A decoupled multiple model approach for soft sensors design

This paper presents the application of a multiple model approach for the design of a soft sensor aiming at predicting the quality of the product of a separation unit in oil sands processing. The variable of interest here for the product quality is the percentage of water present in the product stream and the goal of the soft sensor is to provide an alternative mean for obtaining on-line measurements of the water-content value. The most reliable measurement of the water-content is obtained through laboratory analysis that introduces delays and long sampling time in the availability of the water-content data. These constraints generate a multi-rate sampling problem for the soft sensor design. The usage of a decoupled multiple model structure allows handling the multi-rate problem and designing a dynamical prediction model for the water-content. The effectiveness of the designed soft sensor in predicting the quality of the product stream is illustrated by on-line implementation results.

Research Highlights
► An inferential model for a process quality variable has been developed.
► A decoupled multiple model approach has been used to handle the multi-rate sampling problem.
► Application shows good prediction performance for the soft sensor.