A building construction data processing method based on BIM

By introducing time dimension information and differentiated compression algorithms into the BIM model, key structural information is identified and protected, solving the construction deviation problem caused by data compression in existing technologies, and achieving efficient data management and construction accuracy.

CN122365657APending Publication Date: 2026-07-10SHAANXI COAL & CHEM CONSTR (GRP) CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
SHAANXI COAL & CHEM CONSTR (GRP) CO LTD
Filing Date
2026-04-13
Publication Date
2026-07-10

AI Technical Summary

Technical Problem

Existing BIM model compression methods do not fully utilize time-dimensional information, which may lead to deviations in key structural information during the construction phase and affect the accuracy of on-site construction.

Method used

By acquiring BIM models from different construction stages, structural feature analysis and confidence assessment are performed, cluster distances are adjusted, key structural clusters are identified, and a differentiated compression algorithm is used to process data points to ensure the integrity of key structural information.

Benefits of technology

It achieves the goal of reducing data volume while preserving the integrity of key structural information, reducing the loading pressure on mobile devices, improving the accuracy and efficiency of construction sites, and supporting full-process data management and analysis.

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Abstract

This invention discloses a BIM-based method for processing building construction data, comprising: acquiring BIM models of the same building project at different construction stages and arranging them in chronological order to obtain a sequence of three-dimensional building models; performing structural feature analysis on the target three-dimensional building model and calculating the structural feature information of each data point; evaluating the confidence level of data points in the target model based on the sequence of three-dimensional building models; adjusting the clustering distance according to the confidence level to relatively reduce the clustering distance between high-confidence data points; performing cluster analysis using the adjusted clustering distance to obtain several clusters; identifying key structural clusters; applying a first compression algorithm to the key structural clusters and a second compression algorithm to the non-key structural clusters. This invention, by introducing the time dimension information of multi-stage models, accurately identifies key structural features, effectively maintaining the geometric accuracy of the core structure while ensuring the compression rate, and has good engineering applicability.
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