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Milling tool wear prediction using multi-sensor feature fusion based on stacked sparse autoencoders

Measurement: Journal of the International Measurement Confederation, 2022
Tielin Shi, Jianping Xuan
exaly  

Wear energy density for wear prediction of displaceable spline couplings

Tribologie und Schmierungstechnik
This study presents a comprehensive predictive methodology combining the Archard wear model, Kragelski’s molecular-mechanical fatigue theory, and Fleischer’s energetic wear framework to accurately forecast linear wear depth in displaceable spline couplings.
openaire   +1 more source

Vibration-based monitoring and prediction of surface profile change and pitting density in a spur gear wear process

Mechanical Systems and Signal Processing, 2022
Ke Feng, Wade A Smith, R B Randall
exaly  

Prediction of the impact wear of a valve

2016
The valves used in the oil&gas industry often experience erosion due to the impingements of solids dragged by the extracted fluid. The considerable economic damages related to this phenomenon enhance the interest in techniques for predicting the location of the erosion hotsposts and the loss of material from the valve under aggressive flow conditions ...
MESSA, GIANANDREA VITTORIO   +1 more
openaire   +1 more source

Tyre and road wear prediction

2003
Both tyre wear and road polishing are complex phenomenon, which are obviously strongly related; the energy that polishes the road is the energy that wears the tyre. The both depend non-linearly on numerous parameters, like materials used, vehicle and road usage, environmental conditions (i.e. temperature) and many others.
openaire   +1 more source

Gaussian process regression for tool wear prediction

Mechanical Systems and Signal Processing, 2018
Dongdong Kong, Yongjie Chen, Ning Li
exaly  

Tool wear prediction method based on symmetrized dot pattern and multi-covariance Gaussian process regression

Measurement: Journal of the International Measurement Confederation, 2022
exaly  

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