• Smart Structures and Systems
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• 제29권1호
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• pp.53-62
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• 2022

The deployment of advanced structural health monitoring (SHM) systems in large-scale civil structures collects large amounts of data. Note that these data may contain multiple types of anomalies (e.g., missing, minor, outlier, etc.) caused by harsh environment, sensor faults, transfer omission and other factors. These anomalies seriously affect the evaluation of structural performance. Therefore, the effective analysis and mining of SHM data is an extremely important task. Inspired by the deep learning paradigm, this study develops a novel generative adversarial network (GAN) and convolutional neural network (CNN)-based data anomaly detection approach for SHM. The framework of the proposed approach includes three modules : (a) A three-channel input is established based on fast Fourier transform (FFT) and Gramian angular field (GAF) method; (b) A GANomaly is introduced and trained to extract features from normal samples alone for class-imbalanced problems; (c) Based on the output of GANomaly, a CNN is employed to distinguish the types of anomalies. In addition, a dataset-oriented method (i.e., multistage sampling) is adopted to obtain the optimal sampling ratios between all different samples. The proposed approach is tested with acceleration data from an SHM system of a long-span bridge. The results show that the proposed approach has a higher accuracy in detecting the multi-pattern anomalies of SHM data.

• Smart Structures and Systems
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• 제29권1호
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• pp.105-116
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• 2022

Stay cables play an essential role in cable-stayed bridges. Severe vibrations and/or harsh environment may result in cable failures. Therefore, an efficient structural health monitoring (SHM) solution for cable damage detection is necessary. This study proposes a data-driven method for immediately detecting cable damage from measured cable forces by recognizing pattern transition from the intact condition when damage occurs. In the proposed method, pattern recognition for cable damage detection is realized by time series classification (TSC) using a deep learning (DL) model, namely, the long short term memory fully convolutional network (LSTM-FCN). First, a TSC classifier is trained and validated using the cable forces (or cable force ratios) collected from intact stay cables, setting the segmented data series as input and the cable (or cable pair) ID as class labels. Subsequently, the classifier is tested using the data collected under possible damaged conditions. Finally, the cable or cable pair corresponding to the least classification accuracy is recommended as the most probable damaged cable or cable pair. A case study using measured cable forces from an in-service cable-stayed bridge shows that the cable with damage can be correctly identified using the proposed DL-TSC method. Compared with existing cable damage detection methods in the literature, the DL-TSC method requires minor data preprocessing and feature engineering and thus enables fast and convenient early detection in real applications.

• Journal of Positioning, Navigation, and Timing
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• 제12권2호
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• pp.129-140
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• 2023

Autonomous driving systems are likely to be operated in various complex environments. However, the well-known integrated Global Navigation Satellite System (GNSS)/Inertial Navigation System (INS), which is currently the major source for absolute position information, still has difficulties in accurate positioning in harsh signal environments such as urban canyons. To overcome these difficulties, integrated Visual/Inertial/GNSS (VIG) navigation systems have been extensively studied in various areas. Recently, a Compressed-State Constraint Kalman Filter (CSCKF)-based VIG navigation system (CSCKF-VIG) using a monocular camera, an Inertial Measurement Unit (IMU), and GNSS receivers has been studied with the aim of providing robust and accurate position information in urban areas. For this new filter-based navigation system, on the basis of time-propagation measurement fusion theory, unnecessary camera states are not required in the system state. This paper presents a performance evaluation of the CSCKF-VIG system compared to other conventional navigation systems. First, the CSCKF-VIG is introduced in detail compared to the well-known Multi-State Constraint Kalman Filter (MSCKF). The CSCKF-VIG system is then evaluated by a field experiment in different GNSS availability situations. The results show that accuracy is improved in the GNSS-degraded environment compared to that of the conventional systems.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2021년도 추계학술발표대회
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• pp.700-703
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• 2021

Infrared cameras are widely used in recent research for automatic monitoring the abnormal behaviors of the pig. However, when deployed in real pig farms, infrared cameras always get polluted due to the harsh environment of pig farms which negatively affects the performance of pig monitoring. In this paper, we propose a real-time noise-robust infrared camera-based pig automatic monitoring system to improve the robustness of pigs' automatic monitoring in real pig farms. The proposed system first uses a preprocessor with a U-Net architecture that was trained as a GAN generator to transform the noisy images into clean images, then uses a YOLOv5-based detector to detect pigs. The experimental results show that with adding the preprocessing step, the average pig detection precision improved greatly from 0.639 to 0.759.

• Journal of Electrochemical Science and Technology
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• 제14권4호
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• pp.320-325
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• 2023

In Li-ion batteries, a thick electrode is advantageous for lowering the inactive current collector portion and obtaining a high energy density. One of the critical failure mechanisms of thick electrodes is inhomogeneous lithiation and delithiation owing to the axial location of the electrode. In this study, it was confirmed that the top layer of the composite electrode contributes more to the charging step owing to the high ionic transport from the electrolyte. A high-loading multilayered electrode containing LiFePO₄ (LFP) and LiNi_0.8Co_0.1Mn_0.1O₂ (NCM811) was developed to overcome the inhomogeneous electrochemical reactions in the electrode. The electrode laminated with LFP on the top and NCM811 on the bottom showed superior cyclability compared to the electrode having the reverse stacking order or thoroughly mixed. This improvement is attributed to the structural and interfacial stability of LFP on top of the thick electrode in an electrochemically harsh environment.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2023년도 추계학술발표대회
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• pp.140-142
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• 2023

Federated learning (FL) is a new paradigm in machine learning (ML) that enables multiple devices to collaboratively train a shared ML model without sharing their local data. FL is well-suited for applications where data is sensitive or difficult to transmit in large volumes, or where collaborative learning is required. The Internet of Underwater Things (IoUT) is a network of underwater devices that collect and exchange data. This data can be used for a variety of applications, such as monitoring water quality, detecting marine life, and tracking underwater vehicles. However, the harsh underwater environment makes it difficult to collect and transmit data in large volumes. FL can address these challenges by enabling devices to train a shared ML model without having to transmit their data to a central server. This can help to protect the privacy of the data and improve the efficiency of training. In this view, this paper provides a brief overview of Fed-IoUT, highlighting its various applications, challenges, and opportunities.

• Nuclear Engineering and Technology
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• 제56권8호
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• pp.3236-3241
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• 2024

Ion cyclotron resonance heating (ICRH) is an important auxiliary heating method applied to the China Fusion Engineering Test Reactor, which can effectively heat the ions and electrons in plasma. Owing to the harsh nuclear environment, neutronic analyses are required to verify tritium self-sufficiency and neutron-shielding requirements. In this study, a neutronics analysis of the ICRH antenna was conducted using the COre and System integrated engine for Reactor Monte Carlo (cosRMC) code to estimate the neutron flux, radiation damage, nuclear heating, gas generation rate of key components, and tritium breeding ratio (TBR), providing data support for the subsequent optimization of the shielding design. In addition, the neutron flux of the coils around the antenna was calculated to prevent the entry of neutrons that damage the magnetic field coils through the gaps between the port plugs and antenna, and the shielding effects of the port-plug antenna on the surrounding components were analyzed. Finally, the results obtained using the cosRMC and MCNP codes were compared, which and presented good agreement, thus verifying the reliability of the neutronic analysis using the cosRMC code.

• 한국정보과학회논문지:데이타베이스
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• 제29권3호
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• pp.180-192
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• 2002

Shared nothing 다중 프로세서 환경에서 조인 어트리뷰트의 자료 불균형(data skew)이 파이프라인 해시 조인 연산의 성능에 주는 영향을 연구하고, 자료 불균형을 대비하여 적재부하를 Round-robin 방식으로 정적 분할하는 방법과 자료분포도를 이용하여 동적 분할하는 두 가지 파이프라인 해시 조인 알고리즘을 제안한다. 해시 기반 조인을 사용하면 여러 개의 조인을 파이프라인 방식으로 처리할 수 있다. 다중 조인은 파이프라인 방식 처리는 조인 중간 결과를 디스크를 통하지 않고 다른 프로세서에게 직접 전달하므로 효율적이다. Shared nothing 다중 프로세서 구조는 대용량 데이타베이스를 처리하는데 확장성은 좋으나 자료 불균형 분포에 매우 민감하다. 파이프라인 해시 조인 알고리즘이 동적 부하 균형 유지 메커니즘을 갖고 있지 않다면 자료 불균형은 성능에 매우 심각한 영향을 줄 수 있다. 본 논문은 자료 불균형의 영향과 제안된 두 가지 기법을 비교하기 위하여 파이프라인 세그먼트의 실행 모형, 비용 모형, 그리고 시뮬레이터를 개발한다. 다양한 파라미터로 모의 실험을 한 결과에 의하면 자료 불균형은 조인 선택도와 릴레이션 크기에 비례하여 시스템 성능을 떨어뜨림을 보여준다. 그러나 제안된 파이프라인 해시 조인 알고리즘은 다수의 버켓 사용과 분할의 조율을 통해 자료 불균형도가 심한 경우에도 좋은 성능을 갖게 한다.

• Transactions on Electrical and Electronic Materials
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• 제10권2호
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• pp.58-61
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• 2009

The electrical stability of ZnO: Al thin films deposited on glass substrate by the RF magnetron sputtering method have been modified by a hydrogen annealing treatment and $SiO_2$ protection layer. AZO thin films were deposited at room temperature and different RF powers of 50, 100, 150, and 200 W to optimize the AZO film growth condition. The lowest value of resistivity of $9.44{\times}10^{-4}{\Omega}cm$ was obtained at 2 mtorr, room temperature, and a power level of 150 W. Then, the AZO thin films were annealed at $250-400^{\circ}C$ for 1 h in hydrogen ambient. The minimum resistivity obtained was $8.32{\times}10^{-4}{\Omega}cm$ as-annealed at $300^{\circ}C$. The electrical properties were enhanced by the hydrogen annealing treatment. After a 72 h damp-heat treatment in harsh conditions of a water steam at $110^{\circ}C$ for four representative samples, a degradation of electrical properties was observed. The sample of hydrogen-annealed AZO thin films with $SiO_2$ protection layer showed a slight degradation ratio(17%) of electrical properties and a preferable transmittance of 90%. The electrical stability of AZO thin films had been modified by hydrogen annealing treatment and $SiO_2$ protection layer.

• Corrosion Science and Technology
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• 제13권5호
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• pp.178-185
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• 2014

Alloy 617 is considered as a candidate Ni-based superalloy for the intermediate heat exchanger (IHX) of a very high-temperature gas reactor (VHTR) because of its good creep strength and corrosion resistance at high temperatures. Helium is used as a coolant in a VHTR owing to its high thermal conductivity, inertness, and low neutron absorption. However, helium inevitably includes impurities that create an imbalance in the surface reactivity at the interface of the coolant and the exposed materials. As the Alloy 617 has been exposed to high temperatures at $950^{\circ}C$ in the impure helium environment of a VHTR, the degradation of material is accelerated and mechanical properties decreased. The high-temperature strength, creep, and corrosion properties of the structural material for an IHX are highly important to maintain the integrity in a harsh environment for a 60 year period. Therefore, an alloy superior to alloy 617 should be developed. In this study, the mechanical and high-temperature corrosion properties for Ni-Cr alloys fabricated in the laboratory were evaluated as a function of the grain boundary strengthening and alloying elements. The ductility increased and decreased by increasing the amount of Mo and Cr, respectively. Surface oxide was detached during the corrosion test, when Al was not added to alloy. However the alloy with Al showed improved oxide adhesive property without significant degradation and mechanical property. Aluminum seems to act as an anti-corrosive role in the Ni-based alloy.