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 - 9783662540282 - February 9, 2017
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Xiao-Sheng Si
Data-Driven Remaining Useful Life Prognosis Techniques: Stochastic Models, Methods and Applications - Springer Series in Reliability Engineering 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, 20 black & white illustrations, 84 colour illustrations, biography

Media Books     Hardcover Book   (Book with hard spine and cover)
Released February 9, 2017
ISBN13 9783662540282
Publishers Springer-Verlag Berlin and Heidelberg Gm
Pages 430
Dimensions 155 × 235 × 25 mm   ·   802 g
Language French  

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