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  Paper Details                 Browse papers by sector
Applying Neural Network Technology to the Next Generation Flame Detector
Author            :Ardem Antabian, Shankar Baliga, Javid Huseynov      Contact The Author
Designation    :Product Manager, Flame and Gas Detectors,
Company        :General Monitors
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Synopsis

Neural network technology is a proven solution across a wide range of industries. When NNT is combined with a multi-spectral optical IR sensor package, the resulting MSIR/NNT technology becomes a powerful next generation solution for flame detection with distinct advantages over the various UV, IR, UV/IR, dual and triple IR flame detection devices on the market today.

MSIR/NNT flame detectors, with their custom programming capabilities, also represent a highly productive and cost-effective solution to persistent nuisance alarm sources. They can be programmed to recognize and ignore the footprints of such false alarm sources. This knowledge can be easily replicated in flame detection systems supporting large plant or standardized multi-plant operations.

The Model FL4000 Flame Detector extends the performance parameters of existing optical flame detectors in terms of distance, field of view, accuracy and false alarm immunity. These advantages, in many applications, will reduce the number of detectors necessary for optimum coverage, thus cutting total installation cost while still providing superior performance and protection from false alarms.

Reprinted with Permission from www.generalmonitors.com


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