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دسته بندی:
داده های بزرگ - big data
سال انتشار:
2020
عنوان انگلیسی مقاله:
Model-based vehicular prognostics framework using Big Data architecture
ترجمه فارسی عنوان مقاله:
چارچوب پیش آگهی های وسایل نقلیه مبتنی بر مدل با استفاده از معماری داده های بزرگ
منبع:
Sciencedirect - Elsevier - Computers in Industry, 115 (2020) 103177: doi:10:1016/j:compind:2019:103177
نویسنده:
Alberto Petrillo, Antonio Picariello, Stefania Santini, Biagio Scarciello, Giancarlo Sperlí
چکیده انگلیسی:
Nowadays, the continuous technological advances allow designing novel Integrated Vehicle Health Man-agement (IVHM) systems to deal with strict safety regulations in the automotive field with the aim atimproving efficiency and reliability of automotive components. However, challenging issue, which arisesin this domain, is handling a huge amount of data that are useful for prognostic. To this aim, in thispaper we propose a cloud-based infrastructure, namely Automotive predicTOr Maintenance In Cloud(ATOMIC), for prognostic analysis that leverages Big Data technologies and mathematical models of bothnominal and faulty behaviour of the automotive components to estimate on-line the End-Of-Life (EOL)and Remaining Useful Life (EUL) indicators for the automotive systems under investigation. A case studybased on the Delphi DFG1596 fuel pump has been presented to evaluate the proposed prognostic method.Finally, we perform a benchmark analysis of the deployment configurations of ATOMIC architecture interms of scalability and cost.
Keywords:Model-based prognostic analysis | Big Data analysis | Cloud computing servicesa
قیمت: رایگان
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