Data-Driven Remaining Useful Life Prognosis Techniques: Stochastic Models, Methods and Applications - Springer Series in Reliability Engineering - Xiao-Sheng Si - Books - Springer-Verlag Berlin and Heidelberg Gm - 9783662571736 - July 13, 2018
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Xiao-Sheng Si
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

Media Books     Paperback Book   (Book with soft cover and glued back)
Released July 13, 2018
ISBN13 9783662571736
Publishers Springer-Verlag Berlin and Heidelberg Gm
Pages 430
Dimensions 150 × 220 × 10 mm   ·   625 g
Language German  

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