Povej prijatelju o tem izdelku:
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
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
| 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 |