Characterizing non-Gaussian vibration loading using the trispectrum
- This paper addresses the use of higher-order spectra to study the non-Gaussian nature of random vibration loading. Since the power spectral density is only a full description for stationary Gaussian processes, specifying non-Gaussian random vibration loading requires a sophisticated statistical description. In recent research higher-order statistical moments such as skewness and kurtosis have been used to de_ne non-Gaussian properties of vibration loading. However, useful information contained in the spectral representation of these moments is neglected. This paper introduces the trispectrum as a tool for analyzing vibration loading. It is the spectral representation of the fourth-order moment and thus extends the information content of the kurtosis. For demonstration several common methods for generating non-Gaussian loading are reviewed and used to derive loads that reproduce the power spectral density and kurtosis of a real in-service loading. These loads are analyzed using Fatigue Damage Spectra and trispectra to relate structural response behavior to their non-Gaussian nature. The results suggest that the trispectrum is a valuable tool for analyzing and classifying non-Gaussian random loading.
Author: | Arvid TrappORCiD, Peter WolfsteinerORCiD |
---|---|
URN: | urn:nbn:de:bvb:m347-opus-2355 |
DOI: | https://doi.org/10.1088/1742-6596/1264/1/012040 |
Parent Title (English): | Journal of Physics: Conference Series |
Publisher: | IOP Publishing |
Document Type: | Article |
Language: | English |
Date of Publication (online): | 2022/01/11 |
Year of first Publication: | 2019 |
Publishing Institution: | Hochschule für angewandte Wissenschaften München |
Contributing Corporation: | Thirteenth International Conference on Recent Advances in Structural Dynamics (RASD) 15–17 April 2019, Valpre, Lyon, France |
Release Date: | 2022/01/11 |
Article Number: | 012040 |
Page Number: | 12 |
Note: | Sonderdruck aus: Journal of Physics: Conference Series, Volume 1264 (2019) |
Departments and Institutes: | Fakultäten der Hochschule München / FK 03 Fakultät für Maschinenbau, Fahrzeugtechnik, Flugzeugtechnik |
Dewey Decimal Classification: | 5 Naturwissenschaften und Mathematik / 53 Physik |
Illustrations: | grafische Darstellung/en |
Licence (German): | Creative Commons - CC BY - Namensnennung 4.0 International |