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dc.contributor.authorZhou, Yuhan
dc.contributor.authorLiang, Houhao
dc.contributor.authorFoo, Zhen Lin
dc.contributor.authorKoh, Yong Zhi
dc.contributor.authorYeoh, Justin K. W.
dc.date.accessioned2026-08-20T10:40:21Z
dc.date.available2026-08-20T10:40:21Z
dc.date.copyright2025/10/17
dc.date.issued2026
dc.identifier.otherJCEMD4.COENG-17031.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4311103
dc.description.abstractAbstractRoutine maintenance of construction machinery, such as excavators, is essential for ensuring operational efficiency and reliability. A key component of this process is the daily preoperational check, which traditionally relies on workers’ auditory ...Practical ApplicationsThis study introduces a simple yet powerful method to help construction teams detect machinery problems early—before they lead to costly breakdowns. Currently, workers often rely on what they hear to judge whether a machine, such as ...
dc.publisherAmerican Society of Civil Engineers
dc.titleAudio-Based Excavator Preoperational Checks Using Few-Shot Deep Learning
dc.typeJournal Article
dc.journal.volume152
dc.journal.issue1
dc.journal.titleJournal of Construction Engineering and Management
dc.identifier.doi10.1061/JCEMD4.COENG-17031
dc.journal.fristpage04025212-1
dc.journal.lastpage04025212-14
dc.page14
dc.treeJournal of Construction Engineering and Management:;2026:;Volume ( 152 ):;issue: 001
dc.contenttypeFulltext


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