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A Preliminary Proto...
A Preliminary Prototype Based on Biological Mimicry for Hardware Data Acquisition
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- Zheng, Tao (författare)
- Beijing Jiatong University, China
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- Meng, Zuyao (författare)
- Beijing Jiatong University, China
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- Gu, Quing (författare)
- Shunde Graduate School of University of Science and Technology, China
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- Huang, Fei (författare)
- The Third Affiliated Hospital of Sun Yat-sen University, China
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- Gidlund, Mikael, 1972- (författare)
- Mittuniversitetet,Institutionen för informationssystem och –teknologi,Communication Systems and Networks (CSN)
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(creator_code:org_t)
- IEEE, 2021
- 2021
- Engelska.
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Ingår i: 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA ). - : IEEE. - 9781728129891
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Fault diagnosis in Industrial Internet of Things and Cyber-Physical Systems is essential, especially for the rapidly developing 5G and coming 6G technology. Hardware working status is the basis for fault diagnosis. However, in actual engineering, accurately locating faults is not easy for hardware engineers. In this paper, a prototype based on FPGA is developed to connect with the target field device in data acquisition. This prototype aims to extract the underlying data information in a real-time and unattended manner like the mimicry of natural immunity. The preliminary experiment results from the prototype can be used to guide practice through providing real-time data support for hardware troubleshooting and spontaneous and intelligent analysis.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Kommunikationssystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Communication Systems (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorteknik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Engineering (hsv//eng)
Nyckelord
- Fault diagnosis
- Training
- Machine learning algorithms
- Data acquisition
- Prototypes
- Hardware
- Real-time systems
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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