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Data-Driven Remaining Useful Life Prognosis Techniques: Stochastic Models, Methods and Applications - Springer Series in Reliability Engineering Xiao-Sheng Si 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, 20 black & white illustrations, 84 colour illustrations, biography
| Medios de comunicación | Libros Hardcover Book (Libro con lomo y cubierta duros) |
| Publicado | 9 de febrero de 2017 |
| ISBN13 | 9783662540282 |
| Editores | Springer-Verlag Berlin and Heidelberg Gm |
| Páginas | 430 |
| Dimensiones | 155 × 235 × 25 mm · 802 g |
| Lengua | Francés |
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