Three dimensional detection of rail shape based on self-adaptive filtering

摘要

In three dimensional detection of the rail shape by Fourier Transform profilometry (FTP), filtering is one of the key links before Fourier transform. The choice of filtering window decides the spectrum overlapping degree of deformed fringes, so as to decide the measurement precision of the rail shape. In this paper, based on wavelet ridge theory the size of the filter window is self-adaptive according to the frequency alternation of deformed fringes. And thus the optimum matching window size is decided, the frequency overlapping is furthest reduced and the measurement precision is improved. Simulation and experiments manifest that self-adaptive filtering can greatly enhance the precision in three dimensional detection, which offers a new thinking and method in rail shape recovery and defect detection.