The emphasis of the book is on the shastic models, methods and applications employed in remaining useful life prognosis. It includes a wealth of degradation monitoring experiment data, practical prognosis methods for remaining useful life in various cases, and a series of applications incorporated into prognostic information in decision-making, such as maintenance-related decisions and ordering spare parts. It also highlights the latest advances in data-driven remaining useful life prognosis techniques, especially in the contexts of adaptive prognosis for linear shastic degrading systems, nonlinear degradation modeling based prognosis, residual storage life prognosis, and prognostic information-based decision-making.
The emphasis of the book is on the shastic models, methods and applications employed in remaining useful life prognosis. It includes a wealth of degradation monitoring experiment data, practical prognosis methods for remaining useful life in various cases, and a series of applications incorporated into prognostic information in decision-making, such as maintenance-related decisions and ordering spare parts. It also highlights the latest advances in data-driven remaining useful life prognosis techniques, especially in the contexts of adaptive prognosis for linear shastic degrading systems, nonlinear degradation modeling based prognosis, residual storage life prognosis, and prognostic information-based decision-making.
Data-Driven Remaining Useful Life Prognosis Techniques: Stochastic Models, Methods and Applications
430Data-Driven Remaining Useful Life Prognosis Techniques: Stochastic Models, Methods and Applications
430Hardcover(1st ed. 2017)
Product Details
ISBN-13: | 9783662540282 |
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Publisher: | Springer Berlin Heidelberg |
Publication date: | 02/03/2017 |
Series: | Springer Series in Reliability Engineering |
Edition description: | 1st ed. 2017 |
Pages: | 430 |
Product dimensions: | 6.10(w) x 9.25(h) x (d) |