Intelligent multi-soft sensing for flame position of steam boilers

Abstract

A new inference control system for the flame position in the combustion chamber of a power plant system boiler is presented. The system is based on enhanced multi-softsensing at three operational levels - basic level, providing estimates of all necessary technological variables; a separate Mill Fan (MF) level, and a total Dust Preparation System (DPS) level. The control system involves a subsystem for the stabilization of the position of the common MF ventilation rate momentum in a given threshold area in a burner horizon, which is supervised by an inference correction based on softsensed 2D flame position in the output section of the combustion chamber. A hybrid approach is accepted in softsensing, using fusion of the first principle models, statistical models, neural networks and fuzzy logic based models. Real experimental results are presented from TPP.