A local and online sifting process for the empirical mode decomposition and its application in aircraft damage detection. (March 2015) - Bagherzadeh, Seyed Amin; Sabzehparvar, Mehdi
Abstract: This paper introduces the Variable-Span Smoothing Sifting (VSSS) for the Empirical Mode Decomposition (EMD), as a substitute for the traditional sifting process. In this method, the local mean of the signal at each point is extracted by applying some smoothing filters to its adjacent data points, within a variable span sliding window. The VSSS is direct, local and online; hence, it may improve the EMD performance, and overcome many drawbacks of the classical algorithm. The performance of the VSSS is verified through some numerical studies, in which, results of the new and traditional sifting processes are compared for some benchmark signals. Finally, the VSSS is applied to the aircraft damage detection problem. Highlights: The Variable-Span Smoothing Sifting (VSSS) is introduced for the EMD. The VSSS extract the local mean of the signal by utilizing smoothing filters. The VSSS is direct, local and online. The VSSS can be employed for the real-time detection of aircraft damages.