A condition-based dynamic segmentation of large systems using a Changepoints algorithm: A corroding pipeline case

Abstract

Large structures are systems composed by a significant number of components with parallel or series distributions. How these components fail and interact, aggravate the complexity of the main structure reliability calculation. Some methods commonly proposed to reduce this complexity by dividing the system into segments of similar properties using dynamic or static approaches. Dynamic segmentations may depend on how aggressive is the structure’s surrounding conditions (e.g., the soil properties). Static segmentations could be given by fixed distances. However, in a few cases, these divisions follow a condition-based approach. This paper proposes an alternative dynamic segmentation to identify preliminary critical segments based on a Changepoint approach and data obtained from inspections. Changepoints algorithms have been used to determine changes in spatial measurements for a further reliability evaluation with appropriate limit state functions. This work focuses on onshore pipelines subjected to corrosion defects based on information obtained from In-Line Inspections (ILI). Onshore pipelines cross through a variety of soils, water corridors, and densely populated areas promoting spatial-dependent degradation processes like corrosion. ILI inspections are commonly used to identify the condition of the pipeline in terms of the remaining wall and location of metal loss at the inner and outer walls by using magnetic or ultrasonic instruments. Based on a burst failure limit state, the segments obtained with the changepoints approach are compared with a soil and static segmentations. The results indicate that the proposed approach could identify the main critical points of the pipeline using segments with statistical significance.