Discrete wavelet analysis of blade vortex interaction noise
The discrete wavelet transform, implemented in a multirate filter bank scheme using conjugate quadrature filters, is used to analyze blade vortex interaction (BVI) noise from helicopter rotors in different environments. The discrete wavelet transform successfully isolates the bursty, nonstationary nature of this impulsive noise source. The sub‐band coding scheme is then used for signal reconstruction of only the portion of helicopter noise related to blade vortex interaction by filtering in the frequency and time domains. By eliminating extraneous noise sources, the wavelet analysis can produce a more direct comparison between BVI noise generated in flight and in other environments such as a wind tunnel.
Abstract Wind is one of the fastest-growing renewable sources of electricity. As with most renewables, the economic viability relies on public subsidies. Even among renewables, the economic evaluation of wind projects is particularly challenging due to the unpredictability of the energy source, wind, and the high sensitivity of the project profitability to changes in a number of parameters. This makes the uncertainty analysis an important topic of research in the wind power sector. This study presents a method of combining two uncertainty analysis methods, sensitivity study and the Monte Carlo method, together with a technical and economic model of a wind farm, in an effort to improve the understanding of the practical effects of the uncertainties, and how they affect the financial risks of wind projects.