A study on applications of principal component analysis and kernel principal component analysis for gearbox fault diagnosis

摘要

Principal component analysis (PCA) and kernel principal component analysis (KPCA) are widely used approaches of dimensionality reduction. They have been demonstrated useful for gearbox fault diagnosis. This paper provides a brief review of applications of PCA and KPCA for gearbox fault diagnosis. Literature is mainly grouped into two categories: applications of the conventional PCA/KPCA and applications of the improved PCA/KPCA. Discussions about the future work of PCA/KPCA on gearbox fault diagnosis are also provided in this paper.