corresponding set threshold, the deviation data containing the interval identifier and the deviation judgment result identifier is generated; Differential compensation processing is performed based on the deviation determination result.

[0015] As a preferred method, the step of calculating calibration parameters based on the deviation data includes: Extract the global deviation vector set of the standard point, the local deviation vector set of the deviation to be calibrated in the non-interference interval, and the coupled deviation vector set of the deviation to be calibrated in the interference interval, respectively. The overall consistency of graphic registration is evaluated based on the global deviation vector set; Deviation source tracing and diagnosis are performed based on the distribution characteristics of the local deviation vector set and the identifier of its corresponding interval; Match deviation types to the deviation parameter mapping database to determine the associated processing parameter categories; The graphic compensation value and calibration parameters are calculated by combining the process parameter library and equipment file information.

[0016] Compared with the prior art, the present invention has the following advantages: This invention uses a discrete point configuration library to preset thermal deformation deviation groups, vibration displacement deviation groups, and composite deviation groups. Each group of discrete points is assigned a unique size density based on the physical characteristics of the deviation, so that the distribution of calibration points is highly matched with the characteristics such as thermal deformation gradient and vibration stress distribution, which significantly improves the targeting and efficiency of deviation capture.

[0017] Based on the spatial topological relationship of discrete points, the interference interval and the non-interference interval are divided. A weighted comprehensive threshold Ti is used in the interference interval, and a group-specific threshold Th / Tv is used in the non-interference interval. This enables accurate discrimination between single deviation and thermal vibration coupling deviation, effectively avoiding misjudgment or omission of feature points caused by traditional global thresholds.

[0018] Differential processing is performed based on the deviation judgment result. In the non-interference interval, only the corresponding group compensation logic is triggered. In the interference interval, the weight coefficient is calculated by the proportion of discrete point trigger states. The comprehensive compensation amount is generated by integrating thermal deformation and vibration compensation, which accurately solves the coupling deviation calibration problem and improves the adaptability to complex working conditions.

[0019] The feedback content is selected based on the type and severity of the deviation: when a single deviation exceeds the limit, directional feedback is provided to calibrate the graphic data or calibration parameters; when the coupled deviation is significant, both are fed back simultaneously to achieve coordinated optimization of the graphic data source correction and the processing parameter adjustment, avoiding over-correction or under-correction. Attached Figure Description

[0020] The present invention will be further described with reference to the accompanying drawings, but the embodiments in the drawings do not constitute any limitation on the present invention. For those skilled in the art, other drawings can be obtained based on the following drawings without creative effort.

[0021] Figure 1 This is a schematic diagram of the system provided in an embodiment of the present invention. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] In a first aspect of this embodiment, a graphic calibration system for CNC mold machining is provided, such as... Figure 1 As shown, it includes a data acquisition module, a data calibration module, a data processing module, and a data feedback module. The functions and implementation logic of each module are described in detail below.

[0024] The data acquisition module is configured to receive CNC machining tasks and acquire graphic and measurement data of the mold to be processed based on the machining tasks. This module establishes a connection with the CNC control system or enterprise-level manufacturing execution system via an industrial communication protocol interface, parsing the mold's unique identifier and process parameter information included in the machining task; based on the mold's unique identifier, it retrieves the corresponding version of graphic data from the product data management system. This graphic data is a standardized CAD file format including a complete geometric model and tolerance information. Simultaneously, it acquires measurement data of the mold after machining from a measurement equipment database or online inspection system. This measurement data is 3D point cloud data after coordinate transformation. The module has a built-in data verification unit that performs real-time verification of the feature integrity of the graphic data and the point cloud density and noise level of the measurement data. Abnormal data triggers a retransmission mechanism or marks the processing status, ensuring the reliability and consistency of the input data.

[0025] In this embodiment, graphic data serves as the theoretical design benchmark, while measurement data serves as a quantitative representation of the actual processing results. Together, they constitute the original basis for deviation analysis. The data verification mechanism, through void rate threshold determination and coordinate integrity verification, effectively eliminates transmission noise and measurement anomaly interference, ensuring the physical authenticity and geometric consistency of the input data in subsequent calibration processes. This provides a reliable data source for accurately identifying graphic distortion and process deviations.

[0026] The data calibration module is configured to perform geometric feature calibration on the graphic data based on preset calibration data, generate calibrated calibration graphic data, and spatially register the measurement data and the calibration graphic data to obtain deviation data. The specific implementation process of this module is as follows: First, preset calibration data is loaded from the calibration database. The preset calibration data includes a standard gauge block theoretical dimension library constructed based on international metrological standards, as well as a historical qualified mold benchmark measurement dataset verified by the process, which serves as the benchmark for geometric calibration.

[0027] Secondly, a feature recognition algorithm is executed on the graphic data to extract key points with geometric stability in the mold cavity as standard points. These key points include the center of symmetry, the endpoints of the contour intersection line, and the center of the high curvature region.

[0028] Subsequently, based on the preset processing parameter deviation type identifier in the processing parameter library, a matching discrete point group is called from the discrete point configuration library. The discrete point configuration library pre-stores thermal deformation deviation groups, vibration displacement deviation groups, and composite deviation groups. Each group of discrete points is set with a differentiated spatial size density according to the physical mechanism of its corresponding deviation type (such as the gradient distribution characteristics of thermal deformation and the frequency domain characteristics of vibration displacement) to ensure high-density sampling in process-sensitive areas.

[0029] Subsequently, the standard points are iteratively registered with the reference feature points in the preset calibration data, and the initial scale deviation and rotation deviation parameters are solved iteratively by minimizing the Euclidean distance between the point sets.

[0030] During the spatial registration stage, each set of discrete points is assigned a registration size change threshold that matches the deviation type. This threshold is strictly greater than the conventional registration threshold. When the actual deviation of a discrete point is between the conventional registration threshold and the registration size change threshold, it is determined that the point retains the process feature information and is allowed to participate in subsequent registration calculations.

[0031] Based on the solved initial deviation parameters, affine transformation correction is performed on the original graphic data to generate preliminary calibration graphic data; for the contours of regions that still have out-of-tolerance areas after calibration, a non-uniform rational B-spline algorithm is used to refit the surface and optimize the geometric continuity.

[0032] The measurement data is preprocessed simultaneously: outliers are removed by statistical filtering algorithm, high-frequency noise is suppressed by Gaussian smoothing filter, and coarse registration of coordinate system is completed by random sampling consensus algorithm.

[0033] The preprocessed measurement data and calibration graphic data are spatially registered with high precision, and the shortest Euclidean distance from each measurement point to the theoretical profile is calculated to form an initial set of deviation vectors.

[0034] Furthermore, based on the topological relationship of the discrete points of the thermal deformation deviation group and the vibration displacement deviation group in three-dimensional space, the interference interval and the non-interference interval are divided by calculating the overlap of the region coverage: the interference interval is defined as the intersection of the spatial coverage areas of the two sets of discrete points, and the non-interference interval is defined as the exclusive area covered by only a single set of discrete points.

[0035] Within the interference interval, a comprehensive allowable threshold Ti is set. Ti is calculated as Ti = α × Th + β × Tv, where Th is the registration size change threshold for discrete points in the thermal deformation deviation group, and Tv is the registration size change threshold for discrete points in the vibration displacement deviation group. The weighting coefficients α and β are calculated based on the normalized point density ratio of the two groups of discrete points within the interference interval, and satisfy α + β = 1. When the measurement point is located within the interference interval and the deviation is less than Ti, it is determined to be an allowable deviation and retained for registration. When the deviation is greater than or equal to Ti, it is determined to be a deviation requiring calibration and is marked. A dedicated threshold Th is set within the first non-interference interval, and the same discrimination logic is executed. A dedicated threshold Tv is set within the second non-interference interval, and the same discrimination logic is executed.

[0036] Structured deviation data is generated, including the interval assignment identifier, quantized deviation value, and judgment result identifier for each measurement point. After binding the calibration offset to the key calibration point, differentiated compensation is performed based on the judgment result identifier: in non-interference intervals, the compensation logic of the corresponding group is activated only when the deviation is determined to require calibration; in interference intervals, when the deviation is determined to require calibration, a weighting coefficient is calculated based on the trigger state ratio of the two groups of discrete points, and the thermal deformation compensation amount and vibration displacement compensation amount are weighted and fused to generate a comprehensive compensation amount.

[0037] It should be noted that due to the different processing parameter settings in different regions, the deformation of discrete points during the expected deformation process is finite. Under the premise of finite deformation, there are interference and non-interference intervals between discrete points set for different groups. Within the interference interval, the deformation effects of thermal deformation and vibration displacement are superimposed in physical space, but their respective deformation is still constrained by process parameters and remains within a limited range. By setting a weighted comprehensive threshold Ti = α × Th + β × Tv, the system can quantify the deformation contribution ratio of the two groups of discrete points and accurately determine whether the coupling deviation exceeds the process allowable boundary. Within the non-interference interval, the deformation of a single deviation type evolves independently and the deformation is strictly limited by the corresponding threshold (Th or Tv), allowing the discrimination logic to focus on specific process disturbances. This mechanism ensures that the calibration module, under the physical constraint of finite deformation, effectively distinguishes between process allowable fluctuations (retaining those participating in registration) and distortions that need correction (marked as deviations requiring calibration), avoiding miscalibration of normal process fluctuations, and providing high-confidence, interval-labeled structured deviation data for subsequent parameter traceability.

[0038] In this embodiment, the discrete point configuration strategy and interval division mechanism are the core logic for achieving accurate deviation discrimination. The discrete points of the thermal deformation deviation group and the vibration displacement deviation group are set with differentiated densities based on process-sensitive areas, ensuring a high degree of matching between the calibration point distribution and the physical characteristics of the deviations. The topological division of the interference and non-interference intervals physically separates spatially overlapping coupled deviation regions from single deviation regions. A weighted calculation of the allowable threshold Ti (Ti=α×Th+β×Tv) fuses the process contribution ratios of the two sets of discrete points, avoiding the failure of discrimination in coupled regions with fixed thresholds. The non-interference interval uses a group-specific threshold Th / Tv to ensure sensitive capture of single deviation types. The deviation judgment result identifier (allowed / required calibration) is directly linked to subsequent compensation logic: single threshold discrimination in the non-interference interval ensures a targeted response to specific deviation types; the weighted fusion compensation amount in the interference interval effectively handles the problem of multi-source deviation superposition. This design ensures that the deviation data output by the calibration module includes not only geometric deviation amounts but also deviation types and spatial distribution information, providing a structured input basis for parameter tracing in the data processing module.

[0039] The data processing module is configured to map the deviation data to a processing parameter library in the processing task, and calculate the correction values ​​of each processing parameter to obtain calibration parameters. This module first extracts three types of deviation vector sets from the deviation data: a global deviation vector set corresponding to the standard point, local deviation vector sets marked as deviations requiring calibration within each non-interference interval, and coupled deviation vector sets marked as deviations requiring calibration within interference intervals. Based on the global deviation vector set, the module length statistical mean is calculated. When this mean exceeds a preset systematic deviation threshold, it is determined that there is an overall deviation in the graphic registration. Deviation tracing is performed based on the spatial distribution characteristics and interval identifiers of local deviation vector sets: The gradient distribution characteristics of local deviation vectors in the first non-interference interval are analyzed. When the gradient accumulation trend is significant and the gradient value exceeds the preset thermal deformation judgment threshold, it is associated with deviations in thermal deformation-related processing parameters. The fluctuation characteristics of local deviation vectors in the second non-interference interval are analyzed. When significant periodicity is observed and the fluctuation amplitude exceeds the preset vibration judgment threshold, it is associated with deviations in vibration-related processing parameters. Multi-feature fusion analysis is performed on coupled deviation vectors in the interference interval. When both gradient accumulation and periodic fluctuation characteristics are satisfied, thermal-vibration coupling deviation is determined, and the dominant deviation type is determined based on the weighting coefficients output by the calibration module. The determined deviation type is matched and retrieved against a preset deviation parameter mapping relationship library, which stores the association rules between deviation feature patterns and processing parameter deviations, thereby determining the category of processing parameters that need correction. Based on the associated processing parameter categories, the correction amount of each parameter is calculated using the process knowledge base to generate calibration parameters. Simultaneously, graphic compensation values ​​are calculated, and geometric correction is performed on the calibration graphic data. When the processing allowance adjustment amount caused by graphic compensation is lower than the preset safety threshold, the allowable adjustment limit of the calibration offset is automatically tightened to ensure processing safety. The machining parameter categories cover toolpath offset, spindle speed setting, feed rate, and clamping positioning parameters; the calibration parameters specifically include tool radius compensation correction value, feed rate adjustment coefficient, and clamping reference offset.

[0040] It should be noted that the deviation tracing in the data processing module is based on the physical foundation of the finite deformation at discrete points and the division of intervals. Within the non-interference interval, the gradient accumulation characteristics of the local deviation vector strictly correspond to the physical mechanism of thermal deformation (continuous deformation caused by material thermal expansion), with its upper limit constrained by Th. The periodic fluctuation characteristics are directly related to the physical mechanism of vibration displacement (periodic excitation by cutting force), with the upper limit of the fluctuation amplitude constrained by Tv, ensuring that the parameter mapping has a clear process causal chain. Within the interference interval, the multi-feature fusion analysis of the coupled deviation vector, combined with weighting coefficients α and β, can quantify the deformation contribution ratio of uncoupling thermal deformation and vibration displacement (α+β=1), accurately locating the dominant deviation type. This design ensures that the calibration parameter calculation not only reflects the deviation magnitude but also implies the deviation cause and deformation boundary constraints, ensuring that parameter correction suggestions are strictly limited to the process safety range, avoiding excessive correction that could lead to insufficient machining allowance or the introduction of new deviations. Wherein, the first non-interference interval and the second non-interference interval are non-interference intervals of different groups. It should be noted that the first non-interference interval and the second non-interference interval in this embodiment correspond to the two groups set in this embodiment. In fact, the number of groups is not limited to this. When the number of non-interference intervals changes, the calculation of Ti=α×Th+β×Tv also changes. For example, when the number of non-interference intervals is three or more, the weighting terms involved in the calculation increase with the number of groups.

[0041] In this embodiment, the data processing module establishes a logical chain mapping deviation data to machining parameters by separating, extracting, and analyzing the features of three types of deviation vector sets. The global deviation vector set assesses the overall registration quality and eliminates systematic error interference; the local deviation vector set, combined with interval identifiers, performs feature diagnosis: gradient accumulation features highly match the physical mechanism of thermal deformation (continuous deformation caused by material thermal expansion), periodic fluctuation features are directly related to the physical mechanism of vibration displacement (periodic excitation of cutting force), and multi-feature fusion analysis of coupled deviation vectors accurately identifies the interaction of multiple deviation sources. The deviation parameter mapping relationship library binds feature patterns to machining parameter deviation types in a regularized manner, giving calibration parameter calculations a process physical basis. A graphic compensation value and machining allowance safety verification mechanism ensures that calibration actions improve accuracy without sacrificing machining safety. This logical chain enables the system to deduce specific machining parameter deviations from geometric deviations, achieving executable corrections.

[0042] The data feedback module is configured to feed back the calibration graphic data and / or the calibration parameters to the system, and to perform the remaining graphic data input and machining parameter input for the machining task. This module determines the feedback strategy based on the deviation analysis results: when multiple consecutive measurement points within the first non-interference interval are determined to have deviations requiring calibration and the deviation amount continuously exceeds Th, the calibration graphic data is pushed to the CNC control system through a standardized data interface, replacing the graphic data source for the remaining part of the machining task; when the displacement fluctuation characteristics of the deviation points requiring calibration within the second non-interference interval trigger preset vibration compensation conditions, the calibration parameters are encapsulated into a structured instruction package and sent to the parameter adjustment interface of the CNC control system to correct subsequent machining parameters; when the proportion of deviation points requiring calibration within the interference interval exceeds a preset percentage threshold, and the coupled deviation characteristics simultaneously meet the thermal deformation and vibration judgment conditions, the calibration graphic data and calibration parameters are simultaneously fed back, driving the CNC control system to collaboratively execute graphic data updates and machining parameter optimizations.

[0043] It should be noted that the output decision logic for calibration graphic data and calibration parameters in this embodiment is strictly based on the interval attributes of the deviation data, the deformation physical mechanism, and the efficiency of process correction. When multiple consecutive measurement points within the first non-interference interval are determined to have deviations requiring calibration and the deviation amount continuously exceeds Th, it indicates that the geometric distortion caused by thermal deformation is systematic and has an inherent deviation from the graphic data reference (such as the material's thermal expansion coefficient not matching the design assumption). At this time, the output calibration graphic data can correct the reference profile from the design source, avoiding the repeated accumulation of the same thermal deformation deviation in subsequent processing. This correction action is strictly limited by the deformation boundary defined by Th, ensuring the safety of the processing allowance, and a one-time correction can eliminate systematic deviations in the same batch, improving calibration efficiency. When the displacement fluctuation amplitude of the deviation points requiring calibration in the second non-interference interval exceeds the critical value, it indicates that the vibration displacement deviation is mainly due to improper machining parameter settings (such as excessive feed rate or excessive tool overhang), while the graphic data itself is correct. In this case, the output calibration parameters can be used to specifically optimize vibration suppression parameters (such as reducing the feed rate or adjusting the spindle speed). The adjustment range is constrained by Tv to avoid excessive parameter correction causing new disturbances, while preserving the design integrity and process intent of the original graphic data. When the proportion of deviation points requiring calibration in the interference interval exceeds the preset ratio and the coupled deviation characteristics simultaneously meet the thermal deformation and vibration judgment conditions, it indicates that both the graphic reference and machining parameters have deviations and are coupled with each other. A single correction path cannot decouple multi-source deviations. In this case, the calibration graphic data and calibration parameters are output simultaneously, so that the graphic correction amount and parameter adjustment amount strictly follow the weighted relationship Ti=α×Th+β×Tv. Under the constraint of finite deformation, the calibration benefits are maximized, while ineffective correction or machining risks are avoided, significantly improving the pertinence of calibration actions, process safety, and resource utilization efficiency.

[0044] In this embodiment, the decision-making strategy of the data feedback module is based on the multidimensional characteristics of the deviation data and the process influence mechanism: continuous deviations in the first non-interference interval reflect the cumulative effect of thermal deformation, requiring correction through graphical data to eliminate systematic deviations from the design source; excessive fluctuations in the second non-interference interval indicate vibration parameter mismatch, requiring real-time adjustment of machining parameters to suppress disturbances; and excessive coupling deviation ratios in the interference interval require coordinated correction of both graphics and parameters to simultaneously address geometric distortion and process instability. This feedback mechanism associates the calibration results with the remaining part of the CNC machining task, avoiding the limitations of one-time correction in traditional calibration, and significantly improving the accuracy stability and process adaptability of subsequent machining stages.

[0045] A second aspect of this embodiment provides a graphic calibration method for CNC mold processing, comprising the following steps: Receive CNC machining tasks and acquire graphic data and measurement data of the mold to be machined based on the machining tasks; Based on preset calibration data, the graphic data is geometrically calibrated to generate calibrated graphic data. The measurement data and the calibrated graphic data are then spatially registered to obtain deviation data. Based on the deviation data, the calibration parameters are obtained by mapping the data to the processing parameter library in the processing task and calculating the correction value of each processing parameter. The calibration graphic data and / or the calibration parameters are fed back to the system, and the remaining graphic data and processing parameters for the processing task are input.

[0046] In the geometric feature calibration step, the system extracts key geometric feature points from the graphic data as standard points; calls a matching discrete point group from the discrete point configuration library according to the processing parameter deviation type; performs iterative registration to calculate the initial deviation parameters by matching the standard points with the preset calibration data; performs affine transformation correction on the graphic data based on the initial deviation parameters, and uses a non-uniform rational B-spline algorithm to refit the surface of the out-of-tolerance contour region; performs spatial registration between the preprocessed measurement data and the corrected graphic data; divides the interference interval and non-interference interval based on the spatial topological relationship of the discrete points of the thermal deformation deviation group and the vibration displacement deviation group; sets a comprehensive allowable threshold Ti=α×Th+β×Tv in the interference interval (α and β are weight coefficients determined based on the point density ratio and α+β=1), and sets Th and Tv respectively in the non-interference interval; generates deviation data containing interval identifiers and judgment result identifiers based on the comparison results of the deviation of the measurement points in each interval with the corresponding thresholds; and finally executes the differential compensation processing logic based on the judgment result identifiers.

[0047] In the step of calculating calibration parameters, the system extracts the global deviation vector set of standard points, the local deviation vector set of deviations requiring calibration in non-interference intervals, and the coupled deviation vector set of deviations requiring calibration in interference intervals. Based on the statistical characteristics of the global deviation vector set, the overall consistency of graphic registration is evaluated. Multi-dimensional deviation source diagnosis is performed by combining the spatial distribution characteristics and interval identifiers of the local deviation vector set. The diagnosis results are matched with the deviation parameter mapping relationship library to determine the category of associated processing parameters. Finally, the process parameter library and equipment file information are integrated to calculate and generate graphic compensation values ​​and calibration parameters.

[0048] This embodiment achieves precise coupling between calibration point distribution and process deviation mechanism through discrete point configuration library, constructs a differential threshold discrimination mechanism for interference / non-interference intervals based on spatial topological relationship, establishes a strong correlation path between deviation judgment result and compensation logic, and systematically improves the accuracy, adaptability and process guidance value of graphic calibration based on intelligent decision feedback strategy for deviation scenario, providing a highly reliable graphic data input foundation for CNC mold processing.

[0049] The foregoing description and accompanying drawings fully illustrate embodiments of this disclosure to enable those skilled in the art to practice them. Other embodiments may include structural, logical, electrical, procedural, and other changes. The embodiments represent only possible variations. Individual components and functions are optional unless explicitly required, and the order of operations may vary. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. Moreover, the terminology used in this application is for describing embodiments only and is not intended to limit the claims. As used in the description of embodiments and claims, the singular forms “a,” “an,” and “the” are intended to equally include the plural forms unless the context clearly indicates otherwise. Similarly, the term “and / or,” as used herein, means including one or more of the associated listed items and all possible combinations thereof. Additionally, when used in this application, the term "comprise" and its variations "comprises" and / or "comprising" refer to the presence of stated features, integrals, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof. Without further limitations, an element defined by the phrase "comprises a..." does not exclude the presence of other identical elements in the process, method, or apparatus that includes said element. In this document, each embodiment may focus on the differences from other embodiments, and similar or identical parts between embodiments can be referred to mutually. For methods, products, etc., disclosed in the embodiments, if they correspond to the method section disclosed in the embodiments, the relevant parts can be referred to the description of the method section.

[0050] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented using electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods for each specific application to achieve the described functions, but such implementation should not be considered beyond the scope of the embodiments of this disclosure. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the described devices, apparatuses, and units can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0051] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, function, and operation of possible implementations of the apparatus, method, and computer program product according to embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code, which includes one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different blocks may also occur in a different order than those disclosed in the description; sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. Each block in a block diagram and / or flowchart, and combinations of blocks in a block diagram and / or flowchart, can be implemented using a dedicated hardware-based device that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

Claims

1. A graphic calibration system for CNC mold machining, characterized in that, include: The data acquisition module is configured to receive CNC machining tasks and acquire graphic data and measurement data of the mold to be processed based on the machining tasks. The data calibration module is configured to perform geometric feature calibration on the graphic data based on preset calibration data, generate calibrated calibration graphic data, and spatially register the measurement data and the calibration graphic data to obtain deviation data. The data processing module is configured to map the deviation data to the processing parameter library in the processing task, and calculate the correction value of each processing parameter to obtain the calibration parameter. The data feedback module is configured to feed back the calibration graphic data and / or the calibration parameters to the system, and to input the remaining graphic data and processing parameters for the processing task.

2. The graphic calibration system for CNC mold processing according to claim 1, characterized in that, The data calibration module performs the following steps: The preset calibration data is obtained, which includes a theoretical dimension library of standard gauge blocks or a benchmark measurement dataset of historical qualified molds; Extract key geometric feature points from the graphic data as standard points; According to the preset processing parameter deviation type in the processing parameter library, the corresponding set of discrete points is called from the discrete point configuration library. Each set of discrete points has a specific size density for that deviation type. ICP registration is performed based on the standard points and the corresponding feature points in the preset calibration data to calculate the initial scale deviation and rotation deviation. During spatial registration, each set of discrete points is assigned a registration size change threshold that matches the type of deviation of the processing parameters. The registration size change threshold is greater than the conventional registration threshold. When the actual deviation of a discrete point exceeds the conventional registration threshold but does not exceed the registration size change threshold, the discrete point is retained to participate in the registration calculation. Based on the initial scale deviation and rotation deviation, an affine transformation correction is performed on the graphic data to generate the calibrated graphic data; The measurement data is preprocessed, and the preprocessed measurement data is spatially registered with the calibration graphic data. The Euclidean distance between each measurement point and the theoretical profile is calculated to generate an initial deviation vector. Based on the topological relationship of the spatial distribution of discrete points of different groups, interference intervals and non-interference intervals are divided. The interference interval is the overlapping part of the spatial coverage area of ​​two groups of discrete points, and the non-interference interval is the coverage area of ​​a single group of discrete points.

3. The graphic calibration system for CNC mold processing according to claim 2, characterized in that, The discrete point configuration library pre-stores thermal deformation deviation groups, vibration displacement deviation groups, and composite deviation groups.

4. The graphic calibration system for CNC mold processing according to claim 3, characterized in that, The data calibration module also performs the following steps: Within the interference range, a comprehensive allowable threshold Ti is set. Ti = α × Th + β × Tv Where Th is the registration size change threshold of the discrete points of the thermal deformation deviation group, Tv is the registration size change threshold of the discrete points of the vibration displacement deviation group, and the weighting coefficients α and β are determined according to the point density ratio of the two groups of discrete points in the interference interval, and α+β=1. When the measurement point is within the interference range and its deviation is less than Ti, it is determined to be an allowable deviation and retained for registration; when the deviation is greater than or equal to Ti, it is determined to be a deviation that needs to be calibrated and marked. Within the first non-interference zone, a first-group-specific allowable threshold Th is set; when the deviation of the measurement point is less than Th, it is determined to be an allowable deviation, and when the deviation is greater than or equal to Th, it is determined to be a deviation that needs to be calibrated. Within the second non-interference zone, a second group-specific allowable threshold Tv is set; when the deviation of the measurement point is less than Tv, it is determined to be an allowable deviation, and when the deviation is greater than or equal to Tv, it is determined to be a deviation that needs to be calibrated. The first non-interference interval and the second non-interference interval are non-interference intervals of different groups; Generate the deviation data, which includes the interval identifier of each measurement point, the deviation value, and the deviation judgment result identifier; The calibration offset is bound to a key calibration point, and differential processing is performed based on the deviation determination result: Within the non-interference range, the compensation logic for the corresponding group is triggered only when a deviation is determined to require calibration. Within the interference range, when a deviation is determined to require calibration, a weighting coefficient is calculated based on the proportion of the triggering states of the discrete points of the thermal deformation deviation group and the vibration displacement deviation group. The thermal deformation compensation amount and the vibration displacement compensation amount are then weighted and fused to generate a comprehensive compensation amount.

5. The graphic calibration system for CNC mold processing according to claim 4, characterized in that, The data processing module performs the following steps: Extract the global deviation vector set corresponding to the standard point in the deviation data, the local deviation vector set marked as the deviation to be calibrated in each non-interference interval, and the coupled deviation vector set marked as the deviation to be calibrated in the interference interval, respectively. The overall consistency of graphic registration is evaluated based on the global deviation vector set: when the mean magnitude of the global deviation vector exceeds a first preset threshold, it is determined that there is a systematic deviation in the graphic registration. Based on the local deviation vector set and its corresponding interval identifier, the following deviation source tracing diagnosis is performed: When the local deviation vector of the deviation point to be calibrated in the first non-interference interval shows a gradient accumulation distribution and the gradient value exceeds the third preset threshold, it is determined that there is a deviation in the thermal deformation related parameters. When the local deviation vector of the deviation point to be calibrated within the second non-interference interval exhibits periodic fluctuations and the fluctuation amplitude exceeds the second preset threshold, it is determined that there is a deviation in the vibration-related parameters. When the coupled deviation vector of the deviation point to be calibrated within the interference interval simultaneously satisfies the characteristics of gradient accumulation and periodic fluctuation, it is determined that there is thermal vibration coupling deviation, and the dominant deviation type is determined according to the weighting coefficient. The deviation types identified through traceability diagnosis are matched with a pre-set deviation parameter mapping database to determine the associated processing parameter categories; Based on the associated processing parameter category, the calibration parameters are calculated, the graphic compensation value is calculated, and the calibration graphic data is corrected according to the graphic compensation value. When the graphic compensation value causes the margin adjustment value to be less than the preset safety threshold, the preset upper limit of the calibration offset is adjusted.

6. The graphic calibration system for CNC mold processing according to claim 5, characterized in that... , The machining parameter categories include toolpath offset, spindle speed setting, feed rate, and clamping and positioning parameters; The calibration parameters include tool radius compensation correction value, feed rate adjustment coefficient, and clamping reference offset.

7. The graphic calibration system for CNC mold processing according to claim 6, characterized in that, The data feedback module is further configured to: When multiple consecutive measurement points within the first non-interference interval are determined to have a deviation that requires calibration and the deviation amount continuously exceeds Th, the calibration graphic data is fed back to the system to replace the remaining graphic data input in the processing task. When the displacement fluctuation of the deviation point to be calibrated in the second non-interference interval exceeds the critical value and triggers the compensation strategy of the corresponding group, the calibration parameters are fed back to the system to adjust the input of the remaining processing parameters in the processing task. When the proportion of deviation points requiring calibration within the interference range exceeds a preset ratio, and the coupled deviation vector simultaneously satisfies the threshold values ​​for thermal deformation and vibration characteristics, the calibration graphic data and the calibration parameters are synchronously fed back to the system to collaboratively perform joint correction of the graphic data and processing parameters.

8. A method for calibrating graphics in CNC mold machining, characterized in that, Includes the following steps: Receive CNC machining tasks and acquire graphic data and measurement data of the mold to be machined based on the machining tasks; Based on preset calibration data, the graphic data is geometrically calibrated to generate calibrated graphic data. The measurement data and the calibrated graphic data are then spatially registered to obtain deviation data. Based on the deviation data, the calibration parameters are obtained by mapping the data to the processing parameter library in the processing task and calculating the correction value of each processing parameter. The calibration graphic data and / or the calibration parameters are fed back to the system, and the remaining graphic data and processing parameters for the processing task are input.

9. The CNC mold machining graphic calibration method according to claim 8, characterized in that, The steps for performing geometric feature calibration on the graphic data based on preset calibration data include: Extract key geometric feature points from the graphic data as standard points; Based on the preset processing parameter deviation type in the processing parameter library, the discrete points of the corresponding group are called from the discrete point configuration library; Based on the standard points and the preset calibration data, perform ICP registration to calculate the initial deviation; Based on the initial deviation, the graphic data is corrected by affine transformation, and the out-of-tolerance contour region is refitted by NURBS. After preprocessing the measurement data, spatial registration is performed between the data and the corrected graphic data. The interference and non-interference intervals are divided based on the spatial topological relationship between the discrete points of the thermal deformation deviation group and the discrete points of the vibration displacement deviation group. Within the interference interval, a comprehensive allowable threshold Ti = α × Th + β × Tv is set, where α and β are weighting coefficients, α + β = 1, and α and β are determined based on the point density ratio of the two sets of discrete points within the interference interval; Th and Tv are set separately within the non-interference interval. Based on the comparison results between the deviation of the measurement points in each interval and the corresponding set threshold, the deviation data containing the interval identifier and the deviation judgment result identifier is generated; Differential compensation processing is performed based on the deviation determination result.

10. The CNC mold machining graphic calibration method according to claim 9, characterized in that, The steps for calculating calibration parameters based on the deviation data include: Extract the global deviation vector set of the standard point, the local deviation vector set of the deviation to be calibrated in the non-interference interval, and the coupled deviation vector set of the deviation to be calibrated in the interference interval, respectively. The overall consistency of graphic registration is evaluated based on the global deviation vector set; Deviation source tracing and diagnosis are performed based on the distribution characteristics of the local deviation vector set and the identifier of its corresponding interval; Match deviation types to the deviation parameter mapping database to determine the associated processing parameter categories; The graphic compensation value and calibration parameters are calculated by combining the process parameter library and equipment file information.

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