A cross domain feature extraction method based on transfer component analysis for rolling bearing fault diagnosis

@article{Chen2017ACD,
  title={A cross domain feature extraction method based on transfer component analysis for rolling bearing fault diagnosis},
  author={Chen Chen and Zhiheng Li and Jun Yang and Bin Liang},
  journal={2017 29th Chinese Control And Decision Conference (CCDC)},
  year={2017},
  pages={5622-5626}
}
Feature extraction plays a significant role in the rolling bearing fault diagnosis. However, the complexity and variability of the actual working condition leads to the data unstable and fault characteristics unpredictable. Traditional machine learning methods won't work or have a poor performance under this circumstance. In this paper, we propose a cross domain feature extraction method based on the Transfer Component Analysis algorithm to solve the problem. Transfer Component Analysis, as a… CONTINUE READING