学术动态:Fusion of Embedded Vision and Intelligent Algorithms for Non-Contact Deformation Monitoring-星律科技

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学术动态:Fusion of Embedded Vision and Intelligent Algorithms for Non-Contact Deformation Monitoring

2026-05-25 16:00:22

论文标题:Fusion of Embedded Vision and Intelligent Algorithms for Non-Contact Deformation Monitoring

发布日期:2026-05-25

作者:Mei Dong, Xinyu Liu, Hui Hu, Eisha Zahra, Kuihua Wang

DOI:10.3390/s26113338

论文摘要:With the increasing demand for reliable structural safety assessment in service, high-precision, non-contact, and long-term deformation monitoring has become increasingly urgent for large civil engineering structures. To address this need, this study proposes and validates a system-level non-contact monitoring framework that integrates an embedded vision-based deformation sensor with intelligent algorithms. Rather than treating individual techniques as isolated components, the proposed framework integrates high-precision optical imaging, subpixel localization, and intelligent image processing into a unified monitoring workflow. By continuously imaging and tracking targets on the structural surface, high-precision acquisition of two-dimensional dynamic displacements is achieved. To address issues such as image jitter, environmental disturbances, and camera-induced vibrations under long-distance imaging conditions, a hybrid algorithm based on signal processing and image correction is introduced to effectively compensate and filter the monitoring data, thereby significantly improving the stability and accuracy of deflection measurements. In engineering applications, a girder bridge and an integral open-box sluice structure were selected as monitoring objects, and field experiments were conducted over multiple periods under different working conditions. The results indicate that the proposed system can stably capture small structural displacements, achieving sub-millimeter measurement accuracy. The findings verify the feasibility and reliability of the proposed intelligent vision-based deformation monitoring technology in complex engineering environments, and provide a new technical approach for structural safety assessment and operational monitoring of infrastructure such as bridges and hydraulic structures.

元数据:Crossref 收录的 MDPI Sensors 论文。 DOI: 10.3390/s26113338. Vol. 26, Issue 11. Authors: Mei Dong, Xinyu Liu, Hui Hu, Eisha Zahra, Kuihua Wang.

开放许可:https://creativecommons.org/licenses/by/4.0/

原文链接:https://doi.org/10.3390/s26113338

PDF 链接:https://www.mdpi.com/1424-8220/26/11/3338/pdf


来源:MDPI Sensors via Crossref

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