The length of the gas transmission system (GTS) of the Russian Federation totals 172.6 thousand kilometers. The majority of 254 gas pumping compressor stations (CS) were built in the last century. Integrity of the 40% underground CS pipelines is extremely influenced by corrosion and stress corrosion (SCC) due to deterioration of protective coating. CS pipelines are very specific in terms of technical inspection as a result of their complex spatial arrangement that prevents application of smart PIGs.
The paper presents CS PIMS multiple-factor goal planning model that integrates completeness of technical inspection data, pipeline damage by various groups of defects, financial and technical constraints. CS PIMS model ensures procedural uniformity during evaluation, forecast, monitoring, and target value management of the pipeline technical state. Regularity framework is based on the experimentally proved data on hazard level and propagation rate of pipeline defects, inspection tool parameters, inspection data verification results, pipeline operation modes and conditions.
The paper highlights specifics of robotic inspection, verification of inspection data, CS pipelines technical condition evaluation and forecast. Authors provide practical recommendations on how to consider the time of damage propagation, optimize CS pipeline repair methods on the basis of corrosion and stress corrosion physical models.
Authors conceptualize an intelligent system (IS) for CS gas pipelines technical inspection support as PIMS tool. IS provides visualization, verification, quality control of inspection data and forecast of defect growth rate with the help of custom-made software that applies big data and computer-assisted learning technologies.
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