โ Scribed by Xiao-Sheng Si, Zheng-Xin Zhang, Chang-Hua Hu (auth.)
No coin nor oath required. For personal study only.
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.
Front Matter....Pages i-xvii
Front Matter....Pages 1-1
Advances in Data-Driven RUL Prognosis Techniques....Pages 3-21
Planning Repeated Degradation Testing for Degrading Products....Pages 23-37
Specifying Measurement Errors for Required Lifetime Estimation Performance....Pages 39-69
Front Matter....Pages 71-71
An Adaptive Remaining Useful Life Estimation Approach with a Recursive Filter....Pages 73-102
An Exact and Closed-Form Solution to Degradation Path-Dependent RUL Estimation....Pages 103-142
Estimating RUL with Three-Source Variability in Degradation Modeling....Pages 143-180
Front Matter....Pages 181-181
RUL Estimation Based on a Nonlinear Diffusion Degradation Process....Pages 183-215
Prognostics for Age- and State-Dependent Nonlinear Degrading Systems....Pages 217-246
Adaptive Prognostic Approach via Nonlinear Degradation Modeling....Pages 247-271
Prognostics for Hidden and Age-Dependent Nonlinear Degrading Systems....Pages 273-311
Prognostics for Nonlinear Degrading Systems with Three-Source Variability....Pages 313-336
RSL Prediction Approach for Systems with Operation State Switches....Pages 337-360
Front Matter....Pages 361-361
Reliability Estimation Approach for PMS....Pages 363-392
A Real-Time Variable Cost-Based Maintenance Model....Pages 393-404
An Adaptive Spare Parts Demand Forecasting Method Based on Degradation Modeling....Pages 405-417
Variable Cost-Based Maintenance and Inventory Model....Pages 419-430
Quality Control, Reliability, Safety and Risk;Probability Theory and Stochastic Processes;Operation Research/Decision Theory;Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
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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
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