Marko Nagode (Author), Jernej Klemenc (Author)

Abstract

When the load is stochastic and the service life is a consequence of the fatigue process, the loading histories are transferred into load spectra using rainflow counting. Once the empirical densities of load cycles are known, their probability density is estimated. Here, different probability density mixtures and algorithms for their estimation have been compared according to their ability to model rainflow matrices. The estimated probability density should also consider loading cycles with a small probability. The main scientific contribution of this article is that procedures were identified, which enable more thorough consideration of those clusters with less probable load cycles.

Keywords

rainflow counting;probability density function;load spectrum;finite mixture distributions;fatigue life;

Data

Language: English
Year of publishing:
Typology: 1.01 - Original Scientific Article
Organization: UL FS - Faculty of Mechanical Engineering
UDC: 519.876.5(045)
COBISS: 35679235 Link will open in a new window
ISSN: 0142-1123
Views: 382
Downloads: 45
Average score: 0 (0 votes)
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Other data

Secondary language: Slovenian
Secondary keywords: rainflow števna metoda;gostota porazdelitve verjetnosti;obremenitveni spekter;končna mešanica porazdelitev;doba trajanja;
Type (COBISS): Article
Embargo end date (OpenAIRE): 2022-11-04
Pages: str. 1-10
Issue: ǂVol. ǂ143
Chronology: Feb. 2021
DOI: 10.1016/j.ijfatigue.2020.106006
ID: 12126911