Adaptive total PLS based quality-relevant process monitoring with application to the Tennessee Eastman process

Increasing global competition is setting even higher demands for the safety, quality and operating efficiency of industrial processes. The traditional projection to latent structures (PLS) based methods for quality-relevant fault detection has appeared in several industrial applications, while total PLS that performs more completely has been used as a better tool for monitoring associated with the product quality. However, the running/operating states for the process variables are often non-stationary, time-varying. Thus, the static PLS or TPLS for these processes will reduce the efficiency of the monitoring, unreliable monitoring results will affect the engineers׳ decision-making. Under this background, an adaptive modification on total PLS model named as recursive TPLS will be proposed to adapt the monitoring model on line. The new recursive version is achieved via a far more computation-efficient manner and the operating cost is significantly lowered. The simulation on TE process illustrates the effectiveness of the new adaptive fault monitoring approach based on RTPLS.