A predictive surface profile model for turning based on spectral analysis

Abstract This article presents a predictive approach of surface topography based on the FFT analysis of surface profiles. From a set of experimental machining tests, the parameters investigated are: feed per revolution, insert nose radius, depth of cut and cutting speed. The first step of the analysis consists of normalizing the measured profiles with the feed per revolution. This results in normalized profiles with a feed per revolution and a signal period equal to 1. The effect of each cutting parameter on the surface profile is expressed as a spectrum with respect to the period length. These effects are quantified and can be sorted in descending order of importance as feed per revolution, insert nose radius, depth of cut and cutting speed. The second part of the paper presents a modeling of the surface profile using the parameters effects and one interaction. The proposed model gives the spectrum of the profile to be predicted. The inverse Fourier transform applied to the spectrum yields the expected surface profile. Measured and simulated profiles are compared for two cutting conditions and results correlate well.

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