Study of arc behavior and machining effects of the novel magnetic field assisted blasting erosion arc machining method

Kelin Li, Xiaoka Wang, Lijie Jiang, K. P. Rajurkar,Wansheng Zhao,Lin Gu

JOURNAL OF MATERIALS PROCESSING TECHNOLOGY(2024)

引用 0|浏览0
暂无评分
摘要
Electrical Arc Machining (EAM) is a high-efficiency, cost-effective method for machining electrical conductive materials especially difficult-to-cut ones. Because this thermal process relies on high-density energy to melt and remove material, effective arc control is crucial to maintain stable machining without overheating the workpiece. However, due to the limited discharge gap, it is difficult for the existing arc breaking methods to manage the arc plasma in a timely and uniform manner. This paper proposes a novel method named Magnetic Field Assisted Blasting Erosion Arc Machining (M-BEAM). This method introduces a magnetic field to enhance the control effect on arc plasma by directly influencing charged particles. Initially, the arc control and material removal mechanisms were revealed through an analysis and experiments of single arc discharge. Both simulated particle trajectory and high-speed photographs demonstrated that the arc plasma deflects much earlier in the magnetic field than that of traditional BEAM. Moreover, the expulsion effect of molten metal was significantly improved, resulting in a larger volume crater. Building on this, the magnetic-assisted arc control mechanism was utilized to enhance the performance of BEAM. Experimental results indicate that compared with traditional BEAM, Magnetic Field assisted BEAM increases its Material Removal Rate (MRR) by 10.09% while significantly reducing the Tool Wear Ratio (TWR) by 29.02%. Additionally, surface roughness (Sa) is decreased by 47.73%, and the thickness of the recast layer is decreased by 78.54%. Therefore, M-BEAM can further improve the machining performance and build a good foundation for subsequent machining.
更多
查看译文
关键词
Magnetic assisted arc control mechanism,Blasting erosion arc machining,Material removal rate,Surface quality
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要