主管:中华人民共和国应急管理部
主办:应急管理部天津消防研究所
ISSN 1009-0029  CN 12-1311/TU

Fire Science and Technology ›› 2023, Vol. 42 ›› Issue (12): 1709-1713.

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Research on flame visible and infrared mult-feature fusion image detection algorithm in aircraft cargo compartment

Deng Li1,2, Xie Shuangshuang1, He Yuanhua1,2, Liu Quanyi1,2   

  1. (1.College of Civil Aviation Safety Engineering, Civil Aviation Flight University of China, Sichuan Guanghan 618307, China;2. Civil Aircraft Fire Science and Safty Engineering Key Laboratory of Sichuan Province, Sichuan Guanghan 618307, China)
  • Online:2023-12-15 Published:2023-12-15

Abstract: Cyclohexane and aviation kerosene are used as experimental fuels to carry out pool fire detection experiments in the aircraft cargo model. Combined with the principle of image correlation, combustion image recognition and flame oscillation frequency detection are carried out as the criteria for judging whether a fire occurs. The results indicate that the flame temperature varies significantly when the temperature is below 60 kPa and the jitter is severe; Under equidistant combustion time series, the mean flame oscillation frequency of cyclohexane and aviation kerosene is above 3 Hz, which is in agreement with the theoretical value and can be used as the basis for judging the occurrence of fire. The YOLO model is used to detect the infrared images of cyclo—hexane and aviation kerosene combustion to determine whether there is flame generation, and the accuracy is as high as 0.965. The experimental results show that the proposed method has a good effect on flame detection, which can be used in theory and data to analyze the fire behavior of combustion and the key techniques of fire detection and early warning in low—pressure environment.

Key words: aircraft cargo;fire detection, imagery correlation, flame oscillation frequency, infrared image