• Title/Summary/Keyword: Reconstruction error

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The Sound Field Reconstruction of a Korean Bell Using an Error Minimization Scheme in the BEM-Based Acoustical Holography (경계요소법에 기초한 음향 홀로그래피에서 오차 최소화 과정에 의한 한국 종의 음장 재구성)

  • 김철희;이장무;강연준
    • Journal of KSNVE
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    • v.9 no.1
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    • pp.131-140
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    • 1999
  • A method to reconstruct the sound field around a Korean bell is developed. The sound radiation problem is formulated based on the boundary element method by using the algorithm of the acoustical holography. Sound pressures at the hologram surface are measured and used as input data for the analysis program that was developed in this study. An error minimization scheme is presented to overcome difficulties that arise in the backward reconstruction of the BEM-based acoustical holography In the model fictitious source surfaces were also introduced to reduce the complexity stemmed from the source shape. The sound field associated with the (4.0) vibrational mode of the Korean bell was visualized and verified experimentally.

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Phase Error Reduction for Multi-frequency Fringe Projection Profilometry Using Adaptive Compensation

  • Cho, Choon Sik;Han, Junghee
    • Current Optics and Photonics
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    • v.2 no.4
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    • pp.332-339
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    • 2018
  • A new multi-frequency fringe projection method is proposed to reduce the nonlinear phase error in 3-D shape measurements using an adaptive compensation method. The phase error of the traditional fringe projection technique originates from various sources such as lens distortion, the nonlinear imaging system and a nonsinusoidal fringe pattern that can be very difficult to model. Inherent possibility of phase error appearing hinders one from accurate 3-D reconstruction. In this work, an adaptive compensation algorithm is introduced to reduce adaptively the phase error resulting from the fringe projection profilometry. Three different frequencies are used for generating the gratings of projector and conveyed to the four-step phase-shifting procedure to measure the objects of very discontinuous surfaces. The 3-D shape results show that this proposed technique succeeds in reconstructing the 3-D shape of any type of objects.

Regularized Adaptive High-resolution Image Reconstruction Considering Inaccurate Subpixel Registration (부정확한 부화소 단위의 위치 추정 오류에 적응적인 정규화된 고해상도 영상 재구성 연구)

  • Lee, Eun-Sil;Byun, Min;Kang, Moon-Gi
    • Journal of Broadcast Engineering
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    • v.8 no.1
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    • pp.19-29
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    • 2003
  • The demand for high-resolution images is gradually increasing, whereas many imaging systems yield aliased and undersampled images during image acquisition. In this paper, we propose a high-resolution image reconstruction algorithm considering inaccurate subpixel registration. A regularized Iterative reconstruction algorithm is adopted to overcome the ill-posedness problem resulting from inaccurate subpixel registration. In particular, we use multichannel image reconstruction algorithms suitable for application with multiframe environments. Since the registration error in each low-resolution has a different pattern, the regularization parameters are determined adaptively for each channel. We propose a methods for estimating the regularization parameter automatically. The preposed algorithm are robust against the registration error noise. and they do not require any prior information about the original image or the registration error process. Experimental results indicate that the proposed algorithms outperform conventional approaches in terms of both objective measurements and visual evaluation.

Indoor 3D Dynamic Reconstruction Fingerprint Matching Algorithm in 5G Ultra-Dense Network

  • Zhang, Yuexia;Jin, Jiacheng;Liu, Chong;Jia, Pengfei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.1
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    • pp.343-364
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    • 2021
  • In the 5G era, the communication networks tend to be ultra-densified, which will improve the accuracy of indoor positioning and further improve the quality of positioning service. In this study, we propose an indoor three-dimensional (3D) dynamic reconstruction fingerprint matching algorithm (DSR-FP) in a 5G ultra-dense network. The first step of the algorithm is to construct a local fingerprint matrix having low-rank characteristics using partial fingerprint data, and then reconstruct the local matrix as a complete fingerprint library using the FPCA reconstruction algorithm. In the second step of the algorithm, a dynamic base station matching strategy is used to screen out the best quality service base stations and multiple sub-optimal service base stations. Then, the fingerprints of the other base station numbers are eliminated from the fingerprint database to simplify the fingerprint database. Finally, the 3D estimated coordinates of the point to be located are obtained through the K-nearest neighbor matching algorithm. The analysis of the simulation results demonstrates that the average relative error between the reconstructed fingerprint database by the DSR-FP algorithm and the original fingerprint database is 1.21%, indicating that the accuracy of the reconstruction fingerprint database is high, and the influence of the location error can be ignored. The positioning error of the DSR-FP algorithm is less than 0.31 m. Furthermore, at the same signal-to-noise ratio, the positioning error of the DSR-FP algorithm is lesser than that of the traditional fingerprint matching algorithm, while its positioning accuracy is higher.

Compensation of Errors on Car Black Box Records and Trajectory Reconstruction Analysis (자동차 블랙박스 기록 오차 보정과 경로 재구성 해석)

  • Yang, Kyoung-Soo;Lee, Won-Hee;Han, In-Hwan
    • Transactions of the Korean Society of Automotive Engineers
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    • v.12 no.6
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    • pp.182-190
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    • 2004
  • This paper presents reconstruction analysis of vehicle trajectory using records of a developed black box, and results of validation tests. For reconstruction of vehicle trajectory, the black box records the longitudinal and lateral accelerations and yaw-rate of vehicle during a pre-defined time period before and after the accident. One 2-axis accelerometer is used for measuring accelerations, and one vibrating structure type gyroscope is used for measuring yaw-rate of vehicle. The vehicle's planar trajectory can be reconstructed by integrating twice accelerations along longitudinal and lateral directions with yaw-rate values. However, there may be many kinds of errors in sensor measurements. The causes of errors are as follows: mis-alignment, low frequency offset drift, high frequency noise, and projecting 3-dimensional motion into 2-dimensional motion. Therefore, some procedures are taken for error compensation. In order to evaluate the reliability and the accuracy of trajectory reconstruction results, the black box was mounted on a passenger car. The vehicle was driven and tested along various specified lanes. Through the tests, the accuracy and usefulness of the reconstruction analysis have been validated.

Condition Monitoring and Diagnosis of a Hot Strip Roughing Mill Using an Autoencoder (오토인코더를 이용한 열간 조압연설비 상태모니터링과 진단)

  • Seo, Myung Kyo;Yun, Won Young
    • Journal of Korean Society for Quality Management
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    • v.47 no.1
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    • pp.75-86
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    • 2019
  • Purpose: It is essential for the steel industry to produce steel products without unexpected downtime to reduce costs and produce high quality products. A hot strip rolling mill consists of many mechanical and electrical units. In condition monitoring and diagnosis, various units could fail for unknown reasons. Methods: In this study, we propose an effective method to detect units with abnormal status early to minimize system downtime. The early warning problem with various units was first defined. An autoencoder was modeled to detect abnormal states. An application of the proposed method was also implemented in a simulated field-data analysis. Results: We can compare images of original data and reconstructed images, as well as visually identify differences between original and reconstruction images. We confirmed that normal and abnormal states can be distinguished by reconstruction error of autoencoder. Experimental results show the possibility of prediction due to the increase of reconstruction error from just before equipment failure. Conclusion: In this paper, hot strip roughing mill monitoring method using autoencoder is proposed and experiments are performed to study the benefit of the autoencoder.

Recursive Error-Component Correcting Method for 3D Shape Reconstruction (3차원 형상 복원을 위한 재귀적 오차 성분 보정 방법)

  • Koh, Sung-shik
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.10
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    • pp.1923-1928
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    • 2017
  • This paper is a study on error correction for three-dimensional shape reconstruction based on factorization method. The existing error correction method based on factorization has a limitation of correction because it is optimized globally. Thus in this paper, we propose our new method which can find and correct the only major error influence factor toward three-dimensional reconstructed shape instead of global approach. We define the error-influenced factor in two-dimensional re-projection deviation space and directly control the error components. In addition, it is possible to improve the error correcting performance by recursively applying the above process. This approach has an advantage under noise because it controls the major error components without depending on any geometric information. The performance evaluation of the proposed algorithm is verified by simulation with synthetic and real image sequence to demonstrate noise robustness.

Development of Nuclear Power Plant Instrumentation Signal Faults Identification Algorithm (원전 계측 신호 오류 식별 알고리즘 개발)

  • Kim, SeungGeun
    • Journal of Korea Society of Industrial Information Systems
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    • v.25 no.6
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    • pp.1-13
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    • 2020
  • In this paper, the author proposed a nuclear power plant (NPP) instrumentation signal faults identification algorithm. A variational autoencoder (VAE)-based model is trained by using only normal dataset as same as existing anomaly detection method, and trained model predicts which signal within the entire signal set is anomalous. Classification of anomalous signals is performed based on the reconstruction error for each kind of signal and partial derivatives of reconstruction error with respect to the specific part of an input. Simulation was conducted to acquire the data for the experiments. Through the experiments, it was identified that the proposed signal fault identification method can specify the anomalous signals within acceptable range of error.

Robust control using the sliding mode observer in the presence of unmatched uncertainties (비정합조건 하의 슬라이딩 모드 관측기를 이용한 강인 제어)

  • 한상철;박인규;함운철
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.334-334
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    • 2000
  • In this paper, sliding mode observer design principles based on the equivalent control approach are discussed for the systems which may not satisfy the matching conditions. We propose a new approach for designing a sliding observer and the proof of the stability of the state reconstruction error system for time-invariant systems using the Lyapunov method. The reaching time to the sliding surface, the sliding dynamics of the system, the stability of the reconstruction error system via Lyapunov method, sufficient conditions for the existence of the sliding mode are studied.

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