Development of naphtha dry point soft sensor by adaptive partial least square regression
A novel adapting partial least square regression (APLS R) approach was proposed to develop the naphtha dry point soft sensor of the prima ry distillation tower.Many operation conditions were related to naphtha dry poin t and there existed a significant correlation among them.In order to obtain a na phtha dry point soft sensor with high predicting correctness, the different pred icting contribution ratios of modeling samples were taken into account by APLSR and the optimal number of the latent variables was obtained according to the pre dicting ability of the soft sensor.When APLSR was used for the predicting sample , each modeling sample was weighted according to its ratio of predicting contrib ution for the predicting sample and satisfactory results were obtained.Further, the previous analysis value of the naphtha dry point was regarded as a new indep endent variable for the soft sensor and the predicting correctness of the soft s ensor was enhanced remarkably.