近年来,国内围绕国际功能、残疾和健康分类(International Classification of Functioning,Disability and Health,ICF)临床应用方面的研究逐年增多[1—3],而《国际功能、残疾和健康分类(ICF)专家共识》的发表[4],又推动了ICF及其核心...近年来,国内围绕国际功能、残疾和健康分类(International Classification of Functioning,Disability and Health,ICF)临床应用方面的研究逐年增多[1—3],而《国际功能、残疾和健康分类(ICF)专家共识》的发表[4],又推动了ICF及其核心组合如康复组合(ICF rehabilitation set,ICF-RS)的临床应用及标准的编制[5—6]。本文仅就ICF及ICF-RS在国内的应用作一介绍,旨在进一步推动ICF及ICF-RS在国内临床的应用及研究。展开更多
Remaining useful life（RUL） prognostics is a fundamental premise to perform conditionbased maintenance（CBM） for a system subject to performance degradation. Over the past decades,research has been conducted in RUL ...Remaining useful life（RUL） prognostics is a fundamental premise to perform conditionbased maintenance（CBM） for a system subject to performance degradation. Over the past decades,research has been conducted in RUL prognostics for aeroengine. However, most of the prognostics technologies and methods simply base on single parameter, making it hard to demonstrate the specific characteristics of its degradation. To solve such problems, this paper proposes a novel approach to predict RUL by means of superstatistics and information fusion. The performance degradation evolution of the engine is modeled by fusing multiple monitoring parameters, which manifest non-stationary characteristics while degrading. With the obtained degradation curve,prognostics model can be established by state-space method, and then RUL can be estimated when the time-varying parameters of the model are predicted and updated through Kalman filtering algorithm. By this method, the non-stationary degradation of each parameter is represented, and multiple monitoring parameters are incorporated, both contributing to the final prognostics. A case study shows that this approach enables satisfactory prediction evolution and achieves a markedly better prognosis of RUL.展开更多
文摘近年来,国内围绕国际功能、残疾和健康分类(International Classification of Functioning,Disability and Health,ICF)临床应用方面的研究逐年增多[1—3],而《国际功能、残疾和健康分类(ICF)专家共识》的发表[4],又推动了ICF及其核心组合如康复组合(ICF rehabilitation set,ICF-RS)的临床应用及标准的编制[5—6]。本文仅就ICF及ICF-RS在国内的应用作一介绍,旨在进一步推动ICF及ICF-RS在国内临床的应用及研究。
基金co-supported by the State Key Program of National Natural Science of China (No. 61232002)the Joint Funds of the National Natural Science Foundation of China (No. 60939003)+3 种基金China Postdoctoral Science Foundation (Nos. 2012M521081, 2013T60537)the Fundamental Research Funds for the Central Universities of China (No. NS2014066)Postdoctoral Science Foundation of Jiangsu Province of China (No. 1301107C)Philosophy and Social Science Research Projects in Colleges and Universities in Jiangsu of China (No. 2014SJD041)
文摘Remaining useful life（RUL） prognostics is a fundamental premise to perform conditionbased maintenance（CBM） for a system subject to performance degradation. Over the past decades,research has been conducted in RUL prognostics for aeroengine. However, most of the prognostics technologies and methods simply base on single parameter, making it hard to demonstrate the specific characteristics of its degradation. To solve such problems, this paper proposes a novel approach to predict RUL by means of superstatistics and information fusion. The performance degradation evolution of the engine is modeled by fusing multiple monitoring parameters, which manifest non-stationary characteristics while degrading. With the obtained degradation curve,prognostics model can be established by state-space method, and then RUL can be estimated when the time-varying parameters of the model are predicted and updated through Kalman filtering algorithm. By this method, the non-stationary degradation of each parameter is represented, and multiple monitoring parameters are incorporated, both contributing to the final prognostics. A case study shows that this approach enables satisfactory prediction evolution and achieves a markedly better prognosis of RUL.
