Data-driven remaining useful life prognosis techniques : stochastic models, methods and applications

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...

Full description

Saved in:
Bibliographic Details
Main Authors Si, Xiao-Sheng (Author), Zhang, Zheng-Xin (Author), Hu, Chang-Hua (Author)
Format Electronic eBook
LanguageEnglish
Published Berlin, Germany : Springer, 2017.
SeriesSpringer series in reliability engineering.
Subjects
Service life (Engineering) > Mathematical models.
Economic life of fixed assets.
elektronické knihy
electronic books
Online AccessFull text
ISBN9783662540305
9783662540282
ISSN1614-7839
Physical Description1 online resource

Cover

Table of Contents:
  • 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.

Similar Items