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Detector is certified for hazardous environments

Edited by the Engineeringtalk editorial team Nov 3, 2006

The breakthrough multispectral infra-red (MSIR) FL4000 flame detector has been certified by Factory Mutual (FM) for application in hazardous environments.

The breakthrough multispectral infra-red (MSIR) FL4000 flame detector from General Monitors has been certified by Factory Mutual (FM) for application in hazardous environments.

The FL4000, with its next-generation MSIR sensor that incorporates neural network technology (NNT), provides highly reliable flame monitoring with superior false alarm immunity, an exceptionally wide field of view (FOV) and the industry's longest extended range.

Setting a new industry standard for performance, reliability and value, the FL4000 flame detector gives process and plant engineers a potent new tool in protecting people, equipment and facilities from dangerous hydrocarbon flame sources.

It provides exceptional performance and reliability while minimising operational costs associated with unreliable flame detection due to false alarms.

Designed with an exceptionally reliable NNT flame discrimination algorithm, the FL4000 detector is highly immune to false alarms while at the same time offering extended range (up to 70m) and wide field-of-view (FOV) characteristics (100 degrees at 15m).

For example, the new FL4000 MSIR flame detector provides false alarm immunity to arc welding as close as 1.5-4.5m.

Other features include built-in COPM (continuous optical path monitoring), a self-testing feature designed to check the optical path integrity of the detector elements and the related electronic circuitry once every two minutes.

Serial ports allow up to 128 units (247 using repeaters) to be linked up to a host computer using the Modbus RTU protocol.

The advanced FL4000 combines an 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 optimisation capability.

The resulting flame detector provides the industry's most reliable discrimination between actual flames and costly false alarm sources.

The MSIR sensor array in the FL4000 allows the detector to sample different IR spectral areas to detect a flame.

Each sensor's analogue signal is sampled and then converted into digital format for initial signal preprocessing 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 nonflame source.

The flame or nonflame decision is then reported as an output via LEDs, relays and Modbus.

Flame detectors prior to the FL4000's introduction were prone to false alarms caused by arc welding, hot piping, reflected sunlight, and other false alarm sources.

These legacy types of flame monitoring systems rely on a limited set of rules to detect fires.

Although they meet basic flame detection needs, they are susceptible to nuisance false signals that cause unnecessary emergency shut-downs and time-consuming plant restart activities.

Because of its accurate and reliable flame detection scheme, the FL4000 sets a new standard for performance, reliability, safety and value.

Furthermore, the FL4000's ability to differentiate spectral radiation emitted by actual flames from that emitted by background ambient radiation is exceptional.

This differentiation is extremely crucial, as failure to do so results in either undetected fires, or more commonly, nuisance false alarms.