A wavelet-fractal-based approach for composite characterisation of engineering surfaces

Many types of engineering surfaces have been seen to have fractal characteristics. A good model of the properties can be produced using wavelet-based expansions. For multiscale analysis of surface topography, a difficulty exists in determining quantitatively the feature separation index for comprehensively characterising roughness, waviness, and form errors from a primary surface structure. In this project, we utilise the fractal dimension, which has proved to be an intrinsic parameter capable of measuring surface irregularities, to quantify the feature separation index in the wavelet transform for a composite characterisation of engineering surfaces. The effectiveness of the proposed method is validated in the computational testing of 2D and 3D surfaces.