Variation mode-decomposition based surface recovery algorithm for white light interferometry

Abstract

White light interferometry (WLI) provides noncontact, high-precision surface profiling and inspection for ultra-precision machining. This paper presented a signal time-domain mode-decomposition denoising based surface recovery algorithm for WLI. In this work, the captured correlogram is firstly decomposed into a series of modes with different central spectrums by means of the variation mode-decomposition (VMD), and the spectral component of each intrinsic mode can be derived through the Fourier transform. Afterwards, the noise existed in each spectral component is eliminated through windowed Fourier filtering (WFF), where the filtering threshold is decided by the ratio of spectral energy of intrinsic mode comparing with that of the correlogram. The denoised correlogram could then be extracted as the sum of filtered intrinsic modes. And the surface height isfinally retrieved through envelope peak location by applying Hilbert transform. The effectiveness of the proposed method on noise suppression is investigated under different levels of additive noises occurred on simulated correlograms. Moreover, a height step standard with calibrated values 1.762±0.010μm is further testified, where the measurement accuracy of the proposed method is totally verified.

Guided filtering based surface recovery algorithm for white light interferometry

“…In recent years, some researchers investigated the influence of random noise and proposed various frequency domain filtering processes to suppress the noise of correlogram, such as Window Fourier denoising method(WFD) [8], Variation mode-decomposition windowed fourier filtering (VMD-WFF) denoising method [9] and Wiener filtering method [10]. These methods can suppress the noise and improve the measurement accuracy to a certain extent.…”