A continuous-state Markov model for age- and state-dependent degradation processes |
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Authors: | Maurizio GuidaGianpaolo Pulcini |
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Affiliation: | a Department of Electronic and Computer Engineering, University of Salerno, Fisciano (SA), Italy b Istituto Motori, National Research Council of Italy, Naples, Italy |
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Abstract: | In order to approximate the unknown transition probability densities of a state-dependent, possibly inhomogeneous, Markov degradation model, a continuous-state discrete-time Markov model is proposed, which is based on the use of the Pearson’s family of distributions for approximating the true transition density. Unlike the alternative approach based on Markov chain approximation, the proposed one has the decisive advantage of dramatically reducing the computing time of the estimation procedure, thus allowing a age- and state-dependent model to be potentially applied also in more complex experimental frameworks, e.g., in presence of random effects. Hence, the proposed model is used to analyse, on the basis of real data from the literature, two different degradation phenomena, namely: the wear of some cutting tools and the crack growth of metallic specimens. |
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Keywords: | Degradation processes Continuous-state Markov chain Age and state dependence Wear data Fatigue crack data |
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