By Xiao-Sheng Si,Zheng-Xin Zhang,Chang-Hua Hu
This publication introduces data-driven last beneficial existence diagnosis thoughts, and exhibits how you can make the most of the situation tracking facts to foretell the rest beneficial lifetime of stochastic degrading platforms and to agenda upkeep and logistics plans. it's also the 1st booklet that describes the elemental data-driven ultimate invaluable existence analysis idea systematically and intimately.
The emphasis of the publication is at the stochastic versions, equipment and purposes hired in ultimate priceless lifestyles analysis. It contains a wealth of deterioration tracking scan information, functional diagnosis equipment for last beneficial lifestyles in a variety of instances, and a sequence of purposes integrated into prognostic info in decision-making, comparable to maintenance-related judgements and ordering spare elements. It additionally highlights the newest advances in data-driven closing worthwhile lifestyles analysis recommendations, specifically within the contexts of adaptive diagnosis for linear stochastic degrading structures, nonlinear degradation modeling established diagnosis, residual garage lifestyles analysis, and prognostic information-based decision-making.
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Additional resources for Data-Driven Remaining Useful Life Prognosis Techniques: Stochastic Models, Methods and Applications (Springer Series in Reliability Engineering)
Data-Driven Remaining Useful Life Prognosis Techniques: Stochastic Models, Methods and Applications (Springer Series in Reliability Engineering) by Xiao-Sheng Si,Zheng-Xin Zhang,Chang-Hua Hu