Spindle electrical signal-based evaluation of lubrication performance in milling with micro-textured tools under different lubrication modes

Micro-textured tools and advanced lubrication can reduce friction and improve milling stability of difficult-to-machine superalloys. This study quantified the effects of micro-texture geometry and lubrication mode on dynamic cutting load in GH4169 milling. Circular micro-textured tools with different spacing (Ls), diameter (D), and edge distance (Le) were tested under dry milling, MoS 2 , cold-air minimum quantity lubrication (CMQL), and supercritical CO 2 minimum quantity lubrication (scCO 2 MQL). Three-channel spindle electrical signals were analyzed by short-time Fourier transform, and total time–frequency energy, tooth-passing band energy, and spectral entropy were extracted. CMQL showed the best performance, reducing average total time–frequency energy by 9.57%, 7.74%, and 3.65% compared with dry milling, MoS 2 , and scCO 2 MQL, respectively. The minimum energy under optimal CMQL reached 5842.62, with spectral entropy of 2.9937. The dominant texture factor varied with lubrication mode, confirming the applicability of spindle electrical signals for lubrication evaluation.