Dataset for the identification of a ultra-low frequency multidirectional energy harvester for wind turbines.

This paper presents a publicly available dataset designed to support the identification (characterization) and performance optimization of an ultra-low-frequency multidirectional vibration energy harvester. The dataset includes detailed measurements from experiments performed to fully characterize its dynamic behaviour. The experimental data encompasses both input (acceleration)-output (energy) relationships, as well as internal system dynamics, measured using a synchronized image processing and signal acquisition system.

Comprehensive Characterisation of a Low-Frequency-Vibration Energy Harvester.

In this paper, we describe a measurement procedure to fully characterise a novel vibration energy harvester operating in the ultra-low-frequency range. The procedure, which is more thorough than those usually found in the literature, comprises three main stages: modelling, experimental characterisation and parameter identification. Modelling is accomplished in two alternative ways, a physical model (white box) and a mixed one (black box), which model the magnetic interaction via Fourier series.

Effect of the glottal source and the vocal tract on the partials amplitude of vibrato in male voices.

In this paper the production of vocal vibrato is investigated. The most relevant features of the acoustical vibrato signal, frequency and amplitude variations of the partials, will be related to the voice production features, glottal source (GS) and vocal tract response (VTR). Unlike previous related works, in this approach, the effect on the amplitude variations of the partials of each one of the above-mentioned voice production features will be identified in recordings of natural singing voice.