Data-driven remaining useful life prognosis techniques : stochastic models, methods and applications / Xiao-Sheng Si, Zheng-Xin Zhang, Chang-Hua Hu.
Si, Xiao-Sheng, author.; Zhang, Zheng-Xin, author.; Hu, Chang-Hua, author.
2017
TA409.2
Available Online

Linked e-resources

Linked Resource Online Access
Concurrent users Unlimited
Authorized users Authorized users
Document Delivery Supplied Can lend chapters, not whole ebooks

Details

Title Data-driven remaining useful life prognosis techniques : stochastic models, methods and applications / Xiao-Sheng Si, Zheng-Xin Zhang, Chang-Hua Hu.
Author Si, Xiao-Sheng, author.
ISBN 9783662540305 (electronic book)
3662540304 (electronic book)
9783662540282
DOI https://doi.org/10.1007/978-3-662-54030-5
Published Berlin, Germany : Springer, 2017.
Language English
Description 1 online resource.
Other Standard Identifiers 10.1007/978-3-662-54030-5 doi
Call Number TA409.2
Dewey Decimal Classification 658.5
Summary 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.
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Digital File Characteristics text file PDF
Source of Description Online resource; title from PDF title page (SpringerLink, viewed February 9, 2017).
Added Author Zhang, Zheng-Xin, author.
Hu, Chang-Hua, author.
Series Springer series in reliability engineering.
Available in Other Form Print version: 9783662540282
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
All Resources
From the Contents: Part I Introduction, Basic Concepts and Preliminaries
Overview
Advances in Data-Driven Remaining Useful Life Prognosis
Part II Remaining Useful Life Prognosis for Linear Stochastic Degrading Systems
Part III Remaining Useful Life Prognosis for Nonlinear Stochastic Degrading Systems
Part IV Applications of Prognostics in Decision Making
Variable Cost-based Maintenance Model from Prognostic Information.

Browse Subjects

Show more subjects...

Statistics

from
to
Export