Simultaneous application of time series analysis and wavelet transform for determining surface roughness of the ground workpieces

The absence of a rapid method for the estimation of surface roughness has been considered as one of the main problems in accurate machining processes. The probability of encountering measurement equipment to other production equipments and unsuitable environments for the measurement equipment can be considered as the main problem for lack of utilizing them on the production. On the other hand, the surface roughness is not uniform at different regions of the manufactured workpiece. The vibration of the cutting tool and boundary conditions of the workpiece can be considered as the main source of these variations. Thus, in contact measurement method, the surface roughness must be determined by repeating and averaging of sampling results. In this paper, a novel non-contact method based on combination of the time series analysis and decomposition of the image by wavelet transform is presented. In this method, the image entropy criterion is used for specifying the appropriate position of the camera and light source relation to the calibrated surface roughness sample. Then, the surface texture of the captured image is extracted by wavelet transform. After that, the analysis of the images for finding the logical relationship between surface roughness and the largest Lyapunov exponent of the approximation coefficients is done. To confirm the suggested method, the grinding experiments on ck45 material with different cutting conditions are done, and their surface roughness has been specified and compared using the contact and the suggested method. The results indicate that the accuracy of the suggested method for determining the surface roughness of ground surface is significant.