Civil aircraft health management research based on big data and deep learning technologies
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Guigang Zhang | Jian Wang | Sujie Li | Guigang Zhang | Sujie Li | Jian Wang
[1] Xin Zhou,et al. Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data , 2016 .
[2] Haidong Shao,et al. Rolling bearing fault diagnosis using an optimization deep belief network , 2015 .
[3] Guigang Zhang,et al. Deep Learning , 2016, Int. J. Semantic Comput..
[4] Andrew D. Ball,et al. An approach to fault diagnosis of reciprocating compressor valves using Teager-Kaiser energy operator and deep belief networks , 2014, Expert Syst. Appl..
[5] William Scheuren,et al. Joint Strike Fighter Prognostics and Health Management , 1998 .
[6] Geoffrey E. Hinton,et al. Reducing the Dimensionality of Data with Neural Networks , 2006, Science.
[7] Yi Yang,et al. A integrated vehicle health management framework for aircraft — A preliminary report , 2015, 2015 IEEE Conference on Prognostics and Health Management (PHM).
[8] Diego Cabrera,et al. Multimodal deep support vector classification with homologous features and its application to gearbox fault diagnosis , 2015, Neurocomputing.
[9] Xue Sen Lin,et al. Engine components fault diagnosis using an improved method of deep belief networks , 2016, 2016 7th International Conference on Mechanical and Aerospace Engineering (ICMAE).
[10] Pingfeng Wang,et al. Failure diagnosis using deep belief learning based health state classification , 2013, Reliab. Eng. Syst. Saf..
[11] Geoffrey E. Hinton,et al. Deep Learning , 2015, Nature.
[12] Guigang Zhang,et al. Aviation PHM system research framework based on PHM big data center , 2016, 2016 IEEE International Conference on Prognostics and Health Management (ICPHM).
[13] Pingfeng Wang,et al. Deep Belief Network based state classification for structural health diagnosis , 2012, 2012 IEEE Aerospace Conference.