基于GT-CBR的汽轮机叶片智能CAM系统研发  

Research on CAM Decision System for Blades Based on GT-CBR

作　　者：陈寒松[1] 赵庆龙 王霄[1] Chen Hansong;Zhao Qinglong;Wang Xiao

机构地区：[1]江苏大学机械工程学院

出　　处：《工具技术》2024年第10期122-127,共6页Tool Engineering

摘　　要：针对目前小批量、多种类汽轮机叶片的数控加工程序编制效率低、耗时较长的问题,设计了基于GT-CBR的汽轮机叶片CAM系统。该系统依据实际工艺案例与叶片典型特征,利用成组技术生成工艺路线并简化多参数实例推理问题;提出了AHP属性权重法、距离加权的KNN算法与动态阈值算法相结合的策略,实现叶片数控加工工艺参数的实例推理与数控程序自动生成;利用UG/NX API与MySQL数据库开发了汽轮机叶片智能CAM系统原型,并对系统进行了测试,验证了系统的有效性。In order to solve the problem of low efficiency and wasting time caused by the dependence of manual work on CNC machining programs of small batches and various types of steam turbine blades,a CAM decision-making system for steam turbine blades based on GT-CBR is designed.Based on actual process cases and typical blade characteristics,the system uses grouping technology to generate process routes and simplify multi-parameter example inference.The strategy of combining AHP attribute weighting method,distance-weighted KNN algorithm and dynamic threshold algorithm is proposed.And on this basis,the example matching of blade CNC machining process parameters and the automatic generation of NC program are realized.A prototype of intelligent CAM decision-making system for steam turbine blades is developed by using UG/NX API and MySQL database,and the system is tested to verify the effectiveness of the system.

关 键 词：汽轮机叶片 实例推理 成组技术 计算机辅助制造 

分 类 号：TG659[金属学及工艺—金属切削加工及机床] TH162[机械工程—机械制造及自动化]