Evaluation of data acquisition techniques and workflows for Scan to BIM
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Transcript of Evaluation of data acquisition techniques and workflows for Scan to BIM
![Page 1: Evaluation of data acquisition techniques and workflows for Scan to BIM](https://reader034.fdocuments.us/reader034/viewer/2022051315/55c795b2bb61eb9e6f8b47c4/html5/thumbnails/1.jpg)
Evaluation of data
acquisition techniques
and workflows for Scan
to BIM
Maarten Bassier
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Scan to BIM
• AEC industry buildings
• Mid-to-large scale data sets
• LOD 300
• LOA 30
Image from http://www.severnpartnership.com/
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Traditional Workflow
Images from http://www.quantapoint.com/, http://www.laserscan-3d.com/,
http://nl.kubit-software.com/
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Workflow optimization
• Terrestrial laser scanner measurements
• High overlap
• Cloud to cloud registration
• Network optimization
• Loop closure
• GPS for geolocation
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Mid-Scale Test Case
Dataset from http://www.3dgeosolutions.nl/
• 70x40x4m
• 97 scans
• 5-10 m/scan
• 4h acquisition
• 97 manual constraints
• 1500 auto constraints
• 7h post-processing
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Mid-Scale Test Case
Dataset from http://www.3dgeosolutions.nl/
• 33 targets
• ±2mm
• < 1day
Acquisition time [h] Post processing [h] Total
[h]
Traditional workflow Point cloud 4 7 11
Total station 4 3 7
Efficiency 50% 30% 39%
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Mid-Scale Test Case
Dataset from http://www.3dgeosolutions.nl/
X Y Z
% within specification
(1.5cm) 100% 100% 100%
Biggest error [m] 0,0068 0,0079 0,0120
RMSE [m] 0,0025 0,0028 0,0051
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Mid-Scale Test Case
4m
Dataset from http://www.3dgeosolutions.nl/
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Mid-Scale Test Case
Dataset from http://www.3dgeosolutions.nl/
0.004
0.002
0.002
0.005
0.001 0.011
0.003
0.004
0.006
0.006
0.005
0.003
0.005
0.005
0.005
0.006
0.001
0.001 0.001
0.003
0.002
0.005 0.002
0.012 0.003 0.004
0.003
0.0
0.0
0.004
• Deviations [m]
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Mid-Scale Test Case
Dataset from http://www.3dgeosolutions.nl/
150m ≈ 22,500m²
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Large-Scale Test Case
Dataset from http://www.3dgeosolutions.nl/
• 250x100x10m
• 422 scans
• 16h acquisition
• 421 manual constraints
• 4900 auto constraints
• 30h post-processing
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Large-Scale Test Case
Dataset from http://www.3dgeosolutions.nl/
• 146 targets
• ±2mm
• < 1day
Acquisition time [h] Post processing [h] Total
[h]
Traditional workflow Point cloud 16 30 46
Total station 16 5 21
GPS 3 1 4
Efficiency 46% 14% 30%
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Large-Scale Test Case
X Y Z
% within specification
(1.5cm) 100% 100% 64%
Biggest error [m] 0,0117 0,0107 0,0371
RMSE [m] 0,0052 0,0040 0,0170
0.037 0.011
0.012
0.013
0.010
0.003
0.017
0.020
0.015 0.019
0.017
0.013
Dataset from http://www.3dgeosolutions.nl/
0.007
0.008
• Deviations [m]
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Large-Scale Test Case
Dataset from http://www.3dgeosolutions.nl/
200m ≈ 40,000m²
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Prediction models
Dataset from http://www.3dgeosolutions.nl/
250m
70m
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GPS integration
Dataset from http://www.3dgeosolutions.nl/
X Y Z
% within specification
(1.5cm) 100% 100% 100%
Biggest error [m] 0,0140 0,0126 0,0149
RMSE [m] 0,0067 0,0051 0,0071
• 6 GPS targets • ±1,5cm
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Conclusions
• Terrestrial laserscanning is the best solution for mid-to-
large scale Scan to BIM projects
• Cloud to cloud registration and GPS measurements
can acquire project deliverables without total station
measurements
• Depending on data variance, predictions can be made
about project accuracy