A generic gust definition and detection method based on wavelet-analysis

Download statistics - Document (COUNTER):

Knoop, H.; Ament, F.; Maronga, B.: A generic gust definition and detection method based on wavelet-analysis. In: Advances in Science and Research 16 (2019), S. 143-149. DOI: https://doi.org/10.5194/asr-16-143-2019

Repository version

To cite the version in the repository, please use this identifier: https://doi.org/10.15488/8820

Selected time period:


Sum total of downloads: 37

Wind gusts can have destructive effects on many structures and objects deemed valuable to humans. The aviation industry, for example, views gusts as a major hazard. Their destructive effect is proportional to the momentum that a specific gust imposes onto an object. The actual definition of a gust has a strong influence on how its impact can be quantified. Existing gust definitions, however, are largely based on fixed parameters describing shape requirements and thresholds and are often developed only for specific use cases. These gust definitions do not provide a direct link to the physical impact a particular gust has on a structure or object. The overall goal of this study is to provide such a direct link. The application of a wavelet-analysis to a turbulence-resolving wind velocity signal allows for the localization of signal amplitudes in the period as well as in the time domain. In this paper, we use wavelet-analysis in order to develop a straight-forward method of deriving information about gusts from a wind velocity signal. In order to define what a particular gust might be, we suggest the specification of a characteristic period and amplitude in the time-domain. We define a generic gust as a section of a wind velocity signal, where the wavelet-analysis detects that characteristic amplitude to be matched or exceeded within that characteristic period. The characteristic amplitudes and periods are generic and span a two-dimensional space of generic gust definitions. The method can be applied to turbulence resolving simulation data as well as high-resolution wind velocity measurement data. It can detect gusts of any shape, it is unbiased regarding any specific use case and invariant to changes of the mean wind. We provide a detailed description of the method, its capabilities and demonstrate its application to high resolution wind velocity measurement data.
License of this version: CC BY 4.0 Unported
Document Type: article
Publishing status: publishedVersion
Issue Date: 2019
Appears in Collections:Fakultät für Mathematik und Physik

distribution of downloads over the selected time period:

downloads by country:

pos. country downloads
total perc.
1 image of flag of Germany Germany 17 45.95%
2 image of flag of China China 5 13.51%
3 image of flag of United Kingdom United Kingdom 4 10.81%
4 image of flag of United States United States 3 8.11%
5 image of flag of Canada Canada 2 5.41%
6 image of flag of Turkey Turkey 1 2.70%
7 image of flag of Romania Romania 1 2.70%
8 image of flag of India India 1 2.70%
9 image of flag of Finland Finland 1 2.70%
10 image of flag of Belgium Belgium 1 2.70%
    other countries 1 2.70%

Further download figures and rankings:


Zur Erhebung der Downloadstatistiken kommen entsprechend dem „COUNTER Code of Practice for e-Resources“ international anerkannte Regeln und Normen zur Anwendung. COUNTER ist eine internationale Non-Profit-Organisation, in der Bibliotheksverbände, Datenbankanbieter und Verlage gemeinsam an Standards zur Erhebung, Speicherung und Verarbeitung von Nutzungsdaten elektronischer Ressourcen arbeiten, welche so Objektivität und Vergleichbarkeit gewährleisten sollen. Es werden hierbei ausschließlich Zugriffe auf die entsprechenden Volltexte ausgewertet, keine Aufrufe der Website an sich.

Search the repository