Stochastic Reconstruction of Loading Histories from a Rainflow Matrix

Dreßler, Klaus; Hack, Michael; Krüger, Willian Maciel

doi:10.1002/zamm.19970770315

Cited by 29 publications

(6 citation statements)

References 8 publications

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“…A signal will have several local maximum and minimum points, and this signal is imagined as a pagoda roof where these points define the rain flow. The internal minor loops are, in this context, called “rain-flow cycles” and created based on the local maxima or minima identified as reversal points and serve as the base for counting the cycles [ 99 , 115 , 116 , 117 ].…”

Section: Modeling For Iron Lossesmentioning

confidence: 99%

Review of Play and Preisach Models for Hysteresis in Magnetic Materials

Mörée

Leijon

2023

Materials

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This paper studies the properties of the Preisach model and the play model, and compare their similarities. Both are history-dependent hysteresis models that are used to model magnetic hysteresis. They are described as discrete sums of simple hysteresis operators but can easily be reformulated as integral equations of continuous distribution functions using either a Preisach weight distribution function or a play distribution function. The models are mostly seen as phenomenological or mathematical tools but can also be related to friction-like pinning of domain-wall motions, where Rayleigh’s law of magnetic hysteresis can be seen as the simplest case on either the play model or the Preisach model. They are poor at modeling other domain behavior, such as nucleation-driven hysteresis. Yet another hysteresis model is the stop model, which can be seen as the inverted version of the play model. This type of model has advantages for expressions linked to energy and can be related to Steinmetz equation of hysteresis losses. The models share several mathematical properties, such as the congruency property and wiping-out property, and both models have a history of dependence that can be described by the series of past reversal points. More generally, it is shown that the many models can be expressed as Preisach models, showing that they can be treated as subcategories of the Preisach type models. These include the play model, the stop model and also the alternative KP-hysteron model.

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Section: Modeling For Iron Lossesmentioning

confidence: 99%

Review of Play and Preisach Models for Hysteresis in Magnetic Materials

Mörée

Leijon

2023

Materials

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“…These two types of cycles are defined based on the order of occurrence of maximum and minimum values in the signal. To construct the ARM, a rainflow-counting procedure called the Four-Point Counting (FPC) algorithm is used [25].…”

Section: Asymmetric Rainflow Counting Matricesmentioning

confidence: 99%

Rainflow-counting matrix interpolation over different operating conditions for hydroelectric turbine fatigue assessment

et al. 2021

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“…On the other hand, nonparametric methods provide a direct fit to the data and are routinely used to estimate multimodal densities. The kernel density estimator, the most commonly used nonparametric method, has been recently applied to rainflow stress data 4,5 .…”

Section: Stochastic Modeling Of Aircraft Engine Usagesmentioning

confidence: 99%

Nonparametric Risk Assessment of Gas Turbine Engines

Enright¹,

McClung²,

Hudak³

2006

47th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference

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The accuracy associated with risk assessment of gas turbine engine components is highly dependent on the statistical models used to represent the fundamental random variables. Although parametric models are commonly used to represent the random variables, they are often a poor fit near the tails of the distributions. Also, they may not address some of the general relationships among multiple random variables (e.g., multimodality, skewed discontinuities, among others). In this paper, a nonparametric approach is used to model the probability densities associated with rainflow stress pair data for actual military aircraft engine usages. The data are represented using univariate and multivariate Epanechnikov kernels where the window width is adaptively adjusted to address the number of data points in all regions of the distributions. A brief summary of the nonparametric adaptive kernel density estimator is presented including details regarding a specific algorithm. Algorithm performance is illustrated for standard parametric probability density functions and for rainflow stress pairs associated with military aircraft engine usage histories. The results can be applied to fracture risk prediction of gas turbine engine components subjected to complex usages.

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Stochastic Reconstruction of Loading Histories from a Rainflow Matrix

Cited by 29 publications

References 8 publications

Review of Play and Preisach Models for Hysteresis in Magnetic Materials

Review of Play and Preisach Models for Hysteresis in Magnetic Materials

Rainflow-counting matrix interpolation over different operating conditions for hydroelectric turbine fatigue assessment

Nonparametric Risk Assessment of Gas Turbine Engines

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