Low-rank and sparse model: A new perspective for rolling element bearing diagnosis

Ge Xin, Yong Qin, Li-Min Jia, Shun-Jie Zhang, Jerome Antoni

Open source

DOI
10.1109/icirt.2018.8641577
Published
2018-12
Container
2018 International Conference on Intelligent Rail Transportation (ICIRT)
Publisher
IEEE
Open access
unknown

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BibTeX

@article{allodium:10.1109/icirt.2018.8641577,
  title = {Low-rank and sparse model: A new perspective for rolling element bearing diagnosis},
  author = {Ge Xin and Yong Qin and Li-Min Jia and Shun-Jie Zhang and Jerome Antoni},
  year = {2018},
  journal = {2018 International Conference on Intelligent Rail Transportation (ICIRT)},
  doi = {10.1109/icirt.2018.8641577},
  url = {https://doi.org/10.1109/icirt.2018.8641577}
}

RIS

TY  - JOUR
TI  - Low-rank and sparse model: A new perspective for rolling element bearing diagnosis
AU  - Ge Xin
AU  - Yong Qin
AU  - Li-Min Jia
AU  - Shun-Jie Zhang
AU  - Jerome Antoni
PY  - 2018
JO  - 2018 International Conference on Intelligent Rail Transportation (ICIRT)
DO  - 10.1109/icirt.2018.8641577
UR  - https://doi.org/10.1109/icirt.2018.8641577
ER  - 

APA

Xin, G., Qin, Y., Jia, L., Zhang, S., & Antoni, J. (2018). Low-rank and sparse model: A new perspective for rolling element bearing diagnosis. 2018 International Conference on Intelligent Rail Transportation (ICIRT). https://doi.org/10.1109/icirt.2018.8641577

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