Automatic engineering drawing examination method and system embedded in examination and approval system

Abstract

The invention discloses an automatic engineering drawing auditing method and system embedded into an auditing system. The method comprises the steps that all geometric objects in an engineering drawing are extracted, topology analysis and semantic recognition are conducted on each geometric object, all machining feature elements of each geometric object are obtained, and a feature vector set of each machining feature element is constructed; acquiring a process type and an equipment model corresponding to the processing feature element, setting a processing feasibility evaluation model, and calculating a matching index of the processing feature element relative to the process type and the equipment model according to the feature vector set of the processing feature element; and mapping the matching index into a feasibility score, and judging whether the processing characteristic element can be manufactured relative to the process type and the equipment model according to the feasibility score, so as to complete the automatic drawing checking of the engineering drawing.

Description

Technical Field

[0001] This invention belongs to the field of automatic review technology for engineering drawings, and more specifically, relates to an automatic review method and system for engineering drawings embedded in an approval system. Background Technology

[0002] In existing technologies, the manufacturability (DFM) review of engineering drawings mainly relies on two types of methods: one is manual or semi-automatic inspection based on design specifications and rules of experience. This involves engineers manually comparing various geometric features in the drawings to manufacturing requirements based on factory experience, process manuals, or standardized design specifications. For example, they check whether the inner corner radius is greater than the radius of commonly used cutting tools, whether the hole depth-to-diameter ratio exceeds the processing capabilities of common machine tools, and whether the draft angle meets the requirements for injection molding or die casting. The other method is based on simple geometric rules embedded in the CAD system. This involves extracting dimensions and features using built-in geometric quantification tools in the software and comparing them with preset thresholds. For example, parameters such as "minimum radius" and "maximum depth-to-diameter ratio" are set in the CAD environment to automatically mark features that exceed the conditions. The former relies heavily on expert experience and suffers from low inspection efficiency, numerous missed or misjudged checks, and difficulty in ensuring consistency across industries or equipment. While the latter achieves a certain degree of automation, it typically uses a single-dimensional, fixed-threshold judgment method, which cannot reflect the complex relationships between different processing technologies and equipment capabilities.

[0003] Therefore, there is an urgent need for a new technical solution that can achieve intelligent manufacturability assessment of design features, thereby effectively making up for the shortcomings of existing technologies. Summary of the Invention

[0004] To address the above technical problems, this invention proposes an automatic drawing review method embedded in an approval system, comprising: Extract all geometric objects from the engineering drawings, perform topology analysis and semantic recognition on each geometric object, obtain all processing feature elements of each geometric object, and construct a feature vector set for each processing feature element; Obtain the process type and equipment model corresponding to the processing feature element, set up a processing feasibility assessment model, and calculate the matching index of the processing feature element relative to the process type and equipment model based on the feature vector set of the processing feature element; The matching index is mapped to a feasibility score. Based on the feasibility score, it is determined whether the processing feature elements are manufacturable relative to the process type and equipment model, thereby completing the automatic review of engineering drawings.

[0005] Furthermore, obtaining all machining feature elements for each geometric object also includes assigning a unique number to each machining feature element in the feature vector set and marking it on the engineering drawing.

[0006] Furthermore, determining whether a processing feature element is manufacturable relative to the process type and equipment model based on the feasibility score includes: when the feasibility score falls within the first threshold range, the processing feature element is in the manufacturable zone relative to the process type and equipment model; when the feasibility score falls within the second threshold range, the processing feature element is in the critical risk zone relative to the process type and equipment model; when the feasibility score falls within the third threshold range, the processing feature element is in the non-manufacturable zone relative to the process type and equipment model. The minimum value of the first threshold range is greater than the maximum value of the second threshold range, and the minimum value of the second threshold range is greater than the maximum value of the third threshold range.

[0007] Furthermore, when a processing feature element is in a critical risk zone relative to the process type and equipment model, an alarm message is issued, the corresponding processing feature element number on the engineering drawing is displayed, and the engineering drawing is transferred to manual approval. When a machining feature element is in the non-manufacturable zone relative to the process type and equipment model, the corresponding machining feature element number on the engineering drawing will be displayed, and a prompt will be given to modify the machining feature element so that the corresponding machining feature element is in the manufacturable zone.

[0008] Furthermore, the processing feasibility assessment model includes: , in, For the first Each processing feature element relative to the process type and equipment model The matching index, For the first A set of feature vectors for each processing feature element. For matrix transpose, In terms of process type and equipment model The average value of the manufacturing feature vectors of all samples under the given conditions. In terms of process type and equipment model Under the condition of [condition], the covariance of the manufacturing feature vectors of all samples, and The number and type of feature vectors in the middle The corresponding feature vectors.

[0009] Furthermore, mapping the matching index to a feasibility score includes: , in, For feasibility scoring, For the logistic function, As an adjustment factor for the feasibility score, For the first Each processing feature element relative to the process type and equipment model The matching index threshold.

[0010] Furthermore, obtain the device model in real time. The degree of wear, and for process types and equipment model The average value of the manufacturing feature vectors of all samples under the given conditions Update.

[0011] Furthermore, regarding the type of process and equipment model The average value of the manufacturing feature vectors of all samples under the given conditions The updates include: , in, In terms of process type and equipment model Under the condition that the initial average value of the manufacturing feature vectors of all samples is, For time Time equipment model Wear and tear.

[0012] This invention also proposes an automatic drawing review system for engineering drawings embedded in an approval system, comprising: The data extraction module is used to extract all geometric objects in the engineering drawings, perform topological analysis and semantic recognition on each geometric object, obtain all processing feature elements of each geometric object, and construct a feature vector set for each processing feature element. The index calculation module is used to obtain the process type and equipment model corresponding to the processing feature element, set up the processing feasibility assessment model, and calculate the matching index of the processing feature element relative to the process type and equipment model based on the feature vector set of the processing feature element. The feasibility analysis module maps the matching index to a feasibility score. Based on the feasibility score, it determines whether the processing feature elements are manufacturable relative to the process type and equipment model, thereby completing the automatic review of engineering drawings.

[0013] Furthermore, obtaining all machining feature elements for each geometric object also includes assigning a unique number to each machining feature element in the feature vector set and marking it on the engineering drawing.

[0014] In summary, the technical solutions conceived by this invention have the following beneficial effects compared with the prior art: The technical solution of this invention can avoid the one-sidedness of a single threshold judgment, comprehensively consider the synergistic constraints and correlations of multi-dimensional features, and more accurately determine whether the design exceeds the manufacturability boundary of the process or equipment. This improves the intelligence level of manufacturability review of engineering drawings, reduces reliance on human experience, discovers potential manufacturing risks in advance, shortens the design-manufacturing iteration cycle, and improves the overall design quality and manufacturing consistency. Attached Figure Description

[0015] Figure 1 This is a flowchart of the method in Embodiment 1 of the present invention; Figure 2 This is a system structure diagram of Embodiment 2 of the present invention. Detailed Implementation

[0016] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0017] The method provided by this invention can be implemented in a terminal environment that may include one or more of the following components: a processor, a storage medium, and a display screen. The storage medium stores at least one instruction, which is loaded and executed by the processor to implement the method described in the following embodiments.

[0018] A processor may include one or more processing cores. The processor uses various interfaces and lines to connect various parts of the terminal, and performs various functions and processes data by running or executing instructions, programs, code sets or instruction sets stored in the storage medium, and by calling data stored in the storage medium.

[0019] Storage media can include random access memory (RAM) or read-only memory (ROM). Storage media can be used to store instructions, programs, code, code sets, or instructions.

[0020] The display screen is used to show the user interface of each application.

[0021] In addition, those skilled in the art will understand that the structure of the terminal described above does not constitute a limitation on the terminal. The terminal may include more or fewer components, or combine certain components, or have different component arrangements. For example, the terminal may also include radio frequency circuits, input units, sensors, audio circuits, power supplies, and other components, which will not be described in detail here.

[0022] Example 1 like Figure 1 As shown in the figure, this embodiment proposes an automatic drawing review method for engineering drawings embedded in an approval system, including: Step 101: Extract all geometric objects from the engineering drawings, perform topology analysis and semantic recognition on each geometric object, obtain all processing feature elements of each geometric object, and construct a feature vector set for each processing feature element; Preferably, the input file (DWG / STEP / PDF / other) is read, and the entity information such as layers, line segments, arcs, polygons, and text annotations is read using the SDK provided by Autodesk (this embodiment does not limit the software used, it is only an example here). The entity information is parsed into a unified geometric object, and / or the topological relationship of faces, edges, and vertices is obtained using the STEP / IGES parsing library (OpenCASCADE, PyOCCT, etc.).

[0023] Preferably, semantic recognition refers to understanding the engineering meaning or function of a geometric object, such as identifying whether a cylindrical surface is a "hole" or a "cylinder," or whether a face is a "plane" or a "chamfer." Common examples include: using Autodesk Inventor or SolidWorks, identifying a cylindrical surface + hole axis direction + connected faces → identified as a hole; an arc + face boundary → internal fillet or chamfer, etc.

[0024] Preferably, the feature vector set may include: typical dimensions of the feature, such as aperture or fillet diameter; depth or elongation, such as the depth of a blind hole; local curvature or fillet radius, reflecting the minimum machinable size; and height or thickness. Correspondingly, the manufacturing feature vectors for the process type and equipment model correspond to the feature vector set.

[0025] Specifically, obtaining all machining feature elements for each geometric object also includes assigning a unique number to each machining feature element in the feature vector set and marking it on the engineering drawing.

[0026] Step 102: Obtain the process type and equipment model corresponding to the processing feature element, set up the processing feasibility assessment model, and calculate the matching index of the processing feature element relative to the process type and equipment model based on the feature vector set of the processing feature element; Specifically, the processing feasibility assessment model includes: , in, For the first Each processing feature element relative to the process type and equipment model The matching index, For the first A set of feature vectors for each processing feature element. For matrix transpose, In terms of process type and equipment model The average value of the manufacturing feature vectors of all samples under the given conditions is obtained by using historical processing data. In terms of process type and equipment model Under the given conditions, the covariance of the manufacturing feature vectors of all samples is obtained by using historical processing data. and The number and type of feature vectors in the middle The corresponding feature vectors.

[0027] Specifically, obtain the device model in real time. The degree of wear, and for process types and equipment model The average value of the manufacturing feature vectors of all samples under the given conditions Update.

[0028] Specifically, regarding the type of process and equipment model The average value of the manufacturing feature vectors of all samples under the given conditions The updates include: , in, In terms of process type and equipment model Under the condition that the initial average value of the manufacturing feature vectors of all samples is, For time Time equipment model Wear degree, It belongs to [0,1] (0 indicates new product, 1 indicates severe wear).

[0029] Step 103: Map the matching index to a feasibility score. Based on the feasibility score, determine whether the processing feature elements are manufacturable relative to the process type and equipment model, thereby completing the automatic review of engineering drawings.

[0030] Specifically, determining whether a processing feature element is manufacturable relative to the process type and equipment model based on the feasibility score includes: when the feasibility score falls within the first threshold range, the processing feature element is in the manufacturable zone relative to the process type and equipment model; when the feasibility score falls within the second threshold range, the processing feature element is in the critical risk zone relative to the process type and equipment model; when the feasibility score falls within the third threshold range, the processing feature element is in the non-manufacturable zone relative to the process type and equipment model. The minimum value of the first threshold range is greater than the maximum value of the second threshold range, and the minimum value of the second threshold range is greater than the maximum value of the third threshold range.

[0031] Specifically, when a processing feature element is in a critical risk zone relative to the process type and equipment model, an alarm message is issued, the corresponding processing feature element number on the engineering drawing is displayed, and the engineering drawing is transferred to manual approval. When a machining feature element is in the non-manufacturable zone relative to the process type and equipment model, the corresponding machining feature element number on the engineering drawing will be displayed, and a prompt will be given to modify the machining feature element so that the corresponding machining feature element is in the manufacturable zone.

[0032] Specifically, mapping the matching index to a feasibility score includes: , in, For feasibility scoring, For the logistic function, As an adjustment factor for the feasibility score, A value >0 is used to control the steepness of the feasibility score at the threshold. For the first Each processing feature element relative to the process type and equipment model The matching index threshold.

[0033] Example 2 like Figure 2 As shown, this embodiment proposes an automatic drawing review system for engineering drawings embedded in an approval system, including: The data extraction module is used to extract all geometric objects in the engineering drawings, perform topological analysis and semantic recognition on each geometric object, obtain all processing feature elements of each geometric object, and construct a feature vector set for each processing feature element. Preferably, the input file (DWG / STEP / PDF / other) is read, and the entity information such as layers, line segments, arcs, polygons, and text annotations is read using the SDK provided by Autodesk (this embodiment does not limit the software used, it is only an example here). The entity information is parsed into a unified geometric object, and / or the topological relationship of faces, edges, and vertices is obtained using the STEP / IGES parsing library (OpenCASCADE, PyOCCT, etc.).

[0034] Preferably, semantic recognition refers to understanding the engineering meaning or function of a geometric object, such as identifying whether a cylindrical surface is a "hole" or a "cylinder," or whether a face is a "plane" or a "chamfer." Common examples include: using Autodesk Inventor or SolidWorks, identifying a cylindrical surface + hole axis direction + connected faces → identified as a hole; an arc + face boundary → internal fillet or chamfer, etc.

[0035] Preferably, the feature vector set may include: typical dimensions of the feature, such as aperture or fillet diameter; depth or elongation, such as the depth of a blind hole; local curvature or fillet radius, reflecting the minimum machinable size; and height or thickness. Correspondingly, the manufacturing feature vectors for the process type and equipment model correspond to the feature vector set.

[0036] Specifically, obtaining all machining feature elements for each geometric object also includes assigning a unique number to each machining feature element in the feature vector set and marking it on the engineering drawing.

[0037] The index calculation module is used to obtain the process type and equipment model corresponding to the processing feature element, set up the processing feasibility assessment model, and calculate the matching index of the processing feature element relative to the process type and equipment model based on the feature vector set of the processing feature element. Specifically, the processing feasibility assessment model includes: , in, For the first Each processing feature element relative to the process type and equipment model The matching index, For the first A set of feature vectors for each processing feature element. For matrix transpose, In terms of process type and equipment model The average value of the manufacturing feature vectors of all samples under the given conditions is obtained by using historical processing data. In terms of process type and equipment model Under the given conditions, the covariance of the manufacturing feature vectors of all samples is obtained by using historical processing data. and The number and type of feature vectors in the middle The corresponding feature vectors.

[0038] Specifically, obtain the device model in real time. The degree of wear, and for process types and equipment model The average value of the manufacturing feature vectors of all samples under the given conditions Update.

[0039] Specifically, regarding the type of process and equipment model The average value of the manufacturing feature vectors of all samples under the given conditions The updates include: , in, In terms of process type and equipment model Under the condition that the initial average value of the manufacturing feature vectors of all samples is, For time Time equipment model Wear degree, It belongs to [0,1] (0 indicates new product, 1 indicates severe wear).

[0040] The feasibility analysis module maps the matching index to a feasibility score. Based on the feasibility score, it determines whether the processing feature elements are manufacturable relative to the process type and equipment model, thereby completing the automatic review of engineering drawings.

[0041] Specifically, determining whether a processing feature element is manufacturable relative to the process type and equipment model based on the feasibility score includes: when the feasibility score falls within the first threshold range, the processing feature element is in the manufacturable zone relative to the process type and equipment model; when the feasibility score falls within the second threshold range, the processing feature element is in the critical risk zone relative to the process type and equipment model; when the feasibility score falls within the third threshold range, the processing feature element is in the non-manufacturable zone relative to the process type and equipment model. The minimum value of the first threshold range is greater than the maximum value of the second threshold range, and the minimum value of the second threshold range is greater than the maximum value of the third threshold range.

[0042] Specifically, when a processing feature element is in a critical risk zone relative to the process type and equipment model, an alarm message is issued, the corresponding processing feature element number on the engineering drawing is displayed, and the engineering drawing is transferred to manual approval. When a machining feature element is in the non-manufacturable zone relative to the process type and equipment model, the corresponding machining feature element number on the engineering drawing will be displayed, and a prompt will be given to modify the machining feature element so that the corresponding machining feature element is in the manufacturable zone.

[0043] Specifically, mapping the matching index to a feasibility score includes: , in, For feasibility scoring, For the logistic function, This is an adjustment factor for the feasibility score; a value greater than 0 controls the steepness of the feasibility score at the threshold. For the first Each processing feature element relative to the process type and equipment model The matching index threshold.

[0044] Example 3 This invention also proposes a storage medium storing multiple instructions for implementing the aforementioned automatic drawing review method for engineering drawings embedded in an approval system.

[0045] Optionally, in this embodiment, the storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any mobile terminal in a group of mobile terminals.

[0046] Optionally, in this embodiment, the storage medium is configured to store program code for performing the following method steps: Step 101, extract all geometric objects in the engineering drawing, perform topological analysis and semantic recognition on each geometric object, obtain all processing feature elements of each geometric object, and construct a feature vector set for each processing feature element; Specifically, obtaining all machining feature elements for each geometric object also includes assigning a unique number to each machining feature element in the feature vector set and marking it on the engineering drawing.

[0047] Step 102: Obtain the process type and equipment model corresponding to the processing feature element, set up the processing feasibility assessment model, and calculate the matching index of the processing feature element relative to the process type and equipment model based on the feature vector set of the processing feature element; Specifically, the processing feasibility assessment model includes: , in, For the first Each processing feature element relative to the process type and equipment model The matching index, For the first A set of feature vectors for each processing feature element. For matrix transpose, In terms of process type and equipment model The average value of the manufacturing feature vectors of all samples under the given conditions. In terms of process type and equipment model Under the condition of [condition], the covariance of the manufacturing feature vectors of all samples, and The number and type of feature vectors in the middle The corresponding feature vectors.

[0048] Specifically, obtain the device model in real time. The degree of wear, and for process types and equipment model The average value of the manufacturing feature vectors of all samples under the given conditions Update.

[0049] Specifically, regarding the type of process and equipment model The average value of the manufacturing feature vectors of all samples under the given conditions The updates include: , in, In terms of process type and equipment model Under the condition that the initial average value of the manufacturing feature vectors of all samples is, For time Time equipment model Wear and tear.

[0050] Step 103: Map the matching index to a feasibility score. Based on the feasibility score, determine whether the processing feature elements are manufacturable relative to the process type and equipment model, thereby completing the automatic review of engineering drawings.

[0051] Specifically, determining whether a processing feature element is manufacturable relative to the process type and equipment model based on the feasibility score includes: when the feasibility score falls within the first threshold range, the processing feature element is in the manufacturable zone relative to the process type and equipment model; when the feasibility score falls within the second threshold range, the processing feature element is in the critical risk zone relative to the process type and equipment model; when the feasibility score falls within the third threshold range, the processing feature element is in the non-manufacturable zone relative to the process type and equipment model. The minimum value of the first threshold range is greater than the maximum value of the second threshold range, and the minimum value of the second threshold range is greater than the maximum value of the third threshold range.

[0052] Specifically, when a processing feature element is in a critical risk zone relative to the process type and equipment model, an alarm message is issued, the corresponding processing feature element number on the engineering drawing is displayed, and the engineering drawing is transferred to manual approval. When a machining feature element is in the non-manufacturable zone relative to the process type and equipment model, the corresponding machining feature element number on the engineering drawing will be displayed, and a prompt will be given to modify the machining feature element so that the corresponding machining feature element is in the manufacturable zone.

[0053] Specifically, mapping the matching index to a feasibility score includes: , in, For feasibility scoring, For the logistic function, As an adjustment factor for the feasibility score, For the first Each processing feature element relative to the process type and equipment model The matching index threshold.

[0054] Example 4 This invention also proposes an electronic device, including a processor and a storage medium connected to the processor. The storage medium stores multiple instructions, which can be loaded and executed by the processor to enable the processor to execute the aforementioned automatic drawing review method for engineering drawings embedded in an approval system.

[0055] Specifically, the electronic device in this embodiment can be a computer terminal, which may include one or more processors and a storage medium.

[0056] The storage medium can be used to store software programs and modules, such as the automatic drawing review method for engineering drawings embedded in an approval system according to an embodiment of the present invention. The corresponding program instructions / modules are executed by the processor through running the software programs and modules stored in the storage medium, thereby performing various functional applications and data processing, thus realizing the aforementioned automatic drawing review method for engineering drawings embedded in an approval system. The storage medium may include high-speed random access storage media, and may also include non-volatile storage media, such as one or more magnetic storage systems, flash memory, or other non-volatile solid-state storage media. In some instances, the storage medium may further include storage media remotely configured relative to the processor, which can be connected to the terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0057] The processor can call the information and application stored in the storage medium through the transmission system to execute the following method steps: Step 101, extract all geometric objects in the engineering drawing, perform topological analysis and semantic recognition on each geometric object, obtain all processing feature elements of each geometric object, and construct a feature vector set for each processing feature element; Specifically, obtaining all machining feature elements for each geometric object also includes assigning a unique number to each machining feature element in the feature vector set and marking it on the engineering drawing.

[0058] Step 102: Obtain the process type and equipment model corresponding to the processing feature element, set up the processing feasibility assessment model, and calculate the matching index of the processing feature element relative to the process type and equipment model based on the feature vector set of the processing feature element; Specifically, the processing feasibility assessment model includes: , in, For the first Each processing feature element relative to the process type and equipment model The matching index, For the first A set of feature vectors for each processing feature element. For matrix transpose, In terms of process type and equipment model The average value of the manufacturing feature vectors of all samples under the given conditions. In terms of process type and equipment model Under the condition of [condition], the covariance of the manufacturing feature vectors of all samples, and The number and type of feature vectors in the middle The corresponding feature vectors.

[0059] Specifically, obtain the device model in real time. The degree of wear, and for process types and equipment model The average value of the manufacturing feature vectors of all samples under the given conditions Update.

[0060] Specifically, regarding the type of process and equipment model The average value of the manufacturing feature vectors of all samples under the given conditions The updates include: , in, In terms of process type and equipment model Under the condition that the initial average value of the manufacturing feature vectors of all samples is, For time Time equipment model Wear and tear.

[0061] Step 103: Map the matching index to a feasibility score. Based on the feasibility score, determine whether the processing feature elements are manufacturable relative to the process type and equipment model, thereby completing the automatic review of engineering drawings.

[0062] Specifically, determining whether a processing feature element is manufacturable relative to the process type and equipment model based on the feasibility score includes: when the feasibility score falls within the first threshold range, the processing feature element is in the manufacturable zone relative to the process type and equipment model; when the feasibility score falls within the second threshold range, the processing feature element is in the critical risk zone relative to the process type and equipment model; when the feasibility score falls within the third threshold range, the processing feature element is in the non-manufacturable zone relative to the process type and equipment model. The minimum value of the first threshold range is greater than the maximum value of the second threshold range, and the minimum value of the second threshold range is greater than the maximum value of the third threshold range.

[0063] Specifically, when a processing feature element is in a critical risk zone relative to the process type and equipment model, an alarm message is issued, the corresponding processing feature element number on the engineering drawing is displayed, and the engineering drawing is transferred to manual approval. When a machining feature element is in the non-manufacturable zone relative to the process type and equipment model, the corresponding machining feature element number on the engineering drawing will be displayed, and a prompt will be given to modify the machining feature element so that the corresponding machining feature element is in the manufacturable zone.

[0064] Specifically, mapping the matching index to a feasibility score includes: , in, For feasibility scoring, For the logistic function, As an adjustment factor for the feasibility score, For the first Each processing feature element relative to the process type and equipment model The matching index threshold.

[0065] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0066] In the several embodiments provided by this invention, it should be understood that the disclosed technical content can be implemented in other ways. The system embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, indirect coupling or communication connection between units or modules, and may be electrical or other forms.

[0067] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0068] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0069] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes: USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, optical disks, and other media capable of storing program code.

[0070] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. An automatic drawing checking method for engineering drawings embedded in an approval system, characterized by, The method comprises the following steps: extracting all geometric objects in the engineering drawing, performing topological analysis and semantic recognition on each geometric object, obtaining all machining feature elements of each geometric object, and constructing a feature vector set of each machining feature element; obtaining the process type and equipment model corresponding to the machining feature element, setting up a machining feasibility evaluation model, and calculating the matching index of the machining feature element with respect to the process type and equipment model according to the feature vector set of the machining feature element; mapping the matching index to a feasibility score, and judging whether the machining feature element is manufacturable with respect to the process type and equipment model according to the feasibility score, thereby completing automatic drawing review of the engineering drawing.

2. The method for automatically checking engineering drawings embedded in an approval system according to claim 1, wherein, The step of obtaining all machining feature elements of each geometric object further comprises assigning a unique number to each machining feature element in the feature vector set and marking on the engineering drawing.

3. The method for automatically checking engineering drawings embedded in an approval system according to claim 1, wherein, The step of judging whether the machining feature element is manufacturable with respect to the process type and equipment model according to the feasibility score comprises: when the feasibility score belongs to a first threshold range, the machining feature element is in a manufacturable zone with respect to the process type and equipment model; when the feasibility score belongs to a second threshold range, the machining feature element is in a critical risk zone with respect to the process type and equipment model; and when the feasibility score belongs to a third threshold range, the machining feature element is in an unmanufacturable zone with respect to the process type and equipment model, wherein the minimum value of the first threshold range is greater than the maximum value of the second threshold range, and the minimum value of the second threshold range is greater than the maximum value of the third threshold range.

4. The method for automatically checking engineering drawings embedded in an approval system according to claim 3, wherein, When the machining feature element is in the critical risk zone with respect to the process type and equipment model, an alarm information is issued, and the corresponding machining feature element number on the engineering drawing is displayed, and the engineering drawing is transferred to manual review; When the machining feature element is in the unmanufacturable zone with respect to the process type and equipment model, the corresponding machining feature element number on the engineering drawing is displayed, and a prompt to modify the machining feature element is given so that the corresponding machining feature element is in the manufacturable zone.

5. The method for automatically checking engineering drawings embedded in an approval system according to claim 1, wherein, The machining feasibility evaluation model comprises: ， wherein, is the matching index of the i-th process feature element with respect to the process type and the equipment model, is the feature vector set of the i-th process feature element, is the matrix transpose, is the mean of the manufacturing feature vectors of all samples under the condition of the process type and the equipment model, is the covariance of the manufacturing feature vectors of all samples under the condition of the process type and the equipment model, and the number and type of feature vectors in correspond to the feature vectors in.​​​​ 6. The method for automatically checking engineering drawings embedded in an approval system according to claim 5, wherein, The step of mapping the matching index to the feasibility score comprises: ， wherein, is a feasibility score, is a logistic function, is an adjustment factor for the feasibility score, is a match index threshold for the processing feature element relative to the process type and equipment model. ​ 7. The method for automatically checking engineering drawings embedded in an approval system according to claim 5, wherein, Get device model in real time The degree of wear, and for process types and equipment model The average value of the manufacturing feature vectors of all samples under the given conditions Update.

8. The method for automatically checking engineering drawings embedded in an approval system according to claim 7, wherein, updating the average of the manufacturing feature vectors of all samples under the conditions of the process type and the equipment model includes:​ ， wherein, is the initial average value of the manufacturing feature vector for all samples under the conditions of the process type and the equipment model , is the wear degree of the equipment model at the time .

9. An automatic drawing checking system for engineering drawings embedded in an approval system, characterized by, The method comprises the following steps: The data extraction module is used to extract all geometric objects in the engineering drawing, perform topological analysis and semantic recognition on each geometric object, obtain all machining feature elements of each geometric object, and construct a feature vector set of each machining feature element; The index calculation module is used to obtain the process type and equipment model corresponding to the machining feature element, set up a machining feasibility evaluation model, and calculate the matching index of the machining feature element with respect to the process type and equipment model according to the feature vector set of the machining feature element; The feasibility analysis module is used to map the matching index to a feasibility score, and judge whether the machining feature element is manufacturable with respect to the process type and equipment model according to the feasibility score, thereby completing automatic drawing review of the engineering drawing.

10. The automatic drawing checking system embedded in the approval system of the engineering drawing according to claim 9, characterized in that, The step of obtaining all machining feature elements of each geometric object further comprises assigning a unique number to each machining feature element in the feature vector set and marking on the engineering drawing.

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