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Akademický článek
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Autor:
Amrinder Singh Minhas, Ravinder Kumar, Sukhjeet Singh, Pavan Kumar Kankar, Arman Malhotra, Ming J. Zuo
Publikováno v:
Materials Today: Proceedings. 43:629-635
For fault detection of bearings to avoid unexpected downtime in rotating machinery (RM), their monitoring is continuously required. Whenever a fault develops in any of the rotating machinery components, the characteristics vibration signature of such
Akademický článek
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Publikováno v:
IEEE Transactions on Industrial Informatics. 16:4949-4960
The critical issue for fault diagnosis of wheel-set bearings in high-speed trains is to extract fault features from vibration signals. To handle high complexity, strong coupling, and low signal-to-noise ratio of the vibration signals, this article pr
Publikováno v:
Structural Health Monitoring. 19:1471-1486
Railway faults are usually observed as impulses in the vibration signal, but they are mostly immersed in noise. To effectively remove noise and identify the impulses, an improved morphological filter is proposed in this article. The proposal focuses
Autor:
Yuejian Chen, Ming J. Zuo
Publikováno v:
Mechanical Systems and Signal Processing. 167:108539
Gearboxes often operate under variable speed condition which makes the collected vibration signal, a widely employed type of condition monitoring data, becomes non-stationary. This paper proposes a sparse linear parameter varying vector auto-regressi
Publikováno v:
Mechanical Systems and Signal Processing. 165:108327
Diagnosis of gearbox tooth cracks at an early stage is important to prevent catastrophic failures. The time synchronous average (TSA) of vibration signals of gearboxes with a tooth crack mainly consists of the gear meshing frequency (GMF) and its har
Publikováno v:
Journal of Sound and Vibration. 432:119-132
Frequency contents have been widely investigated to understand the vibration behaviors of planetary gearboxes. Appearances of certain sideband peaks in the frequency spectrum may indicate the occurrence of gear fault. However, analyzing too many side
Publikováno v:
Mechanical Systems and Signal Processing. 109:166-184
This paper presents a signal processing scheme, namely enhanced morphology gradient product filter (EMGPF), for rolling element bearing fault detection. In this scheme, a morphology gradient product operation (MGPO) is firstly proposed to extract imp
Publikováno v:
Journal of Sound and Vibration. 431:192-211
To achieve planetary gearbox fault classification, vibration signal analysis has been widely employed with rich information about the health status and easy measurement. It is critical to extract features with enough health status information for fau