The project “Development of an Industry Test Facility and Qualification Processes for in-line inspection (ILI) technology Evaluation and Enhancements” aims to expand knowledge of ILI technology performance and identify gaps where new technology is needed. Additionally, this project also aims to provide ILI technology developers, researchers and pipeline operators a continuing resource for accessing test samples with a range of pipeline integrity threats and vintages; and inline technology test facilities at the Technology Development Center (TDC) of Pipeline Research Council International, Inc. (PRCI), a PRCI managed facility available for future industry and PHMSA research projects.
An ILI pull test facility was designed and constructed as part of this project based on industry state-of-the-art and opportunities for capability improvement. The major ILI technology providers, together with pipeline operator team members, reviewed the TDC sample inventory and developed a series of ILI performance tests illustrating one of multiple possible research objectives, culminating in 16-inch and 24-inch nominal diameter test strings. The ILI technology providers proposed appropriate inspection tools based on the types of the integrity threats in the test strings, a series of pull tests of the provided ILI tools were performed, and the technology providers delivered reports of integrity anomaly location and dimensions for performance evaluation.
Quantitative measures of detection and sizing performance were confidentially disclosed to the individual ILI technology providers. For instances where ILI predictions were outside of claimed performance, the vendors were given a limited sample of actual defect data to enable re-analysis, thus demonstrating the potential for improved integrity assessment with validation measurements.
In this paper, an evaluation of the ILI data obtained from repeated pull-through testing on the 16 and 24-inch pipeline strings at the TDC is performed. The resulting data was aligned, analyzed, and compared to truth data and the findings of the evaluation are presented.
Impacto de LoRaWAN no Desempenho de Plataformas de IoT baseadas em Nuvem e Névoa Computacional
