Trajectory optimisation in electrical discharge machining of three-dimensional curved and twisted channels

作     者：Jianshe ZHAO Yicong QIU Jian YUAN Chao LIU Jianshe ZHAO;Yicong QIU;Jian YUAN;Chao LIU

作者机构：College of Mechanical and Electrical EngineeringNanjing University of Aeronautics and AstronauticsNanjing 210016China Laboratory of Integrated Electrical ProcessingNanjing HANGPU Machinery Technology Company LimitedNanjing 210000China Military Representative Bureau of the Air Force Equipment Department in Shanghai and Military Representative Office in Zhuzhou RegionZhuzhou 412002China AECC South Industry Company LimitedZhuzhou 412002China 

出 版 物：《Chinese Journal of Aeronautics》 (中国航空学报（英文版）)

年 卷 期：2022年第35卷第4期

页      面：473-484页

核心收录：

学科分类：08[工学] 082503[工学-航空宇航制造工程] 0802[工学-机械工程] 0825[工学-航空宇航科学与技术] 080201[工学-机械制造及其自动化] 

基　　金：financially supported by Aeronautical Science Foundation of China(No.2011ZE52055) Fundamental Research Funds for the Central Universities(No.3082018NF2018006) 

主　　题：Blisk Electrical discharge machining(EDM) Electrode Objective functions Trajectory generation 

摘      要：Numerical control electrical discharge machining(NC EDM) is one of the most widely used machining technologies for manufacturing a closed blisk flow path, particularly for three-dimensional(3D) curved and twisted flow channels. In this process, tool electrode design and machining trajectory planning are the key factors affecting machining accessibility and efficiency. Herein, to reduce the difficulty in designing the electrode and its motion path in the closed curved and twisted channels, a heuristic search hybrid optimisation strategy based on channel grids is adopted to realise the initial electrode trajectory design search and optimised size reduction. By transferring the trajectory optimisation constraints from the complex free-form surface to numbered grids, the search is found to be more orderly and accurate. The two trajectory indicators, namely argument angle and minimum distance, are analysed separately for the optimised results of the adaptive learning particle swarm optimisation algorithm, demonstrating that they can meet the actual processing *** results of NC EDM indicate that the motion path generated by this design method can meet the machining requirements of 3D curved and twisted flow channels.