大型结构应变片多源测量融合定位映射OA

For low efficiency and error-sensitive positioning in large structural static testing,a multi-source heterogeneous measurement fusion positioning and mapping method was proposed.Under a unified spatial measurement framework,multi-device collaboration and uncertainty-weighted fusion coordinated la-ser tracker,3D scanner,and laser projector measurement.High-precision entity models were constructed using multi-station point cloud splicing technology,and the density-based dynamic neighborhood search al-gorithm and position correction software automatically compensated for manufacturing deviations.An end-to-end uncertainty transfer model was constructed and verified through Monte Carlo methods.For a model with 66 613 facets,the improved algorithm reduced neighborhood facet retrieval by 38%～45%,short-ened calculation time to 18.2-20.5 s,and improved efficiency by 17%-26%.High-density tests based on 200 points showed max 0.454 mm and mean 0.400 mm errors,significantly lower than traditional manual methods.The repeatability test pooled standard deviation was 0.178 mm.Within the 3～10 m measure-ment range,positioning error remained within 1 mm.Uncertainty analysis showed a combined standard uncertainty of approximately 0.42 mm,consistent with experimental results.For 200-points positioning scenarios,total time decreased from 1 277 min to 95 min,representing efficiency improvement exceeding 100%.This method significantly improves positioning efficiency while maintaining high precision,and achieves interpretability and traceability of measurement results through uncertainty modeling.It demon-strates good stability,adaptability,and engineering application potential under different materials,struc-tures,and measurement distance conditions,providing effective technical support for high-precision rapid positioning in large complex structural testing.