Modeling a random sequence of extremes of loads for fatigue tests under irregular loading

2020 ◽  
pp. 13-19
Author(s):  
N.A. Mahutov ◽  
I.V. Gadolina ◽  
S.G. Lebedinskiy ◽  
E.S. Oganyan ◽  
A.A. Bautin
Keyword(s):  
Random Sequence ◽  
Fatigue Tests ◽  
Linear Hypothesis ◽  
Resource Estimation ◽  
Transition Matrices ◽  
Random Loading ◽  
Markov Transition ◽  
Random Nature ◽  
Irregular Loading ◽  
Markov Transition Matrices

Methods and approaches to tests under random loading are considered, their role is characterized. To ensure the random nature of loading, a modeling method based on Markov transition matrices and real processes recorded in operation is proposed. Keywords: random loading process, Markov repetition matrices, resource estimation, corrected linear hypothesis, parameter of completeness of the loading spectrum. [email protected]

Optimizing maintenance decisions in railway wheelsets: A Markov decision process approach

2018 ◽  
Vol 233 (2) ◽  
pp. 285-300 ◽  
Author(s):  
Joaquim AP Braga ◽  
António R Andrade
Keyword(s):  
Markov Decision Process ◽  
Decision Process ◽  
Transition Matrices ◽  
Technical Standards ◽  
Current State ◽  
Markov Transition ◽  
Markov Decision ◽  
Maintenance Decisions ◽  
Markov Transition Matrices

This article models the decision problem of maintaining railway wheelsets as a Markov decision process, with the aim to provide a way to support condition-based maintenance for railway wheelsets. A discussion on the role of the railway wheelsets is provided, as well as some background on the technical standards that guide maintenance decisions. A practical example is explored with the estimation of Markov transition matrices for different condition states that depend on the wheelset diameter, its mileage since last turning action (or renewal) and the damage occurrence. Bearing in mind all the possible maintenance actions, an optimal strategy is achieved, providing a map of best actions depending on the current state of the wheelset.

Synthetic generation of standard sky types series using Markov Transition Matrices

2014 ◽  
Vol 62 ◽  
pp. 731-736 ◽  
Author(s):  
J.L. Torres ◽  
M. de Blas ◽  
L.M. Torres ◽  
A. García ◽  
A. de Francisco
Keyword(s):  
Transition Matrices ◽  
Markov Transition ◽  
Markov Transition Matrices ◽  
Synthetic Generation

Bayesian inference for Markov chains

2002 ◽  
Vol 39 (01) ◽  
pp. 91-99 ◽  
Author(s):  
Peter Eichelsbacher ◽  
Ayalvadi Ganesh
Keyword(s):  
Bayesian Inference ◽  
Markov Chains ◽  
Moderate Deviation ◽  
Posterior Distributions ◽  
Transition Matrices ◽  
Bayes Methods ◽  
Markov Transition ◽  
Markov Transition Matrices

We consider the estimation of Markov transition matrices by Bayes’ methods. We obtain large and moderate deviation principles for the sequence of Bayesian posterior distributions.

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