Data-Driven Remaining Useful Life Prognosis Techniques: Stochastic Models, Methods and Applications
Data-Driven Remaining Useful Life Prognosis Techniques: Stochastic Models, Methods and Applications by Xiao-Sheng Si
English | PDF,EPUB | 2017 | 436 Pages | ISBN : 3662540282 | 23.8 MB
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.
Please Please :( We Are Here For You And Without You And Your Support We Can’t Continue
Thanks For Buying Premium From My Links For Support
Thanks For Buying Premium From My Links For Support
i will be very grateful when you support me and buy Or Renew Your Premium from my Blog links
i appreciate your support Too much as it will help me to post more and more
Without You And Your Support We Can’t Continue
Thanks For Buying Premium From My Links For Support
i appreciate your support Too much as it will help me to post more and more
Without You And Your Support We Can’t Continue
Thanks For Buying Premium From My Links For Support