Remaining useful life prognostics for aeroengine based on superstatistics and information fusion

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.     

糖尿病肾病进展性生物标志物的研究现状与挑战

糖尿病肾病(Diabetic Kidney Disease, DKD)是糖尿病(Diabetes Mellitus, DM)患者发生终末期肾病和死亡的主要原因。对 DKD 患者进行预后评估有助于降低疾病进展的风险及减少并发症和死亡的发生。本综述主要讨论 DKD 进展性生物标志物的现状和研究进展，包括常用的白蛋白尿和肾小球滤过率(Glomerular Filtration Rate, GFR)，以及新型生物标志物如肿瘤坏死因子受体(Tumor Necrosis Factor Alpha Receptor, TNFR)和肾小管标志物等。同时，本文还对 DKD 进展性标志物的开发和应用存在的挑战进行了讨论。