• 제목/요약/키워드: Parameter monitoring

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Retrieval of Aerosol Microphysical Parameter by Inversion Algorithm using Multi-wavelength Raman Lidar Data (역행렬 알고리즘을 이용한 다파장 라만 라이다 데이터의 고도별 에어로졸 Microphysical Parameter 도출)

  • Noh, Young-Min;Kim, Young-Joon;Muller, Detlef
    • Journal of Korean Society for Atmospheric Environment
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    • v.23 no.1
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    • pp.97-109
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    • 2007
  • Vertical distribution and optical properties of atmospheric aerosols above the Korean peninsula are quite important to estimate effects of aerosol on atmospheric environment and regional radiative forcing. For the first time in Korea, vertical microphysical properties of atmospheric aerosol obtained by inversion algorithm were analyzed based on optical data of multi-wavelength Raman lidar system developed by the Advanced Environmental Monitoring Research Center (ADEMRC), Gwangju Institute Science and Technology (GIST). Data collected on 14 June 2004 at Gwangju ($35.10^{\circ}N,\;126.53^{\circ}E$) and 27 May 2005 at Anmyeon island ($36.32^{\circ}N,\;126.19^{\circ}E$) were used as raw optical data for inversion algorithm. Siberian forest fire smoke and local originated haze were observed above and within the height of PBL, respectively on 14 June 2004 according to NOAA/Hysplit backstrajectory analysis. The inversion of lidar optical data resulted in particle effective radii around $0.31{\sim}0.33{\mu}m$, single scattering albedo between $0.964{\sim}0.977$ at 532 nm in PBL and effective radii of $0.27{\mu}m$ and single scattering albedo between $0.923{\sim}0.924$ above PBL. In the case on 27 May 2005, biomass burning from east China was a main source of aerosol plume. The inversion results of the data on 27 May 2005 were found to be particle effective radii between $0.23{\sim}0.24{\mu}m$, single scattering albedo around $0.924{\sim}0.929$ at 532 nm. Additionally, the inversion values were well matched with those of Sun/sky radiometer in measurement period.

Adaptively selected autocorrelation structure-based Kriging metamodel for slope reliability analysis

  • Li, Jing-Ze;Zhang, Shao-He;Liu, Lei-Lei;Wu, Jing-Jing;Cheng, Yung-Ming
    • Geomechanics and Engineering
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    • v.30 no.2
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    • pp.187-199
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    • 2022
  • Kriging metamodel, as a flexible machine learning method for approximating deterministic analysis models of an engineering system, has been widely used for efficiently estimating slope reliability in recent years. However, the autocorrelation function (ACF), a key input to Kriging that affects the accuracy of reliability estimation, is usually selected based on empiricism. This paper proposes an adaption of the Kriging method, named as Genetic Algorithm optimized Whittle-Matérn Kriging (GAWMK), for addressing this issue. The non-classical two-parameter Whittle-Matérn (WM) function, which can represent different ACFs in the Matérn family by controlling a smoothness parameter, is adopted in GAWMK to avoid subjectively selecting ACFs. The genetic algorithm is used to optimize the WM model to adaptively select the optimal autocorrelation structure of the GAWMK model. Monte Carlo simulation is then performed based on GAWMK for a subsequent slope reliability analysis. Applications to one explicit analytical example and two slope examples are presented to illustrate and validate the proposed method. It is found that reliability results estimated by the Kriging models using randomly chosen ACFs might be biased. The proposed method performs reasonably well in slope reliability estimation.

Accuracy and robustness of hysteresis loop analysis in the identification and monitoring of plastic stiffness for highly nonlinear pinching structures

  • Hamish Tomlinson;Geoffrey W. Rodgers;Chao Xu;Virginie Avot;Cong Zhou;J. Geoffrey Chase
    • Smart Structures and Systems
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    • v.31 no.2
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    • pp.101-111
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    • 2023
  • Structural health monitoring (SHM) covers a range of damage detection strategies for buildings. In real-time, SHM provides a basis for rapid decision making to optimise the speed and economic efficiency of post-event response. Previous work introduced an SHM method based on identifying structural nonlinear hysteretic parameters and their evolution from structural force-deformation hysteresis loops in real-time. This research extends and generalises this method to investigate the impact of a wide range of flag-shaped or pinching shape nonlinear hysteretic response and its impact on the SHM accuracy. A particular focus is plastic stiffness (Kp), where accurate identification of this parameter enables accurate identification of net and total plastic deformation and plastic energy dissipated, all of which are directly related to damage and infrequently assessed in SHM. A sensitivity study using a realistic seismic case study with known ground truth values investigates the impact of hysteresis loop shape, as well as added noise, on SHM accuracy using a suite of 20 ground motions from the PEER database. Monte Carlo analysis over 22,000 simulations with different hysteresis loops and added noise resulted in absolute percentage identification error (median, (IQR)) in Kp of 1.88% (0.79, 4.94)%. Errors were larger where five events (Earthquakes #1, 6, 9, 14) have very large errors over 100% for resulted Kp as an almost entirely linear response yielded only negligible plastic response, increasing identification error. The sensitivity analysis shows accuracy is reduces to within 3% when plastic drift is induced. This method shows clear potential to provide accurate, real-time metrics of non-linear stiffness and deformation to assist rapid damage assessment and decision making, utilising algorithms significantly simpler than previous non-linear structural model-based parameter identification SHM methods.

A Study on Correlationship between the Induced Plasma and Emission Signals for In-process Monitoring in Stainless Steel Welding of Fiber Laser (II) - Properties Changes of the Measured Signals in a Thick Plate Welding - (파이버 레이저의 스테인리스강 용접시 인프로세스 모니터링을 위한 유기 플라즈마와 방사신호간의 상관성 연구(II) - 후판 용접시 측정신호의 특성 변화 -)

  • Lee, Chang-Je;Kim, Jong-Do
    • Journal of Welding and Joining
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    • v.32 no.6
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    • pp.70-74
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    • 2014
  • On this study, we researched the in-process monitoring during fiber laser welding as well as on the first paper. On the previous/formal study, we analyzed the change of emission signal on thin plate welding. On this study, however, we analyzed RMS and FFT with emission signals in laser welding on lap joint and butt joint of 8mm-thick 316L stainless steel. As the result, the movement of specific frequency peak was observed according to welding speed changes. Furthermore, frequency peak as a result of FFT on the thick plate welding are much clearer than on the thin plate welding. Therefore, it is expected that the welding parameter changes can be predicted in case of applying FFT to in-process monitoring.

Prestress-Loss Monitoring Technique for Prestressd Concrete Girders using Vibration-based System Identification (진동기반 구조식별을 통한 프리스트레스트 콘크리트 거더의 긴장력 손실 검색 기법)

  • Ho, Duc-Duy;Hong, Dong-Soo;Kim, Jeong-Tae
    • Journal of Ocean Engineering and Technology
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    • v.24 no.1
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    • pp.123-132
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    • 2010
  • This paper presents a prestress-loss monitoring technique for prestressed concrete (PSC) girder structures that uses a vibration-based system identification method. First, the theoretical backgrounds of the prestress-loss monitoring technique and the system identification technique are presented. Second, vibration tests are performed on a lab-scaled PSC girder for which the modal parameter was measured for several prestress-force cases. A numerical modal analysis is performed by using an initial finite element (FE) model from the geometric, material, and boundary conditions of the lab-scaled PSC girder. Third, a vibration-based system identification is performed to update the FE model by identifying structural parameters since the natural frequency of the FE model became identical to the experimental results. Finally, the feasibility of the prestress-loss monitoring technique is evaluated for the PSC girder model by using the experimentally measured natural frequency and numerically identified natural frequency for several prestress-force cases.

A Study on Track Record and Trajectory Control of Robot Manipulator with Eight Joints Based on Monitoring Simulator for Smart Factory

  • Kim, Hee-jin;Jang, Gi-won;Kim, Dong-ho;Han, Sung-hyun
    • Journal of the Korean Society of Industry Convergence
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    • v.23 no.4_1
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    • pp.549-558
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    • 2020
  • We describe a new approach to real-time implementation of track record and trajectory control of robotic manipulator with eight joints based on monitoring simulator. Trajectory generator uses the kinematic equations of the arm to convert the task description into a series of set points for each of the joint control loops, while the joint controllers, with simple algorithms for just one joint can move at a fast sampling rate, guaranteeing a smooth motion. The proposed control scheme is robust, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate parameter information, nor values of manipulator parameters and payload. Reliability of the proposed technology is veriefied by monitoring simulation and experimental of robot manipulator for the smart factory with eight degrees of freedom.

Development of a Patient Monitoring System Overall Architecture and Specifications (환자모니터링시스템의 개발 : 전체구조 및 기본사양)

  • 우응제;박승훈
    • Journal of Biomedical Engineering Research
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    • v.18 no.1
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    • pp.17-24
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    • 1997
  • We have developed a patient monitoring system including module-based bedside monitors, interbed network, central stations, clinical workstations, and DB servers. A bedside monitor with a color LCD can accommodate up to 3 module cases and 21 different modules. Six different physiological parameters of ECG, respiration, invasive blood pressure, noninvasive blood pressure, body temperature, and arterial pulse oximetry with plethysmoyaph are provided as parameter modules. In a single bedside monitor, modules and a module controller communicate with IMbps data rate through an intrabed network based on RS-485 and HDU protocol. At the same time, it communicates with other bedside monitors and central stations through interbed network based on 1 OMbps Ethernet and TCP/IP protocol. Central stations using 20" color CRT monitors can be connected with many bedside monitors and they display 18 channels of waveforms simultaneously. Clinical workstations are used mainly for the review of patient datE In order to accommodate more advanced data management capabilities such as 24-hour full disclosure, we have developed a relational database server dedicated to the patient monitoring system. Software for bedside monitor, central station, and clinical workstation fully utilizes graphical user interface techniques and all functions are controlled by a rotate/push button on the bedside monitor arid a mouse on the central station and clinical workstation. The entire system satisfies the requirements of AAMI and ANSI standards in terms of electrical safety and performances.nces.

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Monitoring the Leachate Toxicities from a Pilot Landfill Treated with Chemical Oxidation using Hydrogen Peroxide and Aeration (과산화수소수와 통기에 의한 Chemical oxidation법을 적용한 모형 매립지로부터 생성된 침출수의 독성 monitoring)

  • Cho, Eun-Ah;Tameda, Kazuo;Hanashima, Masataka;Yoshijaki, Koudai;Uchida, Masanobu;Higuchi, Sotaro
    • Environmental Analysis Health and Toxicology
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    • v.23 no.4
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    • pp.307-314
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    • 2008
  • 폐기물 매립지의 조기 안전화를 위해 여러 가지 Chemical Oxidation법이 개발되어 왔지만, 이 방법을 폐기물 매립지에 적용하고 난 후에 생성될 수 있는 부산물들이 주변 환경에 영향을 줄 가능성이 있다. 그래서, 이 방법을 실제 매립지에 적용하기 전에, 일본 키타큐슈에 있는 소각재가 묻혀 있는 모형 매립지에 다섯 가지 조건 -A, 콤포스트 추가; B, 과산화수소수 살수; 과산화수소수+공기주입; D, 공기주입; E, control- 을 적용하여 그 효능을 테스트하였고, 이 매립지에서 이 방법들의 적용 후에 생성되는 침출수의 급성 독성을 세 가지 microbiotests를 이용하여 monitoring하였다. 테스트 기간 중, 침출수의 수질은 개선되었고, 그 급성 독성은 점차적으로 감소하였다. 과산화수소수와 공기의 조합을 적용한 후 생성된 침출수의 급성 독성이 가장 빨리 감소하여 폐기물 매립지의 조기 안정화에 도움을 주었다. 이러한 독성 시험 결과는 몇 가지 화학적 parameters와 상관성이 있었고 여기에 사용된 급성 독성 테스트법은, 매립지 안정화를 위한 Chemical Oxidation법의 적용 후, 침출수 수질을 monitoring하는데 적절하였다. 그러므로 폐기물 매립지의 조기 폐지 기준에 독성 시험의 포함을 고려해 볼 필요가 있다고 생각한다.

A Practical Measurement Method of the Occupied Bandwidth for 8-VSB DTV Signal Using Modified ACPR

  • Kim, Young Soo;Lee, Bong Gyou;Song, Kyeongmin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.7
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    • pp.3550-3565
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    • 2019
  • This paper proposes a new measurement method for the effective measurement of the 99% occupied bandwidth (OBW) at monitoring stations. Although the OBW measurement of radio signal is recommended by the International Telecommunication Union Radio (ITU-R) with several methods, there still does not exist a clear measurement recommendation or standard for terrestrial DTV signal on-air environment. Modified adjacent channel power ratio (MACPR), which can be applied to 8-VSB (Vestigial Side Band) DTV (Digital Television) signal, is herein defined to verify the results of measurements obtained using the proposed measurement method. MACPR is a proper measuring parameter for determining the measuring area of a monitoring station. From measurement results obtained in real field environment, it has been found that the OBW of 8-VSB DTV signal can be effectively measured in areas where the MACPR value is over 35 dB and when the measurements are repeated more than 600 times in the same reception site. It also has been verified that measured results are within an error range of +/-0.1% compared to results directly obtained at a transmission station. It is expected that the proposed method is able to be employed in order to determine the proper location of monitoring station and provide a reliable OBW measurement procedure for 8-VSB DTV signal on-air environment.

Adaptive Milling Process Modeling and Nerual Networks Applied to Tool Wear Monitoring (밀링공정의 적응모델링과 공구마모 검출을 위한 신경회로망의 적용)

  • Ko, Tae-Jo;Cho, Dong-Woo
    • Journal of the Korean Society for Precision Engineering
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    • v.11 no.1
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    • pp.138-149
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    • 1994
  • This paper introduces a new monitoring technique which utilizes an adaptive signal processing for feature generation, coupled with a multilayered merual network for pattern recognition. The cutting force signal in face milling operation was modeled by a low order discrete autoregressive model, shere parameters were estimated recursively at each sampling instant using a parameter adaptation algorithm based on an RLS(recursive least square) method with discounted measurements. The influences of the adaptation algorithm parameters as well as some considerations for modeling on the estimation results are discussed. The sensitivity of the extimated model parameters to the tool state(new and worn tool)is presented, and the application of a multilayered neural network to tool state monitoring using the previously generated features is also demonstrated with a high success rate. The methodology turned out to be quite suitable for in-process tool wear monitoring in the sense that the model parameters are effective as tool state features in milling operation and that the classifier successfully maps the sensors data to correct output decision.

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