Refinery fire identification method based on convolutional neural network

• Main Authors: LI SHENGCHAO, YU YANJU, FANG XIAOFENG, LIU XIAOWEN, ZHOU CHANGZHENG, WANG FENG, LUAN XIANGYU
• Format: Patent
• Language: Chinese; English
• Published: 04.06.2021
• Subjects: ALARM SYSTEMS; CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; HANDLING RECORD CARRIERS; ORDER TELEGRAPHS; PHYSICS; PRESENTATION OF DATA; RECOGNITION OF DATA; RECORD CARRIERS; SIGNALLING; SIGNALLING OR CALLING SYSTEMS

The invention relates to a refinery fire identification method based on a convolutional neural network, and belongs to the technical field of fire video identification. The method comprises the following steps of: 1, detecting a running target through a background difference method, and judging whether a moving object exists in a current picture or not; 2, transmitting the moving target into a flame detection model, and outputting a flame probability and a flame region; 3, transmitting the suspicious area into a false alarm model, and outputting the probability of real flames; and 4, judging whether flame or flame false alarm exists according to the probability of the real flame. Through verification, the method has higher recognition accuracy and lower false alarm rate, and the model can be updated according to the actually running picture, so that the method is more suitable for the actual scene of the scene; through real-time monitoring of a control area, a rapid response can be made at the initial stage o