摘要
随着计算机技术的深入发展,加工中心在线检测已成为数字化环境下集成质量系统的关键环节。在分析在线检测系统结构的基础上,介绍了检测路径规划的层次分类。为了解决检测路径优化问题,针对粒子群和蚁群算法的优缺点,构造一种粒子蚁群算法。该算法充分利用PSO算法的快速、全局收敛性和ACO算法的信息素正反馈机制,达到优势互补。仿真和实验结果证明该算法具有较好的优化效果。在线检测路径优化技术为集成质量系统中加工质量自动补偿提供了必要的技术支持。
With the development of computer technology, machining center on-line inspection has become key links of integrated quality system in digitalization. On the basis of analyzing the structure of online inspecting system, the layer classification of inspecting path planning has been introduced. For resolving the problem of inspecting path optimization, the particle swarm optimization algorithm （PSO） and the ant colony algorithm （ACO） are employed to develop a particle-ant colony optimization algorithm （PACO）. In PACO, the fast con- vergence of PSO and the positive feedback mechanism of ACO are used. Simulation and experiment results show that PACO has a good performance. The technology of online inspecting path optimization can provide necessary technology support for machining quality automatic compensation in the integrated quality system.
出处
《组合机床与自动化加工技术》
北大核心
2009年第5期52-55,60,共5页
Modular Machine Tool & Automatic Manufacturing Technique
基金
黑龙江省高校青年学术骨干支持计划项目(1153G053)
