Estimation of Surface Normals of Aerospace Fasteners from 3D Terrestrial Laser Scanner Point Clouds
Open Access
Abstract
Measurement systems such as laser trackers and 3D imaging systems are being increasingly adopted across the manufacturing industry. These metrology technologies can allow for live, high-precision measurement in a digital system, enabling the spatial component of the digital manufacturing twin. In aircraft wing manufacturing, drilling and fastening operations must be guided by precise measurements from a digital design model. With thousands of fasteners on each aircraft wing, even small errors in alignment of surface covers to wing ribs and spars can impact component longevity due to aerodynamic drag. Determining surface conformance of airstream-facing surfaces is currently largely performed though manual gauge checking by human operators. In order to capture the surface details and reverse engineer components to assure tolerance has been achieved, laser scanners could be utilised alongside a precise registration strategy. This work explores the quality of the aerostructure surface in a captured point cloud and the subsequent accuracy of surface normal determination from planar fastener heads. These point clouds were captured with a reference hand-held laser scanner and two terrestrial laser scanners. This study assesses whether terrestrial laser scanners can achieve <0.5° surface normal accuracy for aerospace fastener alignment. Accuracy of the surface normals was achieved with a nominal mean discrepancy of 0.42 degrees with the Leica RTC360 3D Laser Scanner (Leica Geosystems AG, Heerbrugg, Switzerland) and 0.27 degrees with the Surphaser 80HSX Ultra Short Range (Basis Software Inc., Redmond, WA, USA).Keywords
Funding Information
- Engineering and Physical Sciences Research Council (EP/R513143/1, EP/T517793/1)
This publication has 18 references indexed in Scilit:
- Radiometric correction of laser scanning intensity data applied for terrestrial laser scanningISPRS Journal of Photogrammetry and Remote Sensing, 2021
- A case study on use of 3D scanning for reverse engineering and quality controlMaterials Today: Proceedings, 2021
- Assessment of handheld mobile terrestrial laser scanning for estimating tree parametersJournal of Forestry Research, 2020
- Computational Methods of Acquisition and Processing of 3D Point Cloud Data for Construction ApplicationsArchives of Computational Methods in Engineering, 2019
- A comparison study of algorithms for surface normal determination based on point cloud dataPrecision Engineering, 2015
- Quality assurance for high-frequency mechanical impact (HFMI) treatment of welds using handheld 3D laser scanning technologyWelding in the World, 2014
- A novel method of surface-normal measurement in robotic drilling for aircraft fuselage using three laser range sensors2012
- A comparison of algorithms for vertex normal computationThe Visual Computer, 2005
- Weights for Computing Vertex Normals from Facet NormalsJournal of Graphics Tools, 1999
- Extracting Geometric PrimitivesCVGIP: Image Understanding, 1993