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- Title
基于混合循环算法的复杂装配体装配序列智能规划.
- Authors
曲兴田; 张 昆; 王学旭; 王宏一
- Abstract
A hybrid cycle algorithm was proposed aiming at solving the problems that single algorithm cannot realize intelligent assembly sequence planning of complex assembly and the lack of deep human-computer interaction causes poor improvement effects. This algorithm, based on genetic algorithm, uses interference matrix and contact matrix to adjust random assembly sequence and constructs fitness function on the basis of the uniformity of assembly direction and tool. In addition, combining with simulated annealing algorithm, adding annealing operation and using Metropolis criterion, individual sequences were obtained and accepted by crossover and mutation. Meanwhile, by introducing particle swarm optimization, optimal sequence of individuals and groups were selected to cross with the offspring directly. Finally, assembly simulation platform combined with virtual reality were built and the sequence was optimized from the two dimensions of assembly stability and tool operation space. In conclusion, taking automobile rear axle assembly as an example, it is shown that the assembly sequence obtained fits actual production and the method is effective and practical.
- Subjects
SIMULATED annealing; RANDOM matrices; AUTOMOBILE axles; HUMAN-computer interaction; VIRTUAL reality; GENETIC algorithms; PARTICLE swarm optimization
- Publication
Journal of Northeastern University (Natural Science), 2019, Vol 40, Issue 12, p1767
- ISSN
1005-3026
- Publication type
Article
- DOI
10.12068/j.issn.1005-3026.2019.12.018