Prototype Early Warning Fire Detection System: Test Series 2 Results
Rept. 25 Apr-5 May 2000
NAVY TECHNOLOGY CENTER FOR SAFETY AND SURVIVABILITY WASHINGTON DC
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The system under development combines a multi-criteria sensor array approach with sophisticated data analysis methods. Together an array of sensors and a multivariate classification algorithm has the potential to produce an early warning fire detection system with a low nuisance alarm rate. Several sensors measuring different parameters of the environment produce a pattern or response fingerprint for an event. Multivariate data analysis methods can be trained to recognize the pattern of an important event such as a fire. Multivariate classification methods, such as neural networks, rely on the comparison of events i.e., fires with non- events i.e., background and nuisance sources. Variations in the response of sensors can be used to train an algorithm to recognize events when they occur. A key to the success of these methods is the appropriate design of sensor arrays and training sets of data used to develop the algorithm. This test series included a variety of conditions that may be encountered in a real shipboard environment. Every effort was made to consider many representative fire situations and potential interference sources. including the use of Navy approved materials.
- Safety Engineering