Download or read book Prototype Early Warning Fire Detection System Test Series 2 Results written by and published by . This book was released on 2000 with total page 77 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Prototype Early Warning Fire Detection System Test Series 1 Results written by and published by . This book was released on 2000 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This report documents the results of the Early Warning Fire Detection (EWFD) prototype Series I tests conducted on the ex-USS Shadwell over the period of February 7-18, 2000. Four EWFD prototypes were successfully integrated with a data acquisition system to operate in real time using a probabilistic neural network (PNN) and provided appropriate alarms in real time. Two prototypes were evaluated consisting of different sets of sensors and a PNN based on previous work in this program. EWFD prototype 2 demonstrated slightly better performance than EWFD prototype I and faster response times than the Simplex COTS smoke detection system. Even EWFD prototype 1 demonstrated on average faster response times than the Simplex detectors.

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