Pytorch Implementation of RUL-RVE

This is an unofficial PyTorch implementation of the paper Variational encoding approach for interpretable assessment of remaining useful life estimation. This repo builds on the codebase of the official Tensorflow implementation here.

Requirements

Implementation

Results

Implementation	Dataset	lr	RMSE
Paper	FD001	0.001	13.42
Our Implementation	FD001	0.005	11.05
Paper	FD002	0.001	14.92
Our Implementation	FD002	0.005	13.99
Paper	FD003	0.001	12.51
Our Implementation	FD003	0.001	12.08
Paper	FD004	0.001	16.37
Our Implementation	FD004	0.005	16.70

• We found the optimal LR for each dataset using grid-search (lr = choice(0.1, 0.01, 0.005, 0.001, 0.0001))

References

1. Costa N, Sánchez L. Variational encoding approach for interpretable assessment of remaining useful life estimation. Reliab Eng Syst Saf. 2022;222:108353. doi:10.1016/J.RESS.2022.108353