Abstract
Fire detection system and fire warning are design features of an aircraft. Fire detection system protects the aircraft and passengers both in case of actual fire during flight. But spurious fire warning during flight creates a panic situation in flight crews and passengers. The conventional fire alarm system of an aircraft is triggered by false signal. ANN based fire detection system provides real observation of deployed zones. An intelligent fire detection system is developed based on artificial neural network using three detection information such as heat (temperature), smoke density and CO gas. This Information helps in determining the probability of three representative of Fire condition which is Fire, smoke and no fire. The simulated MATLAB results Show that the errors in identification are very less. The neural network based fire detection system integrates different types of sensor data and improves the ability of system to correct prediction of fires. It gives early alarm when any kind of fire broke out and helps to decrease in spurious warning.
Highlights
In different part of aircraft where a fire protection is required the cargo compartment are important
Fire detection systems based on single sensor input are not able to meet the needs of real fire alarm
In view of the above Artificial Neural Network (ANN) based fire alarm system is more compatible than traditional fire alarm system because it can intelligently handles the multi sensor information theory
Summary
In different part of aircraft where a fire protection is required the cargo compartment are important. For example detection methods using thermal detectors are affected by transient current. Smoke detectors can be affected by different gases developed in cargo compartment. Fire detection systems based on single sensor input are not able to meet the needs of real fire alarm. In view of the above Artificial Neural Network (ANN) based fire alarm system is more compatible than traditional fire alarm system because it can intelligently handles the multi sensor information theory. [Yadav et al, Vol. (Iss.: SE): February, 2018] [Communication, Integrated Networks & Signal Processing-CINSP 2018]. The project presents a fire protection system designed on neural networks which uses the fire heat, smoke density and CO gas in the primary fire stage as a input.
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