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  • Open Access

    REVIEW

    Significant Advancements in UAV Technology for Reliable Oil and Gas Pipeline Monitoring

    Ibrahim Akinjobi Aromoye1, Hai Hiung Lo1, Patrick Sebastian1, Ghulam E Mustafa Abro2,*, Shehu Lukman Ayinla1,3

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1155-1197, 2025, DOI:10.32604/cmes.2025.058598 - 27 January 2025

    Abstract Unmanned aerial vehicles (UAVs) technology is rapidly advancing, offering innovative solutions for various industries, including the critical task of oil and gas pipeline surveillance. However, the limited flight time of conventional UAVs presents a significant challenge to comprehensive and continuous monitoring, which is crucial for maintaining the integrity of pipeline infrastructure. This review paper evaluates methods for extending UAV flight endurance, focusing on their potential application in pipeline inspection. Through an extensive literature review, this study identifies the latest advancements in UAV technology, evaluates their effectiveness, and highlights the existing gaps in achieving prolonged flight… More > Graphic Abstract

    Significant Advancements in UAV Technology for Reliable Oil and Gas Pipeline Monitoring

  • Open Access

    ARTICLE

    Prediction on Failure Pressure of Pipeline Containing Corrosion Defects Based on ISSA-BPNN Model

    Qi Zhuang1,*, Dong Liu2, Zhuo Chen3

    Energy Engineering, Vol.121, No.3, pp. 821-834, 2024, DOI:10.32604/ee.2023.044054 - 27 February 2024

    Abstract Oil and gas pipelines are affected by many factors, such as pipe wall thinning and pipeline rupture. Accurate prediction of failure pressure of oil and gas pipelines can provide technical support for pipeline safety management. Aiming at the shortcomings of the BP Neural Network (BPNN) model, such as low learning efficiency, sensitivity to initial weights, and easy falling into a local optimal state, an Improved Sparrow Search Algorithm (ISSA) is adopted to optimize the initial weights and thresholds of BPNN, and an ISSA-BPNN failure pressure prediction model for corroded pipelines is established. Taking 61 sets More >

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