Akira Sugano

Prediction method of unburnt carbon for coal fired utility boiler using image processing technique of combustion flame

A method for predicting unburnt carbon in a coal-fired utility boiler has been developed using an image processing technique. The method consists of an image processing unit and a furnace model unit. The temperature distribution of combustion flames can be obtained through the former unit. The latter calculates dynamics of the carbon reduction from the burner stages to the furnace outlet using coal feed rate, air flow rate, and the chemical and ash content of the coal. An experimental study in the Sendai Power Station of Tohoku Electric Company Inc. shows that the prediction error of the unburnt carbon can be reduced to 10%. The results show that the unburnt carbon prediction algorithm could be widely used for evaluation, optimization and diagnosis of combustion systems for various boiler and coal types. >

Hierarchical function-structured and autonomous control systems for fossil power plants

A distributed digital monitoring and control system suitable for fossil-fueled power plants is described along with the associated minicomputers, communication devices, and man-machine interface devices. The corresponding hardware and software are also discussed. The system covers the plant-wide (distributed) monitoring and control functions including data acquisition, boiler control, burner management, turbine control, auxiliaries control, and protection. >