Data-Driven Remaining Useful Life Prognosis Techniques: Stochastic Models, Methods and Applications - Springer Series in Reliability Engineering - Xiao-Sheng Si - Knjige - Springer-Verlag Berlin and Heidelberg Gm - 9783662571736 - 13. julija 2018
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Data-Driven Remaining Useful Life Prognosis Techniques: Stochastic Models, Methods and Applications - Springer Series in Reliability Engineering Softcover reprint of the original 1st ed. 2017 edition

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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.


430 pages, 84 Illustrations, color; 20 Illustrations, black and white; XVII, 430 p. 104 illus., 84 i

Medij Knjige     Paperback Book   (Knjiga z mehkimi platnicami in lepljenim hrbtom)
Izdano 13. julija 2018
ISBN13 9783662571736
Založniki Springer-Verlag Berlin and Heidelberg Gm
Strani 430
Dimenzije 150 × 220 × 10 mm   ·   625 g
Jezik Nemščina  

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