Results 201 to 210 of about 25,726 (266)

Cross-Condition Tool Wear State Monitoring via Multi-Source Sensor Signal Fusion and Supervised Transfer Learning. [PDF]

Sensors (Basel)
Huang Y, Lu X, Zhang D.
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Temporal and Behaviour-Aware Multimodal Modelling for Hour-Ahead Hypoglycaemia Prediction During Ramadan Fasting in Type 1 Diabetes. [PDF]

Sensors (Basel)
Alkhateeb M, AlSaad R, Brahim Belhaouari S, Aziz S, Ahmed A, Ali H, Al-Mohanadi D, Mohamud K, Al-Naimi N, Alsaud A, Al-Sharshani H, Sheikh JI, Baagar K, Abd-Alrazaq A.   +13 more
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Study on D6AC Steel PCBN Hard Turning and Optimization. [PDF]

Materials (Basel)
Liu Y, Huang S, Li R, Cui Z, Zhang Y, Liu C.   +5 more
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Physics-Informed Monotonic Conformer for Remaining Useful Life Prediction of Hydraulic Systems. [PDF]

Sensors (Basel)
He X, Zhang C, Wang J, Zhao X, Yao J, Lu C, Yang X.   +6 more
europepmc   +1 more source

Analysis of the Influence of the Outlet Slot on the Distribution of the Product as a Method of Assessing the Quality of Jaw Crusher Operation. [PDF]

Materials (Basel)
Ciężkowski P, Stankiewicz J, Bąk S, Chiliński B, Caban J.   +4 more
europepmc   +1 more source

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On Prediction of Wear Coefficients in Sliding Wear

A S L E Transactions, 1983
The wear rates and wear coefficients of metals are analytically predicted based on the delamination theory of wear when the wear rates are controlled by the subsurface crack propagation rate. The wear rate and the wear coefficient are predicted to be directly proportional to the depth of crack location and the crack growth rate. The numerical values of
N. P. Suh, H.-C. Sin
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On the Prediction of Transient Wear

Journal of Tribology, 2016
During the running-in process, a friction pair experiences drastic evolution in many of its tribological parameters, such as surface roughness, wear rate, and coefficient of friction until steady-state is attained. In this paper, we present a model for predicting the behavior of the running-in process.
Vahid Mortazavi, M. M. Khonsari
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Wear prediction of ceramics

Wear, 2004
Abstract Advanced ceramics are increasingly being used for wear applications. Wear prediction of ceramics has become an important subject in these arenas. Ceramic wear is a complex function of microstructure, grain size and shape, grain boundary toughness, and the operating conditions.
S.M. Hsu, Ming Shen
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