Oil and gas pipeline networks have complicated, irregular operational factors. Traditional risk prewarning techniques, including time–frequency domain transformation, are good at forecasting changes in data points at a certain instant in time, but they are unable to detect and identify the system’s operational condition over an extended period of time. The operational status of an oil and gas pipeline may be accurately identified using a data-driven strategy for identifying time series patterns that is introduced in this chapter. The monitoring procedure and identification outcomes of the pipeline operation may be managed and understood in the meanwhile. The goal of the suggested solution is to offer a comprehensible anomaly warning system for the operation management of product oil pipelines.


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    Title :

    Risk Prewarning Method for Pipeline Systems


    Contributors:
    Su, Huai (editor) / Liao, Qi (editor) / Zhang, Haoran (editor) / Zio, Enrico (editor) / Yang, Zhaoming (author) / Chi, Lixun (author)

    Published in:

    Publication date :

    2023-12-13


    Size :

    28 pages




    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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