Failure probability estimation of dynamic systems employing relaxed power spectral density functions with dependent frequency modeling and sampling

verfasst von
Marco Behrendt, Meng Ze Lyu, Yi Luo, Jian Bing Chen, Michael Beer
Abstract

This work addresses the critical task of accurately estimating failure probabilities in dynamic systems by utilizing a probabilistic load model based on a set of data with similar characteristics, namely the relaxed power spectral density (PSD) function. A major drawback of the relaxed PSD function is the lack of dependency between frequencies, which leads to unrealistic PSD functions being sampled, resulting in an unfavorable effect on the failure probability estimation. In this work, this limitation is addressed by various methods of modeling the dependency, including the incorporation of statistical quantities such as the correlation present in the data set. Specifically, a novel technique is proposed, incorporating probabilistic dependencies between different frequencies for sampling representative PSD functions, thereby enhancing the realism of load representation. By accounting for the dependencies between frequencies, the relaxed PSD function enhances the precision of failure probability estimates, opening the opportunity for a more robust and accurate reliability assessment under uncertainty. The effectiveness and accuracy of the proposed approach is demonstrated through numerical examples, showcasing its ability to provide reliable failure probability estimates in dynamic systems.

Organisationseinheit(en)
Institut für Risiko und Zuverlässigkeit
Externe Organisation(en)
Tongji University
The University of Liverpool
Typ
Artikel
Journal
Probabilistic Engineering Mechanics
Band
75
Anzahl der Seiten
10
ISSN
0266-8920
Publikationsdatum
01.2024
Publikationsstatus
Veröffentlicht
Peer-reviewed
Ja
ASJC Scopus Sachgebiete
Statistische und nichtlineare Physik, Tief- und Ingenieurbau, Kernenergie und Kernkraftwerkstechnik, Physik der kondensierten Materie, Luft- und Raumfahrttechnik, Meerestechnik, Maschinenbau
Elektronische Version(en)
https://doi.org/10.1016/j.probengmech.2024.103592 (Zugang: Geschlossen)