A soft sensor for carbon content of spent catalyst in a continuous eforming plant using LSSVM-GA

CATEGORY: CCR - CONTINUOUS CATALYTIC REFORMING
2012 31st Chinese Control Conference (CCC), 25-27 July 2012, Page(s): 7056 - 7060A soft sensor for carbon content of spent catalyst in a continuous eforming plant using LSSVM-GA
Yuqiao, Wang
School of Energy and Power Engineering, Xi'an Jiaotong University, Xi'an 710049, China
Guangxu, Cheng ;  Haijun, Hu ;  Jieguo, Tang
Abstract
Continuous catalytic reforming (CCR) is used to convert low-octane gasoline blending components to high-octane components for use in high-performance gasoline fuels or as source of aromatics. Carbon deposition rate is a critical performance factor of reforming catalysts.  The carbon content of spent catalyst directly affects catalyst regeneration. Consequently, it is important to monitor the carbon content of spent catalysts in real time.
Authors propose a soft sensor using least squares support vector machine (LSSVM) with genetic algorithm (GA) to solve this problem in an existing CCR plant.  The GA is used to select the free parameters of the LSSVM model. The LSSVM with traditional grid algorithm and artificial neural network (ANN) are also applied to model two soft sensors using the same data sets for comparison. Simulation results reveal that GA shows outstanding performance compared to the conventional grid algorithm for selecting free parameters of LSSVM.
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