制造特征提取与智能工艺决策技术研究

发布时间：2018-04-02 23:43

本文选题：工艺决策　切入点：制造特征　出处：《山东科技大学》2011年硕士论文

【摘要】：智能工艺决策技术是在传统CAPP工艺决策的基础上,结合专家系统中的推理技术,根据工艺知识和人类经验,辅助工艺设计人员实现智能工艺决策,提高决策的效率和准确程度,得到更为符合实际的工艺方案。工艺决策面向的对象是零件的制造信息,包括尺寸、精度和管理等信息。特征是一种描述零件设计和制造信息的工具,包括设计特征与制造特征,其中设计特征是Pro/E等CAD建模软件的基本信息单元,制造特征是描述零件制造信息的基本单元。制造特征提取技术,是通过定义制造特征,再将设计特征向制造特征进行识别,来直接从CAD系统中提取制造信息,并将其用于工艺决策。本文在分析了现有特征提取与工艺决策技术的基础上,提出了面向机械加工工艺决策的制造特征提取与智能工艺决策技术及其实现方法。分析了工艺决策的主要内容,建立了系统体系结构,阐述了系统关键技术；研究了特征技术,提出了使用制造特征描述零件制造信息的方法,通过对Pro/E模型的特征分析,定义了基于Pro/E模型的制造特征,对其进行了C++描述,并提出了特征识别和提取方法,建立了特征提取流程,通过Pro/E二次开发实现了制造特征的提取；研究了基于规则的反向推理与基于可信度的不确定推理的使用方法,及其在工艺决策中的应用,提出了综合反向推理与不确定推理的智能工艺决策技术,建立了智能工艺决策流程,提出了智能工艺决策在工艺路线的确定与工序设计中的实现方法；研究了工艺知识获取和表示方法,采用关系数据结构和产生式规则表示法对工艺知识进行表示和存储,建立了工艺知识库。对系统进行了安全和功能设计,划分了系统功能模块。采用C++语言编程,使用Pro/Toolkit和VS2005开发工具进行了Pro/E二次开发；采用C#语言编程,使用VS2008和SQL Server 2005开发工具,开发了系统软件原型。给出了各个功能模块的实现界面,实现了制造特征提取和智能工艺决策的功能,并实现了工艺知识与信息的统一管理和网络共享。
[Abstract]:Intelligent process decision technology is based on the traditional CAPP process decision, combined with the reasoning technology in the expert system, according to the process knowledge and human experience, the intelligent process decision is assisted by the process designer to improve the efficiency and accuracy of the decision.Get more realistic process plan.The object of process decision is the manufacturing information of parts, including dimension, precision and management information.Feature is a tool for describing part design and manufacturing information, including design feature and manufacturing feature, in which design feature is the basic information unit of CAD modeling software such as Pro/E, and manufacturing feature is the basic unit to describe part manufacturing information.Manufacturing feature extraction technology is to extract manufacturing information directly from CAD system by defining manufacturing feature and then identifying design feature to manufacturing feature and then applying it to process decision.Based on the analysis of the existing technology of feature extraction and process decision, this paper puts forward the manufacturing feature extraction and intelligent process decision technology for machining process decision and its realization method.The main contents of process decision are analyzed, the system architecture is established, the key technology of the system is expounded, the feature technology is studied, and the method of describing the manufacturing information of parts using manufacturing features is put forward, and the feature analysis of Pro/E model is given.The manufacturing feature based on Pro/E model is defined and described in C, and the method of feature recognition and extraction is put forward, and the feature extraction process is established, and the manufacturing feature extraction is realized by the second development of Pro/E.This paper studies the methods of using rule-based reverse reasoning and credit-based uncertain reasoning, and its application in process decision, and puts forward an intelligent process decision technology which integrates reverse reasoning and uncertain reasoning.The process flow of intelligent process decision is established, the realization method of intelligent process decision in the determination of process route and process design is put forward, and the method of acquiring and expressing process knowledge is studied.The relational data structure and the production rule representation are used to represent and store the process knowledge, and the process knowledge base is established.The security and function of the system are designed, and the system function modules are divided.C language programming, Pro/Toolkit and VS2005 development tools for Pro/E secondary development, C # language programming, using VS2008 and SQL Server 2005 development tools, developed the system software prototype.The realization interface of each function module is given, and the functions of manufacturing feature extraction and intelligent process decision are realized, and the unified management of process knowledge and information and the sharing of network are realized.
【学位授予单位】：山东科技大学
【学位级别】：硕士
【学位授予年份】：2011
【分类号】：TP391.72

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