Parameter Identification in Markov Damage Models

This paper is concerned with the identification of parameters in cumulative damage processes whose underlying statistics are Markov. We consider the problem of parameter estimation during normal field operation and maintenance, and discuss almost-sure convergence of the estimates. We present a theorem on convergence which is valid under a very general class of maintenance policies, and a computer simulation example to demonstrate the theorem.