Improved nonlinear process monitoring based on ensemble KPCA with local structure analysis

•Ensemble local kernel principal components analysis (ELKPCA) is proposed.•ELKPCA model makes width parameter selection easier.•Both global and local structure information of the original data are preserved.•ET2 and ESPE are constructed by Bayesian inference approach.•Two case studies demonstrate the effectiveness of the ELKPCA model.