Characterization of Real-world Vibration Sources and Application to Nonlinear Vibration Energy Harvesters

Analysis of vibration data in the design of vibration energy harvesters.

(De Gruyter) – Determining the prevalence of vibration signals may provide insight into the design of vibration
energy harvesters. Design and analysis of vibration energy harvester architectures has with the goal of optimizing power output.

Common ambient vibration data representing 333 vibration signals were downloaded and processed according to the source of the signal (e. g. vehicle, machine, etc.), the number of dominant frequencies, the nature of the dominant frequencies (e. g. stationary, band-limited noise, etc.), and other metrics.

The set of idealized vibration inputs (i. e. single stationary frequency, Gaussian white noise, etc.) commonly assumed for harvester input were corroborated and refined. The classification determined that, of the set of signals used in the study, 64 % of the animal source signals are best described with non-stationary dominant frequencies, 58 % of machine source signals are best described with stationary frequencies, and vehicle source signals are poorly described by any one signal type used in the classification.

The researchers determined that a standard linear oscillator harvester is likely the best design for at least 23 % of the signals and that harvesters with the common cubic non-linear stiffness function could offer an improvement at most 53 % of the time. Their next step is to refine the analysis to better improve the results.


Edited for Content and Length by Dr. Matthew A. Hood.

The original full article can be found at De Gruyter in Energy Harvesting and Systems.

DOI: 10.1515/ehs-2016-0021

Energy Harvesting and Systems. 2017, 4(2) 67–76.

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