By Xiao-Sheng Si,Zheng-Xin Zhang,Chang-Hua Hu
This e-book introduces data-driven closing valuable existence analysis strategies, and indicates the right way to make the most of the tracking facts to foretell the remainder invaluable lifetime of stochastic degrading structures and to agenda upkeep and logistics plans. it's also the 1st ebook that describes the fundamental data-driven final worthwhile existence diagnosis conception systematically and intimately.
The emphasis of the booklet is at the stochastic types, tools and purposes hired in last worthwhile existence diagnosis. It contains a wealth of deterioration tracking scan information, useful analysis tools for ultimate precious existence in a variety of circumstances, and a chain of purposes integrated into prognostic details in decision-making, reminiscent of maintenance-related judgements and ordering spare components. It additionally highlights the most recent advances in data-driven closing valuable lifestyles analysis ideas, specifically within the contexts of adaptive diagnosis for linear stochastic degrading platforms, nonlinear degradation modeling established analysis, residual garage lifestyles diagnosis, and prognostic information-based decision-making.
Read or Download Data-Driven Remaining Useful Life Prognosis Techniques: Stochastic Models, Methods and Applications (Springer Series in Reliability Engineering) PDF
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Additional info 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