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Wave-ConvNeXt: An Efficient and Precise Fault Diagnosis Method for IIoT Leveraging Tailored ConvNeXt and Wavelet Transform
Department of Industrial Engineering, Dongguan University of Technology, Dongguan, China.
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics. Division of Product Realization, Mälardalen University, Eskilstuna, Sweden.ORCID iD: 0000-0002-7458-6820
Department of Industrial Engineering, Dongguan University of Technology, Dongguan, China.
State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, College of Mechanical and Vehicle Engineering, Hunan University, Changsha, China.
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2024 (English)In: IEEE Internet of Things Journal, ISSN 2327-4662, Vol. 11, no 13, p. 23096-23109Article in journal (Refereed) Published
Place, publisher, year, edition, pages
IEEE, 2024. Vol. 11, no 13, p. 23096-23109
Keywords [en]
Computational Efficiency, Computational modeling, Computer architecture, Continuous wavelet transforms, ConvNeXt Architecture, Fault diagnosis, Fault Diagnosis, Industrial Internet of Things, Industrial Internet of Things (IIoT), Time-frequency analysis, Transforms, Wavelet Transform
National Category
Computer Engineering
Research subject
Operation and Maintenance Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-105213DOI: 10.1109/JIOT.2024.3386965ISI: 001258244000018Scopus ID: 2-s2.0-85190168707OAI: oai:DiVA.org:ltu-105213DiVA, id: diva2:1853863
Note

Validerad;2024;Nivå 2;2024-07-01 (joosat);

Funder: National Natural Science Foundation of China (52275104;71971064); Dongguan Scitech Commissioner Program (20231800500112); Research start-up funds of DGUT (GC300502-46); Basic and Applied Basic Research Foundation of Guangdong Province (2022A1515140035; 2022A1515140093);

Available from: 2024-04-23 Created: 2024-04-23 Last updated: 2024-11-20Bibliographically approved

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