All Issue

2024 Vol.66, Issue 5
Structural Shape Estimation Based on 3D LiDAR Scanning Method for On-site Safety Diagnostic of Plastic Greenhouse

비닐 온실의 현장 안전진단을 위한 3차원 LiDAR 스캔 기법 기반 구조 형상 추정

Byung-hun Seoa
,
Sangik Leeb
,
Jonghyuk Leea
,
Dongsu Kima
,
Dongwoo Kimc
,
Yerim Joc
,
Yuyong Kimd
,
Jeongmin Leed
,
Won Choie†
서 병훈a
,
이 상익b
,
이 종혁a
,
김 동수a
,
김 동우c
,
조 예림c
,
김 유용d
,
이 정민d
,
최 원e†
aPh.D. Student, Department of Rural Systems Engineering, Integrated Major in Global Smart Farm, Seoul National University
bAssistant Professor, Department of Agricultural Civil Engineering, Kyungpook National University
cMS Student, Department of Rural Systems Engineering, Seoul National University
dResearcher, National Institute of Agricultural Sciences, Rural Development Administration
eAssociate Professor, Department of Rural Systems Engineering, Research Institute of Agriculture and Life Sciences, Integrated Major in Global Smart Farm, Seoul National University
a서울대학교 농촌시스템공학과 박사과정 글로벌스마트팜 통합전공
b경북대학교 농업토목공학과 조교수
c서울대 농촌시스템공학과 학생
d국립농업과학원 농촌진흥청 연구원
e서울대학교 농업생명과학연구소 농촌시스템공학과 부교수 글로벌스마트팜 통합전공
† Corresponding author Tel.: +82-2-880-4715, Fax: +82-2-873-2087 E-mail: fembem@snu.ac.kr
2024. pp. 1-13
PDF XML Citation
Abstract

In this study, we applied an on-site diagnostic method for estimating the structural safety of a plastic greenhouse. A three-dimensional light detection and ranging (3D LiDAR) sensor was used to scan the greenhouse to extract point cloud data (PCD). Differential thresholds of the color index were applied to the partitions of raw PCD to separate steel frames from plastic films. Additionally, the K-means algorithm was used to convert the steel frame PCD into the nodes of unit members. These nodes were subsequently transformed into structural shape data. To verify greenhouse shape reproducibility, the member lengths of the scan and blueprint models were compared with the measurements along the X-, Y-, and Z-axes. The error of the scan model was accurate at 2%-3%, whereas the error of the blueprint model was 5.4%. At a maximum snow depth of 0.5 m, the scan model revealed asymmetric horizontal deflection and extreme bending stress, which indicated that even minor shape irregularities could result in critical failures in extreme weather. The safety factor for bending stress in the scan model was 18.7% lower than that in the blueprint model. This phenomenon indicated that precise shape estimation is crucial for safety diagnostic. Future studies should focus on the development of an automated process based on supervised learning to ensure the widespread adoption of greenhouse safety diagnostics.

Keywords
Light detection and ranging (LiDAR)
plastic greenhouse
structural analysis
structural safety diagnostic
unsupervised algorithm
References

REFERENCES

1
P. K. Agarwal and C. M. Procopiuc, Algorithmica, Exact and approximation algorithms for clustering, 33; 201-226 (2002)10.1007/s00453-001-0110-y
2
M. Bassier and M. Vergauwen, Automation in Construction, Unsupervised reconstruction of building information modeling wall objects from point cloud data, 120; 103338 (2020)10.1016/j.autcon.2020.103338
3
G. Bitelli, G. Castellazzi, A. M. D’altri, S. De Miranda, A. Lambertini and I. Selvaggi, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Automated voxel model from point clouds for structural analysis of cultural heritage, 41; 191-197 (2016)10.5194/isprsarchives-xli-b5-191-2016
4
M. K. Choi, H. R. Ryu, M. W. Cho and I. H. Yu, Journal of Bio- Environment Control, Effect of the member joint on structural performance of an arch-type multi-span greenhouse: A full-scale experimental and numerical study, 26(4); 402-410, (in Korean) (2017)10.12791/ksbec.2017.26.4.402
5
M. Javaid, A. Haleem, R. P. Singh and R. Suman, Sensors International, Industrial perspectives of 3D scanning: Features, roles and its analytical applications, 2; 100114 (2021)10.1016/j.sintl.2021.100114
6
Z. Ji, Y. Wang and R. Zhao, Highlights in Science, Engineering and Technology, Bridge structure and material stability analysis using Monte Carlo and COMSOL 3D modeling, 28; 193-199 (2022)10.54097/hset.v28i.4106
7
J. Y. Lee and H. R. Ryu, Engineering Structures, Structural analysis of pipe-framed greenhouses using interface elements for cross-over connections, 266; 114504 (2022)10.1016/j.engstruct.2022.114504
8
S. I. Lee, J. H. Lee, Y. J. Jeong and W. Choi, Biosystems Engineering, Development of a structural analysis model for pipe structures to reflect ground conditions, 197; 231-244 (2020)10.1016/j.biosystemseng.2020.06.018
9
S. I. Lee, J. H. Lee, Y. J. Jeong, D. S. Kim, B. H. Seo, Y. J. Seo and W. Choi, Journal of the Korean Society of Agricultural Engineers, System reliability analysis of semi-rigid frame structures - Focusing on greenhouses, 64(5); 67-77, (in Korean) (2022)
10
H. Liu, X. Wang, Z. Li and Z. Zhong, In Hydraulic and Civil Engineering Technology VII, Comparative study on ultimate stress test and COMSOL analysis of steel beam of pull-up cantilever scaffold; 525-531 (2022)10.3233/atde220907
11
D. Mader, R. Blaskow, P. Westfeld and C. Weller, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Potential of UAV-based laser scanner and multispectral camera data in building inspection, 41; 1135-1142 (2016)10.5194/isprs-archives-xli-b1-1135-2016
12
Ministry of Agriculture, Food and Rural Affairs, Agriculture, food and rural affairs statistical yearbook 2022, No.11-1543000-000128-10 (in Korean) (2023a)
13
Ministry of Agriculture, Food and Rural Affairs, Regulations on the registration of disaster resistant design standards and disaster resistant facility standards for horticultural and special production facilities, No. 2022-104 (in Korean) (2023b)
14
Ministry of the Interior and Safety, 2022 Disaster Report, (in Korean) (2023)
15
S. W. Nam and I. H. Yu, Journal of the Korean Society of Agricultural Engineers, Survey and analysis of the structure and maintenance status of pipe frame greenhouses, 42(4); 106-114, (in Korean) (2000)
16
X. Pan and T. Y. Yang, Journal of Building Engineering, 3D vision-based bolt loosening assessment using photogrammetry, deep neural networks, and 3D point-cloud processing, 70; 106326 (2023)10.1016/j.jobe.2023.106326
17
M. Pepe, D. Costantino and A. Restuccia Garofalo, Applied Sciences, An efficient pipeline to obtain 3D model for HBIM and structural analysis purposes from 3D point clouds, 10(4); 1235 (2020)10.3390/app10041235
18
R. Rolin, E. Antaluca, J. L. Batoz, F. Lamarque and M. Lejeune, Journal on Computing and Cultural Heritage (JOCCH), From point cloud data to structural analysis through a geometrical hBIM-oriented model, 12(2); 1-26 (2019)10.1145/3242901
19
Rural Development Administration, Greenhouse structural design standards (Draft), (in Korean) (2017)
20
H. R. Ryu, E. H. Lee, M. W. Cho, I. H. Yu and Y. C. Kim, Journal of Bio-Environment Control, Evaluation on the behavioral characteristics of plastic greenhouse by full-scale testing and finite element analysis, 21(4); 459-465, (in Korean) (2012)10.12791/ksbec.2012.21.4.459
21
H. R. Ryu, I. H. Yu, M. W. Cho and Y. C. Um, Journal of Bio-Environment Control, Structural reinforcement methods and structural safety analysis for the elevated eaves height 1-2W type plastic greenhouse, 18(3); 192-199, (in Korean) (2009)
22
W. M. Suh, M. K. Choi, Y. H. Bae, J. W. Lee and Y. C. Yoon, Journal of Bio-Environment Control, Structural safely analysis of a modified 1-2W type greenhouse enhanced for culturing paprika, 17(3); 197-203, (in Korean) (2008)
23
H. Tran and K. Khoshelham, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Building change detection through comparison of a lidar scan with a building information model, 42; 889-893 (2019)10.5194/isprs-archives-xlii-2-w13-889-2019
24
A. Trias, Y. Yu, J. Gong and F. L. Moon, Structure and Infrastructure Engineering, Supporting quantitative structural assessment of highway bridges through the use of LiDAR scanning, 18(6); 824-835 (2022)10.1080/15732479.2021.1880446
25
R. L. Wood and M. E. Mohammadi, International LiDAR Mapping Forum, LiDAR scanning with supplementary UAV captured images for structural inspections, 2015; 10 (2015)
Information
  • Publisher :The Korean Society of Agricultural Engineers
  • Publisher(Ko) :한국농공학회
  • Journal Title :Journal of Korean Society of Agricultural Engineers
  • Journal Title(Ko) :한국농공학회논문집
  • Volume : 66
  • No :5
  • Pages :1-13
  • Received Date : 2024-06-11
  • Revised Date : 2024-07-08
  • Accepted Date : 2024-07-15
  • DOI :https://doi.org/10.5389/KSAE.2024.66.5.001
Journal Informaiton Journal of Korean Society of Agricultural Engineers Journal of Korean Society of Agricultural Engineers
  • NRF
  • KOFST
  • crossref crossmark
  • crossref cited-by
  • crossref funder-registry
  • crosscheck
  • orcid
  • open access
Journal Informaiton Journal Informaiton - close