• Title/Summary/Keyword: vibration-based monitoring

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Safety assessment of nuclear fuel reprocessing plant under the free drop impact of spent fuel cask and fuel assembly part I: Large-scale model test and finite element model validation

  • Li, Z.C.;Yang, Y.H.;Dong, Z.F.;Huang, T.;Wu, H.
    • Nuclear Engineering and Technology
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    • v.53 no.8
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    • pp.2682-2695
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    • 2021
  • This paper aims to evaluate the structural dynamic responses and damage/failure of the nuclear fuel reprocessing plant under the free drop impact of spent fuel cask (SFC) and fuel assembly (FA) during the on-site transportation. At the present Part I of this paper, the large-scale SFC model free drop test and the corresponding numerical simulations are performed. Firstly, a composite target which is composed of the protective structure, i.e., a thin RC plate (representing the inverted U-shaped slab in the loading shaft) and/or an autoclaved aerated concrete (AAC) blocks sacrificial layer, as well as a thick RC plate (representing the bottom slab in the loading shaft) is designed and fabricated. Then, based on the large dropping tower, the free drop test of large-scale SFC model with the mass of 3 t is carried out from the height of 7 m-11 m. It indicates that the bottom slab in the loading shaft could not resist the free drop impact of SFC. The composite protective structure can effectively reduce the damage and vibrations of the bottom slab, and the inverted U-shaped slab could relieve the damage of the AAC blocks layer dramatically. Furthermore, based on the finite element (FE) program LS-DYNA, the corresponding refined numerical simulations are performed. By comparing the experimental and numerical damage and vibration accelerations of the composite structures, the present adopted numerical algorithms, constitutive models and parameters are validated, which will be applied in the further assessment of drop impact effects of full-scale SFC and FA on prototype nuclear fuel reprocessing plant in the next Part II of this paper.

Fault diagnosis system of induction motor using artificial neural network (인공신경망을 이용한 유도전동기고장진단)

  • Byun, Yeun-Sub;Wang, Jong-Bae;Kim, Jong-Ki
    • Proceedings of the KIEE Conference
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    • 2002.07d
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    • pp.2222-2224
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    • 2002
  • Induction motors are critical components of many industrial machines and are frequently integrated in commercial equipment. The heavy economical losses and the deterioration of system reliability might be caused by the failure of induction motors in industrial field. Based on the reliability and cost competitiveness of driving system (motors), the faults detection and diagnosis of system is considered very important factors. In order to perform the faults detection and diagnosis of motors, the vibration monitoring method and motor current signature analysis (MCSA) method are emphasized. In this paper, MCSA method are used for induction motor fault diagnosis. This method analyzes the motors supply current. since this diagnoses faults of the motor. The diagnostic algorithm is based on the artificial neural network, and the diagnosis system is programmed by using LabVIEW and MATLAB.

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Fault diagnosis of induction motor using principal component analysis (주성분 분석기법을 통한 유도전동기 고장진단)

  • Byun Yeun-Sub;Lee Byung-Song;Bae Chang-Han;Wang Jong-Bae
    • Proceedings of the KSR Conference
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    • 2003.10c
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    • pp.529-534
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    • 2003
  • Within industry induction motors have a broad application area to drive pumps, fans, elevators and electric trains. Sudden failures of such machines can cause the heavy economical losses and the deterioration of system reliability. Based on the reliability and cost competitiveness of driving system (motors), the faults detection and the diagnosis of system are considered very important factors. In order to perform the faults detection and diagnosis of motors, the vibration monitoring method and motor current signature analysis (MCSA) method are emphasized. In this paper, MCSA method are used for induction motor fault diagnosis. This method analyzes the motor's supply current, since this diagnoses faults of the motor. The diagnostic algorithm is based on the principal component analysis(PCA), and the diagnosis system is programmed by using LabVIEW and MATLAB.

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Fault diagnosis of induction motor using principal component analysis (주성분 분석기법을 이용한 유도전동기 고장진단)

  • Byun, Yeun-Sub;Lee, Byung-Song;Baek, Jong-Hyen;Wang, Jong-Bae
    • Proceedings of the KIEE Conference
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    • 2003.11c
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    • pp.645-648
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    • 2003
  • Induction motors are a critical component of industrial processes. Sudden failures of such machines can cause the heavy economical losses and the deterioration of system reliability. Based on the reliability and cost competitiveness of driving system (motors), the faults detection and the diagnosis of system are considered very important factors. In order to perform the faults detection and diagnosis of motors, the vibration monitoring method and motor current signature analysis (MCSA) method are emphasized. In this paper, MCSA method is used for induction motor fault diagnosis. This method analyses the motor's supply current. since this diagnoses faults of the motor. The diagnostic algorithm is based on the principal component analysis(PCA), and the diagnosis system is programmed by using LabVIEW and MATLAB.

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Development and deployment of large scale wireless sensor network on a long-span bridge

  • Pakzad, Shamim N.
    • Smart Structures and Systems
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    • v.6 no.5_6
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    • pp.525-543
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    • 2010
  • Testing and validation processes are critical tasks in developing a new hardware platform based on a new technology. This paper describes a series of experiments to evaluate the performance of a newly developed MEMS-based wireless sensor node as part of a wireless sensor network (WSN). The sensor node consists of a sensor board with four accelerometers, a thermometer and filtering and digitization units, and a MICAz mote for control, local computation and communication. The experiments include calibration and linearity tests for all sensor channels on the sensor boards, dynamic range tests to evaluate their performance when subjected to varying excitation, noise characteristic tests to quantify the noise floor of the sensor board, and temperature tests to study the behavior of the sensors under changing temperature profiles. The paper also describes a large-scale deployment of the WSN on a long-span suspension bridge, which lasted over three months and continuously collected ambient vibration and temperature data on the bridge. Statistical modal properties of a bridge tower are presented and compared with similar estimates from a previous deployment of sensors on the bridge and finite element models.

The Study of Predictive Diagnosis Technology Development Status and Promotion Plan for Reactor Coolant Pump (원자로냉각재펌프 예측진단 기술개발 현황 및 추진방안)

  • Hee Chan Kim
    • Transactions of the Korean Society of Pressure Vessels and Piping
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    • v.19 no.1
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    • pp.44-51
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    • 2023
  • The RCP is one of the main components in nuclear power plants and plays an important role in circulating coolant to the RCS system. Currently, nuclear plants are monitored using various monitoring systems. However, since they operate independently according to their functional purpose, it is not able to analyze vibration and operation/performance information comprehensively, and thus failure diagnosis accuracy is limited. In addition, these systems do not provide some important information (such as fault type, parts and cause) necessary for emergency actions, but provide only alarm information. To improve these technical problems, this study proposes a diagnosis technique (M/L, Rule-based model, Data-driven model, Narrow band model) and methodology for comprehensive analysis.

Development of Diagnosis System for LNG Pump (LNG 펌프 고장 진단 시스템 개발)

  • Hong S. H.;Lee Y. W.;Hwang W G.;Ki Ch. D.;Kim Y. B.
    • Journal of the Korean Institute of Gas
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    • v.2 no.3
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    • pp.88-95
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    • 1998
  • Vibration analysis of rotating machinery can give an indication of possible faults thus allowing maintenance before further damage occurs. Current predictive maintenance system installed in Pyung-tak has the ability to diagnose the mechanical problems within the LNG Pump when the vibration exceeds preset overall alarm levels. In this study, LNG pump auto-diagnosis system based upon Windows NT and DSP Board is developed. This system analysis velocity signal acquired from dual accelerometer input monitor system to diagnose pump condition. Many plots which display machine condition are shown and features of vibration are stored in every time. If the fault is found, the system diagnoses automatically using expert system and trend monitoring. Operator checks pump condition intuitively using personal computer monitor.

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Design and evaluation of an experimental system for monitoring the mechanical response of piezoelectric energy harvesters

  • Kim, Changho;Ko, Youngsu;Kim, Taemin;Yoo, Chan-Sei;Choi, BeomJin;Han, Seung Ho;Jang, YongHo;Kim, Youngho;Kim, Namsu
    • Smart Structures and Systems
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    • v.22 no.2
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    • pp.133-137
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    • 2018
  • Increasing interest in prognostics and health management has heightened the need for wireless sensor networks (WSN) with efficient power sources. Piezoelectric energy harvesters using Pb(Zr,Ti)O3 (PZT) are one of the candidate power sources for WSNs as they efficiently convert mechanical vibration energy into electrical energy. These types of devices are resonated at a specific frequency, which has a significant impact on the amount of energy harvested, by external vibration. Hence, precise prediction of mechanical deformation including modal analysis of piezoelectric devices is crucial for estimating the energy generated under specific conditions. In this study, an experimental vibrational system capable of controlling a wide range of frequencies and accelerations was designed to generate mechanical vibration for piezoelectric energy harvesters. In conjunction with MATLAB, the system automatically finds the resonance frequency of harvesters. A small accelerometer and non-contact laser displacement sensor are employed to investigate the mechanical deformation of harvesters. Mechanical deformation under various frequencies and accelerations were investigated and analyzed based on data from two types of sensors. The results verify that the proposed system can be employed to carry out vibration experiments for piezoelectric harvesters and measurement of their mechanical deformation.

Dynamic Parameter Estimation of a CANDU Type Containment Using Ambient Vibration Measurements (상시진동을 이용한 CANDU형 격납건물의 동적파라미터 산정)

  • Choi, Sanghyun;Park, Sooyong;Hyun, Chang-Hun;Kim, Moon-Soo
    • Journal of the Society of Disaster Information
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    • v.8 no.2
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    • pp.188-196
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    • 2012
  • Dynamic parameters such as natural frequencies can provide global stiffness information of a structure, and thus be utilized in monitoring structural integrity of large structures such as a containment. To identify the dynamic parameters without interrupting normal operation, a modal analysis method based on ambient vibration measurements should be applied. In this study, dynamic parameters of the containment of Wolsong Unit 2 are identified using ambient vibration measurement data. The feasibility of the study is verified using a numerical model for the containment. From the modal analysis, dynamic parameters of the containment with acceptable correlation to analytical modes can be estimated.

Multi-condition optimization and experimental verification of impeller for a marine centrifugal pump

  • Wang, Kai;Luo, Guangzhao;Li, Yu;Xia, Ruichao;Liu, Houlin
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.12 no.1
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    • pp.71-84
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    • 2020
  • In order to improve the performance of marine centrifugal pump, a centrifugal pump whose specific speed is 66.7 was selected for the research. Outlet diameter D2, outlet width b2, blade outlet angle β2, blade wrap φ and blade number z of the impeller were chosen as the variables. The maximum weighted average efficiency and the minimum vibration intensity at the base were calculated as objectives. Based on the Latin Hypercube method, the impeller was numerically optimized. The numerical results show that after optimization, the amplitudes of pressure fluctuation on the main frequency at different monitoring points decrease in varying degrees. The radial force on impeller decreases obviously under off-design flow rates and is more symmetrical during the operation of the pump. The variation of the axial force is relatively small, which has no obvious relationship with the rotating angle of the impeller. The energy performance and vibration experiment was performed for verifying. The test results show that the weighted average efficiency under 0.8Qd, 1.0Qd and 1.2Qd increases by 4.3% after optimization. The maximal vibration intensity at M1-M4 on the pump base reduced from 0.36 mm/s to 0.25 mm/s, decreasing by 30.5%. In addition, the vibration velocities of bracket in pump side and outlet flange also have significant reductions.