Pipeline reliability assessment and predictive maintenance considering multi-crack dependent degradation

Abstract

Cracks due to corrosion are one of the main reasons for natural-gas pipeline leaks. Making the reliability assessment, prediction, and maintenance decision of pipelines based on measurable crack data is a central issue at present. The failure of pipelines is usually a result of the cumulative impact of multiple cracks. The interaction between adjacent cracks accelerates crack propagation, and greatly affects the degradation mechanism of pipelines. In this study, the reliability prediction and maintenance decisions were studied by considering the dependent degradation between multiple cracks in pipelines. Firstly, the initiation and propagation of pipeline cracks were modeled using a non-homogeneous Poisson process and a Gamma process, respectively. The interaction between cracks was defined to be a function of the random crack distance, which could be reflected by the change of shape parameters in the Gamma process. Secondly, the pipeline’s failure was defined as the competitive failure of the number of cracks, the maximum crack depth, and the total crack depth. The reliability prediction model of a pipeline under this failure mode was determined. A non-periodic combined maintenance policy considering both the pipeline condition and its predictive reliability was then proposed, and an optimal predictive maintenance decision model was constructed to minimize the long-term average cost rate. Finally, the effectiveness of the proposed model and policy was verified by a numerical experiment and a crack dataset of a transnational pipeline.