Results 221 to 230 of about 3,281,484 (268)

Growth Performance, Milk Productivity, Productive Longevity, and Milk Composition of Mugalzhar Horses. [PDF]

Animals (Basel)
Toishimanov M, Alikhanov O, Aubakirov K, Karibayeva D, Kargaeva M, Sapakhova Z, Begaliyeva D, Kanat R, Tugunova Y, Daurov D, Daurova A, Zhambakin K, Shamekova M, Baimukanov D.   +13 more
europepmc   +1 more source

Impact of Generalized Order Statistics and Its Dual on Entropy Estimation for the Exponentiated Generalized Pham Distribution: Theory and Applications. [PDF]

Entropy (Basel)
Kalantan ZI, Binhimd SMS, Abd Al-Fattah AM, Ahmed AA, Al-Dayian GR, El-Helbawy AA, Abd Elaal MK.   +6 more
europepmc   +1 more source

Helium spin-echo as a surface-sensitive probe of vibrational energy dissipation.

Faraday Discuss
Tamtögl A, Ellis J, Allison W, Sabik A, Antczak G, Jardine AP.   +5 more
europepmc   +1 more source

Remaining-useful-lifetime and system-remaining-profit based importance measures for decisions on preventive maintenance

Reliability Engineering and System Safety, 2021
Abstract We propose two types of importance measures for component selection in preventive maintenance. The first type evaluates the relative importance of a component in terms of how much the component restoration increases the remaining useful lifetime of the system. The second type of importance measures evaluates the contribution of a maintenance
Emanuele Borgonovo, Xiaoyan Zhu
exaly   +5 more sources

Remaining useful lifetime estimation and noisy gamma deterioration process

Reliability Engineering and System Safety, 2016
In many industrial issues where safety, reliability, and availability are considered of first importance, the lifetime prediction is a basic requirement. In this paper, by developing a prognostic probabilistic approach, a remaining lifetime distribution is associated to the system or component under consideration.
Khanh LE SON, Mitra Fouladirad, Anne Barros   +2 more
exaly   +5 more sources

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Remaining Useful Lifetime Estimation with Sobolev Training

2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 2020
Remaining useful lifetime (RUL) estimation of engineering assets is of great importance in an efficient operation of a production system. This paper deals with the RUL estimation with deep convolutional neural networks (DCNN) of bearings being operated in different load conditions by measuring the horizontal and vertical vibration.
Gavneet Singh Chadha, S. M. Nazmus Sakeib, Andreas Schwung   +2 more
openaire   +2 more sources

Generalized dilation convolutional neural networks for remaining useful lifetime estimation

Neurocomputing, 2021
Abstract In this paper, we present a novel approach for multivariate time series data analysis with special emphasis on industrial sensor data sets. The approach applies deep convolutional neural networks as a base architecture, incorporating a generalization of the dilated convolution operation on the receptive fields.
Gavneet Singh Chadha, Utkarsh Panara, Andreas Schwung, Steven X. Ding   +3 more
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Prediction of Remaining Useful Lifetime of Membrane Using Machine Learning

Science of Advanced Materials, 2020
We present a novel analytical procedure estimating the remaining useful life (RUL) of complex systems or facilities based on degradation data obtained over time; we consider the maintenance characteristics of units that are incompletely repaired.
Dong-Yeon Won, Hyun Su Sim, Yong Soo Kim
openaire   +1 more source