Optimizing Pulse Cleaning with ITM’s Patented Vibration-Based Fouling Detection and Fouling Monitoring System

Executive Summary

Boiler operators are under constant pressure to maximize efficiency, control fuel costs, and minimize downtime. To combat slagging and fouling, many plants deploy high-energy cleaning technologies such as shock pulse, acoustic cleaning, impulse systems, and other energy-pulse methods. These approaches can be highly effective at dislodging ash and slag deposits, but most operators lack the real-time visibility needed to confirm whether a cleaning event was successful, how much material was removed, or when the next pulse should be deployed. 

ITM provides the missing link. With patented Vibration-Based Fouling Detection, operators can measure the effectiveness of each cleaning event in real time — quantifying ash and slag removal rates achieved by every pulse. Complementing this, ITM’s Fouling Monitoring System (FMS) delivers continuous, plant-wide visibility into fouling buildup. Together, these technologies seamlessly integrate with pulse cleaning systems to enable closed-loop optimization — ensuring cleaning events are deployed only when needed and their results are immediately verified. 

Applicable across coal-fired power plants, waste-to-energy facilities, HRSGs, recovery boilers, and biomass boilers, ITM’s monitoring technologies give operators the tools to reduce fuel consumption, extend equipment availability, and maximize the impact of advanced cleaning strategies. 

The Challenge of Boiler Fouling

Fouling reduces heat transfer efficiency, increased fuel use and emissions, and in extreme cases can force the boiler to be taken off-line for cleaning. Traditional sootblowing or pulse cleaning is often performed on a fixed schedule, which often results in:  

  • Over-cleaning: wasted resources, accelerated tube erosion, and unnecessary maintenance. 
  • Under-cleaning: lost steam generation, higher fuel costs, and forced outages. 

Pulse cleaning can be highly effective — but without measurement, operators cannot confirm its impact or optimize cleaning frequency.  Complicating matters further, changes in fuel properties and boiler operating practices can accelerate fouling or make deposits more difficult to remove. Real-time monitoring of fouling rates provides the insight needed to identify these root causes and adjust cleaning strategies accordingly. 

ITM’s Monitoring Technologies

Patented Vibration-Based Fouling Detection

ITM’s patented vibration-based fouling detection technology provides real-time, dynamic measurements of boiler cleaning events. By capturing both the magnitude of the initial pulse and the subsequent system response, the technology quantifies ash and slag removal rates and verifies cleaning effectiveness immediately. This closed-loop feedback enables operators and vendors to fine-tune cleaning frequency and other parameters, maximizing efficiency while minimizing resource use, fuel consumption, and maintenance costs. 

Fouling Monitoring System (FMS)

FMS provides long-term visibility of fouling on heat-transfer surfaces such as superheaters, economizers, and furnace walls. By identifying when deposits reach critical thresholds, FMS supports predictive scheduling of cleaning based on hard data rather than guesswork. When paired with pulse cleaning systems, it ensures that pulses are applied at the most effective time and location, improving both efficiency and reliability. 

Closed-Loop Optimization of Pulse Cleaning

When used together, ITM’s Vibration-Based Fouling Detection and Fouling Monitoring System (FMS) transform pulse cleaning from a fixed schedule operation to a fully data-driven strategy: 

  1. Measure Cleaning Intensity – Vibration-Based Fouling Detection captures the strength of each cleaning pulse and its system response. 
  2. Confirm the Need for Action – FMS trends show when fouling has reached levels where cleaning will provide measurable benefits. 
  3. Target the Right Timing and Location – FMS pinpoints the onset and acceleration of fouling, guiding pulses to the most affected boiler zones. 
  4. Optimize Cleaning Frequency – Vibration-Based Detection verifies ash and slag removal rates, enabling operators to dynamically adjust cleaning cycles for maximum efficiency. 

Benefits to Plant Operations

Benefit  Description 
Efficiency Gains  Optimize pulses to maintain peak heat transfer and minimize fuel costs. 
Steam & Resource Savings  Eliminate unnecessary sootblowing and reduce excessive pulse cleaning events 
Asset Protection  Reduce tube erosion and wear caused by over-cleaning. 
Predictive Maintenance  Detect declining pulse effectiveness early, signaling maintenance needs. 
Financial Justification 

 

Link pulse cleaning performance directly to operational savings and reliability improvements, while lowering maintenance costs due to fewer cleaning cycles. 

Conclusion

Pulse cleaning is one of the most effective ways to combat boiler fouling. However, without visibility, operators are unable to confirm when cleaning is truly needed or whether it achieved the desired results.  By combining the real-time performance verification of ITM’s patented Vibration-Based Fouling Detection with the long-term fouling visibility of FMS, operators gain a data-driven, closed-loop control system. This ensures pulse cleaning is always used at the right time, in the right place, and with verifiable, measurable results. 

Next Steps for Boiler Operators

To evaluate and optimize pulsed cleaning with ITM’s monitoring technologies, operators should compile key baseline data, including fouling and heat absorption data, current cleaning schedules, steam and fuel costs, and maintenance or outage records related to fouling. Using these inputs, ITM can help calculate ROI and design a tailored pulse cleaning strategy backed by real performance data. 

For facilities planning new installations, ITM works directly with vendors to deliver fully integrated solutions that combine advanced cleaning systems with real-time analytics, ensuring maximum efficiency, reliability, and long-term operational performance.