Every coal plant owner must generate the maximum amount of energy with the lowest emissions in the safest and most economical way.
To do so, plant operators constantly change the fuels that their plants burn; yet while switching coals may help to meet price and emissions standards, it can produce greater fouling and slagging of the boiler tube surfaces.
Dirty boiler tubes can reduce efficiency, so to keep plants running at the highest efficiency, soot and ash must be cleaned from the boiler tubes. Currently, coal plant operators use a number of ways to clean these tubes, but have inadequate methods to measure the effectiveness of the procedures. Worse still, many such measurement methods have negative impacts such as prolonged downtime and thermal stress to the boiler tubes.
Now, thanks to a radiometric thermal imaging system from LumaSense (Santa Clara, CA, USA) that uses video and data analysis software, those coal-fired power plants can capture clear images from inside boilers, furnaces and kilns, helping them to better monitor the boiler tubes and slag deposits that prevent the boilers from running at peak efficiency.
By proactively maintaining boilers in such a way, the coal plants can improve boiler uptime by reducing the number of manual cleaning cycles and decreasing tube erosion typically caused by excessive cleaning.
As an example, Alabama Power's Miller Steam Plant -- located in West Jefferson, Alabama -- has significantly reduced the number of "de-slags" on two of its four boilers using BoilerSpection, and eliminated the need for online washes during a six-month beta period.
Prior to using BoilerSpection, the plant estimates it performed approximately 51 de-slags (a process that decreases generation on the units from 720 to 300 MW for approximately 4-6 hours) on the boilers in 2010. During the six-month beta test of the BoilerSpection system, they performed only 12 of these processes. The plant is now planning to outfit its remaining two boilers with the vision system.
-- Posted by Vision Systems Design