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The phenomenon of spontaneous combustion of coal piles often occurs in closed coal yards of power plants, automatic fire-fighting equipments are generally used to detect and locate the spontaneous combustion point. However, their performance (false alarm rate) are largely limited due to the complicated environment of the coal yard. To deal with this problem, this paper proposes a composite image recognition based method for detecting and positioning the spontaneous combustion point (SCP) in coal yard. Yolov5s is trained to efficiently detect SCPs and infrared information is fused to distinguish the realiability of SCP detection result via composite image registration method. In addition, an angle compensation algorithm is proposed to adjust the spray angle of the equipment for positioning the cooling area. The experimental results show that after integrating the above related technologies, the false alarm rate of the spontaneous combustion point in the scene is greatly reduced, and the work efficiency is effectively improved.

A composite image recognition based approach for spontaneous combustion point detection and positioning in coal piles