Zobrazeno 1 - 10
of 53
pro vyhledávání: '"Gaofeng He"'
Publikováno v:
IEEE Access, Vol 12, Pp 169467-169486 (2024)
In practical engineering, significant noise and amplitude fluctuations in bearing vibration data, hinder the accuracy of fault identification. In order to overcome these difficulties, reduce external interference, and accurately obtain effective bear
Externí odkaz:
https://doaj.org/article/7e7fc0cc12584ab19a4f2c610f116c59
Publikováno v:
Tongxin xuebao, Vol 43, Pp 156-170 (2022)
In order to solve the problem that excessive false positives in the detection of encrypted malicious traffic based on machine learning, secure two-party computation was used to compare character segments between network traffic and intrusion detectio
Externí odkaz:
https://doaj.org/article/716135ddd97e4ac18202a849b852d4d1
Publikováno v:
Axioms, Vol 12, Iss 9, p 814 (2023)
The phenomenon “bufferbloat” occurs when the buffers of the network intermediary nodes fill up, causing long queuing delays. This has a significant negative impact on the quality of service of network applications, particularly those that are sen
Externí odkaz:
https://doaj.org/article/624b842854904c8fb0fe25ec80a72875
Publikováno v:
IEEE Access, Vol 7, Pp 29520-29532 (2019)
Minimum entropy deconvolution (MED) is widely used in the gearbox fault diagnosis because it can enhance the energy of the impact signal. However, it is sensitive to single abnormal impulsive oscillation. This is because it takes kurtosis as the obje
Externí odkaz:
https://doaj.org/article/5ccba95870274225adbc23c701d23f13
Autor:
Zhijian Wang, Gaofeng He, Wenhua Du, Jie Zhou, Xiaofeng Han, Jingtai Wang, Huihui He, Xiaoming Guo, Junyuan Wang, Yanfei Kou
Publikováno v:
IEEE Access, Vol 7, Pp 44871-44882 (2019)
The selection of variational mode decomposition (VMD) parameters usually adopts the empirical method, trial-and-error method, or single-objective optimization method. The above-mentioned method cannot achieve the global optimal effect. Therefore, a m
Externí odkaz:
https://doaj.org/article/845ae29d818549f9a88d7970da6ec68e
Autor:
Zhijian Wang, Junyuan Wang, Wenan Cai, Jie Zhou, Wenhua Du, Jingtai Wang, Gaofeng He, Huihui He
Publikováno v:
Complexity, Vol 2019 (2019)
In industrial production, it is highly essential to extract faults in gearbox accurately. Specifically, in a strong noise environment, it is difficult to extract the fault features accurately. LMD (local mean decomposition) is widely used as an adapt
Externí odkaz:
https://doaj.org/article/44b835af037845749697e56540ea6389
Autor:
Zhijian Wang, Likang Zheng, Wenhua Du, Wenan Cai, Jie Zhou, Jingtai Wang, Xiaofeng Han, Gaofeng He
Publikováno v:
Complexity, Vol 2019 (2019)
In the era of big data, data-driven methods mainly based on deep learning have been widely used in the field of intelligent fault diagnosis. Traditional neural networks tend to be more subjective when classifying fault time-frequency graphs, such as
Externí odkaz:
https://doaj.org/article/7e6660be0b814d92a261a730594c69a2
Publikováno v:
International Journal of Distributed Sensor Networks, Vol 14 (2018)
Mobile application (simply “app”) identification at a per-flow granularity is vital for traffic engineering, network management, and security practices. However, uncertainty is caused by a growing fraction of encrypted traffic such as Hypertext T
Externí odkaz:
https://doaj.org/article/5a5acbfb927044c4b6023ce15609d891
Autor:
Jie Zhou, Xiaoming Guo, Zhijian Wang, Wenhua Du, Junyuan Wang, Xiaofeng Han, Jingtai Wang, Gaofeng He, Huihui He, Huiling Xue, Yanfei Kou
Publikováno v:
Entropy, Vol 21, Iss 4, p 400 (2019)
In recent years, a new method of fault diagnosis, named variational mode decomposition (VMD), has been widely used in industrial production, but the decomposition accuracy of VMD is determined by two parameters, which are respectively the decompositi
Externí odkaz:
https://doaj.org/article/915bdd407a254da1b8cef70956b4fa5f
Autor:
Gaofeng He, Bingfeng Xu
Publikováno v:
International Journal of Safety and Security Engineering. 11:663-669
State/Event Fault Tree (SEFT) can be used for safety modeling and assessment. However, SEFT does not provide adequate semantics for analyzing the minimal scenarios leading to system failures. In this paper, we propose a novel qualitative analysis met
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7e5dfd170000ac0995385012b57932f4
https://doi.org/10.18280/ijsse.110606
https://doi.org/10.18280/ijsse.110606