Risk analysis and maintenance decision making of natural gas pipelines with external corrosion based on Bayesian network

Abstract

Buried natural gas pipelines are vulnerable to external corrosion because they are encased in a soil environment for a long time. Identifying the causes of external corrosion and taking specific maintenance measures is essential. In this work, a risk analysis and maintenance decision-making model for natural gas pipelines with external corrosion is proposed based on a Bayesian network. A fault tree model is first employed to identify the causes of external corrosion. The Bayesian network for risk analysis is determined accordingly. The maintenance strategies are then inserted into the Bayesian network to show a reduction of the risk. The costs of maintenance strategies and the reduced risk after maintenance are combined in an optimization function to build a decision-making model. Because of the limitations of historical data, some of the parameters in the Bayesian network are obtained from a probabilistic estimation model, which combines expert experience and fuzzy set theory. Finally, a case study is carried out to verify the feasibility of the maintenance decision model. This indicates that the method proposed in this work can be used to provide effective maintenance schemes for different pipeline external corrosion scenarios and to reduce the possible losses caused by external corrosion.