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TECHNOLOGY NEWS

 
     
 

IR Flame Detector delivers superior false alarm immunity

Posted: 28 March 2006

For oil/gas offshore drilling platforms, pipelines, LNG & LPG plants, refineries, marine fuel load/unload facilities, chemical plants

With a next-generation multi-spectral infrared flame sensor that incorporates neural network technology (NNT), the new FL4000 Intelligent Multi-Spectral IR (MSIR) Flame Detection System from General Monitors sets a new industry standard for performance, reliability and value.

The FL4000 gives process and plant engineers a potent new tool in protecting people, equipment and facilities from dangerous hydrocarbon flame sources.

Until now, flame detection has been based on multi-spectral optical flame detectors integrated with expert signal processing.

This type of system relies on an expert to design a fixed set of conditions.

While these devices meet basic flame detection needs, they are prone to false alarms caused by reflected sunlight, arc welding, hot piping, machinery, and other false alarm sources.

The new FL4000 combines an advanced optical MSIR sensor array with NNT processing.

NNT is based on artificial neural networks (ANN), which are mathematical models of biological neurons in the human brain that correlate given signal patterns with target flame conditions.

The optical IR sensor array and the neural network function together as an adaptive and intuitive decision-making mechanism with boundless optimization capability.

The result is a breakthrough flame detector that provides the industry’s most reliable discrimination between actual flames and nuisance false alarm sources.

The FL4000’s MSIR detector makes use of four separate infrared spectrums sampling different IR spectral areas to detect a flame. Each sensor’s analog signals is sampled and then converted into digital format for initial signal pre-processing to extract time and frequency information.

The time and frequency information are used by the FL4000’s proprietary neural network classification algorithm to identify if input IR signals are emitted from a flame or non-flame source. The flame or non-flame decision is then reported as an output via LEDs, relays, and MODBUS.

 

 
     

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