Soft-sensing of the Dry Point of Benzene Using Pca and Drbfn
نویسندگان
چکیده
Measurements of temperatures and flows and pressures are used to estimate the dry point of the product for the distillation column. The Problem is characterized by the model complication and the strong colinearity between the measurements. In this article, the distributed RBF neural network (DRBFN) and principal component analysis (PCA) are used to develop the soft sensor (PCA-DRBFN model), and PCA is also used for data compressing and validation. Another two models are used to compare the performance with the proposed soft sensor.
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