• Journal of Computational Design and Engineering
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• v.2 no.4
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• pp.261-267
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• 2015

Free-form blades are widely used in different industries, such as aero-engine and steam turbine. Blades that are damaged during service or have production deficiencies are usually replaced with new ones. This leads to the waste of expensive material and is not sustainable. However, material and costs can be saved by repairing of locally damaged blades or blades with localized production deficiencies. The blade needs to be further machined after welding process to reach the aerodynamic performance requirements. This paper outlines an adaptive location approach of repaired blade for model reconstruction and NC machining. Firstly, a mathematical model is established to describe the localization problem under constraints. Secondly, by solving the mathematical model, localization of repaired blade for NC machining can be obtained. Furthermore, a more flexible method based on the proposed mathematical model and the continuity of the deformation process is developed to realize a better localization. Thirdly, by rebuilding the model of the repaired blade and extracting repair error, optimized tool paths for NC machining is generated adaptively for each individual part. Finally, three examples are given to validate the proposed method.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.2
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• pp.95-102
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• 2001

Fuzzy system is capable of uniformly approximating any nonlinear function over compact input space. The applications of fuzzy system, however, have been primarily limited by the need for large number of fuzzy rules, in particular, for the high-order nonlinear system. In this paper, we propose the reconstruction methods of fuzzy systems, parallel type and cascade, based on the decomposition of some classes of high-order nonlinear functions. Using the both types appropriately, we can reduce the number of fuzzy rules geometrically. It can be applied to the fuzzy system that has an online adaptive structure. Two examples of adaptive fuzzy sliding mode control are shown in the computer simulations to verify the validity of the proposed algorithm.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.481-484
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• 2005

Inherent opportunities on research for restoring high resolution image from low resolution images are increasing in these days. Super resolution image reconstruction is the process of combining multiple low resolution images to form a higher resolution one. To achieve super resolution reconstruction, proper observation model which is based on subpixel shift information is required. In this context, the importance of the subpixel registration cannot be estimated because subpixel shift information cannot be obtained from original image. This paper presents a regularized adaptive super resolution reconstruction method based on phase correlated subpixel registration, where the Constrained Least Squares(CLS) Restoration is adopted as a post process.

• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.1
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• pp.1-6
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• 2015

Recently, handy pulse measurement method was introduced by using smart phone camera. However, measured values are not consistent with the variations of external light conditions, because the external light interfere with dynamic range of captured pulse image. Thus, adaptive dynamic range reconstruction algorithm is proposed to conduct pulse measurement robust to light condition. The minimum and maximum values for dynamic ranges of green and blue channels are adjusted to appropriate values for pulse measurement. In addition, sigmoid function based curve is applied to adjusted dynamic range. Experimental results show that the proposed algorithm conducts suitably dynamic range reconstruction of pulse image for the interference of external light sources.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.839-842
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• 2000

A new and modified neural network model Is proposed for CT image reconstruction from four projection directions only. The model uses the Resilient Back-Propagation (Rprop) algorithm, which is derived from the original Back-Propagation, for adaptation of its weights. In addition to the error in projection directions of the image being reconstructed, the proposed network makes use of errors in pixels between an image which passed the median filter and the reconstructed one. Improved reconstruction was obtained, and the proposed method was found to be very effective in CT image reconstruction when the given number of projection directions is very limited.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.410-421
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• 2019

Distributed compressed sensing (DCS) states that we can recover the sparse signals from very few linear measurements. Various studies about DCS have been carried out recently. In many practical applications, there is no prior information except for standard sparsity on signals. The typical example is the sparse signals have block-sparse structures whose non-zero coefficients occurring in clusters, while the cluster pattern is usually unavailable as the prior information. To discuss this issue, a new algorithm, called backtracking-based adaptive orthogonal matching pursuit for block distributed compressed sensing (DCSBBAOMP), is proposed. In contrast to existing block methods which consider the single-channel signal reconstruction, the DCSBBAOMP resorts to the multi-channel signals reconstruction. Moreover, this algorithm is an iterative approach, which consists of forward selection and backward removal stages in each iteration. An advantage of this method is that perfect reconstruction performance can be achieved without prior information on the block-sparsity structure. Numerical experiments are provided to illustrate the desirable performance of the proposed method.

• Journal of the Korean Society for Nondestructive Testing
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• v.20 no.6
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• pp.545-554
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• 2000

Compton X-ray backscatter technique has been used to quantitatively assess the impact damage in quasi-isotropic laminated composites and to obtain a cross-sectional profile of impact-damaged laminated composites from the density variation of the cross section. An adaptive filter is applied to the Compton backscattering data for the reconstruction and noise reduction from many sources including quantum noise, especially when the SNR(signal-to-noise ratio) of the image is relatively low. A nonlinear reconstruction model is also proposed to overcome distortion of the Compton backscatter image due to attenuation effects, beam hardening, and irregular distributions of the fibers and the matrix in composites. Delaminations masked or distorted by the first few delaminations near the front surface are detected and characterized both in width and location, by application of an error minimization algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1B
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• pp.89-98
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• 2000

This paper presents an active noise cancelling model using wavelet transform and subband filter banks based on adaptive filter. The analysis filter banks decompose input and error signals into QMF filter banks of lowpass and highpass bands. Each filter bank uses wavelet filter with dyadic tree structure. The decomposed input and error signals are iterated by adaptive filter coefficients of each subband using filtered-X LMS algorithm. The synthesis filter banks make output signal of wideband with perfect reconstruction to prepare adaptive filter output signals of each subband. The analysis and synthesis niter hants use conjugate quadrature filters for Pefect reconstruction. Also, The delayed LMS algorithm model for on-line identification of error path transfer characteristics is used gain and acoustic time delay factors. The proposed adaptive active noise cancelling modelis suggested by system retaining the computational and convergence speed advantage using wavelet subband filter banks.

• 한국정보컨버전스학회:학술대회논문집
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• 2008.06a
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• pp.145-150
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• 2008

This thesis explores the problem of reconstructing a three-dimensional(3D) scene given a set of images or image sequences of the scene. It describes efficient methods for the 3D reconstruction of static and dynamic scenes from stereo images, stereo image sequences, and images captured from multiple viewpoints. Novel methods for image-based and volumetric modelling approaches to 3D reconstruction are presented, with an emphasis on the development of efficient algorithm which produce high quality and accurate reconstructions. For image-based 3D reconstruction a novel energy minimisation scheme, Iterated Dynamic Programming, is presented for the efficient computation of strong local minima of discontinuity preserving energyy functions. Coupled with a novel morphological decomposition method and subregioning schemes for the efficient computation of a narrowband matching cost volume. the minimisation framework is applied to solve problems in stereo matching, stereo-temporal reconstruction, motion estimation, 2D image registration and 3D image registration. This thesis establishes Iterated Dynamic Programming as an efficient and effective energy minimisation scheme suitable for computer vision problems which involve finding correspondences across images. For 3D reconstruction from multiple view images with arbitrary camera placement, a novel volumetric modelling technique, Embedded Voxel Colouring, is presented that efficiently embeds all reconstructions of a 3D scene into a single output in a single scan of the volumetric space under exact visibility. An adaptive thresholding framework is also introduced for the computation of the optimal set of thresholds to obtain high quality 3D reconstructions. This thesis establishes the Embedded Voxel Colouring framework as a fast, efficient and effective method for 3D reconstruction from multiple view images.

• Journal of the Korea Computer Graphics Society
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• v.23 no.4
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• pp.11-19
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• 2017

We propose a new pipeline of fluid surface reconstruction that incorporates hybrid SDF(signed distance fields) and adaptive fluid surface techniques to finely reconstruct liquid-solid mixed surfaces. Previous particle-based fluid simulation suffer from a noisy surface problem when the particles are distributed irregularly. If a smoothing scheme is applied to reduce the problem, sharp and detailed features can be lost by over-smoothing artifacts. Our method constructs a hybrid SDF by combining signed distance values from the solid and liquid parts of the object. We also proposed a method of adaptively reconstructing the surface of the fluid to further improve the overall efficiency. This not only shows the detailed surface of the solid and liquid parts, but also the detail of the solid surface and the smooth fluid surface when both materials are mixed. We introduce the concept of guiding shape and propose a method to get signed distance value quickly. In addition, the hybrid SDF and mesh reconstruction techniques are integrated in the adaptive framework. As a result, our method improves the overall efficiency of the pipeline to restore fluid surfaces.