Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Yixin Huangfu"'
Publikováno v:
IEEE Access, Vol 12, Pp 70392-70404 (2024)
This study proposes a hybrid fault detection methodology for detecting epoxy faults in hairpin-based stator windings of electric motors. The hybrid methodology integrates a model-based approach for feature extraction and a data-driven approach for fa
Externí odkaz:
https://doaj.org/article/44ad6922379743d78f6840053eebecb8
Publikováno v:
IEEE Access, Vol 11, Pp 92838-92846 (2023)
This study investigates various hairpin winding faults in electric motors using impedance measurements. Both high-frequency and low-frequency impedances are measured to characterize winding fault conditions. This study proposes various techniques to
Externí odkaz:
https://doaj.org/article/0cec655ae8b447ffab99a544e83ca5c3
System Failure Detection Using Deep Learning Models Integrating Timestamps With Nonuniform Intervals
Publikováno v:
IEEE Access, Vol 10, Pp 17629-17640 (2022)
System logs play an important role in software development and system maintenance. Many system software programs continuously generate system logs during software runtimes for failure detection and diagnosis purposes. Currently, the analysis of syste
Externí odkaz:
https://doaj.org/article/08db0d2092ce41ae9a7e0ac7fd720ef5
Publikováno v:
ASHRAE Transactions. 2024, Vol. 130 Issue Part 1, p528-533. 6p.
Publikováno v:
SAE International Journal of Engines. 15:515-525
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::04a7de49f721048164b950cfba710e9d
https://doi.org/10.4271/03-15-04-0027
https://doi.org/10.4271/03-15-04-0027
Publikováno v:
ASME 2022 ICE Forward Conference.
Fault Detection and Diagnosis (FDD) in internal combustion engines is an important tool for better performance, safety, reliability, and instrument to reduce maintenance costs. Early detection of engine faults can help avoid abnormal event progressio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dc5a39eed8c8811d7b2a25de390302c1
https://doi.org/10.1115/icef2022-88851
https://doi.org/10.1115/icef2022-88851
Publikováno v:
IEEE Transactions on Vehicular Technology. 70:8682-8691
Many autonomous vehicles and advanced driver-assistance systems are equipped with front-facing cameras that detect and track objects using deep-learning-based algorithms. However, the localization capability of monocular cameras is often overlooked.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::af7903a631be36764c2d33b688a34051
https://doi.org/10.1109/tvt.2021.3097589
https://doi.org/10.1109/tvt.2021.3097589
Publikováno v:
2022 IEEE Transportation Electrification Conference & Expo (ITEC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a9f73af10939354ec85c1889f603de3b
https://doi.org/10.1109/itec53557.2022.9813980
https://doi.org/10.1109/itec53557.2022.9813980