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

초록

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

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