Intelligent Continuous Replacement Policy using Diagnosis and Prediction Techniques

Abstract

The paper presents the problem of time renewal determination using the real probabilities of the Markov model state. The diagnosis subsystem, based on neural networks, provides the probabilities for current states of Markov model of the equipment with positive wear. The Markov model’s parameters are adjusted using a neural network.