Automated Optical Inspection and Image Analysis of Superconducting Radio-Frequency Cavities

The inner surface of superconducting cavities plays a crucial role to achieve highest accelerating fields and low losses. For an investigation of this inner surface of more than 100 cavities within the cavity fabrication for the European XFEL and the ILC HiGrade Research Project, an optical inspection robot OBACHT was constructed. To analyze up to 2325 images per cavity, an image processing and analysis code was developed and new variables to describe the cavity surface were obtained. The accuracy of this code is up to 97% and the PPV 99% within the resolution of 15.63 $\mu \mathrm{m}$. The optical obtained surface roughness is in agreement with standard profilometric methods. The image analysis algorithm identified and quantified vendor specific fabrication properties as the electron beam welding speed and the different surface roughness due to the different chemical treatments. In addition, a correlation of $\rho = -0.93$ with a significance of $6\,\sigma$ between an obtained surface variable and the maximal accelerating field was found

Robust surface segmentation and edge feature lines extraction from fractured fragments of relics

AbstractSurface segmentation and edge feature lines extraction from fractured fragments of relics are essential steps for computer assisted restoration of fragmented relics. As these fragments were heavily eroded, it is a challenging work to segment surface and extract edge feature lines. This paper presents a novel method to segment surface and extract edge feature lines from triangular meshes of irregular fractured fragments. Firstly, a rough surface segmentation is accomplished by using a clustering algorithm based on the vertex normal vector. Secondly, in order to differentiate between original and fracture faces, a novel integral invariant is introduced to compute the surface roughness. Thirdly, an accurate surface segmentation is implemented by merging faces based on face normal vector and roughness. Finally, edge feature lines are extracted based on the surface segmentation. Some experiments are made and analyzed, and the results show that our method can achieve surface segmentation and edge extraction effectively

Geometric reconstruction methods for electron tomography

Electron tomography is becoming an increasingly important tool in materials science for studying the three-dimensional morphologies and chemical compositions of nanostructures. The image quality obtained by many current algorithms is seriously affected by the problems of missing wedge artefacts and nonlinear projection intensities due to diffraction effects. The former refers to the fact that data cannot be acquired over the full $180^\circ$ tilt range; the latter implies that for some orientations, crystalline structures can show strong contrast changes. To overcome these problems we introduce and discuss several algorithms from the mathematical fields of geometric and discrete tomography. The algorithms incorporate geometric prior knowledge (mainly convexity and homogeneity), which also in principle considerably reduces the number of tilt angles required. Results are discussed for the reconstruction of an InAs nanowire

A Regularization Technique for the Analysis of Photographic Data Used in Chemical Release Wind Measurements

The neutral winds are a key parameter in the electrodynamics of the ionosphere. The available techniques for measuring vertical neutral wind profiles, especially with good height resolution, are extremely limited. This is especially true with sounding rocket flights as it is not practical to take direct measurements of neutral winds with onboard instruments. Chemical releases from sounding rockets, however, allow such measurements by providing a tracer of the motion of the neutral atmosphere at altitudes in the mesosphere and lower thermosphere (MLT). The resulting chemiluminescent trail is typically photographed from two or more locations to track neutral motions. Triangulation based on these photographs then yields position information at each instant when simultaneous photographs are available from different locations. The resulting time series of position information can then be used to obtain a neutral wind profile. A technique is presented that improves this existing triangulation procedure by implementing computer vision-based automation techniques and an improved tracking algorithm that can accommodate non-simultaneous image data more easily and can provide better continuity in the motions inferred from consecutive images. Neutral wind profiles from the Joule II and HEX II sounding rocket experiments are presented and compared with results from the previous method