Neural network representation of fatigue damage dynamics

Recently, a model of fatigue damage dynamics has been reported, which allows the damage information on critical plant components to be integrated with the plant dynamics for both on-line life prediction and off-line control synthesis. This paper proposes a neural network implementation of the fatigue damage model in order to alleviate the problem of slow computation via conventional numerical methods. The results of simulation experiments reveal that a neural network algorithm could be used as an intelligent instrument for on-line monitoring of fatigue damage and also as a tool for failure prognostics and service life prediction.