Asymmetric morphological filter for roughness evaluation of multifunctional surfaces

The scope of multifunctional surfaces in mechanical engineering and instrumentation is constantly expanding. Examples are products with multilayer coatings, products made of composite materials or using additive manufacturing technologies. A feature of multifunctional surfaces is two levels of texture with different parameter values. Various types of filters are used to decomposition and then analyze texture components. Traditionally, for such problems, a robust Gaussian regression filter and a morphological filter are used. The advantage of the morphological filter lies in the lower computational complexity and the ease of removing the shape component from the profile. This research presents generalized analysis of various types of an asymmetric morphological filter based on simulation. The asymmetric filter differs from the standard morphological filter by using different nesting indexes for combinations of morphological opening and closing operations. We have designed a compositional model of profile, which is superposition of two Gaussian distributions with different parameters and waviness. Relative filtering error of the arithmetic mean heights Ra was chosen as evaluation parameter. Based on the Monte Carlo experiments technique, the relative errors of the filters are determined. The main result of the research is algorithm for choosing nesting indexes depending on the type of primary profile. Thus, we give scientifically justified choice of the filter type and its task-specific parameters for applied use. The choice of filter type and two different nesting indexes in accordance with the developed algorithm provide relative error with a coverage interval less 3 % for 95 % coverage probability. The asymmetric morphological filter is effective for scale space analysis of surfaces with significant shape errors and waviness. The results obtained can be used to analyze the tribological properties of multifunctional surfaces of products.