Research on multi feature fusion perception technology of mine fire based on inspection robot

Abstract

Abstract In order to improve the real-time and accuracy of mine fire identification, based on the summary of the existing fire monitoring methods, a mine fire early warning model based on patrol robot and multi-sensor and image recognition is proposed. The video image is obtained by using the high-definition camera of inspection robot, and the flame suspected area of video image is obtained by combining frame difference and background difference after filtering. The improved three scale analytic hierarchy process is used to fuse the circularity feature, sharp angle feature, centroid movement feature, color feature and area growth feature of the flame suspected area image to obtain the flame result. The three-frame difference method is used to binarize the smoke video image, and the smoke texture feature, smoke motion feature and smoke color feature are extracted to recognize the smoke image. The improved three-scale analytic hierarchy process (AHP) is used to fuse and judge the smoke in the combination of infrared thermal imager temperature measurement and smoke sensor. Inspection robot uses unified detection standards and intelligent analysis technology to sense mine smoke and flame. This method can improve the real-time, accuracy and robustness of mine fire perception.