Precise engine displacement testing technique based on stereo vision and circular mark points

To accurately measure the three-dimensional deformation of the structure in engine static and swing tests, we propose a high-precision displacement measurement method based on stereo vision and circular markers. This method involves affixing reflective circular markers onto the engine structure surface and capturing a sequence of images during the structural deformation process. Firstly, the Sobel edge detection algorithm is used to extract the pixel-level edges of each circular marker. Then, an interpolation-based sub-pixel edge detection method is employed to obtain sub-pixel edge points, enabling more precise localization of the markers. Finally, the elliptical least squares fitting is applied to obtain the edge contours of the markers, thereby achieving accurate positioning. To evaluate the performance of this method, we conducted displacement measurements on stationary markers placed on a vibration isolation platform. When the camera was positioned 0.6 meters away from the markers, the standard deviations of in-plane displacements in two directions were found to be 0.36 μm and 0.32 μm, respectively, while that of out-of-plane displacement was 0.58 μm. Additionally, by using a displacement stage to provide standard displacements, we further validated the applicability of the algorithm in measuring the structure displacements with inclined surfaces at a 60° angle to the camera plane, as well as ∅12 mm small-diameter pipelines. The proposed visual measurement system was applied in a static test of an engine frame, yielding satisfactory results. The experiments demonstrated that the algorithm could track the displacements of 29 circular markers in real time, with a maximum error of 5.6% compared to an inductive displacement sensor. In comparison to traditional contact-based displacement testing methods, the visual testing method offers numerous advantages, including rapid setup, low cost, high measurement accuracy, and the ability to increase the measurement quantity without significantly increasing workload, making it a reliable and effective alternative to traditional displacement testing methods.