Data-Driven Remaining Useful Life Prognosis Techniques

Stochastic Models, Methods and Applications

By: Chang-Hua Hu, Zheng-Xin Zhang, Xiao-Sheng Si

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Paperback | 13 July 2018

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450 Pages

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23.5 x 15.5 x 2.31

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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.

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