The invention relates to the field of
coal blending optimization, and discloses a blending
combustion coal blending optimization method based on a micro-service technology, which is used for realizing accurate characterization of a pulverized
coal combustion process, accurate construction of a
combustion kinetic model and effective prediction of a slagging risk. Comprising the following steps: acquiring three-dimensional
point cloud data of a pulverized
coal particle swarm by using a
laser scanner, and generating a topological
feature vector representing
particle mixing uniformity through series
processing; and in combination with parameters of a coal quality analyzer, the concentration distribution of unburned carbon and the generation condition of pollutants are accurately predicted. A Doppler
laser velocimeter is used for collecting boiler turbulence
field data, and ash component parameters are combined to generate a
topological map for marking
slag-bonding risk vortex core coordinates. And solving a
global optimal anti-disturbance
coal blending scheme through homotopy mapping. According to the method, multi-dimensional innovation is achieved, the defects of the traditional technology in the aspects of pulverized coal characteristic characterization, combustion prediction, slagging
risk assessment,
coal blending optimization, equipment control and the like are effectively overcome, the coal combustion efficiency and stability are improved, and
pollutant emission is reduced.