Kazantsev, Mikhail
Interaction models for remaining useful life estimation
Zhevnenko, Dmitry, Kazantsev, Mikhail, Makarov, Ilya
The current methods rely on one approach to feature extraction in which the prediction occurs. We proposed a technique to build a scalable model that combines multiple different feature extractor blocks. A new model based on sequential sensor space analysis achieves state-of-the-art results on the C-MAPSS benchmark for equipment remaining useful life estimation. The resulting model performance was validated including the prediction changes with scaling.