Alignment detection of segmental precast bridges via close-range photogrammetry

Abstract:

To address the reliance on manual inspection and the low efficiency of alignment detection during the segmental precast bridge construction process, a method for detecting assembly alignment is proposed based on close-range photogrammetry. The principles of close-range photogrammetry are integrated and the rigorous forward intersection and bundle adjustment algorithms are employed to enhance the accuracy and efficiency of alignment detection in bridge construction. According to actual engineering scenarios, simulation software and an indoor experimental setup were used to conduct both simulated and real indoor experiments, exploring the feasibility of the proposed method and the influence of shooting distance and the number of segmental beams on measurement accuracy. Experimental results show that the method can process captured image data in real time to obtain the bridge’s alignment data. Using bundle adjustment, the measurement accuracy of target points can be significantly improved to within 2 mm, and the resulting bridge alignment accuracy reaches within 1 mm, which verifies the effectiveness of the technique. Additionally, under various shooting distances, the method can still accurately identify marker points through sufficient pixel data while maintaining consistent measurement accuracy, ensuring the reliability and stability of the alignment detection results. The study demonstrates that this method not only improves the reliability of bridge construction but also significantly enhances the efficiency of alignment detection, providing strong support for the successful implementation of bridge construction projects.