AI-enabled industrial equipment monitoring, diagnosis and health management

^*Corresponding author for this work

Research output: Contribution to journal › Editorial

10 Citations (Scopus)

Original language	English
Article number	050102
Journal	Measurement Science and Technology
Volume	35
Issue number	5
DOIs	https://doi.org/10.1088/1361-6501/ad2bcd
Publication status	Published - May 2024

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title = "AI-enabled industrial equipment monitoring, diagnosis and health management",

author = "Zhuyun Chen and Haidong Shao and Te Han and Konstantinos Gryllias",

year = "2024",

month = may,

doi = "10.1088/1361-6501/ad2bcd",

language = "English",

volume = "35",

journal = "Measurement Science and Technology",

issn = "0957-0233",

publisher = "Institute of Physics",

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T1 - AI-enabled industrial equipment monitoring, diagnosis and health management

AU - Chen, Zhuyun

AU - Shao, Haidong

AU - Han, Te

AU - Gryllias, Konstantinos

PY - 2024/5

Y1 - 2024/5

UR - https://www.scopus.com/pages/publications/85188210454

U2 - 10.1088/1361-6501/ad2bcd

DO - 10.1088/1361-6501/ad2bcd

M3 - Editorial

AN - SCOPUS:85188210454

SN - 0957-0233

VL - 35

JO - Measurement Science and Technology

JF - Measurement Science and Technology

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M1 - 050102

ER -