scholarly journals Adaptive Directional Cubic Convolution for Integrated Circuit Chip Defect Image Interpolation

2021 ◽  
Vol 15 ◽  
pp. 1084-1090
Author(s):  
Yuan Chao ◽  
Chengxia Ma ◽  
Wentao Shan ◽  
Junping Feng ◽  
Zhisheng Zhang
Keyword(s):  
Defect Detection ◽  
Integrated Circuit ◽  
Interpolation Method ◽  
Computational Time ◽  
Otsu Thresholding ◽  
Vision Inspection ◽  
Texture Information ◽  
Interpolation Accuracy ◽  
Defect Image ◽  
Texture Preservation

An adaptive directional cubic convolution interpolation method for integrated circuit (IC) chip defect images is proposed in this paper, to meet the challenge of preserving edge and texture information. In the proposed method, Otsu thresholding technique is employed to distinguish strong edge pixels from weak ones and texture regions, and estimate the direction of strong edges, adaptively. Boundary pixels are pre-interpolated using the original bicubic interpolation method to help improve the interpolation accuracy of the interior pixels. The experimental results of both classic test images and IC chip defect images demonstrate that the proposed method outperforms the competing methods with better edge and texture preservation, interpolation quality, more natural visual effect of the interpolated images and reasonable computational time. The proposed method can provide high quality IC chip images for defect detection and has been successfully applied on practical vision inspection for IC chips

Research about Influencing Factor on Interpolation Accuracy in Data Exchange of Fluid-Structure Interaction

2013 ◽  
Vol 318 ◽  
pp. 100-107
Author(s):  
Zhen Shen ◽  
Biao Wang ◽  
Hui Yang ◽  
Yun Zheng
Keyword(s):  
Data Exchange ◽  
Shape Function ◽  
Interpolation Method ◽  
Matching Condition ◽  
Optimal Interpolation ◽  
Complex Interpolation ◽  
Interpolation Function ◽  
Interpolation Methods ◽  
Interpolation Accuracy ◽  
Lower Accuracy

Six kinds of interpolation methods, including projection-shape function method, three-dimensional linear interpolation method, optimal interpolation method, constant volume transformation method and so on, were adoped in the study of interpolation accuracy. From the point of view about the characterization of matching condition of two different grids and interpolation function, the infuencing factor on the interpolation accuracy was studied. The results revealed that different interpolation methods had different interpolation accuracy. The projection-shape function interpolation method had the best effect and the more complex interpolation function had lower accuracy. In many cases, the matching condition of two grids had much greater impact on the interpolation accuracy than the method itself. The error of interpolation method is inevitable, but the error caused by the grid quality could be reduced through efforts.

Study on Lidar Data Interpolation Method Based on GA-BP

2012 ◽  
Vol 588-589 ◽  
pp. 1312-1315
Author(s):  
Yi Kun Zhang ◽  
Ming Hui Zhang ◽  
Xin Hong Hei ◽  
Deng Xin Hua ◽  
Hao Chen
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Interpolation Method ◽  
Linear Interpolation ◽  
Lidar Data ◽  
Data Interpolation ◽  
Interpolation Model ◽  
Genetic Method ◽  
Interpolation Accuracy ◽  
Linear Interpolation Method

Aiming at building a Lidar data interpolation model, this paper designs and implements a GA-BP interpolation method. The proposed method uses genetic method to optimize BP neural network, which greatly improves the calculation accuracy and convergence rate of BP neural network. Experimental results show that the proposed method has a higher interpolation accuracy compared with BP neural network as well as linear interpolation method.

Simulating swing dynamics of a power system model using nonlinear model order reduction

2019 ◽  
Vol 38 (6) ◽  
pp. 1918-1930
Author(s):  
Satyavir Singh ◽  
Mohammad Abid Bazaz ◽  
Shahkar Ahmad Nahvi
Keyword(s):  
Power System ◽  
System Dynamics ◽  
Interpolation Method ◽  
Computational Cost ◽  
Nonlinear Function ◽  
Computational Time ◽  
Reduced Basis ◽  
Power System Dynamics ◽  
Content Type ◽  
On Line

Purpose The purpose of this paper is to demonstrate the applicability of the Discrete Empirical Interpolation method (DEIM) for simulating the swing dynamics of benchmark power system problems. The authors demonstrate that considerable savings in computational time and resources are obtained using this methodology. Another purpose is to apply a recently developed modified DEIM strategy with a reduced on-line computational burden on this problem. Design/methodology/approach On-line computational cost of the power system dynamics problem is reduced by using DEIM, which reduces the complexity of the evaluation of the nonlinear function in the reduced model to a cost proportional to the number of reduced modes. The on-line computational cost is reduced by using an approximate snap-shot ensemble to construct the reduced basis. Findings Considerable savings in computational resources and time are obtained when DEIM is used for simulating swing dynamics. The on-line cost implications of DEIM are also reduced considerably by using approximate snapshots to construct the reduced basis. Originality/value Applicability of DEIM (with and without approximate ensemble) to a large-scale power system dynamics problem is demonstrated for the first time.

A Review of TFT-LCD Panel Defect Detection Methods

2013 ◽  
Vol 734-737 ◽  
pp. 2898-2902 ◽  
Author(s):  
Chuan Xia Jian ◽  
Jian Gao ◽  
Xin Chen
Keyword(s):  
Defect Detection ◽  
Detection Methods ◽  
Image Subtraction ◽  
Low Contrast ◽  
Defect Image ◽  
Key Issues ◽  
Segmentation Image ◽  
Fuzzy Boundary ◽  
Current Detection ◽  
Defect Boundary

TFT-LCD panel defect detection has been one of the difficulties in this field because of fuzzy defect boundary, low contrast between defects and background, and low detection speed. The structure of TFT-LCD panels and classification are introduced. Through the analysis of panel defect features, current detection methods for the TFT-LCD panel defects are reviewed. The key technologies of feature extraction and defect classification are analyzed in the defect image recognition of TFT-LCD panel. Meanwhile the methods of fuzzy boundary defect segmentation, image subtraction and image filtering are also discussed. Finally, the characteristics and advantages of these detection methods are concluded, and several key issues for the TFT-LCD defect detection have been proposed for future development.

Effects of Linear Hysteric Material Damping and Shock Pulse Shapes for Uniform Board Response

2016 ◽  
Author(s):  
Sharan Kallolimath ◽  
Jiang Zhou
Keyword(s):  
Test Performance ◽  
Strain Distribution ◽  
Computational Models ◽  
Numerical Solutions ◽  
Flexural Rigidity ◽  
Interpolation Method ◽  
Computational Time ◽  
Stress Concentrations ◽  
Stress Strain ◽  
Test Board

Validation of surface mounted electronic devices for drop test performance is considered as one of the most challenging tasks for researchers to search for key dynamic parameters either by experimentation or by numerical simulation. It has not only become challenging task to capture some of the important parameters that affect board flexural rigidity, stiffness, dynamic stresses and strains, but also avoid stress concentrations near undesired locations resulting in non-uniform strain distribution throughout the test board. There is a requirement to simulate exact drop condition that quantifies high impact energy on the board and also control drop to improve the board surface stress/strain distribution measured should be independent from standoff stress region. In this paper, an effort to find the importance of viscous and linear hysteric damping characteristics on uniform board response has been made. The influence of damped responses during no ring impact has been analyzed. Two different types of computational models are developed and an approximate FEA numerical solutions are obtained to compare current JEDEC test board and alternative hexagonal boards at reduced computational time and challenging experimental cost. The effect of board responses with two types of linear damping models are considered to study the effect. An approach towards finding key parameters that affect stress/strain distribution under both free as well as constrained model has been made, with including different pulse shapes parameters into effect. Maximum board strains are validated and compared using Global FEA model and maximum stresses on the components are evaluated using cut boundary interpolation method. Comparative to empirical results data, an effort to improve uniform stress strain distribution of package solder joints has been made and results are correlated.

Steel Strip Defect Detection Based on Human Visual Attention Mechanism Model

2014 ◽  
Vol 530-531 ◽  
pp. 456-462 ◽  
Author(s):  
Shuai Hua Xu ◽  
Sheng Qi Guan ◽  
Long Long Chen
Keyword(s):  
Visual Attention ◽  
Defect Detection ◽  
Steel Strip ◽  
Molecular Graph ◽  
Input Image ◽  
Attention Mechanism ◽  
Threshold Method ◽  
Central Difference ◽  
Defect Image ◽  
Visual Attention Mechanism

According to the characteristics of steel strip, This paper propose the strip defect detection algorithm which is based on visual attention mechanism. First, extract the input image color, brightness and orientation characteristics and form simple feature map; secondly, prognosis on the features, get defective attention region by threshold segmentation to color characteristics of colored defect image. The wavelet decomposition to colorless defect image of brightness and direction features will form the multi-feature subgraph; then construct feature difference molecular graph through the feature decomposition map around central difference operations, and the characteristic difference of molecular graph is formed by the fusion of feature saliency map; finally, defect targets by using local threshold method and region growing segmentation. The experimental results show that this method can rapidly and accurately detect the defects of the strip image, at the same time it can improve the efficiency of detection.

The Application of Adaptive Wavelet Method to Multi-Dimensional Limiting Process for Enhancement of Computational Efficiency

2011 ◽  
Author(s):  
Hyungmin Kang ◽  
Kyunghyun Park ◽  
Dongho Lee ◽  
Kyuhong Kim ◽  
Seunghwan Park ◽  
...  
Keyword(s):  
Computational Efficiency ◽  
Interpolation Method ◽  
Higher Order ◽  
High Order ◽  
Computational Time ◽  
Numerical Accuracy ◽  
Wavelet Method ◽  
Adaptive Wavelet ◽  
Computational Fluid Dynamics Cfd ◽  
Adaptive Wavelet Method

An adaptive wavelet method is applied in order to enhance the computational efficiency of enhanced Multi-dimensional Limiting Process (e-MLP) without deterioration of the numerical accuracy of original Computational Fluid Dynamics (CFD) scheme. For this purpose, higher order of adaptive wavelet method is constructed including higher order of wavelet decomposition and modified thresholding. Besides, the locations of crucial features such as shock, vortex core, etc. are automatically and accurately searched in the CFD dataset through wavelet transformation. Only on these locations, high order spatial interpolation scheme with e-MLP are performed; in the other locations, interpolation method is utilized to compute residual values, which reduces the computational time of flux evaluation. This high order adaptive wavelet method was applied to unsteady Euler flow computations such as shock-vortex interaction problem. Throughout these processes, it was verified that computational efficiency was enhanced with preservation of numerical accuracy of CFD solver.

scholarly journals Image processing of Casting defects based on Convolutional neural network

2021 ◽  
Vol 2137 (1) ◽  
pp. 012059
Author(s):  
Bowen Wei ◽  
Weixin Gao
Keyword(s):  
Neural Network ◽  
Image Processing ◽  
Convolutional Neural Network ◽  
Defect Detection ◽  
Network Architecture ◽  
Casting Defect ◽  
Neural Network Architecture ◽  
Vision Inspection ◽  
Design Requirements ◽  
Metal Castings

Abstract At present, there are numerous losses caused by corrosion cracking of metal castings in engineering in China. In order to detect the possible defects of metal castings in engineering, the laser ultrasonic vision inspection technology is used to image the castings, and then the identification efficiency is low. In order to process these images efficiently and quickly, convolutional neural network image processing technology is introduced. According to the actual needs, a convolutional neural network architecture is designed to recognize images, and whether the architecture meets the requirements is verified. Experimental results show that the performance of the architecture meets the design requirements. Under the same conditions, this structure provides a solution for casting defect detection combined with artificial intelligence.

On-the-Fly Treatment of Discrete Representation Thermal Neutron Scattering Data in RMC Code

2020 ◽  
Author(s):  
Lei Zheng ◽  
Kaiwen Li ◽  
Kan Wang
Keyword(s):  
Elastic Scattering ◽  
Neutron Scattering ◽  
Thermal Neutron ◽  
Interpolation Method ◽  
Beryllium Oxide ◽  
Scattering Data ◽  
Computational Time ◽  
Discrete Representation ◽  
Thermal Region ◽  
Thermal Neutron Scattering

Abstract A proper treatment of thermal neutron scattering data is required for the high-fidelity neutronics calculation of thermal reactors. Monte Carlo codes typically use an S(α, β) treatment to describe scattering events in the thermal region if the S(α, β) data is available for the material. The S(α,β) model stores a large majority of scattering physics and can handle thermal scattering process accurately. In neutronic-thermohydraulic coupling calculations, the temperature effect on nuclear data must be treated properly. The on-the-fly sampling method or the on-the-fly interpolation method are typically used in thermal region. In this paper, the on-the-fly interpolation method for the discrete representation S(α,β) data was introduced. The two-dimensional linear-linear interpolation was used to calculate the scattering cross sections and the secondary information for inelastic scattering, coherent elastic scattering and incoherent elastic scattering. The implemented on-the-fly capability was tested by a series of benchmarks that contain various thermal materials, including light water, beryllium and beryllium oxide. The integral kinf eigenvalues, the efficiency and the fine energy spectra of the on-the-fly treatment capacity were compared with those of the references. Results show that the on-the-fly treatment capability has high accuracy, and the computational time increases up to 20%.

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