Research On Fire Alarm System Of Aircraft Cargo Cabin Based On Data Fusion

Cargo compartment fire detection is an important part of the aircraft fire detection system.Improving the accuracy of fire detection in the cargo compartment can not only improve the safety of aircraft navigation,but also reduce the additional expenses due to false alarms.In order to reduce the false alarm rate of cargo fire compartment and improve the reliability of detection,this paper studied the aircraft cargo fire detection system.The main research contents are as follows:1.This paper analyzed the combustion characteristics at different stages of the cargo,selected the CO sensor,temperature rise sensor and smoke sensor to build a three fusion fixed fire detection module,studied the main characteristic parameters of the airborne container,analyzed the importance of the container fire detection,and designed a portable airborne container fire detection module.The three fusion fixed fire detection module is based on the BP neural network,the detection result is set to the probability of no fire,open flame and smoldering,the detection result of container fire detection module is container fire.With the help of MATLAB programming,combining three fusion detection and the portable container fire detection module to build a cargo compartment fire detection system.2.This paper introduced the original data source of training mode pair,took the maximum and minimum normalization of original data;This paper studied the setting rules of hidden layer network nodes and selected the optimal number of hidden layer nodes;Through the network model,the three fusion fixed fire detection module is optimized to obtain the weight matrix;Using the MATLAB graphical user interface to integrate different modules,develop a multi-data fusion fire detection software system for aircraft cargo,and provide users with graphical software interfaces.