Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Xunkai Wei"'
Publikováno v:
Measurement + Control, Vol 57 (2024)
Small and imbalanced fault samples have a profound impact on the diagnostic performance of a model in the process of locating and quantifying the rolling bearing damage of aeroengines in practice. Therefore, a Siamese Convolutional Neural Network-Bid
Externí odkaz:
https://doaj.org/article/13948f9d713d47f98d75f1f8e3739bcb
Publikováno v:
Applied Sciences, Vol 14, Iss 13, p 5405 (2024)
The flight service environment spectrum is essential to the evaluation of the life of components in aeroengines; however, real altitude, as an important flight parameter, introduces considerable challenges when compiling the service environment spect
Externí odkaz:
https://doaj.org/article/1883030ddaf74abbad03308d22e46ae5
Publikováno v:
Applied Sciences, Vol 14, Iss 12, p 5072 (2024)
The prediction of spalling failure evolution in the lifespan of aeroengine bearings is crucial for en-suring the safe return of aircrafts after such failures occur. This study examines the spalling failure evolution process in bearings by integrating
Externí odkaz:
https://doaj.org/article/42f368cdd0724d45a2e6fa0a981c693f
Publikováno v:
Sensors, Vol 23, Iss 18, p 8013 (2023)
To address the problem of low fault diagnosis accuracy caused by insufficient fault samples of rolling bearings, a dual-input deep anomaly detection method with zero fault samples is proposed for early fault warning of rolling bearings. First, the ma
Externí odkaz:
https://doaj.org/article/d9111d7784674048b44ea1f02e797f86
Publikováno v:
Applied Sciences, Vol 13, Iss 16, p 9435 (2023)
Compared to maximum state parameters, such as maximum altitude and Mach, the number of hovers and S turns can be used as process parameters representing the complexity of military aircraft maneuvers when classifying big flight mission data to compile
Externí odkaz:
https://doaj.org/article/4260142c742e41da892a75aec38b8e0d
Publikováno v:
Advances in Mechanical Engineering, Vol 14 (2022)
Aiming at the problem of remaining useful life prediction of rolling bearing in aero engine, a data-driven prediction method based on deep learning and particle filter is proposed. Initially, only the vibration data of rolling bearing in normal stage
Externí odkaz:
https://doaj.org/article/d661440becb34ddfb5f92c1b732eb6fd
Publikováno v:
Materials, Vol 16, Iss 6, p 2386 (2023)
M50 bearing steel has great potential for applications in the field of aerospace engineering, as it exhibits outstanding mechanical and physical properties. From a microscopic point of view, bearing wear originates from the microscopic region of the
Externí odkaz:
https://doaj.org/article/376cbf8a67e6499aa514f5a922e6c6e0
Publikováno v:
Machines, Vol 10, Iss 3, p 199 (2022)
Fatigue failure usually occurs on the subsurface in rolling bearings due to multiaxial and non-proportional fatigue loadings between rolling elements. One of the main stress components is the alternating shear stress. This paper focuses on the microm
Externí odkaz:
https://doaj.org/article/a4e4173146344dc69214b202b0fc370c
Akademický článek
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Publikováno v:
International Journal of Electrochemical Science. Jun2024, Vol. 19 Issue 6, p1-15. 15p.