Bootstrap confidence interval on IOHMM parameters for system health diagnostic under multiple operating conditions
Résumé
The operating conditions have an important impact on system degradation. This paper uses the Input-Output Hidden Markov Model to represent the system degradation having multiple operating conditions. In this paper the bootstrap method is applied to estimate the model parameters and applied to diagnostic system health. Parameters of the model are computed with 95% confidence intervals. The uncertainty about multiple data sequences and degradation speed is handled in the proposed model. A numerical application is given to explain the methodologies used to estimate the model parameters and the system healthdiagnostic.
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