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contributor authorYufeng Yang
contributor authorQiang Zhang
contributor authorXixiang Zhang
contributor authorShuyi Xie
contributor authorGang Wu
contributor authorLifeng Li
date accessioned2024-04-27T22:27:28Z
date available2024-04-27T22:27:28Z
date issued2024/02/01
identifier other10.1061-JPSEA2.PSENG-1490.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4296700
description abstractAs an important part of the energy transportation system, oil and gas pipelines are developing toward intelligence and digitalization. Vigorously developing and constructing pipeline networks based on intelligent methods such as big data and neural networks will help improve the efficiency of operation and management. This work provides an overview of recent developments of intelligent methods, including machine learning approaches, heuristic algorithms, and mathematical programming, used in the pipeline industry that can provide beneficial support for various applications enhancing operation and maintenance. Several aspects such as operating condition recognition, safety monitoring, pipeline remaining life prediction, and fault detection are reviewed and discussed. The study shows the need to focus on improving management level and ensuring pipeline safety.
publisherASCE
titleIntelligent Methods for Pipeline Operation and Integrity
typeJournal Article
journal volume15
journal issue1
journal titleJournal of Pipeline Systems Engineering and Practice
identifier doi10.1061/JPSEA2.PSENG-1490
journal fristpage04023053-1
journal lastpage04023053-8
page8
treeJournal of Pipeline Systems Engineering and Practice:;2024:;Volume ( 015 ):;issue: 001
contenttypeFulltext


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