Testing topological data analysis for wind turbine condition monitoring

Condition monitoring and predictive maintenance help prevent failures and reduce downtime. In this work, topological data analysis (TDA) was combined with classical (Fourier) signal analysis for condition-based monitoring of wind turbines. Acceleration and spectra were collected from a wind park in Norway; TDA was applied to point clouds built from vibration time series to derive topology-based health indicators, which were evaluated for fault detection and classification.

Presented at PHM Europe 2024. The paper appears in the PHM Society European Conference proceedings (DOI 10.36001/phme.2024.v8i1.4117); an extended version is also on arXiv.

Wind turbine condition monitoring illustration

(Casolo et al., 2024)

References

2024

Testing Topological Data Analysis for Condition Monitoring of Wind Turbines

Simone Casolo, Alexander Stasik, Zhenyou Zhang, and 1 more author

In PHM Society European Conference, 8 (1), 10, (2024)

DOI arXiv Bib HTML

@inproceedings{casolo2024wind,
  title = {Testing Topological Data Analysis for Condition Monitoring of Wind Turbines},
  author = {Casolo, Simone and Stasik, Alexander and Zhang, Zhenyou and Riemer-S{\o}rensen, Signe},
  booktitle = {PHM Society European Conference},
  volume = {8},
  number = {1},
  pages = {10},
  year = {2024},
  doi = {10.36001/phme.2024.v8i1.4117},
}