کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4971820 | 1450536 | 2016 | 5 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
DRES: Data recovery for condition monitoring to enhance system reliability
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
سخت افزارها و معماری
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
The system reliability depends heavily on the sensed condition data which are mainly collected by various types of sensors. The missing or faulty condition data can result in wrong decision-making or lead to system fault. To realize data integrity for system condition monitoring, one data-driven framework for recovering condition data is proposed in this article. The proposed model is combined by mutual information and Multivariable Linear Regression (MLR). The correlations among condition monitoring data sets are firstly analysed by mutual information. Then, MLR is utilized to recover condition monitoring data. A case study of aircraft engine condition monitoring data sets which are offered by National Aeronautics and Space Administration Ames Research Center is carried out to evaluate the performance of the data-driven framework.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Microelectronics Reliability - Volume 64, September 2016, Pages 125-129
Journal: Microelectronics Reliability - Volume 64, September 2016, Pages 125-129
نویسندگان
Liansheng Liu, Dawei Pan, Datong Liu, Yujie Zhang, Yu Peng,