Sheet metal processing monitoring, regulating and controlling system
By constructing and registering sheet metal part models, and monitoring and adjusting processing parameters in real time, the problem of difficulty in real-time monitoring of errors in sheet metal processing is solved, achieving high-precision and high-efficiency processing.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- NANTONG STERN MASCH TECH CO LTD
- Filing Date
- 2025-12-22
- Publication Date
- 2026-05-05
AI Technical Summary
In existing sheet metal processing, it is difficult to achieve real-time monitoring and control, resulting in low processing quality and efficiency.
By constructing standard sheet metal part models and actual sheet metal part models, and performing registration and comparison, processing errors are monitored in real time, and processing control parameters are adjusted according to the errors to achieve closed-loop optimization control.
It improves the precision and efficiency of sheet metal processing, ensures that product quality meets design requirements, and reduces scrap rate.
Smart Images
Figure CN121979108A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of sheet metal processing control, and more specifically to a sheet metal processing monitoring and control system. Background Technology
[0002] Sheet metal processing is widely used in many industries such as aerospace, automotive manufacturing, and electronics. With the development of modern manufacturing, increasingly higher requirements are being placed on the processing accuracy and production efficiency of sheet metal parts. However, in existing technologies, sheet metal parts are easily affected by many factors during processing, such as sheet metal characteristics, mold wear, and equipment precision, leading to deviations in product dimensions and shapes, and reducing processing quality. At the same time, traditional sheet metal production methods lack effective online monitoring and real-time feedback mechanisms, making it difficult for operators to detect and correct processing errors in a timely manner, resulting in low production efficiency. Summary of the Invention
[0003] This application provides a sheet metal processing monitoring and control system, which aims to solve the technical problem in the prior art that the difficulty in real-time monitoring and control of sheet metal processing errors leads to low processing quality and efficiency.
[0004] This application discloses a sheet metal processing monitoring and control system, comprising: a standard model construction module for determining a target sheet metal part, collecting design data of the target sheet metal part, and constructing a standard sheet metal part model based on the design data; a processing equipment configuration module for obtaining processing control parameters of the sheet metal processing equipment based on the design data and configuring the sheet metal processing equipment; a sheet metal part processing module for executing sheet metal part processing through processing control parameters, acquiring the processed sheet metal part, and transmitting the processed sheet metal part to the processing monitoring area; a measured model construction module for activating the processing monitoring device in the processing monitoring area, acquiring three-dimensional data of the processed sheet metal part, and constructing a measured sheet metal part model based on the data acquisition results; a model registration module for registering the standard sheet metal part model and the measured sheet metal part model and acquiring the model registration result; and a parameter control module for acquiring the processing error of the processed sheet metal part based on the model registration result and controlling the processing control parameters based on the processing error.
[0005] One or more technical solutions provided in this application have at least the following technical effects or advantages: By employing a standard model construction module to determine the target sheet metal part, collect its design data, and build a standard sheet metal part model based on the design data, the standard dimensions and shape information of the sheet metal part were obtained, providing a reference for subsequent processing monitoring and error analysis. The processing equipment configuration module obtained the processing control parameters of the sheet metal processing equipment based on the design data, and configured the sheet metal processing equipment accordingly, realizing the transformation of design requirements into processing instructions and preparing for the precise manufacturing of the sheet metal part. The sheet metal part processing module executed the sheet metal part processing according to the processing control parameters, acquired the processed sheet metal part, and transmitted it to the processing monitoring area, completing the actual production of the sheet metal part and sending it to the monitoring position, creating conditions for online inspection. The actual measurement model construction module activated the processing monitoring device in the processing monitoring area to collect three-dimensional data of the processed sheet metal part, and built an actual measurement sheet metal part model based on the collected data, obtaining the actual measurement of the processed part. The system uses the actual dimensions and shape of the sheet metal parts to form a digital model that reflects their true state. A model registration module registers the standard sheet metal model with the measured sheet metal model, obtaining the registration results. Comparison and analysis of the standard and measured models accurately assess the deviation between the processed part and the design requirements, providing a basis for optimizing processing parameters. The parameter control module obtains the processing error of the sheet metal part based on the model registration results and adjusts the processing control parameters accordingly. Based on the monitoring and analysis results, the processing instructions are corrected, achieving closed-loop optimization control of the processing process. This technical solution ensures the processing accuracy and efficiency of the sheet metal parts, solving the technical problem of low processing quality and efficiency caused by the difficulty in real-time monitoring and control of sheet metal processing errors in existing technologies. By comparing and registering the model, processing errors are obtained in real time, and processing parameters are adjusted based on these errors, achieving the technical effect of improving the processing quality and efficiency of sheet metal parts.
[0006] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description
[0007] Figure 1 This application provides a schematic diagram of a sheet metal processing monitoring and control system. Figure 2 This application provides a schematic flowchart of a sheet metal processing monitoring and control system for obtaining model registration results.
[0008] Explanation of reference numerals in the attached figures: Standard model construction module 11, processing equipment configuration module 12, sheet metal processing module 13, actual measurement model construction module 14, model registration module 15, parameter control module 16. Detailed Implementation
[0009] The overall concept of the technical solution provided in this application is as follows: This application provides a sheet metal processing monitoring and control system. By constructing a standard sheet metal part model and a measured sheet metal part model, and registering and comparing the two, the system monitors the sheet metal part processing process in real time, obtains processing error data, and adjusts the processing control parameters of the processing equipment accordingly, thereby realizing online detection and closed-loop optimization control of sheet metal processing.
[0010] First, the target sheet metal part is identified, its design data is collected, and a standard sheet metal part model reflecting its ideal dimensions and shape is constructed. Based on the design requirements, processing equipment is configured, and the actual processing of the sheet metal part is executed. During processing, the system activates a processing monitoring device to acquire 3D data of the sheet metal part being processed, and reconstructs the measured sheet metal part model through point cloud data analysis. Subsequently, the system performs high-precision registration between the standard model and the measured model, quantitatively analyzes the deviation between the two models, and evaluates the actual accuracy of the processed part. Based on the registration results, the system further acquires processing error data, optimizes the processing control parameters of the processing equipment, guides dynamic adjustments in the processing process, and ultimately ensures that the production quality of the sheet metal part meets the design requirements.
[0011] In summary, the sheet metal processing monitoring and control system of this application improves the accuracy and efficiency of sheet metal processing by using a technical approach that guides production with standard sheet metal part models, provides feedback on the current status of measured sheet metal part models, analyzes deviations through model registration, and optimizes processing through parameter control.
[0012] After introducing the basic principles of this application, the non-limiting embodiments of this application will be described in detail below with reference to the accompanying drawings.
[0013] like Figure 1 As shown in the figure, this application embodiment provides a sheet metal processing monitoring and control system, which includes: The standard model construction module 11 is used to determine the target sheet metal part, collect the design data of the target sheet metal part, and construct a standard sheet metal part model based on the design data.
[0014] Specifically, the standard model building module 11 first determines the target sheet metal part. The target sheet metal part is selected based on actual production needs; for example, it can be various sheet metal processing parts such as vehicle body parts or appliance housings. After determining the target sheet metal part, the standard model building module 11 collects its design data. This design data includes the target sheet metal part's CAD drawing data, 3D design dimensions, tolerance requirements, etc. The standard model building module 11 interacts with the product design system to directly obtain the aforementioned design data.
[0015] After collecting the design data of the target sheet metal part, the standard model construction module 11 constructs a standard sheet metal part model based on the design data for subsequent processing monitoring. The standard sheet metal part model is represented in various forms such as 3D CAD model or surface mesh model. The model data contains information that fully describes the shape and size of the sheet metal part, which is used for subsequent comparison and analysis with the measured sheet metal part model.
[0016] The standard model building module collects the design data of the target sheet metal parts and builds a standard model based on the design data, providing a reference for subsequent monitoring of sheet metal part processing and laying the foundation for intelligent monitoring and control of sheet metal processing.
[0017] The processing equipment configuration module 12 is used to obtain the processing control parameters of the sheet metal processing equipment based on the design data, and to configure the sheet metal processing equipment.
[0018] Specifically, after the target sheet metal part is determined and a standard sheet metal part model is constructed, the processing equipment configuration module 12 needs to obtain the processing control parameters of the sheet metal processing equipment based on the design data, and configure the sheet metal processing equipment so that the sheet metal part processing task can be executed subsequently.
[0019] The processing equipment configuration module 12 first receives the design data of the target sheet metal part. This design data is described in the form of CAD drawings and includes comprehensive information such as the sheet metal part's geometric shape, dimensional tolerances, and material properties. Then, the processing equipment configuration module 12 parses and extracts features from the received design data. For example, it reads the CAD drawing data through a CAD parsing engine to identify the sheet metal part's characteristic information, such as plate thickness, unfolded dimensions, and bending radius, obtaining the design parameters of the target sheet metal part. On the other hand, the processing equipment configuration module 12 connects to the CNC system of the sheet metal processing equipment, acquiring and synchronizing machine parameters through MES systems, industrial buses, and other means.
[0020] After obtaining the design and machine parameters, the processing equipment configuration module 12 analyzes the design requirements and equipment capabilities through mathematical modeling and logical reasoning to derive the processing control parameters. For example, it determines the blank holder force range based on the sheet thickness and material, selects the punch stroke based on the workpiece size and accuracy requirements, and sets compensation parameters while considering the material springback characteristics. Finally, the processing equipment configuration module 12 uploads the obtained processing control parameter set to the controller of the sheet metal processing equipment via wired or wireless means to configure the sheet metal processing equipment.
[0021] The sheet metal processing module 13 is used to perform sheet metal processing through the processing control parameters, obtain the processed sheet metal parts, and transmit the processed sheet metal parts to the processing monitoring area.
[0022] Specifically, after the sheet metal processing equipment completes the parameter configuration, the sheet metal processing module 13 begins to execute the actual processing task of the sheet metal part, and finally obtains the processed sheet metal part workpiece, and transfers it to the processing monitoring area for subsequent sheet metal part processing monitoring.
[0023] The sheet metal processing module 13 controls the sheet metal processing equipment to process sheet metal parts according to the processing control parameters generated by the processing equipment configuration module 12. The sheet metal processing equipment, based on the processing control parameters and following a preset processing flow, sequentially executes multiple processes such as blanking, leveling, stamping, and bending, gradually shaping the raw material into the actual processed sheet metal part. Upon completion of processing, the sheet metal processing module 13 controls a robotic arm or conveyor to remove the processed sheet metal part from the blanking area and send it to the designated processing monitoring area. Simultaneously, the sheet metal processing module 13 generates an electronic processing file for the processed sheet metal part, recording information such as the production batch, process parameters, and process data, and associates it with the workpiece's physical ID for quality traceability.
[0024] The measured model construction module 14 is used to start the processing monitoring device in the processing monitoring area, collect three-dimensional data of the processed sheet metal parts, and construct a measured sheet metal part model based on the data collection results.
[0025] Specifically, after the sheet metal parts are processed and transferred to the processing monitoring area, the actual measurement model construction module 14 begins to perform actual measurement modeling on the processed sheet metal parts. By collecting the three-dimensional morphology data of the processed parts, an actual measurement sheet metal part model reflecting its actual production state is constructed.
[0026] The measured model construction module 14 first activates the 3D measuring equipment, such as a structured light scanner and a laser tracker, deployed in the processing monitoring area. The measuring equipment uses optical or contact methods to collect data from all directions of the sheet metal component entering the processing monitoring area, acquiring point cloud data and line trajectories that characterize its appearance contours and dimensional relationships. During the data acquisition process, the measured model construction module 14 uses a registration algorithm to unify the coordinate system and spatially stitch the local data collected from different perspectives and measuring equipment, obtaining a complete digital representation of the entire sheet metal component's 3D shape, thus obtaining the measured sheet metal model.
[0027] The actual shape and size information of the processed sheet metal parts are obtained through the measured model construction module 14, and a high-fidelity measured 3D model is constructed to truly reflect the production and processing status of the processed sheet metal, providing a data basis for subsequent deviation comparison and error analysis.
[0028] The model registration module 15 is used to register the standard sheet metal part model and the measured sheet metal part model to obtain the model registration result.
[0029] Specifically, once both the standard sheet metal part model and the actual sheet metal part model are constructed, the model registration module 15 begins to spatially register the two models, preparing for subsequent processing error analysis.
[0030] The model registration module 15 first receives the standard sheet metal model from the standard model construction module 11 and the measured sheet metal model from the measured model construction module 14. Then, the model registration module 15 extracts feature elements from the two models, such as points, lines, and surfaces, to construct local or global feature descriptors. Subsequently, by calculating the similarity between the feature descriptors, it finds pairs of corresponding feature points on different models, establishing a feature correspondence between the two models. Based on the identified feature correspondence, the model registration module 15 constructs an error function to measure the pose difference between different models. This error function includes point-to-point distance and point-to-surface distance. Then, with the goal of minimizing the error function, an optimization algorithm is used to solve for the rotation matrix and translation vector, obtaining the optimal spatial transformation parameters from the measured sheet metal model to the standard sheet metal model. After obtaining the spatial transformation parameters, the model registration module 15 applies this transformation to the measured sheet metal model, aligning it with the standard sheet metal model to achieve model registration and obtain the model registration result.
[0031] The model registration module 15 realizes the spatial mapping between the processed sheet metal parts and their design models, establishes a precise correlation between the actual production state and the ideal state, and provides data support for the subsequent adjustment of processing control parameters.
[0032] The parameter control module 16 is used to obtain the processing error of the sheet metal part based on the model registration result, and to control the processing control parameters based on the processing error.
[0033] Specifically, after the standard sheet metal part model and the actual sheet metal part model are registered, the parameter control module 16 begins to evaluate the processing error of the sheet metal part and dynamically adjusts the processing control parameters of the sheet metal processing equipment according to the processing error, so as to realize closed-loop optimization control of the processing process.
[0034] The parameter control module 16 first extracts the registered measured sheet metal part model and the standard sheet metal part model generated by the model registration module 15. By comparing and analyzing the shape and size differences between the two models, it obtains the processing errors of the sheet metal part, including processing error indicators such as distance error, angle error, and geometric tolerance. The parameter control module 16 compares the obtained processing error indicators with the preset processing error thresholds to determine whether the current processing accuracy meets the design requirements. If the processing error exceeds the allowable range, the parameter control mechanism will be activated to determine the processing control parameters that need to be adjusted and their adjustment direction and magnitude based on the type and magnitude of the processing error.
[0035] After determining the adjustment plan, the parameter control module 16 further evaluates the potential impact of parameter adjustments and verifies their feasibility and effectiveness through simulation analysis and other means. Under the premise of ensuring reliable control, the system generates an updated set of processing control parameters and transmits it to the processing equipment configuration module 12, guiding the sheet metal processing equipment to complete parameter updates and providing optimized control instructions for subsequent sheet metal part processing. The parameter control process is continuously carried out at a certain sampling period according to the actual production rhythm. By dynamically acquiring processing error feedback, processing parameters are continuously optimized, achieving intelligent closed-loop control of the sheet metal processing process, ensuring high precision, high stability, and consistency throughout the entire production process. Through the parameter control module 16, the processing control parameters of the sheet metal processing equipment are adjusted to maximize product quality, reduce the generation of defective products, and improve production efficiency and yield.
[0036] Furthermore, the execution steps of the processing equipment configuration module include: Identify the original sheet metal part, collect the original parameters of the original sheet metal part, and simultaneously extract the design parameters based on the design data; retrieve the processing technology database of the sheet metal processing equipment, input the original parameters and the design parameters into the processing technology database, and obtain the processing control parameters of the sheet metal processing equipment.
[0037] In one feasible implementation, the processing equipment configuration module first identifies the original sheet metal part, i.e., the sheet metal blank or rough material to be processed. Through inspection and analysis of the original sheet metal part, its original parameters are obtained, including original dimensions, material, thickness, and other information. Simultaneously, the processing equipment configuration module extracts design parameters from the design data. These design parameters reflect the quality requirements of the target sheet metal part, such as mechanical properties and precision tolerances. By simultaneously acquiring both original and design parameters, the processing equipment configuration module can comprehensively grasp the technical requirements from raw materials to the target product, providing data input for generating processing control parameters.
[0038] After obtaining the original and design parameters, the processing equipment configuration module retrieves the corresponding processing technology database for the sheet metal processing equipment. This database contains a wealth of process knowledge and practical experience, including material properties, mold parameters, process specifications, and more, serving as a crucial knowledge source for intelligent generation of process parameters. The processing equipment configuration module inputs the collected original and design parameters into the processing technology database. Using the database's empirical rules and computational models, and through logical operations and optimization analysis, it derives a set of processing control parameters that match the input conditions. These parameters cover various process parameters such as pressure, speed, and temperature, guiding the sheet metal processing equipment in its production operations and transforming the original sheet metal parts into target sheet metal parts that meet the design requirements.
[0039] By making full use of existing process knowledge and combining the specific parameters of the original and target parts, the processing control parameters required by the sheet metal processing equipment are generated, reducing reliance on manual experience and improving production efficiency.
[0040] Furthermore, the execution steps of the processing equipment configuration module also include: The historical processing database of the interactive sheet metal processing equipment is used to collect multiple historical processing case data. Each historical processing case data includes original sheet metal part data, sheet metal part design data, and corresponding sheet metal part processing control data. The multiple historical processing case data are processed to extract feature parameters of the original sheet metal part data, sheet metal part design data, and sheet metal part processing control data, and the feature parameters are standardized. Based on the standardized feature parameters, a correlation mapping model between the original parameters, design parameters, and processing control parameters is constructed to obtain the processing technology database.
[0041] In a preferred embodiment, the processing equipment configuration module first interacts with the historical processing database of the sheet metal processing equipment to collect data from multiple historical processing cases. Each historical processing case contains complete production information, covering the original parameters of the sheet metal part (such as material, dimensions, etc.), design parameters (such as mechanical properties, precision requirements, dimensions, etc.), and the actual processing control parameters used (such as pressure, speed, etc.). This data records successful processing experience of different types of sheet metal parts under different process conditions, containing rich process knowledge. After collecting multiple historical processing case data, the processing equipment configuration module begins to intelligently process and analyze this data. First, it extracts key features such as the original parameters, design parameters, and processing control parameters of the sheet metal part from each historical processing case data, forming structured feature parameters. To facilitate the construction of the processing technology database, the processing equipment configuration module performs standardization processing on the extracted feature parameters. Through data normalization, dimensionless processing, and other operations, it maps parameters with different dimensions to a unified scale space, eliminating scale differences between data.
[0042] After data preprocessing, the processing equipment configuration module utilizes standardized feature parameters to construct a correlation mapping model between original parameters, design parameters, and processing control parameters through regression analysis, neural networks, and support vector machines. This model, from a data-driven perspective, characterizes the inherent relationships and changing patterns among the three types of parameters, reflecting the constraints and balance among materials, design, and processes. By constructing this correlation mapping model, the processing equipment configuration module summarizes and extracts a processing technology database from historical processing case data. When a new sheet metal processing task arises, only its original and design parameters need to be input; the correlation mapping model in the processing technology database can then generate applicable processing control parameters, thereby achieving intelligent recommendation and optimization of process parameters.
[0043] By fully utilizing historical production data accumulated from sheet metal processing equipment, and through data mining and machine learning modeling, a processing technology database was built, realizing the transformation from experience-driven to data-driven approaches. This improved the intelligence level of sheet metal processing control parameter generation and laid a solid foundation for achieving adaptive control and continuous optimization of sheet metal processing.
[0044] Furthermore, the execution steps of the model registration module include: Key feature points are extracted from the measured sheet metal part model to obtain a set of feature points to be registered, wherein the set of feature points to be registered includes multiple feature points to be registered; standard feature points corresponding to the multiple feature points to be registered are extracted from the standard sheet metal part model to obtain a set of standard feature points; with the goal of minimizing the pose error between the models, the ICP algorithm is used to register the set of standard feature points and the set of feature points to be registered, and the optimal rigid transformation parameters are solved to obtain the model registration result.
[0045] In one feasible implementation, during model registration, a set of key feature points is first extracted from the measured sheet metal model as a reference for subsequent registration operations. These feature points are selected at locations where the geometric features of the sheet metal part are obvious and easily identifiable and matched, such as edges, corners, and hole centers. The model registration module analyzes the geometric shape and topology of the measured sheet metal model and uses feature extraction algorithms (such as Harris corner detection and SIFT feature description) to identify and extract these key feature points, forming a set of feature points to be registered. This set of feature points contains multiple feature points distributed at different locations on the measured sheet metal model, comprehensively depicting the spatial morphology of the measured sheet metal model. These extracted feature points will serve as reference benchmarks for the measured sheet metal model during the registration process, matching and aligning with corresponding feature points on the standard sheet metal model, providing a reference for accurate registration.
[0046] Subsequently, a set of standard feature points corresponding to the feature points to be registered is found in the standard sheet metal part model. Using the feature points to be registered as references, corresponding feature points are searched on the standard sheet metal part model. Specifically, for each feature point in the set to be registered, the model registration module searches for its corresponding point on the standard sheet metal part model. For example, if the feature point to be registered is located at the center of a hole in the measured sheet metal part model, then the corresponding standard feature point on the standard sheet metal part model should also be located at the center of the corresponding hole; similarly, if the feature point to be registered is a sharp corner point in the measured sheet metal part model, then the corresponding standard feature point should also be a corner point on the standard sheet metal part model. Through feature point extraction based on the correspondence, the model registration module finally obtains a set of standard feature points that match the set of feature points to be registered. In this way, a one-to-one mapping relationship is formed between the feature points to be registered and the standard feature points, providing a foundation for subsequent registration operations.
[0047] After obtaining the standard feature point set and the feature point set to be registered, the model registration module executes the registration algorithm to align the spatial pose of the measured sheet metal model with that of the standard sheet metal model. The ICP algorithm iteratively updates the spatial pose of the measured sheet metal model to maximize its overlap with the standard model. Specifically, in each iteration, a corresponding point is first found for each feature point in the feature point set to be registered, forming a pairing relationship. Then, using minimizing the distance error between the paired points in the two feature point sets as the objective function, an optimal rigid transformation (including rotation matrix and translation vector) is solved to spatially transform the measured sheet metal model, bringing it closer to the standard model. Next, the nearest point correspondence is recalculated, and the next round of iterative optimization begins. This process is repeated until a preset error threshold or the maximum number of iterations is reached. The rigid transformation parameters ultimately solved by the ICP algorithm, including the rotation matrix and translation vector, describe how the measured sheet metal model is aligned with the standard sheet metal model through rigid body motion. By performing spatial transformation on the measured sheet metal part model according to the solved optimal rigidity transformation parameters, the registered measured sheet metal part model can be obtained. This realizes the transformation and alignment of the measured sheet metal part model to the standard sheet metal part model coordinate system, providing a spatial reference for subsequent processing error analysis.
[0048] Furthermore, such as Figure 2 As shown, the execution steps of the model registration module include: Based on the standard sheet metal part model, multiple registration reference points are selected, and the multiple registration reference points have a first spatial constraint relationship; reference point query is performed on the measured sheet metal part model according to the multiple registration reference points to obtain multiple measured reference points; it is determined whether the multiple measured reference points satisfy the first spatial constraint relationship, and when the multiple measured reference points satisfy the spatial constraint relationship, the model registration result is obtained.
[0049] In a preferred embodiment, during model registration, a set of registration reference points must first be selected on the standard sheet metal model. These reference points are chosen at key locations on the standard sheet metal model, such as distinctive corner points, edge points, and hole centers. When selecting registration reference points, in addition to considering their representativeness and identifiability on the model, certain first spatial constraints must also be satisfied. These first spatial constraints refer to the geometric topological rules that multiple registration reference points must satisfy, such as collinearity, coplanarity, symmetry, and parallelism. These reflect the structural characteristics of the standard sheet metal model itself and help improve the accuracy and reliability of registration. For example, for a certain sheet metal part, three non-collinear corner points on the standard sheet metal model can be selected as registration reference points, and the lines connecting each pair of them must satisfy a triangle constraint; or points on two parallel edges of the standard sheet metal model can be selected as reference points, and they must satisfy the constraints of being parallel and equidistant. The model registration module selects a set of registration reference points that satisfy the first spatial constraint relationship based on the geometric features of the standard sheet metal part model. These reference points and their spatial constraint relationships provide a reference standard for finding the corresponding points in the actual sheet metal part model.
[0050] After determining the registration reference points on the standard sheet metal part model, the model registration module needs to find a set of corresponding measured reference points on the actual sheet metal part model. Specifically, the model registration module uses the feature information (such as position coordinates, local geometric attributes, etc.) of each registration reference point on the standard sheet metal part model as query conditions to search for the most matching point on the actual sheet metal part model, which is then used as the corresponding measured reference point. This query process considers the possible differences in scale, position, orientation, etc., between the actual sheet metal part model and the standard sheet metal model, and finds the most likely corresponding point through feature matching algorithms (such as feature point descriptor matching, local shape context matching, etc.). By querying the registration reference points on the standard sheet metal part model one by one, the model registration module finally obtains a set of corresponding measured reference points on the actual sheet metal part model. These measured reference points are the set of reference points on the actual sheet metal part model that best match the standard sheet metal model, and there is a one-to-one correspondence between them and the registration reference points.
[0051] After obtaining a set of measured reference points on the actual sheet metal part model corresponding to the registration reference points, the model registration module needs to verify whether these measured reference points satisfy the same first spatial constraint relationship as the registration reference points. Specifically, the model registration module checks whether the spatial relationship between the measured reference points meets the requirements according to the geometric topological rules described by the first spatial constraint relationship. For example, if the registration reference points need to satisfy the collinearity constraint, then the corresponding measured reference points should also be collinear; if the registration reference points need to satisfy the symmetry constraint, then the measured reference points should also be symmetrical. If the measured reference points satisfy the first spatial constraint relationship, it means that they are consistent with the registration reference points in terms of spatial distribution and structural features, and there is a reasonable correspondence between the two sets of reference points. At this time, this reference point correspondence relationship can be used to establish the registration between the standard sheet metal part model and the actual sheet metal part model to obtain the model registration result. If the measured reference points do not satisfy the first spatial constraint relationship, it means that they deviate from the registration reference points in terms of spatial distribution, and a reliable correspondence cannot be established. At this point, it is necessary to reselect the registration reference points or adjust the method for finding the measured reference points until a set of measured reference points that satisfies the constraint relationship is found.
[0052] By using a registration benchmark selection mechanism based on spatial constraints, benchmarks that satisfy specific geometric topological rules are selected on standard sheet metal models and actual sheet metal models to establish a correspondence between them, thereby achieving model registration and laying the foundation for subsequent error analysis.
[0053] Furthermore, the execution steps of the model registration module also include: When multiple measured reference points satisfy the first spatial constraint relationship, multiple additional registration reference points are randomly selected again in the standard sheet metal model. These additional registration reference points have a second spatial constraint relationship. Reference point queries are performed in the measured sheet metal model according to the multiple additional registration reference points to obtain multiple additional measured reference points. Additional authentication results are generated based on the multiple additional measured reference points and the second spatial constraint relationship. Model registration results are obtained based on the additional authentication results.
[0054] In a preferred embodiment, after confirming that the measured reference points satisfy the first spatial constraint relationship, the model registration module will select another set of additional registration reference points on the standard sheet metal model to further improve the reliability and accuracy of the registration. Similar to the initial registration reference points, these additional registration reference points are also selected from key feature locations (such as corner points, edge points, hole centers, etc.) of the standard model. However, unlike the initial registration reference points, the selection of additional registration reference points is random. A set of points is randomly sampled on the standard sheet metal model as additional registration reference points, and these additional registration reference points have a second spatial constraint relationship. The second spatial constraint relationship is a rule describing the geometric topological relationship between the additional registration reference points, such as collinearity, coplanarity, symmetry, etc. By randomly selecting a set of additional registration reference points, the model registration module can further optimize the distribution of registration reference points based on the initial registration, thereby improving the robustness of the registration.
[0055] After selecting additional registration reference points on the standard sheet metal part model, the model registration module needs to find a set of corresponding additional measured reference points on the actual sheet metal part model. The model registration module uses the feature information of each additional registration reference point as a query condition, searching for the most matching point on the actual sheet metal part model as the corresponding additional measured reference point. This query process also considers the differences in scale, position, and orientation between the actual sheet metal part model and the standard sheet metal part model, finding the most likely corresponding point through a feature matching algorithm. By querying each additional registration reference point, the model registration module finally obtains a set of corresponding additional measured reference points on the actual sheet metal part model. These additional measured reference points also have a one-to-one correspondence with the additional registration reference points, reflecting the spatial correspondence between the actual sheet metal part model and the standard sheet metal part model at the additional reference points.
[0056] After obtaining a set of additional measured reference points on the actual sheet metal part model corresponding to the additional registration reference points, the model registration module needs to verify whether these additional measured reference points satisfy the second spatial constraint relationship and generate additional certification results accordingly. Specifically, the model registration module checks whether the spatial relationship between the additional measured reference points meets the requirements according to the geometric topology rules described by the second spatial constraint relationship. If the additional measured reference points satisfy the second spatial constraint relationship, it means that they are consistent with the additional registration reference points in terms of spatial distribution and structural features, and there is a reasonable correspondence between the two sets of reference points, and the additional certification result is positive; conversely, if the additional measured reference points do not satisfy the second spatial constraint relationship, it means that the model registration result is inaccurate, and the additional certification result is negative.
[0057] The model registration module comprehensively considers the initial model registration result and the additional certification result to obtain the final model registration result. If both the initial model registration result and the additional certification result are positive, it means that the initial registration reference point and the additional registration reference point have found reasonable corresponding points on both the standard sheet metal model and the actual sheet metal model, and the registration relationship between the two models is reliable. At this time, the final model registration result can be output. If the initial registration result is positive but the additional certification result is negative, it means that the initial registration is basically correct, but further optimization is needed. At this time, the initial model registration result is fine-tuned based on the feedback information of the additional certification.
[0058] By introducing additional registration reference points and an additional verification mechanism, the reliability and accuracy of model registration are further improved. By randomly selecting and verifying additional registration reference points that satisfy the second spatial constraint relationship, the model registration module evaluates the correctness of registration at multiple scales and angles, avoiding the limitations of a single registration standard. Simultaneously, the additional verification results provide feedback for the optimization and iteration of the registration results, enabling the registration process to dynamically adjust and adapt, ultimately resulting in a more accurate and stable registration relationship. Compared with traditional single registration methods, this scheme significantly improves the credibility of the registration results through multi-level and multi-angle registration verification, providing a more reliable data foundation for subsequent processing error analysis and processing control parameter optimization.
[0059] Furthermore, the execution steps of the parameter control module include: The processing error is compared with a preset processing error threshold to obtain the target error type and target error value that exceed the processing error threshold; a pre-built mapping relationship library between processing error characteristics and control parameter changes is accessed to convert the target error type and target error value into corresponding control parameter adjustment directions and control parameter adjustment amounts, generating control parameter adjustment data; the control parameter adjustment data is processed with the current processing control parameters to obtain the adjusted processing control parameters; the adjusted processing control parameters are configured on the sheet metal processing equipment to complete the processing control parameter regulation.
[0060] In one reliable implementation, after model registration is complete, the parameter control module acquires the machining error between the measured sheet metal part model and the standard sheet metal part model. To determine whether the machining error is within an acceptable range, the parameter control module compares the machining error with a preset machining error threshold. The machining error threshold is set based on the design data of the target sheet metal part and represents the upper limit of the machining error. Specifically, the machining error threshold is set separately for different types of errors (such as dimensional errors, form and position errors, surface quality errors, etc.) to consider the impact of different errors on the quality of the sheet metal part. The parameter control module compares the machining error with the corresponding machining error threshold one by one, identifies error items that exceed the threshold, and records their error type and specific error value to obtain the target error type and target error value.
[0061] After identifying the target error type and target error value, the parameter control module needs to determine how to adjust the machining control parameters to eliminate or reduce these errors. To this end, a mapping database of machining error characteristics and control parameter changes is pre-built. This database, based on extensive machining experience and experimental data, summarizes the correspondence between different types and degrees of machining errors and control parameter adjustments. Each record in the database describes the mapping relationship between a certain error characteristic (such as error type, error value range, etc.) and the corresponding control parameter adjustment strategy (such as adjustment direction, adjustment amount, etc.). When the parameter control module obtains the target error type and target error value, it accesses this mapping database to find records that match the target error type and target error value. Through matching, the parameter control module transforms the target error type and target error value into a specific control parameter adjustment scheme, determining which control parameters need to be adjusted, the direction of adjustment (increase or decrease), and the magnitude of adjustment. For example, if the target error is that the size of a certain hole is too large, a record is found in the mapping relationship library, indicating that when the hole size error is within a certain range, the punching force needs to be appropriately reduced, and a recommended reduction amount is given. Based on this, the parameter control module generates control parameter adjustment data, instructing the punching force parameter to be reduced according to a specific value.
[0062] After generating the control parameter adjustment data, the parameter control module integrates it with the currently used machining control parameters to obtain updated control parameter values. Specifically, the parameter control module performs arithmetic operations on the adjustment values (such as increments or decrements) of each parameter indicated in the control parameter adjustment data with the corresponding current control parameters. For numerical parameters (such as pressure, speed, etc.), addition and subtraction are performed directly; for categorical parameters (such as mold type, process sequence, etc.), switching or replacement is performed according to predetermined rules. By processing the control parameter adjustment data with the current machining control parameters, the parameter control module obtains a set of adjusted machining control parameters. This set considers the original machining control parameter settings and targeted error optimization adjustments, enabling targeted improvement of machining quality and elimination or reduction of the impact of errors while ensuring machining stability.
[0063] After receiving the adjusted machining control parameters, the parameter control module applies them to the sheet metal processing equipment to guide subsequent production processes. The module transmits the adjusted machining control parameters to the CNC system or PLC of the sheet metal processing equipment via a digital interface or communication protocol. Upon receiving the adjusted parameters, the CNC system or PLC replaces the original settings. After the parameter update, the sheet metal processing equipment optimizes the machining process according to the adjusted parameters, thereby improving the dimensional accuracy, form and position accuracy, and surface quality of the produced sheet metal parts, and eliminating or reducing machining errors.
[0064] By configuring the adjusted processing control parameters to the sheet metal processing equipment in real time, the parameter control module completes a full parameter control process. This closed-loop feedback control mechanism ensures that the processing error analysis results can guide production processing in a timely and effective manner, achieving continuous improvement and optimization of sheet metal processing quality.
[0065] Furthermore, embodiments of this application also include a timing parameter control module, the execution steps of which include: Set a monitoring time zone for control parameters, and extract multiple sets of processing control parameters for the monitoring time zone; obtain multiple sets of processing errors corresponding to the multiple sets of processing control parameters, and analyze the error change trend of the multiple sets of processing errors; analyze the parameter time sequence change of the multiple sets of processing control parameters based on the error change trend, and adjust the processing control parameters according to the analysis results.
[0066] In a preferred embodiment, during continuous sheet metal production, processing control parameters may change over time, affecting production quality. To understand the dynamic changes in these parameters, continuous monitoring and analysis are necessary. The timing parameter control module first sets a control parameter monitoring time zone. This time zone is a continuous time window used to collect and analyze time-series data of the processing control parameters. The length of the time zone can be set according to factors such as production cycle time and process requirements. After determining the control parameter monitoring time zone, the timing parameter control module extracts multiple sets of processing control parameters within that time zone from the CNC system of the sheet metal processing equipment. The extracted sets of processing control parameters exist as multiple sets of parameter values, each containing the actual values of various processing control parameters at a specific time point or time period, such as pressure, speed, and displacement. By setting a control parameter monitoring time zone and extracting the parameter data within it, the timing parameter control module obtains a time-series sample reflecting the dynamic changes in processing control parameters, laying a data foundation for subsequent timing analysis and trend prediction.
[0067] After acquiring multiple sets of processing control parameters within the monitoring time zone, the time-series parameter control module needs to perform correlation analysis with the processing errors of sheet metal parts produced within the corresponding time period to reveal the dynamic relationship between control parameter changes and processing quality. To this end, the time-series parameter control module acquires multiple sets of processing error data corresponding to the multiple sets of processing control parameters within the monitoring time zone. Each set of processing error data reflects various error indicators of the sheet metal parts produced with the corresponding processing control parameters, such as dimensional errors, form and position errors, and surface roughness. By establishing a one-to-one correspondence between multiple sets of processing control parameters and multiple sets of processing errors, the time-series parameter control module establishes a dynamic mapping relationship between parameter changes and error fluctuations. Based on this, time-series data analysis methods, such as time series decomposition, trend extraction, and anomaly detection, are used to comprehensively analyze the multiple sets of processing error data, uncover their changing trends and regularities, and obtain the error change trends of the multiple sets of processing errors. For example, by processing the machining error data through moving averages, periodic analysis, etc., we can discover whether the error index has a trend of gradually increasing or decreasing, whether it exhibits a periodic fluctuation pattern, or whether there are sudden outliers. These error change trends reflect the dynamic change characteristics of machining quality and are an important basis for parameter timing optimization.
[0068] After obtaining the trend of machining errors, the time-series parameter control module further analyzes the causes of these quality fluctuations in the control parameters and generates a dynamic parameter control strategy accordingly. Specifically, the time-series parameter control module performs correlation analysis between the error change trends of multiple sets of machining errors and the time-series changes of multiple sets of machining control parameters. By calculating the correlation and causal relationship between machining control parameters and machining errors at different time scales, it identifies machining control parameters that significantly affect machining quality fluctuations and explores the correspondence between their change patterns and quality trends. For example, the analysis found that a certain dimensional error showed a gradually increasing trend, while the corresponding pressure parameter also showed a continuous upward trend, and there was a significant positive correlation between the two. Based on this, it can be inferred that the abnormal increase in the pressure parameter may be the main reason for the increase in dimensional error. Based on the results of the parameter time-series change analysis, the time-series parameter control module generates a corresponding control parameter control strategy. This strategy differs from the immediate control of single machining error feedback; instead, it is a dynamic optimization for continuous production processes, comprehensively considering factors such as error change trends, parameter fluctuation patterns, and the long-term effects of control, and provides a dynamic parameter adjustment scheme based on time series. For example, regarding the issue of increased dimensional errors caused by abnormal increases in pressure parameters, the control strategy suggests gradually reducing the pressure parameters over a future period to suppress further deterioration of the errors. Simultaneously, the strategy may also recommend increasing the frequency of pressure parameter monitoring during production to promptly detect and address abnormal fluctuations. The timing parameter control module transforms the generated control strategy into parameter adjustment instructions executable by the CNC system, which are then sent to the sheet metal processing equipment via a digital interface. This guides the equipment to dynamically adjust processing control parameters during production, achieving predictive control and continuous optimization of processing quality.
[0069] By introducing a time-series parameter control mechanism, dynamic monitoring, analysis, and optimization of sheet metal processing parameters are achieved. This mechanism focuses on the correlation between processing parameters and processing quality over time during continuous production. Through time-series parameter analysis and trend prediction, it generates dynamic parameter optimization strategies for the future, enabling predictive dynamic control of processing parameters during production. Compared to parameter adjustments based on single error feedback, this approach fully leverages historical data to uncover production patterns and quality trends, allowing for proactive prevention and dynamic optimization before problems occur, thus improving the foresight and effectiveness of parameter control. Furthermore, continuous monitoring and dynamic feedback enable long-term closed-loop optimization between processing control parameters and processing quality, contributing to continuously improving the stability of sheet metal processing and the consistency of product quality.
[0070] In summary, the sheet metal processing monitoring and control system provided in this application has the following technical effects: The standard model construction module is used to identify the target sheet metal part, collect its design data, and construct a standard sheet metal part model based on the design data, providing a reference for subsequent processing monitoring and error analysis. The processing equipment configuration module is used to obtain the processing control parameters of the sheet metal processing equipment based on the design data, configure the equipment, and translate design requirements into processing instructions for sheet metal part manufacturing. The sheet metal part processing module executes sheet metal part processing according to the processing control parameters, acquires the processed sheet metal part, and transmits it to the processing monitoring area to complete the sheet metal part manufacturing process. The measured model construction module activates the processing monitoring device in the processing monitoring area, collects 3D data of the processed sheet metal part, and constructs a measured sheet metal part model based on the data acquisition results. It also collects 3D data of the completed sheet metal part and reconstructs a measured sheet metal part model reflecting its actual size and shape through point cloud data analysis, providing a data foundation for accuracy assessment. The model registration module is used to register standard sheet metal part models and actual measured sheet metal part models, obtain the model registration results, and quantitatively evaluate the actual accuracy of the machined part by comparing and analyzing the deviation between the two models, providing a basis for optimizing machining parameters. The parameter control module is used to obtain the machining error of the machined sheet metal part based on the model registration results, and adjust the machining control parameters based on the machining error to ensure that the machining accuracy of the sheet metal part meets the design requirements, thus improving the machining accuracy and efficiency of sheet metal parts.
[0071] In summary, any step of the system described above can be stored as a computer instruction or program in an unrestricted computer memory, and can be called and recognized by an unrestricted computer processor to implement any of the systems in the embodiments of this application, without any additional restrictions.
[0072] Furthermore, the "first" or "second" mentioned above may not only represent a sequential relationship, but may also represent a specific concept, and / or refer to the individual or collective selection of multiple elements. Clearly, those skilled in the art can make various modifications and variations to this application without departing from its scope. Therefore, if such modifications and variations fall within the scope of this application and its equivalents, this application intends to include such modifications and variations.
Claims
1. A sheet metal processing monitoring and control system, characterized in that, The system includes: A standard model construction module is used to determine the target sheet metal part, collect the design data of the target sheet metal part, and construct a standard sheet metal part model based on the design data. A processing equipment configuration module is used to obtain the processing control parameters of the sheet metal processing equipment based on the design data, and to configure the sheet metal processing equipment. A sheet metal processing module is used to perform sheet metal processing according to the processing control parameters, obtain the processed sheet metal parts, and transmit the processed sheet metal parts to the processing monitoring area. The measured model construction module is used to start the processing monitoring device in the processing monitoring area, collect three-dimensional data of the processed sheet metal part, and construct a measured sheet metal part model based on the data collection results. The model registration module is used to register the standard sheet metal part model and the measured sheet metal part model to obtain the model registration result. The parameter control module is used to obtain the processing error of the sheet metal part based on the model registration result, and to adjust the processing control parameters based on the processing error.
2. The system according to claim 1, characterized in that, The execution steps of the processing equipment configuration module include: Identify the original sheet metal parts, collect the original parameters of the original sheet metal parts, and simultaneously extract design parameters based on the design data; The processing technology database of the sheet metal processing equipment is retrieved, and the original parameters and the design parameters are input into the processing technology database to obtain the processing control parameters of the sheet metal processing equipment.
3. The system according to claim 2, characterized in that, The execution steps of the processing equipment configuration module also include: The historical processing database of the sheet metal processing equipment is interactive to collect data from multiple historical processing cases. Each historical processing case includes original sheet metal data, sheet metal design data, and corresponding sheet metal processing control data. Multiple historical processing case data are processed to extract feature parameters from sheet metal original data, sheet metal design data and sheet metal processing control data, and the feature parameters are then standardized. Based on the standardized feature parameters, a correlation mapping model is constructed between the original parameters, design parameters and machining control parameters to obtain a machining process database.
4. The system according to claim 1, characterized in that, The execution steps of the model registration module include: Key feature points are extracted from the measured sheet metal model to obtain a set of feature points to be registered, wherein the set of feature points to be registered includes multiple feature points to be registered. Standard feature points corresponding to multiple feature points to be registered are extracted from the standard sheet metal part model to obtain a standard feature point set. With the goal of minimizing the pose error between models, the ICP algorithm is used to register the standard feature point set and the feature point set to be registered, and the optimal rigid transformation parameters are solved to obtain the model registration result.
5. The system according to claim 1, characterized in that, The execution steps of the model registration module include: Based on the standard sheet metal part model, multiple registration reference points are selected, and the multiple registration reference points have a first spatial constraint relationship. Based on multiple registration reference points, the reference point query is performed on the actual sheet metal part model to obtain multiple actual reference points; Determine whether the plurality of measured reference points satisfy the first spatial constraint relationship. When the plurality of measured reference points satisfy the spatial constraint relationship, obtain the model registration result.
6. The system according to claim 5, characterized in that, The execution steps of the model registration module also include: When multiple measured reference points satisfy the first spatial constraint relationship, multiple additional registration reference points are randomly selected again in the standard sheet metal model, and the multiple additional registration reference points have a second spatial constraint relationship. Based on multiple additional registration reference points, the reference point query is performed on the actual sheet metal part model to obtain multiple additional actual measurement reference points; Additional authentication results are generated based on the multiple additional measured reference points and the second spatial constraint relationship, and model registration results are obtained based on the additional authentication results.
7. The system according to claim 1, characterized in that, The execution steps of the parameter control module include: The processing error is compared with a preset processing error threshold to obtain the target error type and target error value that exceed the processing error threshold; Access a pre-built mapping database of processing error characteristics and control parameter changes, convert the target error type and target error value into the corresponding control parameter adjustment direction and control parameter adjustment amount, and generate control parameter adjustment data; The control parameter adjustment data is processed together with the current machining control parameters to obtain the adjusted machining control parameters; Configure the adjusted processing control parameters on the sheet metal processing equipment to complete the processing control parameter adjustment.
8. The system according to claim 1, characterized in that, The system also includes a timing parameter control module, the execution steps of which include: Set the control parameter monitoring time zone, and extract multiple sets of processing control parameters for the control parameter monitoring time zone; Multiple sets of machining errors corresponding to multiple sets of machining control parameters are obtained respectively, and the error variation trend of multiple sets of machining errors is analyzed. Based on the error change trend, the time-series changes of the multiple sets of machining control parameters are analyzed, and the machining control parameters are adjusted according to the analysis results.