装配序列规划中子装配体的识别算法研究

发布时间：2018-05-20 15:23

本文选题：子装配体识别 + 带权无向联接图　；参考：《西安工业大学》2015年硕士论文

【摘要】：随着国家工业化高速发展,装配问题已成为产品成本居高不下的原因之一。装配序列自动规划面临的主要难题之一就是子装配体的识别。随着装配体复杂程度的增加,装配过程也往往需要各部门人员的共同分工完成。装配体的子装配体识别可有效实现装配体的并行开发与规划。本文着重研究装配序列规划问题中的子装配体识别算法,使得对不同规模的装配体都能够识别生成子装配体,以达到简化装配序列,降低装配难度与成本的目的。(1)对装配序列规划中的子装配体进行定义及分析,结合模糊集与聚类的方法,探究子装配体识别算法的基本原理。选取带权无向联接图定义装配的结构信息模型,然后把带权无向联接图转换为邻接关联矩阵,判定出零部件间的隶属度关系,最终得出得到子装配。(2)根据子装配体识别的过程及原理进行数学建模,在Matlab环境下对子装配体识别算法进行编程,通过三个具有不同代表性的实例进行验证。第一个实例验证子装配识别算法能否实现自主识别功能,第二个实例验证子装配体识别算法对零件间关联关系的准确判定,第三个实例则是验证装配模体零件数目较多时算法的准确性。(3)选取算法中的重要因素中的子装配体个数c及模糊指数m进行参数影响分析。对参数取不同值时,算法的有效性及收敛速度会产生的不同变化,通过分析与评价,最后为参数的合理取值提出建议。
[Abstract]:With the rapid development of national industrialization, assembly problem has become one of the reasons of high product cost. One of the main problems in automatic assembly sequence planning is subassembly recognition. With the increase of assembly complexity, the assembly process often needs the common division of labor. Assembly subassembly recognition can effectively realize the parallel development and planning of assembly. In this paper, we focus on the subassembly recognition algorithm in assembly sequence planning, which makes it possible to identify the generated sub-assembly for different size assembly, so as to simplify the assembly sequence. The purpose of reducing the difficulty and cost of assembly is to define and analyze the subassembly in assembly sequence planning, and to explore the basic principle of subassembly recognition algorithm with the method of fuzzy set and clustering. The weighted undirected join graph is selected to define the assembly structure information model, and then the weighted undirected join graph is transformed into the adjacent correlation matrix, and the membership relationship between parts is determined. Finally, we get sub-assembly. 2) according to the process and principle of sub-assembly recognition, we model the mathematical model, program the algorithm of sub-assembly recognition in Matlab environment, and verify it by three representative examples. The first example verifies whether the sub-assembly recognition algorithm can realize the autonomous recognition function, and the second example verifies the accuracy of the sub-assembly recognition algorithm to determine the correlation relationship between parts. The third example is to verify the accuracy of the algorithm when the number of parts of the assembly die is more. (3) to select the number of subassemblies and the fuzzy exponent m of the important factors in the algorithm to analyze the influence of the parameters. The efficiency and convergence rate of the algorithm will vary with different values of parameters. Through analysis and evaluation, some suggestions are put forward for the reasonable selection of parameters.
【学位授予单位】：西安工业大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TG95

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