Zobrazeno 1 - 10
of 44
pro vyhledávání: '"Jianliang He"'
Publikováno v:
Chinese Journal of Mechanical Engineering, Vol 36, Iss 1, Pp 1-17 (2023)
Abstract Deployable mechanism with preferable deployable performance, strong expansibility, and lightweight has attracted much attention because of their potential in aerospace. A basic deployable pyramid unit with good deployability and expandabilit
Externí odkaz:
https://doaj.org/article/cfb6494947d04733a1de47bfdb532d0a
Publikováno v:
IEEE Access, Vol 9, Pp 135285-135303 (2021)
Recently, data-driven remaining useful life (RUL) prediction has become a promising tool in prognostics and health management for rolling bearings. In many actual applications, however, it is not easy to collect whole-life degradation data of bearing
Externí odkaz:
https://doaj.org/article/1e2eda25372148fcad1e8440fd8eeb56
Publikováno v:
AIP Advances, Vol 12, Iss 2, Pp 025321-025321-11 (2022)
The tracking range and pointing performance of the antenna are important indices to measure the antenna system. First, the 3 degree of freedom parallel mechanism is proposed for the supporting mechanism of the antenna. The trajectory tracking princip
Externí odkaz:
https://doaj.org/article/f7e0c64b298a4de4bc8b777692d8ff1a
A UAV Maneuver Decision-Making Algorithm for Autonomous Airdrop Based on Deep Reinforcement Learning
Publikováno v:
Sensors, Vol 21, Iss 6, p 2233 (2021)
How to operate an unmanned aerial vehicle (UAV) safely and efficiently in an interactive environment is challenging. A large amount of research has been devoted to improve the intelligence of a UAV while performing a mission, where finding an optimal
Externí odkaz:
https://doaj.org/article/f22d2ee3c6fe432f814b9559c821e266
Publikováno v:
Entropy, Vol 22, Iss 3, p 279 (2020)
To improve the effectiveness of air combat decision-making systems, target intention has been extensively studied. In general, aerial target intention is composed of attack, surveillance, penetration, feint, defense, reconnaissance, cover and electro
Externí odkaz:
https://doaj.org/article/533f67f0747141dc8db1990012d95b97
Publikováno v:
Advances in Mechanical Engineering, Vol 10 (2018)
For bearing remaining useful life prediction problem, the traditional machine-learning-based methods are generally short of feature representation ability and incapable of adaptive feature extraction. Although deep-learning-based remaining useful lif
Externí odkaz:
https://doaj.org/article/54dd48069e064764ac06f436397048c3
Publikováno v:
Environmental Science & Technology; 7/30/2024, Vol. 58 Issue 30, p13327-13336, 10p
Publikováno v:
Journal of Intelligent Manufacturing.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::66e5afc27dd8b83cb7af6571e05d8884
https://doi.org/10.1007/s10845-022-02005-z
https://doi.org/10.1007/s10845-022-02005-z
Publikováno v:
IEEE Access, Vol 9, Pp 135285-135303 (2021)
Recently, data-driven remaining useful life (RUL) prediction has become a promising tool in prognostics and health management for rolling bearings. In many actual applications, however, it is not easy to collect whole-life degradation data of bearing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c02af6ec99faeafbdd103f0835d25b21
https://ieeexplore.ieee.org/document/9555648/
https://ieeexplore.ieee.org/document/9555648/
Publikováno v:
IEEE Transactions on Instrumentation and Measurement. 69:1594-1608
For the data-driven remaining useful life (RUL) prediction for rolling bearings, the traditional machine learning-based methods generally provide insufficient feature representation and adaptive extraction. Although deep learning-based RUL prediction
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b457f858378798039ac197fcbacb8f9e
https://doi.org/10.1109/tim.2019.2917735
https://doi.org/10.1109/tim.2019.2917735