Condition Monitoring of Limestone and Soft Sensing Model of SO2 Emissions in a Circulating Fluidized Bed Boiler

Abstract

Soft sensing models of the desulfurization process are developed in a circulating fluidized bed (CFB) boiler that can capture sulfur dioxide (SO2) with the limestone sorbent in the furnace. First, calcining utilization of CaCO3 and sulfating utilization of CaO are proposed by mechanism analysis of the theoretical air and flue gas, and the online prediction method is achieved by using an adaptive-tree-structure-based fuzzy inference system (ATSFIS). Second, condition monitoring models of active CaCO3, active CaO, and soft sensing model of SO2 emissions are studied by using the experimental data of a CFB boiler in China, which can monitor the storage and condition of the limestone in the furnace and predict SO2 emissions. Finally, a nonlinear proportional–integral–derivative (PID) control system based on the above models is designed to control the feed rate of limestone for the reduction of SO2 emissions. The simulation results show that the soft sensing models are consistent with the mechanism test results...