1. Milling data set;Agogino,2007
2. Deep convolutional neural network based regression approach for estimation of remaining useful life;Babu,2016
3. Baptista, M., Prendinger, H., Henriques, E., 2020. Prognostics in Aeronautics with Deep Recurrent Neural Networks. In: PHM Society European Conference. Vol. 5.
4. Bolander, N., Qiu, H., Eklund, N., Hindle, E., Rosenfeld, T., 2009. Physics-based remaining useful life prediction for aircraft engine bearing prognosis. In: Annual Conference of the PHM Society. Vol. 1. (1).
5. Prognostic issues for rotorcraft health and usage monitoring systems;Byington,1997