Research of Fire Detection Based on Process Characteristic and LM Arithmetic

The additional method of fire detection is not reliable and accurate as be influenced by random environmental disturbance. In this paper, first, a novel identification method for fire based on the process information of feature and the neural network of fire detection is discussed. CO and CO₂ gas concentration ratio, the ratio of increase in rates and characteristics of the acceleration are chosen as characteristic parameters of the process of fire and input of three layers back-propagation (BP) artificial neural network, which is extracted by extrapolation method and least square method. Second, the true and false fire source can be identified effectively by the trained network based on improved BP arithmetic-LM arithmetic. The tests prove that fire detection system based on BP artificial neural network can detected the process signal of fire and identify the true fire effectively. The reliability and accuracy of fire detection makes better improvement compared with traditional method.