Analytic prognostic model for stochastic fatigue of petrochemical pipelines

Predicting remaining useful lifetime (RUL) of industrial systems becomes an important aim for industrialists very afraid from sudden failures that can lead to very expensive consequences. The recent prognostic approaches try to compensate for the inconveniences emanating from classical maintenance strategies. In fatigue failures, an analytic prognostic methodology based on existing laws of damage in fracture mechanics, such as Paris-Erdogan's and Palmgren-Miner's laws, is recently developed to determine the RUL of the system. This approach shows to be important in ensuring high availability and performance with minimum global costs for industrial systems, like in aerospace, defense, petro-chemistry and automobiles. To get a more realistic prediction, it is important to introduce the stochastic description in these previously developed models. In our fatigue damage model evolving from the point of macro-crack initiation to total failure, the state of damage is expressed by a scalar damage function D(N) in terms of loading cycles N. The RUL is estimated from a predefined threshold of damage D. Pipelines tubes belong to vital mechanical systems in petrochemical industries that serve to transport natural gases or liquids. They are subject to fatigue effects due to pressure-depression alternation. Their adequate prognostic process increases largely their performance, their availability, and minimizes the global cost of their missions.