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A Synergistic Method for Deformation Sensing of Port Approach Bridges Based on BIM and Multi-Source Remote Sensing
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Honglei ZHU1, Liqiang HOU1, Pengfei JIANG2, Lei GU3
Industrial Construction | 2026, 56(5) : 201 - 207
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Industrial Construction | 2026, 56(5): 201-207
A Synergistic Method for Deformation Sensing of Port Approach Bridges Based on BIM and Multi-Source Remote Sensing
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Honglei ZHU1, Liqiang HOU1, Pengfei JIANG2, Lei GU3
Affiliations
  • 1Power China SEPCO1 Electric Power Construction Co., Ltd., Jinan250102, China
  • 2Coal Mine, Yankuang Energy Group Company Limited, Jining272069, China
  • 3College of Mechanical and Electrical Engineering, Hohai University, Changzhou213200, China
Published: 2026-05-20 doi: 10.3724/j.gyjzG26020903
Outline
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In order to accurately separate the contributions of foundation settlement and structural damage to the deformation of port approach bridges and realize the physical attribution of structural damage, an integrated framework of "multi-source perception–physical modeling–deviation diagnosis" was adopted to develop a synergistic method combining time-series PS-InSAR-based foundation settlement monitoring, high-resolution optical image shadow analysis, and BIM-based parametric mechanical modeling. First, under a unified spatiotemporal datum, time-series PS-InSAR technology was applied to extract the foundation settlement field, while an improved Normalized Shadow Index (NSI) was used to invert the relative deformation at the tops of bridge piers. Second, an LOD350-level BIM model was converted into a parametric beam-grid mechanical model, and foundation settlement as well as thermal loads were taken as inputs to calculate the theoretical deformation response. Finally, a Damage Risk Index (DRI) was constructed to quantify the deviation between monitored and theoretical deformations, enabling damage early warning and localization. Closed-loop verification was further performed using an actual engineering case. The results showed that the proposed method achieved a mean absolute error (MAE) of approximately 1.14 mm and a root mean square error (RMSE) of approximately 1.46 mm in deformation monitoring, with 88% of data points having an error no greater than 2 mm and a damage identification accuracy of 93.7%. This method also supports the full-chain diagnostic process of "large-scale early warning – localized positioning – on-site verification – repair validation". It is concluded that this method effectively overcomes the limitations of single remote sensing techniques in interpreting deformation causes, achieves the transition from "phenomenon perception" to "mechanism interpretation", and thus provides a reliable technical paradigm for the intelligent operation and maintenance of long linear steel-structure infrastructures such as port approach bridges.

BIM  /  multi-source remote sensing  /  damage diagnosis  /  digital twin
Honglei ZHU, Liqiang HOU, Pengfei JIANG, Lei GU. A Synergistic Method for Deformation Sensing of Port Approach Bridges Based on BIM and Multi-Source Remote Sensing[J]. Industrial Construction, 2026 , 56 (5) : 201 -207 . DOI: 10.3724/j.gyjzG26020903
Year 2026 volume 56 Issue 5
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Article Info
doi: 10.3724/j.gyjzG26020903
  • Receive Date:2026-02-09
  • Online Date:2026-06-25
  • Published:2026-05-20
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  • Received:2026-02-09
Affiliations
    1Power China SEPCO1 Electric Power Construction Co., Ltd., Jinan250102, China
    2Coal Mine, Yankuang Energy Group Company Limited, Jining272069, China
    3College of Mechanical and Electrical Engineering, Hohai University, Changzhou213200, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
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占总种数比例
Percentage of
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种数
Number of
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Percentage of total
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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