Due to lightweight construction numerous parts in turbomachinery industry with aerodynamic properties exhibit thin-walled features. Typical examples are compressor blades or turbine blades. Finish-milling depicts a stage of the manufacturing process of these parts with significant value creation. A major limitation of productivity is process stability in terms of self-excited or forced vibration. Different simulation approaches attempt determining a priori the process stability to avoid a bad surface quality, accelerated tool wear, tool breakage or scrapped parts. One distinctive part of these simulations is a cutting force model which incorporates material and tool dependent coefficients. The simulation accuracy directly depends on the exactness of these coefficients. Usually, these coefficients are identified experimentally from cutting force measurements with piezoelectric sensors, whose transmissibility is nonlinear. In this paper a multidimensional stationary inverse filter for compensating the influence of the nonlinear transmissibility of force sensors is presented. In a subsequent step, a Levenberg–Marquardt algorithm is used to identify cutting force coefficients from filtered force measurements. The functionality of the filter is validated by comparing highly nonlinear and almost linear piezoelectric force measurement sensors connected in series during finish-milling experiments. The accuracy of the identified cutting force coefficients is assessed by comparing cutting force simulations to measurements.

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