Data Driven Remaining Useful Life Prognosis Techniques

Download or Read online Data Driven Remaining Useful Life Prognosis Techniques full in PDF, ePub and kindle. This book written by Xiao-Sheng Si and published by Springer which was released on 20 January 2017 with total pages 430. We cannot guarantee that Data Driven Remaining Useful Life Prognosis Techniques book is available in the library, click Get Book button to download or read online books. Join over 650.000 happy Readers and READ as many books as you like.

Data Driven Remaining Useful Life Prognosis Techniques
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Publisher : Springer
Release Date :
ISBN : 9783662540305
Pages : 430 pages
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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. It is also the first book that describes the basic data-driven remaining useful life prognosis theory systematically and in detail. The emphasis of the book is on the stochastic 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 stochastic degrading systems, nonlinear degradation modeling based prognosis, residual storage life prognosis, and prognostic information-based decision-making.

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Data Driven Remaining Useful Life Prognosis Techniques

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