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Michael Candon,
Marco Esposito, Haytham Fayek, Oleg Levinski, Stephan Koschel, Nish Joseph,
Robert Carrese, Pier Marzocca, Advanced multi-input system identification for
next generation aircraft loads monitoring using linear regression, neural
networks and deep learning, Mechanical Systems and Signal Processing, Volume
171, 2022, 108809, ISSN
0888-3270,
https://doi.org/10.1016/j.ymssp.2022.108809.
(https://www.sciencedirect.com/science/article/pii/S0888327022000085)
Weihua Li, Ruyi
Huang, Jipu Li, Yixiao Liao, Zhuyun Chen, Guolin He, Ruqiang Yan, Konstantinos
Gryllias, A perspective survey on deep transfer learning for fault diagnosis in
industrial scenarios: Theories, applications and challenges, Mechanical Systems
and Signal Processing, Volume 167, Part A, 2022, 108487, ISSN 0888-3270,
https://doi.org/10.1016/j.ymssp.2021.108487.
(https://www.sciencedirect.com/science/article/pii/S088832702100830X)
Ying Lin, Maohua
Xiao, Huijia Liu, Zhuolong Li, Shuang Zhou, Xiaomei Xu, Dicheng Wang, Gear
fault diagnosis based on CS-improved variational mode decomposition and
probabilistic neural network, Measurement,
Volume 192, 2022, 110913,
ISSN 0263-2241,
https://doi.org/10.1016/j.measurement.2022.110913.
(https://www.sciencedirect.com/science/article/pii/S0263224122001944)
Pengcheng Li,
Zhurong Liu, Burkay Anduv, Xu Zhu, Xinqiao Jin, Zhimin Du, Diagnosis for
multiple faults of chiller using ELM-KNN model enhanced by multi-label learning
and specific feature combinations, Building and Environment, Volume 214, 2022, 108904,
ISSN 0360-1323,
https://doi.org/10.1016/j.buildenv.2022.108904.
(https://www.sciencedirect.com/science/article/pii/S0360132322001494)
Pin Lyu, Kewei
Zhang, Wenbing Yu, Baicun Wang, Chao Liu, A novel RSG-based intelligent bearing
fault diagnosis method for motors in high-noise industrial environment, Advanced
Engineering Informatics, Volume 52, 2022, 101564, ISSN 1474-0346,
https://doi.org/10.1016/j.aei.2022.101564.
(https://www.sciencedirect.com/science/article/pii/S1474034622000374)
Jianzhong Zhang,
Yongbin Wu, Zheng Xu, Zakiud Din, Hao Chen, Fault diagnosis of high voltage
circuit breaker based on multi-sensor information fusion with training weights,
Measurement, Volume 192, 2022, 110894, ISSN 0263-2241,
https://doi.org/10.1016/j.measurement.2022.110894.
(https://www.sciencedirect.com/science/article/pii/S0263224122001786)
Dong Zhang,
ZhaoQiu Ning, Bai Yang, TianYou Wang, Yanjuan Ma, Fault diagnosis of permanent
magnet motor based on DCGAN-RCCNN, Energy Reports, Volume 8, Supplement 4, 2022,
Pages 616-626, ISSN 2352-4847,
https://doi.org/10.1016/j.egyr.2022.01.226.
(https://www.sciencedirect.com/science/article/pii/S2352484722002268)
Andreas Lundgren,
Daniel Jung, Data-driven fault diagnosis analysis and open-set classification
of time-series data, Control Engineering Practice, Volume 121, 2022, 105006, ISSN
0967-0661,
https://doi.org/10.1016/j.conengprac.2021.105006.
(https://www.sciencedirect.com/science/article/pii/S0967066121002732)
Quanqing Yu, Lei
Dai, Rui Xiong, Zeyu Chen, Xin Zhang, Weixiang Shen, Current sensor fault
diagnosis method based on an improved equivalent circuit battery model, Applied
Energy, Volume 310, 2022, 118588, ISSN 0306-2619,
https://doi.org/10.1016/j.apenergy.2022.118588.
(https://www.sciencedirect.com/science/article/pii/S0306261922000691)
Lanjun Wan,
Yuanyuan Li, Keyu Chen, Kun Gong, Changyun Li, A novel deep convolution
multi-adversarial domain adaptation model for rolling bearing fault diagnosis, Measurement,
Volume 191, 2022, 110752, ISSN 0263-2241,
https://doi.org/10.1016/j.measurement.2022.110752.
(https://www.sciencedirect.com/science/article/pii/S0263224122000549)
Yong Zhang, Yuqi
Xin, Zhi-wei Liu, Ming Chi, Guijun Ma, Health status assessment and remaining
useful life prediction of aero-engine based on BiGRU and MMoE, Reliability
Engineering & System Safety, Volume 220, 2022, 108263, ISSN 0951-8320,
https://doi.org/10.1016/j.ress.2021.108263.
(https://www.sciencedirect.com/science/article/pii/S0951832021007389)
Kamyar Azar,
Zohreh hajiakhondi-Meybodi, Farnoosh Naderkhani, Semi-supervised
clustering-based method for fault diagnosis and prognosis: A case study, Reliability
Engineering & System Safety, 2022, 108405, ISSN 0951-8320,
https://doi.org/10.1016/j.ress.2022.108405.
(https://www.sciencedirect.com/science/article/pii/S0951832022000783)
Maren David
Dangut, Ian K. Jennions, Steve King, Zakwan Skaf, Application of deep
reinforcement learning for extremely rare failure prediction in aircraft
maintenance, Mechanical Systems and Signal Processing, Volume 171, 2022, 108873,
ISSN 0888-3270,
https://doi.org/10.1016/j.ymssp.2022.108873.
(https://www.sciencedirect.com/science/article/pii/S0888327022000693)
Jieyang Peng,
Andreas Kimmig, Zhibin Niu, Jiahai Wang, Xiufeng Liu, Dongkun Wang, Jivka
Ovtcharova, Wind turbine failure prediction and health assessment based on
adaptive maximum mean discrepancy, International Journal of Electrical Power
& Energy Systems, Volume 134, 2022, 107391, ISSN 0142-0615,
https://doi.org/10.1016/j.ijepes.2021.107391.
(https://www.sciencedirect.com/science/article/pii/S014206152100630X)
Shaowei Liu,
Hongkai Jiang, Zhenghong Wu, Xingqiu Li, Data synthesis using deep feature
enhanced generative adversarial networks for rolling bearing imbalanced fault
diagnosis, Mechanical Systems and Signal Processing,
Volume 163, 2022, 108139,
ISSN 0888-3270,
https://doi.org/10.1016/j.ymssp.2021.108139.
(https://www.sciencedirect.com/science/article/pii/S0888327021005197) |
