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Digital twin driven prognostics and health management for complex equipment

  • Beihang University
  • National University of Singapore

Research output: Contribution to journalArticlepeer-review

Abstract

Prognostics and health management (PHM) is crucial in the lifecycle monitoring of a product, especially for complex equipment working in a harsh environment. In order to improve the accuracy and efficiency of PHM, digital twin (DT), an emerging technology to achieve physical–virtual convergence, is proposed for complex equipment. A general DT for complex equipment is first constructed, then a new method using DT driven PHM is proposed, making effective use of the interaction mechanism and fused data of DT. A case study of a wind turbine is used to illustrate the effectiveness of the proposed method.

Original languageEnglish
Pages (from-to)169-172
Number of pages4
JournalCIRP Annals
Volume67
Issue number1
DOIs
StatePublished - 1 Jan 2018

Keywords

  • Condition monitoring
  • Digital twin
  • Maintenance

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