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Data-Driven Remaining Useful Life Prognosis Techniques: Stochastic Models, Methods and Applications - Springer Series in Reliability Engineering Xiao-Sheng Si Softcover reprint of the original 1st ed. 2017 edition
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Data-Driven Remaining Useful Life Prognosis Techniques: Stochastic Models, Methods and Applications - Springer Series in Reliability Engineering
Xiao-Sheng Si
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
| Medios de comunicación | Libros Paperback Book (Libro con tapa blanda y lomo encolado) |
| Publicado | 13 de julio de 2018 |
| ISBN13 | 9783662571736 |
| Editores | Springer-Verlag Berlin and Heidelberg Gm |
| Páginas | 430 |
| Dimensiones | 150 × 220 × 10 mm · 625 g |
| Lengua | Alemán |
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