Remaining useful life prediction based on state assessment using edge computing on deep learning

Hsin Yao Hsu, Gautam Srivastava, Hsin Te Wu, Mu Yen Chen

研究成果: Article同行評審

21 引文 斯高帕斯(Scopus)

摘要

Intelligent industrial production has recently emerged as an important trend for application of the Industrial Internet of Things (IIoT) in edge computing. This study applied remote edge devices and edge servers, preprocessing the signal sensor, through covert data to cloud storage, and loaded the data to propose several deep learning methods to assess the status of aircraft engines in operation, and to classify stages of operational degradation so as to predict the functional remaining lifespan of components. The predicted results are transmitted to a cloud-based server for monitoring and maintenance.

原文English
頁(從 - 到)91-100
頁數10
期刊Computer Communications
160
DOIs
出版狀態Published - 2020 7月 1

All Science Journal Classification (ASJC) codes

  • 電腦網路與通信

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