Методика анализа объемных дефектов по цифровой модели рельефа поверхности

2021 ◽  
pp. 41-48
Author(s):  
А.А. Дедкова ◽  
И.В. Флоринский ◽  
Е.Э. Гусев ◽  
Н.А. Дюжев ◽  
М.Ю. Фомичев ◽  
...  
Keyword(s):  
Quality Control ◽  
Silicon Wafer ◽  
Gaussian Curvature ◽  
Mean Curvature ◽  
Surface Defects ◽  
Individual Volume ◽  
Digital Elevation ◽  
Silicon Silicon ◽  
Minimum Curvature ◽  
Shape And Size

We developed a technique for revealing and analyzing volumetric surface defects based on geomorphometric modeling, in particular, an analysis of models and maps of some morphometric variables (minimum curvature, maximum curvature, mean curvature, Gaussian curvature, unsphericity, etc.), derived from digital elevation models of a surface. The technique allows one to reveal areas of individual volume defects (cracks, film delaminations, shape deviations, etc.), to determine shape and size of both the defects themselves and adjucent modified areas, as well as to study patterns of their distribution. The technique effectiveness is exempified by defects on silicon–glass and silicon–silicon wafer assemblies, as well as a cracked Ni–W film. The technique can be promising for quality control of manufacturing and diagnostics of damages of various items, in particular, microelectronic products.

scholarly journals A New Approach to the Quality Control of Slope and Aspect Classes Derived from Digital Elevation Models

2021 ◽  
Vol 13 (11) ◽  
pp. 2069
Author(s):  
M. V. Alba-Fernández ◽  
F. J. Ariza-López ◽  
M. D. Jiménez-Gamero
Keyword(s):  
Quality Control ◽  
Hypothesis Test ◽  
Simulated Data ◽  
Slope Aspect ◽  
New Approach ◽  
Reference Set ◽  
Digital Elevation ◽  
Using Data ◽  
Elevation Model ◽  
Degree Of Similarity

The usefulness of the parameters (e.g., slope, aspect) derived from a Digital Elevation Model (DEM) is limited by its accuracy. In this paper, a thematic-like quality control (class-based) of aspect and slope classes is proposed. A product can be compared against a reference dataset, which provides the quality requirements to be achieved, by comparing the product proportions of each class with those of the reference set. If a distance between the product proportions and the reference proportions is smaller than a small enough positive tolerance, which is fixed by the user, it will be considered that the degree of similarity between the product and the reference set is acceptable, and hence that its quality meets the requirements. A formal statistical procedure, based on a hypothesis test, is developed and its performance is analyzed using simulated data. It uses the Hellinger distance between the proportions. The application to the slope and aspect is illustrated using data derived from a 2×2 m DEM (reference) and 5×5 m DEM in Allo (province of Navarra, Spain).

scholarly journals Umbilical points on surfaces in RN

1985 ◽  
Vol 100 ◽  
pp. 135-143 ◽  
Author(s):  
Kazuyuki Enomoto
Keyword(s):  
Gaussian Curvature ◽  
Mean Curvature ◽  
Curvature Vector ◽  
Mean Curvature Vector ◽  
Normal Connection ◽  
Round Sphere ◽  
Positive Gaussian Curvature ◽  
Connected Surface ◽  
Umbilical Points ◽  
The Mean

Let ϕ: M → RN be an isometric imbedding of a compact, connected surface M into a Euclidean space RN. ψ is said to be umbilical at a point p of M if all principal curvatures are equal for any normal direction. It is known that if the Euler characteristic of M is not zero and N = 3, then ψ is umbilical at some point on M. In this paper we study umbilical points of surfaces of higher codimension. In Theorem 1, we show that if M is homeomorphic to either a 2-sphere or a 2-dimensional projective space and if the normal connection of ψ is flat, then ψ is umbilical at some point on M. In Section 2, we consider a surface M whose Gaussian curvature is positive constant. If the surface is compact and N = 3, Liebmann’s theorem says that it must be a round sphere. However, if N ≥ 4, the surface is not rigid: For any isometric imbedding Φ of R3 into R4 Φ(S2(r)) is a compact surface of constant positive Gaussian curvature 1/r2. We use Theorem 1 to show that if the normal connection of ψ is flat and the length of the mean curvature vector of ψ is constant, then ψ(M) is a round sphere in some R3 ⊂ RN. When N = 4, our conditions on ψ is satisfied if the mean curvature vector is parallel with respect to the normal connection. Our theorem fails if the surface is not compact, while the corresponding theorem holds locally for a surface with parallel mean curvature vector (See Remark (i) in Section 3).

scholarly journals Modified Roller Coaster Surface in Space

Mathematics ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 195 ◽  
Author(s):  
Selçuk BAŞ ◽  
Talat KÖRPINAR
Keyword(s):  
Gaussian Curvature ◽  
Mean Curvature ◽  
Roller Coaster ◽  
Orthogonal Frame

In this paper, a new modified roller coaster surface according to a modified orthogonal frame is investigated in Euclidean 3-space. In this method, a new modified roller coaster surface is modeled. Both the Gaussian curvature and mean curvature of roller coaster surfaces are investigated. Subsequently, we obtain several characterizations in Euclidean 3-space.

scholarly journals On the second Gaussian curvature of ruled surfaces in Euclidean $3$-space

2006 ◽  
Vol 37 (3) ◽  
pp. 221-226 ◽  
Author(s):  
Dae Won Yoon
Keyword(s):  
Euclidean Space ◽  
Gaussian Curvature ◽  
Mean Curvature ◽  
Ruled Surface ◽  
Ruled Surfaces ◽  
Dimensional Euclidean Space ◽  
3 Dimensional ◽  
The Mean ◽  
Second Gaussian Curvature

In this paper, we mainly investigate non developable ruled surface in a 3-dimensional Euclidean space satisfying the equation $K_{II} = KH$ along each ruling, where $K$ is the Gaussian curvature, $H$ is the mean curvature and $K_{II}$ is the second Gaussian curvature.

scholarly journals A large-scale image dataset of wood surface defects for automated vision-based quality control processes

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 581
Author(s):  
Pavel Kodytek ◽  
Alexandra Bodzas ◽  
Petr Bilik
Keyword(s):  
Quality Control ◽  
High Speed ◽  
Large Scale ◽  
Surface Defects ◽  
Recognition Rate ◽  
Raw Material ◽  
Technical Solution ◽  
Control Processes ◽  
Wide Range ◽  
Authentic Data

The wood industry is facing many challenges. The high variability of raw material and the complexity of manufacturing processes results in a wide range of visible structure defects, which have to be controlled by trained specialists. These manual processes are not only tedious and biased, but also less effective. To overcome the drawbacks of the manual quality control processes, several automated vision-based systems have been proposed. Even though some conducted studies achieved a higher recognition rate than trained experts, researchers have to deal with a lack of large-scale databases and authentic data in this field. To address this issue, we performed a data acquisition experiment set in the industrial environment, where we were able to acquire an extensive set of authentic data from a production line. For this purpose, we designed and implemented a complex technical solution suitable for high-speed acquisition during harsh manufacturing conditions. In this data note, we present a large-scale dataset of high-resolution sawn timber surface images containing more than 43 000 labelled surface defects and covering 10 types of the most common wood defects. Moreover, with each image record, we provide two types of labels allowing researchers to perform semantic segmentation, as well as defect classification, and localization.

scholarly journals Growth and Self-Assembly of Silicon–Silicon Carbide Nanoparticles into Hybrid Worm-Like Nanostructures at the Silicon Wafer Surface

Nanomaterials ◽  
2018 ◽  
Vol 8 (11) ◽  
pp. 954 ◽  
Author(s):  
Manuel Perez-Guzman ◽  
Rebeca Ortega-Amaya ◽  
Yasuhiro Matsumoto ◽  
Andres Espinoza-Rivas ◽  
Juan Morales-Corona ◽  
...  
Keyword(s):  
Silicon Carbide ◽  
Silicon Wafer ◽  
Self Assembly ◽  
Silicon Nanoparticles ◽  
Hybrid Nanostructures ◽  
Wafer Surface ◽  
Silicon Carbide Nanoparticles ◽  
Silicon Based ◽  
Silicon Silicon ◽  
Si Wafer

This work describes the growth of silicon–silicon carbide nanoparticles (Si–SiC) and their self-assembly into worm-like 1D hybrid nanostructures at the interface of graphene oxide/silicon wafer (GO/Si) under Ar atmosphere at 1000 °C. Depending on GO film thickness, spread silicon nanoparticles apparently develop on GO layers, or GO-embedded Si–SiC nanoparticles self-assembled into some-micrometers-long worm-like nanowires. It was found that the nanoarrays show that carbon–silicon-based nanowires (CSNW) are standing on the Si wafer. It was assumed that Si nanoparticles originated from melted Si at the Si wafer surface and GO-induced nucleation. Additionally, a mechanism for the formation of CSNW is proposed.

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