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

• Main Authors: Si, Xiao-Sheng (Author), Zhang, Zheng-Xin (Author), Hu, Chang-Hua (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2017.
• Series: Springer Series in Reliability Engineering,
• Subjects: Engineering.; Operations research.; Decision making.; Probabilities.; Statistics.; Quality control.; Reliability.; Industrial safety.; 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.

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...