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| author | mjkwiatkowski <mati.rewa@gmail.com> | 2026-05-17 14:21:09 +0200 |
|---|---|---|
| committer | mjkwiatkowski <mati.rewa@gmail.com> | 2026-05-17 14:21:09 +0200 |
| commit | a5a140c6286e8b113ca8d371f88e3ed54e731cea (patch) | |
| tree | cd648c36df09d30c217166865a81a0c4e523932b /images | |
| parent | a4102d0252236e85b2813160b4b11e3a19a00d62 (diff) | |
feat: added lots of citations and slowly finishing the introduction
Diffstat (limited to 'images')
| -rw-r--r-- | images/S0007850618300799.bib | 14 | ||||
| -rw-r--r-- | images/five_dimensional_dt.pdf | bin | 0 -> 160459 bytes | |||
| -rw-r--r-- | images/introduction-digital-twin.png | bin | 0 -> 71741 bytes |
3 files changed, 14 insertions, 0 deletions
diff --git a/images/S0007850618300799.bib b/images/S0007850618300799.bib new file mode 100644 index 0000000..80c465c --- /dev/null +++ b/images/S0007850618300799.bib @@ -0,0 +1,14 @@ +@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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