• Title/Summary/Keyword: multi resolution analysis

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Strain-based structural condition assessment of an instrumented arch bridge using FBG monitoring data

  • Ye, X.W.;Yi, Ting-Hua;Su, Y.H.;Liu, T.;Chen, B.
    • Smart Structures and Systems
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    • v.20 no.2
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    • pp.139-150
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    • 2017
  • The structural strain plays a significant role in structural condition assessment of in-service bridges in terms of structural bearing capacity, structural reliability level and entire safety redundancy. Therefore, it has been one of the most important parameters concerned by researchers and engineers engaged in structural health monitoring (SHM) practices. In this paper, an SHM system instrumented on the Jiubao Bridge located in Hangzhou, China is firstly introduced. This system involves nine subsystems and has been continuously operated for five years since 2012. As part of the SHM system, a total of 166 fiber Bragg grating (FBG) strain sensors are installed on the bridge to measure the dynamic strain responses of key structural components. Based on the strain monitoring data acquired in recent two years, the strain-based structural condition assessment of the Jiubao Bridge is carried out. The wavelet multi-resolution algorithm is applied to separate the temperature effect from the raw strain data. The obtained strain data under the normal traffic and wind condition and under the typhoon condition are examined for structural safety evaluation. The structural condition rating of the bridge in accordance with the AASHTO specification for condition evaluation and load and resistance factor rating of highway bridges is performed by use of the processed strain data in combination with finite element analysis. The analysis framework presented in this study can be used as a reference for facilitating the assessment, inspection and maintenance activities of in-service bridges instrumented with long-term SHM system.

Multiscale features and information extraction of online strain for long-span bridges

  • Wu, Baijian;Li, Zhaoxia;Chan, Tommy H.T.;Wang, Ying
    • Smart Structures and Systems
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    • v.14 no.4
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    • pp.679-697
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    • 2014
  • The strain data acquired from structural health monitoring (SHM) systems play an important role in the state monitoring and damage identification of bridges. Due to the environmental complexity of civil structures, a better understanding of the actual strain data will help filling the gap between theoretical/laboratorial results and practical application. In the study, the multi-scale features of strain response are first revealed after abundant investigations on the actual data from two typical long-span bridges. Results show that, strain types at the three typical temporal scales of $10^5$, $10^2$ and $10^0$ sec are caused by temperature change, trains and heavy trucks, and have their respective cut-off frequency in the order of $10^{-2}$, $10^{-1}$ and $10^0$ Hz. Multi-resolution analysis and wavelet shrinkage are applied for separating and extracting these strain types. During the above process, two methods for determining thresholds are introduced. The excellent ability of wavelet transform on simultaneously time-frequency analysis leads to an effective information extraction. After extraction, the strain data will be compressed at an attractive ratio. This research may contribute to a further understanding of actual strain data of long-span bridges; also, the proposed extracting methodology is applicable on actual SHM systems.

Sliding Manifold Tuning Method Using Wavelet Neural Network (웨이브릿 신경회로망을 활용한 슬라이딩 매니폴드 조정기법)

  • 홍석우;전홍태
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2000.11a
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    • pp.195-198
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    • 2000
  • Sliding mode control method is popularly used for robustness to distrurbance and variance of systems internal parameter. However, one of the serious problem of this method is Chattering which occurs in neighborhood of sliding manifold. Another problem is that we cannot expect robustness before system starts sliding mode. A new tuning method of sliding manifold which changes the parameter of sliding manifold dynamically using Wavelet Neural Network is proposed in this paper. We can expect the better performance in sliding mode control by the wavelet neural networks excellent property of approximating arbitrary function for multi-resolution analysis and decrease chattering drastically.

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AN ANALYSIS ON THE RARE SUBTYPES OF THE FAST SOLAR RADIO ACTIVITY

  • XIE R. X.;WANG M.
    • Journal of The Korean Astronomical Society
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    • v.29 no.spc1
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    • pp.331-332
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    • 1996
  • We present 3 rare subtypes of the FFSs observed with high temporal resolution at 4-frequency (1.42, 2.13, 2.84 and 4.2G GHz). The various FFSs occurred during the main and post-flare phase can demonstrate that coronal nonthermal electron acceleration/injection may go through the whole development process of flares, and deduce that there may exist the re-forming of loop-like structures in the post-flare phase, and the complex multi-type magnetic structures in corona.

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Analysis of the wavelength selective filter using optimized CGH (최적화된 CGH를 이용한 파장선택 필터 특성 분석)

  • An, Jun-Won;Do, Duc-Dung;Kim, Nam;Jeon, Seok-Hui
    • Proceedings of the Optical Society of Korea Conference
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    • 2007.02a
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    • pp.167-168
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    • 2007
  • A novel holographic demultiplexer with multi-group has been firstly proposed and experimentally demonstrated using optimized CGH by genetic algorithm. For experimental demonstrations, a LCOS with 8.1um pixel size and spatial resolution of 1920X1200 is used.

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AN ALGORITHM FOR CONSTRUCTING SYMMETRIC DUAL FILTERS

  • Kim, Hong-Oh;Kim, Rae-Young;Ku, Ja-Seung
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.11 no.3
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    • pp.21-28
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    • 2007
  • The symmetric dual filters are essential for the construction of biorthogonal multiresolution an analyses and wavelets. We propose an algorithm to seek for dual symmetric trigonometric filters $\tilde{m}_0$ for for the given symmetric trigonometric filter $m_0$ and illustrate our algorithm by examples.

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Applications of artificial neural networks;Detections of the location of a sound-source

  • Oobayashi, Koji;Yuan, Yan;Aoyama, Tomoo
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1036-1041
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    • 2003
  • Non-destruction examinations are required in medical sciences and various engineering now. We wish to emulate the examinations in very simplified experiments. It is an educational program. We show a neural network analysis to predict the locations of a sound-source or a body irradiated by sound-waves in audio-region. The sound is an interest flux, and it enables to clear local-structures in a non-transparent space. However, the sound-propagation equations are not solved easily, therefore, we consider to adopt multi-layer neural-networks instead of the direct solutions. We used detected intensities and coordinates for input data and teaching data. A neural network learned them. The neural-network analysis decomposed the distance of 50cm. The resolution is rather rough; however, it is caused by the limitation of our equipments. Since there is no problem in the neural network processing, if we could revise experiments, then, progress of the resolution would be got. Thus, the proposed method functioned as an educational and simplified non-destruction examination.

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A Feature Map Compression Method for Multi-resolution Feature Map with PCA-based Transformation (PCA 기반 변환을 통한 다해상도 피처 맵 압축 방법)

  • Park, Seungjin;Lee, Minhun;Choi, Hansol;Kim, Minsub;Oh, Seoung-Jun;Kim, Younhee;Do, Jihoon;Jeong, Se Yoon;Sim, Donggyu
    • Journal of Broadcast Engineering
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    • v.27 no.1
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    • pp.56-68
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    • 2022
  • In this paper, we propose a compression method for multi-resolution feature maps for VCM. The proposed compression method removes the redundancy between the channels and resolution levels of the multi-resolution feature map through PCA-based transformation. According to each characteristic, the basis vectors and mean vector used for transformation, and the transformation coefficient obtained through the transformation are compressed using a VVC-based coder and DeepCABAC. In order to evaluate performance of the proposed method, the object detection performance was measured for the OpenImageV6 and COCO 2017 validation set, and the BD-rate of MPEG-VCM anchor and feature map compression anchor proposed in this paper was compared using bpp and mAP. As a result of the experiment, the proposed method shows a 25.71% BD-rate performance improvement compared to feature map compression anchor in OpenImageV6. Furthermore, for large objects of the COCO 2017 validation set, the BD-rate performance is improved by up to 43.72% compared to the MPEG-VCM anchor.

Interferometric coherence analysis using space-borne synthetic aperture radar with respect to spatial resolution (공간해상도에 따른 위성 영상레이더 위상간섭기법 긴밀도 분석)

  • Hong, Sang-Hoon;Wdowinski, Shimon
    • Korean Journal of Remote Sensing
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    • v.29 no.4
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    • pp.389-397
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    • 2013
  • Recently high spatial resolution space-borne Synthetic Aperture Radar (SAR) systems have launched and have been operated successfully. Interferometric SAR (InSAR) processing with the space-based high resolution observations acquired by these systems can provide more detail information for various geodetic applications. Coherence is regarded as a critical parameter in the evaluating the quality of an InSAR pair. In this study, we evaluate the coherence characteristics of high-resolution data acquired by TerraSAR-X (X-band) and ALOS PALSAR (L-band) and intermediate-resolution data acquired by Envisat ASAR (C-band) over western Texas, U.S.A. Our coherence analysis reveals that the high-resolution X-band TSX (3.1 cm) data has a high coherence level (0.3-0.6), similar to that of the L-band ALOS PALSAR data (23.5 cm) in short temporal baselines. Further more, the TSX coherence values are significantly higher than those of the C-band (5.6 cm) Envisat ASAR data. The higher coherence of the TSX dataset is a surprising result, because common scattering theories suggest that the longer wavelength SAR data maintain better coherence. In vegetated areas the shorter wavelength radar pulse interacts mostly with upper sections of the vegetation and, hence, does not provide good correlation over time in InSAR pairs. Thus, we suggest that the higher coherence values of the TSX data reflect the data's high-resolution, in which stable and coherent scatters are better maintained. Although, however, the TSX data show a very good coherence with short temporal baseline (11-33 days), the coherences are significantly degraded as the temporal baselines are increased. This result confirms previous studies showing that the coherence has a strong dependency on the temporal baseline.

Landcover classification by coherence analysis from multi-temporal SAR images (다중시기 SAR 영상자료 긴밀도 분석을 통한 토지피복 분류)

  • Yoon, Bo-Yeol;Kim, Youn-Soo
    • Aerospace Engineering and Technology
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    • v.8 no.1
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    • pp.132-137
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    • 2009
  • This study has regard to classification by using multi-temporal SAR data. Multi-temporal JERS-1 SAR images are used for extract the land cover information and possibility. So far, land cover information extracted by high resolution aerial photo, satellite images, and field survey. This study developed on multi-temporal land cover status monitoring and coherence information mapping can be processing by L band SAR image. From July, 1997 to October, 1998 JERS SAR images (9 scenes) coherence values are analyzed and then extracted land cover information factors, so on. This technique which forms the basis of what is called SAR Interferometry or InSAR for short has also been employed in spaceborne systems. In such systems the separation of the antennas, called the baseline is obtained by utilizing a single antenna in a repeat pass.

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