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¡ß Huixing Meng, Yan-Fu Li, A review on prognostics and health management (PHM) methods of lithium-ion batteries, Renewable and Sustainable Energy Reviews, Volume 116, 2019, 109405, ISSN 1364-0321,
DOI: https://doi.org/10.1016/j.rser.2019.109405.
(http://www.sciencedirect.com/science/article/pii/S1364032119306136)
¡ß N. Omri, Z. Al Masry, N. Mairot, S. Giampiccolo, N. Zerhouni, Industrial data management strategy towards an SME-oriented PHM, Journal of Manufacturing Systems, Volume 56, 2020, Pages 23-36, ISSN 0278-6125,
DOI: https://doi.org/10.1016/j.jmsy.2020.04.002.
(http://www.sciencedirect.com/science/article/pii/S0278612520300467)
¡ß Ramin Moradi, Katrina M. Groth, Modernizing risk assessment: A systematic integration of PRA and PHM techniques, Reliability Engineering & System Safety, Volume 204, 2020, 107194, ISSN 0951-8320,
DOI: https://doi.org/10.1016/j.ress.2020.107194.
(http://www.sciencedirect.com/science/article/pii/S0951832020306955)
¡ß Masoumeh Zareapoor, Pourya Shamsolmoali, Jie Yang, Oversampling adversarial network for class-imbalanced fault diagnosis, Mechanical Systems and Signal Processing, Volume 149, 2021, 107175, ISSN 0888-3270,
DOI: https://doi.org/10.1016/j.ymssp.2020.107175.
(http://www.sciencedirect.com/science/article/pii/S0888327020305616)
¡ß Unai Izagirre, Imanol Andonegui, Luka Eciolaza, Urko Zurutuza, Towards manufacturing robotics accuracy degradation assessment: A vision-based data-driven implementation, Robotics and Computer-Integrated Manufacturing, Volume 67, 2021, 102029, ISSN 0736-5845,
DOI: https://doi.org/10.1016/j.rcim.2020.102029.
(http://www.sciencedirect.com/science/article/pii/S0736584520302404)
¡ß Han Cheng, Xianguang Kong, Gaige Chen, Qibin Wang, Rongbo Wang, Transferable convolutional neural network based remaining useful life prediction of bearing under multiple failure behaviors, Measurement,Volume 168, 2021, 108286, ISSN 0263-2241,
DOI: https://doi.org/10.1016/j.measurement.2020.108286.
(http://www.sciencedirect.com/science/article/pii/S0263224120308265)
¡ß Haoshu Cai, Jianshe Feng, Feng Zhu, Qibo Yang, Xiang Li, Jay Lee, Adaptive virtual metrology method based on Just-in-time reference and particle filter for semiconductor manufacturing, Measurement, Volume 168, 2021, 108338, ISSN 0263-2241,
DOI: https://doi.org/10.1016/j.measurement.2020.108338.
(http://www.sciencedirect.com/science/article/pii/S0263224120308757)
¡ß Fausing Olesen, J.; Shaker, H.R. Predictive Maintenance for Pump Systems and Thermal Power Plants: State-of-the-Art Review, Trends and Challenges. Sensors 2020, 20, 2425.
DOI: https://doi.org/10.3390/s20082425
¡ß Guan, F.; Cui, W.-W.; Li, L.-F.; Wu, J. A Comprehensive Evaluation Method of Sensor Selection for PHM Based on Grey Clustering. Sensors 2020, 20, 1710.
DOI: https://doi.org/10.3390/s20061710
¡ß Qu, Y.; Ming, X.; Qiu, S.; Zheng, M.; Hou, Z. An Integrative Framework for Online Prognostic and Health Management Using Internet of Things and Convolutional Neural Network. Sensors 2019, 19, 2338.
DOI: https://doi.org/10.3390/s19102338
¡ß Huh, J.; Pham Van, H.; Han, S.; Choi, H.-J.; Choi, S.-K. A Data-Driven Approach for the Diagnosis of Mechanical Systems Using Trained Subtracted Signal Spectrograms. Sensors 2019, 19, 1055.
DOI: https://doi.org/10.3390/s19051055
¡ß Huang, G.; Li, H.; Ou, J.; Zhang, Y.; Zhang, M. A Reliable Prognosis Approach for Degradation Evaluation of Rolling Bearing Using MCLSTM. Sensors 2020, 20, 1864.
DOI: https://doi.org/10.3390/s20071864
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