Skip to content

Latest commit

 

History

History
31 lines (18 loc) · 1.15 KB

README.md

File metadata and controls

31 lines (18 loc) · 1.15 KB
Raw

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