Téléchargez le livre : Data-Driven Remaining Useful Life Prognosis Techniques

Data-Driven Remaining Useful Life Prognosis Techniques

Stochastic Models, Methods and Applications de

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Éditeur :

Springer


Collection :

Springer Series in Reliability Engineering

Paru le : 2017-01-20

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Description

This book introduces data-driven remaining useful life prognosis techniques, and shows how to utilize the condition monitoring data to predict the remaining useful life of stochastic degrading systems and to schedule maintenance and logistics plans. It is also the first book that describes the basic data-driven remaining useful life prognosis theory systematically and in detail.
The emphasis of the book is on the stochastic models, methods and applications employed in remaining useful life prognosis. It includes a wealth of degradation monitoring experiment data, practical prognosis methods for remaining useful life in various cases, and a series of applications incorporated into prognostic information in decision-making, such as maintenance-related decisions and ordering spare parts. It also highlights the latest advances in data-driven remaining useful life prognosis techniques, especially in the contexts of adaptive prognosis for linear stochastic degrading systems, nonlinear degradation modeling based prognosis, residual storage life prognosis, and prognostic information-based decision-making.
Pages
430 pages
Collection
Springer Series in Reliability Engineering
Parution
2017-01-20
Marque
Springer
EAN papier
9783662540282
EAN PDF
9783662540305
Informations sur l'ebook
Nombre pages copiables
4
Nombre pages imprimables
43
Taille du fichier
15688 Ko
Prix
179,34 €
EAN EPUB
9783662540305
Informations sur l'ebook
Nombre pages copiables
4
Nombre pages imprimables
43
Taille du fichier
8673 Ko
Prix
179,34 €

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