CN-121997499-A - Tool clamp design method, system and equipment based on artificial intelligence

CN121997499ACN 121997499 ACN121997499 ACN 121997499ACN-121997499-A

Abstract

The invention provides a tool fixture design method, a system and equipment based on artificial intelligence, which relate to the technical field of artificial intelligence, wherein the design method is realized by acquiring and fusing a three-dimensional model, process information and manufacturing constraint of a part to be processed, and constructing a clamping state model and a design semantic graph which uniformly represent clamping requirements, further intelligently searching similar cases from a historical case library based on the semantic graph, extracting a reusable constraint mode, and finally combining a large model to generate a clamp design scheme with both historical engineering experience and current constraint. According to the method, discrete geometric, technological and constraint information is converted into structural and computable design semantics, engineering rationality of large model reasoning is enhanced by using historical case knowledge, dependence of a design process on individual artificial experience is remarkably reduced, and automation level and knowledge multiplexing efficiency of tool fixture design are greatly improved on the premise that stable positioning and reliable clamping of a design scheme are ensured and engineering constraints such as space interference are met.

Inventors

ZHANG DAQIANG
XIAO HUIXIANG
ZHAO HUA
LI NING
XU LIYUN
ZHANG LEI

Assignees

爱孚迪(上海)制造系统工程有限公司

Dates

Publication Date: 20260508
Application Date: 20260407

Claims (10)

1. The utility model provides a frock clamp design method based on artificial intelligence which characterized in that includes: acquiring three-dimensional model data, processing technology information and manufacturing constraint conditions of a part to be processed; Based on the three-dimensional model data and the processing technology information, constructing a clamping state model for representing the clamping requirement of the part to be processed in the processing process; Fusing the clamping state model and the manufacturing constraint conditions to obtain a design semantic graph; Based on the design semantic graph, similar historical fixture cases are retrieved from a historical fixture case library, and reusable constraint modes and configuration rules are extracted from the retrieved historical fixture cases to form a structured case context; and inputting the design semantic graph and the case context into a preset large model together to generate a tool clamp design scheme of the part to be processed, wherein the tool clamp design scheme is a structural scheme comprising a clamp structural form, a positioning scheme, a clamping configuration and key parameters.
2. The method for designing an artificial intelligence based tool clamp according to claim 1, wherein the constructing a clamping state model for representing a clamping requirement of the part to be machined in a machining process based on the three-dimensional model data and the machining process information comprises: Performing geometric analysis on the three-dimensional model data to obtain geometric features, wherein the geometric features comprise a positioning reference plane, a clampable area and a key stress area; determining process characteristic parameters and constraint requirements according to the processing process information; And uniformly modeling the geometric features, the technological feature parameters and the constraint requirements to obtain the structured clamping state model.
3. The method for designing an artificial intelligence based fixture according to claim 1, wherein the fusing the clamping state model and the manufacturing constraint condition to obtain a design semantic graph includes: Extracting part structural feature data and process feature data from the clamping state model, and extracting engineering constraint data from the manufacturing constraint conditions; Determining a positioning relationship, a clamping relationship and a constraint relationship based on clamping logic information in the clamping state model and engineering constraint information in the manufacturing constraint condition; Taking the part structural feature data, the process feature data and engineering constraint data as semantic nodes, and taking the positioning relationship, the clamping relationship and the constraint relationship as semantic edges; and constructing the design semantic graph based on the semantic nodes and the semantic edges.
4. The artificial intelligence based fixture design method of claim 1, wherein the retrieving similar historical fixture cases from a historical fixture case library based on the design semantic graph comprises: Carrying out multi-mode feature analysis on the design semantic graph to obtain geometric mode features, process mode features and engineering constraint mode features; Fusing the geometric mode characteristics, the process mode characteristics and the engineering constraint mode characteristics in a preset fusion mode to obtain a joint feature vector; and performing similarity matching on the joint feature vector and the corresponding feature vector of each case in the historical fixture case library, and determining one or more similar historical fixture cases according to a similarity matching result.
5. The method for designing the tool clamp based on the artificial intelligence according to claim 4, wherein the geometric mode features comprise a positioning reference plane, a clampable area, a hole feature and key stress area information, the process mode features comprise a machining mode, a machining direction, clamping times and machine tool type information, and the engineering constraint mode features comprise a degree-of-freedom constraint set, a clamping force allowed range, a spatial interference limitation and an interface constraint information.
6. The method for designing a fixture based on artificial intelligence according to claim 1, wherein the step of inputting the design semantic graph and the case context together into a preset large model, and the step of generating a fixture design scheme further comprises: based on a preset inspection mode, carrying out engineering feasibility inspection on the design scheme of the tool clamp to obtain an inspection result; If the verification result is that the specific constraint violation type verification feedback information is not passed, generating verification feedback information containing the specific constraint violation type verification feedback information, and feeding the verification feedback information back to the preset large model to guide correction of the tool fixture design scheme, and re-executing the step of carrying out engineering feasibility verification on the tool fixture design scheme until the tool fixture design scheme meets engineering constraint.
7. The method for designing an artificial intelligence based tool clamp according to claim 6, wherein the preset inspection mode comprises degree-of-freedom constraint integrity check, clamping mechanical feasibility check and machining space interference check.
8. The artificial intelligence based tool clamp design method of claim 1, wherein the manufacturing constraints include at least one of machining accuracy requirements, clamping stiffness requirements, clamping time requirements, machine tool interface constraints, and clamp manufacturing cost constraints.
9. Frock clamp design system based on artificial intelligence, its characterized in that includes: the acquisition unit is used for acquiring three-dimensional model data, processing technology information and manufacturing constraint conditions of the part to be processed; The construction unit is used for constructing a clamping state model for representing the clamping requirement of the part to be machined in the machining process based on the three-dimensional model data and the machining process information; The fusion unit is used for fusing the clamping state model and the manufacturing constraint conditions to obtain a design semantic graph; The processing unit is used for retrieving similar historical fixture cases from the historical fixture case library based on the design semantic graph, extracting reusable constraint modes and configuration rules from the retrieved historical fixture cases and forming a structured case context; The processing unit is further used for inputting the design semantic graph and the case context into a preset large model together to generate a tool clamp design scheme of the part to be processed, wherein the tool clamp design scheme is a structural scheme comprising a clamp structural form, a positioning scheme, a clamping configuration and key parameters.
10. An artificial intelligence based tool fixture design apparatus comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the artificial intelligence based tool fixture design method of any one of claims 1 to 8 when executing the computer program.

Description

Tool clamp design method, system and equipment based on artificial intelligence Technical Field The invention relates to the technical field of artificial intelligence, in particular to a method, a system and equipment for designing a tool clamp based on artificial intelligence. Background The tool clamp is used as key process equipment for realizing accurate positioning, reliable clamping and stable support of workpieces in a mechanical manufacturing system, and the design quality of the tool clamp directly determines the machining precision, the production efficiency and the process cost. The traditional fixture design is highly dependent on personal experience and knowledge accumulation of designers, and a computer aided design mode based on rule base or instance reasoning is generally adopted, so that the inherent limitations of long design period, repeated labor, difficulty in realizing effective multiplexing and standardized migration of design results in enterprises and the like exist. In recent years, with the development of artificial intelligence technology, automated design methods based on deep learning or large models are beginning to be introduced into the field, but most of these methods focus on generating conceptual schemes from texts or simple rules, so that the generated design schemes tend to have low engineering reliability and are difficult to directly apply to actual production. In addition, a large number of practical and verified historical jig design cases accumulated by manufacturing enterprises for a long time are usually stored in an unstructured or semi-structured form, but are difficult to effectively convert into structured knowledge for retrieval and reasoning of an intelligent system, so that valuable engineering experience is deposited and wasted. Therefore, the prior art lacks a fixture design method based on artificial intelligence reasoning capability, and realizes automation, intellectualization and knowledge continuous multiplexing of the design process while guaranteeing the project reliability of the scheme. Disclosure of Invention The present invention solves one or more of the above-mentioned problems of the related art. In order to solve the problems, the invention provides a method, a system and equipment for designing a fixture based on artificial intelligence. In a first aspect, the present invention provides a method for designing a tool fixture based on artificial intelligence, including: acquiring three-dimensional model data, processing technology information and manufacturing constraint conditions of a part to be processed; Based on the three-dimensional model data and the processing technology information, constructing a clamping state model for representing the clamping requirement of the part to be processed in the processing process; Fusing the clamping state model and the manufacturing constraint conditions to obtain a design semantic graph; Based on the design semantic graph, similar historical fixture cases are retrieved from a historical fixture case library, and reusable constraint modes and configuration rules are extracted from the retrieved historical fixture cases to form a structured case context; and inputting the design semantic graph and the case context into a preset large model together to generate a tool clamp design scheme of the part to be processed, wherein the tool clamp design scheme is a structural scheme comprising a clamp structural form, a positioning scheme, a clamping configuration and key parameters. Optionally, the constructing a clamping state model for representing the clamping requirement of the part to be machined in the machining process based on the three-dimensional model data and the machining process information includes: Performing geometric analysis on the three-dimensional model data to obtain geometric features, wherein the geometric features comprise a positioning reference plane, a clampable area and a key stress area; determining process characteristic parameters and constraint requirements according to the processing process information; And uniformly modeling the geometric features, the technological feature parameters and the constraint requirements to obtain the structured clamping state model. Optionally, the fusing the clamping state model with the manufacturing constraint condition to obtain a design semantic graph includes: extracting part structural feature data and process feature data from the clamping state model, and extracting engineering constraint data from the manufacturing constraint condition data; Determining a positioning relationship, a clamping relationship and a constraint relationship based on clamping logic information in the clamping state model and engineering constraint information in the manufacturing constraint condition; Taking the part structural feature data, the process feature data and engineering constraint data as semantic nodes, and taking the positioning relationship,