Study on material removal behavior and surface roughness prediction in longitudinal-torsional ultrasonic electrolytic composite internal grinding of GCr15 bearing steel

Regarding the internal grinding of bearing components, surface roughness (Ra) directly affects the bearing’s wear resistance, fit stability, fatigue resistance, and service life. Therefore, accurately predicting Ra in internal grinding is crucial. Currently, studies on Ra of ordinary internal grinding or single-energy-field assisted internal grinding have been very extensive, but the scope and effect of single-energy-field assisted methods are limited, which cannot accommodate the growing demands for precision and ultra-precision manufacturing. Longitudinal torsional ultrasonic electrolytic composite internal grinding (LTUEG) combines the advantages of ultrasonic vibration, electrolysis, and mechanical grinding, significantly enhancing the machining quality. However, there are currently few reports on the prediction of Ra in LTUEG. Therefore, this paper developed a Ra prediction model for LTUEG of GCr15 steel bearing rings. Firstly, based on the machining principle and kinematic analysis of LTUEG, the motion trajectory and contact arc length of single abrasive grain were investigated. Through single-factor experiments on passivation film formation, the influences of electrolytic parameters on the thickness, hardness, micro-morphology, and chemical components of passivation film were studied, revealing the formation mechanism of passivation film and elucidating the material removal mechanism in LTUEG. Secondly, based on the thickness model of electrolytic passivation film growth, models for electrolytic material removal height and actual mechanical grinding depth were established. Considering the concept that the undeformed chip thickness follows Rayleigh probability density function and accounting for the effects of material pile-up in grooves and abrasive grain trajectories interference, a theoretical model for Ra in LTUEG was developed. Finally, the abrasive grain trajectory interference coefficients were determined through experiments, the influence of machining parameters on Ra was investigated, and the model was validated with a mean error of 5.15%.