Richard Markert

TL;DR: VMD is a newly developed technique for adaptive signal decomposition, which can non-recursively decompose a multi-component signal into a number of quasi-orthogonal intrinsic mode functions and shows that the multiple features can be better extracted with the VMD, simultaneously.

TL;DR: In this article, the spectral kurtosis (SK) technique is extended to that of a function of frequency that indicates how the impulsiveness of a signal can be detected and analyzed.

TL;DR: This work analyzes the behavior of VMD in the presence of irregular samples, impulsive response, fractional Gaussian noise as well as tones separation, and finds that it reveals a different equivalent filter bank structure, robustness with respect to the nonuniformly sampling and good resolution in spectrum analysis.

TL;DR: In this article, the maximum amplitude and the respective resonance frequencies of a linear oscillator passing resonance are derived analytically, starting from the exact solution for run-up or run-down with constant acceleration, irrelevant terms are omitted.

TL;DR: In this article, a model based method for the on-line identification of malfunctions in rotor systems is proposed, where the fault-induced change of the rotor system is taken into account by equivalent loads which are virtual forces and moments acting on the linear undamaged system model to generate a dynamic behaviour identical to the measured one of the damaged system.