Intelligent measurement method of aircraft leading edge slats based on vision

The safety performance of civil aircraft is closely related to the reliability of aircraft slat mechanism, and the slat failures of civil aircraft have been occurring continuously in recent years. The design of aircraft slats has a great impact on the resistance during flight. The relative chord displacement of slats and main wings cannot be ignored, which has a great impact on aircraft resistance. In order to accurately and quantitatively obtain the relative displacement of the leading edge slat and the main wing of the aircraft, this paper adopts the combined measurement method of stereo intersection photogrammetry and relay measurement, and designs a multi-target real-time tracking algorithm based on the YOLO Tiny algorithm and the Kernel Correlation Filter (KCF) algorithm, which can accurately and quantitatively measure the change of the leading edge of the slat, At the same time, the variation trend of the measured results also conforms to the variation trend of the leading edge slats during the movement process.