Data-Driven Remaining Useful Life Prognosis Techniques (Record no. 80022)

000 -LEADER
fixed length control field 03939nam a22005895i 4500
001 - CONTROL NUMBER
control field 978-3-662-54030-5
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220801221746.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 170201s2017 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783662540305
-- 978-3-662-54030-5
082 04 - CLASSIFICATION NUMBER
Call Number 621
100 1# - AUTHOR NAME
Author Si, Xiao-Sheng.
245 10 - TITLE STATEMENT
Title Data-Driven Remaining Useful Life Prognosis Techniques
Sub Title Stochastic Models, Methods and Applications /
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2017.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XVII, 430 p. 104 illus., 84 illus. in color.
490 1# - SERIES STATEMENT
Series statement Springer Series in Reliability Engineering,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 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.
520 ## - SUMMARY, ETC.
Summary, etc 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.
700 1# - AUTHOR 2
Author 2 Zhang, Zheng-Xin.
700 1# - AUTHOR 2
Author 2 Hu, Chang-Hua.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-662-54030-5
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Berlin, Heidelberg :
-- Springer Berlin Heidelberg :
-- Imprint: Springer,
-- 2017.
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-- text
-- txt
-- rdacontent
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-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Security systems.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Probabilities.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Operations research.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Statistics .
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Security Science and Technology.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Probability Theory.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Operations Research and Decision Theory.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 2196-999X
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-- ZDB-2-ENG
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-- ZDB-2-SXE

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