Data-Driven Remaining Useful Life Prognosis Techniques: Stochastic Models, Methods and Applications

Si, Xiao-Sheng (Author)/ Zhang, Zheng-Xin (Author)/ Hu, Chang-Hua (Author)

ISBN 10: 3662540282 / ISBN 13: 9783662540282

Edité par Springer, 2017

A propos de cet article

450 pages. 9.25x6.25x1.00 inches. In Stock. N° de réf. du vendeur x-3662540282

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Titre : Data-Driven Remaining Useful Life Prognosis ...

Éditeur : Springer

Date d'édition : 2017

Reliure : Hardcover

Etat : Brand New

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Synopsis :

Part I Introduction, Basic Concepts and Preliminaries.- Overview.- Advances in Data-Driven Remaining Useful Life Prognosis.- Model Determination for Lifetime Prognosis.- Part II Remaining Useful Life Prognosis for Linear Stochastic Degrading Systems.- Adaptive Remaining Useful Life Prediction Method.- Exact and Closed-Form Solution to Remaining Useful Life Prediction.- Remaining Useful Life Prediction With Three-Level Variability.- Part III Remaining Useful Life Prognosis for Nonlinear Stochastic Degrading Systems.- Nonlinear Degradation Modeling and Remaining Useful Life Prediction Method.- Hidden and Nonlinear Degradation Modeling and Online Remaining Useful Life Prediction Method.- Remaining Useful Life Prediction Method With State Switches.- Remaining Useful Life Prediction for Degrading Systems with Imperfect Maintenance.- Part IV Applications of Prognostics in Decision Making.- Variable Cost-based Maintenance Model from Prognostic Information.- Forecasting Spare Parts Demand under Prognostic Information.- Variable Cost-Based Maintenance and Inventory Model from Prognostic Information.- Prognostic-information-Based Order-Replacement Policy for Degrading Systems.