RUL
collection of predictive maintenance solutions for NASAs turbofan (CMAPSS) dataset
This repository contains code that implement common machine learning algorithms for remaining useful life (RUL) prediction.
Transformer implementation with PyTorch for remaining useful life prediction on turbofan engine with NASA CMAPSS data set. Inspired by Mo, Y., Wu, Q., Li, X., & Huang, B. (2021). Remaining useful l…
PyTorch implementation of remaining useful life prediction with long-short term memories (LSTM), performing on NASA C-MAPSS data sets. Partially inspired by Zheng, S., Ristovski, K., Farahat, A., &…
Deep learning approach for estimation of Remaining Useful Life (RUL) of an engine
Estimating the Remaining Useful Lifetime (RUL) with LSTM Autoencoders
Project that tests the influence of monotonic constraints on the estimation of a RF and CNN-LSTM Model for C-MAPSS
Code and supplementary material for ICPHM2020