No abstract

The mechanism of surface topography formation of Inconel 718 in low-speed wire electrical discharge machining was studied, and its on-line prediction based on acoustic emission detection technology is carried out. An optimized truncated cone-shaped thermal conduction model considering the scattering velocity difference between electrons and ions was put forward. Based on this model, discharge craters and temperature variation at different discharge energy conditions were systematically discussed in finite element analysis. Experimentally, five machining regimes that are reduced in accordance with the discharge energy were conducted with acoustic emission detection technology in low-speed wire electrical discharge machining. A novel denoising method has been proposed, which combines filtering analysis and Fast Fourier Transform. The experimental results indicate that acoustic emission testing technique provides great technical support in researching the discharge energy variation rule in low-speed wire electrical discharge machining. It is also concluded that the change trends of the theoretically calculated temperature in the discharge channel and acoustic emission signal root mean square and the surface roughness value and the acoustic emission signal root mean square show a similar exponential growth law. A regression equation about the arithmetic mean roughness (R a ) values and root mean square values of acoustic emission is established to predict surface roughness value R a whose error is less than 1%.