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    An Intelligent Method for Identifying and Analyzing PCCP Wire-Break Signals Based on Prototype Testing and an Ensemble Deep Learning Model

    Source: Journal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 003::page 04026014-1
    Author:
    Zhang, Ye
    ,
    Yuan, Simin
    ,
    Li, Yanlong
    ,
    Li, Kangping
    ,
    Zhou, Heng
    ,
    Sun, Kaiyu
    DOI: 10.1061/JCCEE5.CPENG-6666
    Publisher: American Society of Civil Engineers
    Abstract: AbstractWire breakage is the predominant cause of failure in prestressed concrete cylinder pipe (PCCP) within water diversion and transfer projects. This paper employs deep learning models to extract signal features and identify wire breakage types. A ...
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      An Intelligent Method for Identifying and Analyzing PCCP Wire-Break Signals Based on Prototype Testing and an Ensemble Deep Learning Model

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4314411
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    • Journal of Computing in Civil Engineering

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    contributor authorZhang, Ye
    contributor authorYuan, Simin
    contributor authorLi, Yanlong
    contributor authorLi, Kangping
    contributor authorZhou, Heng
    contributor authorSun, Kaiyu
    date accessioned2026-08-20T21:24:48Z
    date available2026-08-20T21:24:48Z
    date copyright2026/01/31
    date issued2026
    identifier otherJCCEE5.CPENG-6666.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314411
    description abstractAbstractWire breakage is the predominant cause of failure in prestressed concrete cylinder pipe (PCCP) within water diversion and transfer projects. This paper employs deep learning models to extract signal features and identify wire breakage types. A ...
    publisherAmerican Society of Civil Engineers
    titleAn Intelligent Method for Identifying and Analyzing PCCP Wire-Break Signals Based on Prototype Testing and an Ensemble Deep Learning Model
    typeJournal Article
    journal volume40
    journal issue3
    journal titleJournal of Computing in Civil Engineering
    identifier doi10.1061/JCCEE5.CPENG-6666
    journal fristpage04026014-1
    journal lastpage04026014-18
    page18
    treeJournal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 003
    contenttypeFulltext
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