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Wyszukujesz frazę "Wu, Gang" wg kryterium: Autor


Wyświetlanie 1-3 z 3
Tytuł:
An experimental study of the effects of cylinder lubricating oils on the vibration characteristics of a two-stroke low-speed marine diesel engine
Autorzy:
Wu, Gang
Jiang, Guodong
Chen, Changsheng
Jiang, Guohe
Pu, Xigang
Chen, Biwen
Powiązania:
https://bibliotekanauki.pl/articles/34603764.pdf
Data publikacji:
2023
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
two-stroke
low-speed marine diesel engine
cylinder lubricating oils
vibration characteristic
condition monitoring
Opis:
Two-stroke, low-speed diesel engines are widely used in large ships due to their good performance and fuel economy. However, there have been few studies of the effects of lubricating oils on the vibration of two-stroke, low-speed diesel engines. In this work, the effects of three different lubricating oils on the vibration characteristics of a low-speed engine are investigated, using the frequency domain, time-frequency domain, fast Fourier transform (FFT) and short-time Fourier transform (STFT) methods. The results show that non-invasive condition monitoring of the wear to a cylinder liner in a low-speed marine engine can be successfully achieved based on vibration signals. Both the FFT and STFT methods are capable of capturing information about combustion in the cylinder online in real time, and the STFT method also provides the ability to visualise the results with more comprehensive information. From the online condition monitoring of vibration signals, cylinder lubricants with medium viscosity and medium alkali content are found to have the best wear protection properties. This result is consistent with those of an elemental analysis of cylinder lubrication properties and an analysis of the data measured from a piston lifted from the cylinder after 300 h of engine operation.
Źródło:
Polish Maritime Research; 2023, 4; 92-101
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Hereditary Equality of Domination and Exponential Domination in Subcubic Graphs
Autorzy:
Chen, Xue-Gang
Wang, Yu-Feng
Wu, Xiao-Fei
Powiązania:
https://bibliotekanauki.pl/articles/32324524.pdf
Data publikacji:
2021-11-01
Wydawca:
Uniwersytet Zielonogórski. Wydział Matematyki, Informatyki i Ekonometrii
Tematy:
dominating set
exponential dominating set
subcubic graphs
Opis:
Let γ(G) and γe(G) denote the domination number and exponential domination number of graph G, respectively. Henning et al., in [Hereditary equality of domination and exponential domination, Discuss. Math. Graph Theory 38 (2018) 275–285] gave a conjecture: There is a finite set ℱ of graphs such that a graph G satisfies (H) = γe(H) for every induced subgraph H of G if and only if G is ℱ-free. In this paper, we study the conjecture for subcubic graphs. We characterize the class ℱ by minimal forbidden induced subgraphs and prove that the conjecture holds for subcubic graphs.
Źródło:
Discussiones Mathematicae Graph Theory; 2021, 41, 4; 1067-1075
2083-5892
Pojawia się w:
Discussiones Mathematicae Graph Theory
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An automated driving strategy generating method based on WGAIL–DDPG
Autorzy:
Zhang, Mingheng
Wan, Xing
Gang, Longhui
Lv, Xinfei
Wu, Zengwen
Liu, Zhaoyang
Powiązania:
https://bibliotekanauki.pl/articles/2055167.pdf
Data publikacji:
2021
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
automated driving system
deep learning
deep reinforcement learning
imitation learning
deep deterministic policy gradient
system jezdny
uczenie głębokie
uczenie przez naśladowanie
Opis:
Reliability, efficiency and generalization are basic evaluation criteria for a vehicle automated driving system. This paper proposes an automated driving decision-making method based on the Wasserstein generative adversarial imitation learning–deep deterministic policy gradient (WGAIL–DDPG(λ)). Here the exact reward function is designed based on the requirements of a vehicle’s driving performance, i.e., safety, dynamic and ride comfort performance. The model’s training efficiency is improved through the proposed imitation learning strategy, and a gain regulator is designed to smooth the transition from imitation to reinforcement phases. Test results show that the proposed decision-making model can generate actions quickly and accurately according to the surrounding environment. Meanwhile, the imitation learning strategy based on expert experience and the gain regulator can effectively improve the training efficiency for the reinforcement learning model. Additionally, an extended test also proves its good adaptability for different driving conditions.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2021, 31, 3; 461--470
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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