A new fault isolation method based on unified contribution plots

Contribution plots are important to identify the unusual process variables for fault isolation. In this paper a new fault isolation method based on unified contribution plots was presented for linear and nonlinear principal component analysis. Principal component analysis based process monitoring was first analyzed and variable contributions to monitoring statistic were modified to bring a new unified framework for contribution calculation. Then this method was generalized to nonlinear kernel principal component analysis. Some issues were further discussed including negative contribution and confidence limit, and then relative contribution was introduced to give a more reasonable explanation on variable contribution. Simulations on a continuous stirred tank reactor system were performed to show the proposed method is effective to isolate fault variables.