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摘要:
缠绕机具有生产效率高、产品质量稳定等特点，是碳纤维复合材料成型的关键工艺装备。针对产品小批量、定制化的生产需求，提出了针对缠绕机结构和控制系统的模块化设计方法（MDM），拓展缠绕机的功能多样性。将缠绕机的结构部件进行功能分解和关联强度分析，采用组遗传算法（GGA）将部件聚类为标准化的模块，根据产品需求，以产品性能最好和成本最低为目标建立模块配置模型，基于快速分类的非支配遗传算法（NSGA-Ⅱ）求解多目标优化模型完成机械结构模块化配置。提出基于现场总线的分布式网络控制器结构，将控制器的接口标准化和网络化，根据机械结构的模块化配置实现控制器的快速重构。基于模型组件对象（COM）技术将软件模块设计为COM组件，采用k近邻（kNN）方法进行控制模式分类，并进行COM组件的重构，控制软件动态解析控制模式并管理COM组件的状态转移关系，从而实现软件的快速重构。对结构、控制器和软件模块化方法的研究能够实现缠绕机的快速重构，拓展缠绕机的功能。
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关键词:
- 缠绕机 /
- 模块化方法 /
- 多目标优化 /
- 分布式控制 /
- 模型组件对象(COM)技术
Abstract:Winding machine is the core equipment for filament winding with the features of high production efficiency and stable product quality. To meet the requirements of customized and small batch production, the modular design method (MDM) is proposed to expand the function of winding machine. The system structure is analyzed, relation matrices between components are established, and the grouping genetic algorithm (GGA) is then employed to conduct modular optimization to cluster components into standard modules. Multi-objective optimization method based on non-dominated sorting genetic algorithm Ⅱ (NSGA-Ⅱ) is proposed to create a complete system by combining instances with consideration of performance and cost simultaneously. The modular design method for the control system is presented based on distributed network controller for a bus system, and the network interface of the controller is standardized as independent function module, and then the rapid configuration of the controller is achieved according to the modular configuration of the mechanical structure. The k-nearest neighbor (kNN) method is used to classify the control mode by detecting the connection state of the module and the dynamic reconfiguration method based on component object model (COM) component to realize the state transition sequence and data exchange of the modules. The research on the modularization of mechanical structure, controller and software can realize the rapid reconfiguration of the winding machine, and expand the function of the winding machine.
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图 1 缠绕机机电系统模块化设计模型
Figure 1. Modular design model for mechatronic system of winding machine
图 10 天线支撑杆缠绕的NSGA-Ⅱ优化结果
Figure 10. NSGA-Ⅱ optimization results for aerial studdle winding
图 11 天线支撑杆缠绕模块之间的拓扑关系
Figure 11. Topological relationship between modules for aerial studdle winding
图 14 湿法缠绕模块之间的拓扑关系
Figure 14. Topological relationship between modules for wet winding
图 15 筒形壳体缠绕的NSGA-Ⅱ优化结果
Figure 15. NSGA-Ⅱ optimization results for cylindrical shell winding
图 16 筒形壳体缠绕模块之间的拓扑关系
Figure 16. Topological relationship between modules for cylindrical shell winding
表 1 不同测试样本数量和k值的加权kNN方法准确率
Table 1. Woighted kNN method accuracy for different test sample sizes and values of k
样本数量 加权kNN方法准确率/% k=5 k=7 k=9 100 94 91.3 93.3 200 92.7 92.3 91.5 
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