Complex process operating optimality assessment and nonoptimal cause identification using modified total kernel PLS
Due to process disturbances and some uncertainties, the process operating performance will deviate from the optimal operating point along with time, so it is very important to develop strategies for online operating performance assessment on optimality. However, a little work has been published in this research area to our knowledge. In this study, a new online operating optimality assessment method for complex industrial process is proposed. Firstly, a new version of T-KPLS algorithm combined with the modified KPLS is developed and used to establish the assessment models for each of the performance grades. By calculating the similarities between the online data and each performance grade, one can obtain the assessment result online, and the assessment results not only include the certain performance grade but also the performance grade conversion. For nonoptimal operating performance, a method of nonoptimal cause identification based on variable contribution is developed. Finally, the proposed online assessment method is applied in a gold hydrometallurgical process, which indicates the efficiency of the proposed approach.