Surface characteristic profile extraction based on Hilbert-Huang transform

Engineering surfaces consist of a wide range of spatial frequencies. Prior to numerical characterization, the decomposition and filtration of the data measured for such surfaces should be performed. This paper introduces a new technique for the extraction of different frequency components of surfaces of interest by applying the Hilbert-Huang transform. The main features of the Hilbert-Huang transform are its adaptive signal decomposition and time/space domain filtering. The data measured in two cases, a runout measurement for a turning pulley and ground surface profile scanning, respectively, were analyzed using the Hilbert-Huang transform, and some results are compared with those obtained using robust zero-order Gaussian regression filters. The analysis process and results show that the new technique proposed is useful and complementary to other existing techniques.