LAUSR

Abstract Spindle dynamic conditions such as stiffness, damping, runout, and resonance frequencies are the most important factors to determine the quality of the machined part. Thus, spindle dynamic characterization to in-situ identify the spindle behavior is crucial to achieve high dimensional accuracy during the machining. This paper presents a new class of dimensional sensors, the so-called curved-edge sensors (CES), capable of spindle dynamic characterization and in-situ spindle condition monitoring while machining. Unlike conventional dimensional sensors such as capacitive proves or eddy current probes whose sensitivities are sensitive to the curvature of the target surface and lateral motion of the spindle, CES is not sensitive to those effects that CES can be used for spindle metrology, providing more accurate dimensional information available for spindle dynamic characterization. In this study, two-axis CES were embedded inside the aerostatic spindle system not to disturb the spindle system while machining a part, even under working fluid conditions. The CES showed the sensitivity 0.301 and 0.304 V/μm along the X and Y axes, and the linearity was 0.06 % and 0.05 % in full scale, respectively. In addition to the calibration, bandwidth, noise level, and reliability of CES were characterized. Also, the spindle runouts at different speed conditions were characterized by CES, and the cutting forces were in-situ estimated by multiplying 3 × 3 spindle stiffness matrix and the measured displacement.