Graph Neural Networks with Trainable Adjacency Matrices for Fault Diagnosis on Multivariate Sensor Data

This repository is the official implementation of model architectures from the paper Graph Neural Networks with Trainable Adjacency Matrices for Fault Diagnosis on Multivariate Sensor Data.

Training and evaluation examples

FDDBenchmark was used in our experiments.

Training step:

python train.py

Evaluation step:

python evaluate.py

Citation

Please cite our paper as follows:

@article{kovalenko2024graph,
  title={Graph neural networks with trainable adjacency matrices for fault diagnosis on multivariate sensor data},
  author={Kovalenko, Aleksandr and Pozdnyakov, Vitaliy and Makarov, Ilya},
  journal={IEEE Access},
  year={2024},
  volume={12},
  pages={152860-152872},
  publisher={IEEE}
}