Abstract

The article presents theoretical analysis of machined surface roughness after sawing on circular saw and implementation of fast Fourier transform (FFT) as a possible simple filtering method for filtering out just the saw blade and saw tooth influence on the surface roughness. Surface roughness profile is represented as a signal that can be obtained as a sum of complex periodic signals that represent theoretical profile of tooth marks and lateral movement of tooth due to saw lateral movement and signals that represent structural roughness of wood combined with machining roughness, represented as a Gaussian noise. The application of FFT based filtering on such a signal can be effectively used to extract the main frequency components due to tool influence on total surface signal and the time domain of filtered signals display can then be obtained by use of the inverse Fourier transform. In order to test the theoretical assumptions, the machining tests in sawing of solid oak wood (Quercus robur L.) and medium density fiberboard (MDF) was conducted. Machined surface roughness was measured and analyzed in accordance with theoretical assumptions. It was concluded that a combination of discrete Fourier transform of surface roughness profile and standard roughness parameters can give a more complete representation of machined surface roughness after sawing with circular saws and that filtering of surface roughness profile signal with FFT filter can be used as a simple and effective method in quantifying tool influence on machined surface roughness after sawing on circular saw in varying machining conditions and on different workpiece material.

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