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diff --git a/images/S0007850618300799.bib b/images/S0007850618300799.bib
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-@article{TAO2018169,
-title = {Digital twin driven prognostics and health management for complex equipment},
-journal = {CIRP Annals},
-volume = {67},
-number = {1},
-pages = {169-172},
-year = {2018},
-issn = {0007-8506},
-doi = {https://doi.org/10.1016/j.cirp.2018.04.055},
-url = {https://www.sciencedirect.com/science/article/pii/S0007850618300799},
-author = {Fei Tao and Meng Zhang and Yushan Liu and A.Y.C. Nee},
-keywords = {Maintenance, Condition monitoring, Digital twin},
-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.}
-}
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