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Multiscale analysis of the effect of debris on fretting wear process using a semi-concurrent method [PDF]
, 2020 Fretting wear is a phenomenon, in which wear happens between two oscillatory moving contact surfaces in microscale amplitude. In this paper, the effect of debris between pad and specimen is analyzed by using a semi-concurrent multiscale method.
Abdel Wahab, Magd +2 more
core +1 more source
Tribological Properties of Brake Disc Material for a High-Speed Train and the Evolution of Debris
Lubricants, 2022 The stability and reliability of braking system are essential factors for the safe operation of high-speed trains. In the proposed work, tribological properties of a newly developed brake disc material namely BD-1 were studied considering the thermal ...
Jinnan Wang +6 more
doaj +1 more source
A numerical study on the effect of debris layer on frettingwear [PDF]
, 2016 Fretting wear is the material damage of two contact surfaces caused by micro relative displacement. Its characteristic is that debris is trapped on the contact surfaces.
Abdel Wahab, Magd, Yue, Tongyan
core +3 more sources
Review on online inductive wear debris monitoring technology
The Journal of Engineering, 2019 Online oil monitoring technique is now an important development means to monitor wear condition and diagnose wear fault real time. Inductive wear debris monitoring is the research hotspot in the current online oil monitoring for its unique ...
Tao Chen +4 more
doaj +1 more source
Sensors, 2019 Through real-time acquisition of the visual characteristics of wear debris in lube oil, an on-line visual ferrograph (OLVF) achieves online monitoring of equipment wear in practice.
Leng Han +5 more
doaj +1 more source
Image Denoising and Feature Extraction of Wear Debris for Online Monitoring of Planetary Gearboxes
IEEE Access, 2021 Wear debris generated in a pitting process of planetary gearboxes carries valuable information about health status. However, RGB images of online wear debris are often affected by image blur caused by Gaussian noise, high-frequency noise, and other ...
Wei Cao +6 more
doaj +1 more source
Integrated model of BP neural network and CNN algorithm for automatic wear debris classification
Wear, 2019 Mechanism-based wear debris classification (WDC) is important for root cause analysis and prediction of wear related faults. Compared to manual classifications, automatic WDC is more efficient and often more reliable for a wide range of industrial ...
Shuo Wang +3 more
semanticscholar +1 more source
The gearbox wears state monitoring and evaluation based on on-line wear debris features
Wear, 2019 The teeth of planetary gear trains are prone to wear and can be damaged. In traditional wear monitoring, the equipment needs to be disassembled, and the efficiency is low. The wear debris in lubricating oil can provide information about machine wear.
W. Cao +4 more
semanticscholar +1 more source
Effect of Impact Block Shape and Material on Impact Wear Behavior of Zr-4 Alloy Cladding Tube
Metals, 2022 In a pressurized water reactor nuclear power plant, metal foreign matter in the rod–rod gap of the fuel assembly is constantly rubbed and collided with the fuel rod under continuous scouring of the coolant, resulting in wear to the fuel rod and even ...
Shijia Yu +6 more
doaj +1 more source
Sensors, 2018 Leakage is the most important failure mode in aircraft hydraulic systems caused by wear and tear between friction pairs of components. The accurate detection of abrasive debris can reveal the wear condition and predict a system’s lifespan.
Tongyang Li +4 more
doaj +1 more source