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SMART CLEAN ISB –
Intelligent on-load
boiler cleaning
Your benefits
The modules
Furnace optimiser
Convective area optimiser
Applications
Selected case studies

SMART CLEAN ISB –
Intelligent on-load boiler cleaning: demand-driven, automatic, real time
We made boiler cleaning thinking
A whole new philosophy has evolved out of the advantages of demand-driven boiler cleaning. We call this “SMART CLEAN ISB” and is built on the principle that on-load boiler cleaning optimizes boiler efficiency when it is carried out considering the requirements of the entire process.

The core component of SMART CLEAN ISB and therefore the key to intelligent on-load boiler cleaning is CEOS. CEOS incorporates all necessary process engineering knowledge to carry out on-load boiler cleaning in a demand-driven and intelligent way.

 
 

 


CEOS, the core
component of
SMART CLEAN ISB
for intelligent on-load
boiler cleaning:
demand-driven,
automatic, real time

What makes boiler cleaning intelligent?
CEOS holds the intelligence to recognise where exactly in the boiler are the deposits, to what extent and what effects will they have on the efficiency and availability of the boiler. This is the crucial information to control cleaning devices with demand-driven parameters.

Here, the combined application of diagnostics and analysis is the enabler. These data are passed on to a superordinate-level system  which defines by considering maintaining the boiler efficiency and availability the optimum on-load boiler cleaning strategy. Once the analysis is complete, the results are transformed into necessary cleaning actions incorporating following three key information:

  • WHERE in the boiler is the deposit located?
  • HOW intensive has the cleaning to be?
  • WHEN is the best point in time to initiate cleaning?

Why is intelligent on-load boiler cleaning needed?
The most frequent cause of reduced boiler efficiency and unplanned shutdowns is deposit build up on the heating and reaction surfaces. The formation of deposits is  subject to many influencing factors which may continuously fluctuate.
Examples for influencing factors are:

  • the chemical composition of the fuel used and with it the amount and combination of  ashforming matter
  • boiler load
  • temperature profile of the flue gas
  • characteristics of the ash particles in the flue gas

Due to the multitude of influencing factors and their interdependencies, there cannot be a global, once defined and always applicable cleaning strategy.

Therefore, an intelligent on-load boiler cleaning is needed – a boiler cleaning process which “knows” at any time what is going on in the entire steam generation process. Only then, cleaning performance can be adjusted to respond to the current deposit situation – delivering automatic, demand-driven and real time optimized and integrated cleaning functionality.

Installation
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