To solve the problem of severe ash accumulation and slagging on heating surface of boilers caused by a large proportion of blended economic coal

based on the close relationship between the ash fouling layer and the flue gas flow field parameters

the concept of cross-sectional “ash fouling characteristic field” is proposed

and a new intelligent soot blowing control system for boilers is developed

which includes functions such as characteristic field detection and generation

and benchmark field prediction. By comparing the difference in “drop value” and “concentration” between the benchmark feature field and the current feature field

the system can timely and accurately determine the appropriate blowing time

achieving “intelligent perception and on-demand blowing”. The new system solves the problem of lack of measurement points and low accuracy in existing model calculation methods

overcomes the disadvantage of high equipment cost in furnace observation methods

and uses on-site full section data collectors combined with intelligent prediction models for ash pollution characteristic fields to achieve low-cost and high-precision detection of ash and slag accumulation

effectively solving the problems of over blowing and under blowing. The actual application effect of the power plant shows that

after the new system was put into use for 3 months

the monthly blowing frequency decreased by 19.6%

and the monthly blowing steam consumption decreased by 229.0 tons

which is equivalent to a direct economic benefit of 284 000 yuan per year. In addition

the system also brings multiple indirect benefits

such as avoiding sudden coking that causes the unit to stop

extending the service life of the heating surface

and avoiding delayed soot blowing that leads to a decrease in boiler efficiency. The relevant control optimization experience can be used as a reference for similar units in the future.