• 제목/요약/키워드: Fatigue Monitoring

검색결과 206건 처리시간 0.023초

2차원 영상을 이용한 근전도신호의 피로도 해석에 관한연구 (A Study on the Measuring EMG Signal Using Two-Dimensional images of the Fatigue analysis)

  • 강병종;이영석
    • 한국산학기술학회:학술대회논문집
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    • 한국산학기술학회 2009년도 추계학술발표논문집
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    • pp.1010-1013
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    • 2009
  • 본 논문에서는 STFT을 이용한 이두박근의 근전도 신호 근피로도 측정 방법을 제시한다. 개선된 STFT방식은 기존연구에서 사용되어져 왔던 중간주파수를 이용한 근피로도 측정 방법과 달리 STFT를 이용한 시간, 주파수 평면에서 2차원 영상을 이용하여 근피로도를 측정할 수 있는 방법이다. 제안한 방법은 이두박근에서 수집한 근전도 신호의 근피로도 측정에 사용하여 제안한 방법의 타당성을 검증하였다.

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Characteristics of Elastic Waves Generated by Fatigue Crack Penetration and Growth in an Aluminum Plate

  • Ahn, Seok-Hwan;Nam, Ki-Woo
    • Journal of Mechanical Science and Technology
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    • 제17권11호
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    • pp.1599-1607
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    • 2003
  • The characteristics of elastic waves emanated from crack initiation in 6061 aluminum alloy subjected to fatigue loading are investigated through experiments. The objective of the study is to determine the differences in the properties of the signals generated from fatigue test and also to examine if the sources of the waves could be identified from the temporal and spectral characteristics of the acoustic emission (AE) waveforms. The signals are recorded using nonresonant, flat, broadband transducers attached to the surface of the alloy specimens. The time dependence and power spectra of the signals recorded during the tests were examined and classified according to their special features. Six distinct types of signals were observed. The waveforms and their power spectra were found to be dependent on the crack propagation stage and the type of fracture associated with the signals. The potential application of the approach in health monitoring of structural components using a network of surface mounted broadband sensors is discussed.

배기계 플랜지 용접부 피로파괴 예측을 위한 음향방출 신호 특성 (Signal Characteristics of Acoustic Emission from Welded Exhaust Flange for Fatigue Fracture Prediction)

  • 손민영;최정황;김찬묵
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2007년도 춘계학술대회논문집
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    • pp.905-908
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    • 2007
  • The purpose of this work is to obtain fundamental data about fatigue crack detection of the welded exhaust flange by using the AE method. The acoustic emission method as a nondestructive evaluation is one of high technical test for realtime monitoring in the dangerous industry fields. Signal analysis of both AE sensor and accelerometer for fatigue crack failure are presented in this paper.

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Application of the Electrochemical Noise Method with Three Electrodes to Monitor Corrosion and Environmental Cracking in Chemical Plants

  • Ohtsu, Takao;Miyazawa, Masazumi;Ebara, Ryuicluro
    • Corrosion Science and Technology
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    • 제7권3호
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    • pp.173-178
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    • 2008
  • Recently an electrochemical noise method (ENM) with three electrodes has gained attention as a corrosion monitoring system in chemical plants. So far a few studies have been carried out for localized corrosion and environmental cracking of chemical plant materials. In this paper the ENM system is briefly summarized. Then an application of ENM to general corrosion for chemical plant materials is described. The emphasis is focused upon the analysis of stress on the corrosion cracking process of austenitic stainless steel in 30% $MgCl_2$ aqueous solution and the corrosion fatigue crack initiation process of 12 Cr stainless steel in 3% NaCl aqueous solution by ENM. Finally future problems for ENM to monitor regarding corrosion and environmental cracking in chemical plants are discussed.

피로균열의 지연거동에 따른 수명예측 및 비파괴평가 (Life Prediction by Retardation Behavior of Fatigue Crack and its Nondestructive Evaluation)

  • 남기우;김선진
    • 한국해양공학회지
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    • 제13권3호통권33호
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    • pp.36-48
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    • 1999
  • Fatigue life and crack retardation behavior after penetration were experimentally examined using surface pre-cracked specimens of aluminium alloy 5083. The Wheeler model retardation parameter was used successfully to predict crack growth behavior after penetration. By using a crack propagation rule, the change in crack shape after penetration can be evaluated quantitatively. Advanced, waveform-based acoustic emission (AE) techniques have been successfully used to evaluate signal characteristics obtained form fatigue crack propagation and penetratin behavior in 6061 aluminum plate with surface crack under fatigue stress. Surface defects in the structural members are apt to be origins of fatigue crack growth, which may cause serious failure of the whole structure. The nondestructive analysis on the crack growth and penetration from these defects may, therefore, be one of the most important subjects on the reliability of the leak before break (LBB) design. The goal of the present study is to determine if different sources of the AE could be identified by characteristics of the waveforms produced from the crack growth and penetration. AE signals detected in four stages were found to have different signal per stage. With analysis of waveform and power spectrum in 6061 aluminum alloys with a surface crack, it is found to be capabilities on real-time monitoring for the crack propagation and penetration behavior of various damages and defects in structural members.

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광섬유센서를 이용한 복합재 패치수리된 알루미늄판의 균열관찰 (FATIGUE CRACK GROWTH MONITORING OF CRACKED ALUMINUM PLATE REPAIRED WITH COMPOSITE PATCH USING EMBEDDED OPTICAL FIBER SENSORS)

  • 서대철;이정주;김상훈
    • 한국복합재료학회:학술대회논문집
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    • 한국복합재료학회 2001년도 춘계학술발표대회 논문집
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    • pp.250-253
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    • 2001
  • Recently, based on the smart structure concept, optical fiber sensors have been increasingly applied to monitor the various engineering and civil structural components. Repairs based on adhesively bonded fiber reinforce composite patches are more structurally efficient and much less damaging to the parent structure than standard repairs based on mechanically fastened metallic patches. As a result of the high reinforcing efficiency of bonded patches fatigue cracks can be successfully repaired. However, when such repairs are applied to primary structures, it is needed to demonstrate that its loss can be immediately detected. This approach is based on the "smart patch" concept in which the patch system monitors its own health. The objective of this study is to evaluate the potentiality of application of transmission-type extrinsic Fabry-Perot optical fiber sensor (TEFPI) to the monitoring of crack growth behavior of composite patch repaired structures. The sensing system of TEFPI and the data reduction principle for the detection of crack detection are presented. Finally, experimental results from the tests of center-cracked-tension aluminum specimens repaired with bonded composite patch is presented and discussed.

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Applications of fiber optic sensors for structural health monitoring

  • Kesavan, K.;Ravisankar, K.;Parivallal, S.;Sreeshylam, P.
    • Smart Structures and Systems
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    • 제1권4호
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    • pp.355-368
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    • 2005
  • Large and complex structures are being built now-a-days and, they are required to be functional even under extreme loading and environmental conditions. In order to meet the safety and maintenance demands, there is a need to build sensors integrated structural system, which can sense and provide necessary information about the structural response to complex loading and environment. Sophisticated tools have been developed for the design and construction of civil engineering structures. However, very little has been accomplished in the area of monitoring and rehabilitation. The employment of appropriate sensor is therefore crucial, and efforts must be directed towards non-destructive testing techniques that remain functional throughout the life of the structure. Fiber optic sensors are emerging as a superior non-destructive tool for evaluating the health of civil engineering structures. Flexibility, small in size and corrosion resistance of optical fibers allow them to be directly embedded in concrete structures. The inherent advantages of fiber optic sensors over conventional sensors include high resolution, ability to work in difficult environment, immunity from electromagnetic interference, large band width of signal, low noise and high sensitivity. This paper brings out the potential and current status of technology of fiber optic sensors for civil engineering applications. The importance of employing fiber optic sensors for health monitoring of civil engineering structures has been highlighted. Details of laboratory studies carried out on fiber optic strain sensors to assess their suitability for civil engineering applications are also covered.

Systematic test on the effectiveness of MEMS nano-sensing technology in monitoring heart rate of Wushu exercise

  • Shuo Guan
    • Advances in nano research
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    • 제15권2호
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    • pp.155-163
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    • 2023
  • Exercise is beneficial to the body in some ways. It is vital for people who have heart problems to perform exercise according to their condition. This paper describes how an Android platform can provide early warnings of fatigue during wushu exercise using Photoplethysmography (PPG) signals. Using the data from a micro-electro-mechanical system (MEMS) gyroscope to detect heart rate, this study contributes an algorithm to determine a user's fatigue during wushu exercise. It sends vibration messages to the user's smartphone device when the heart rate exceeds the limit or is too fast during exercise. The heart rate monitoring system in the app records heart rate data in real-time while exercising. A simple pulse sensor and Android app can be used to monitor heart rate. This plug-in sensor measures heart rate based on photoplethysmography (PPG) signals during exercise. Pulse sensors can be easily inserted into the fingertip of the user. An embedded microcontroller detects the heart rate by connecting a pulse sensor transmitted via Bluetooth to the smartphone. In order to measure the impact of physical activity on heart rate, Wushu System tests are conducted using various factors, such as age, exercise speed, and duration. During testing, the Android app was found to detect heart rate with an accuracy of 95.3% and to warn the user when their heart rate rises to an abnormal level.

스마트 웨어러블 디바이스를 이용한 모바일 기반 사용자 피로도 측정 시스템 개발 (Development of mobile user fatigue measurement system using smart wearable device)

  • 김나연;김동근
    • 한국정보통신학회논문지
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    • 제21권12호
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    • pp.2357-2364
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    • 2017
  • 최근 건강관리에 대한 관심이 높아지면서 건강상태를 모니터링 하기 위한 스마트 웨어러블 디바이스가 활용되어 오고 있다. 본 논문에서는 스마트 웨어러블 디바이스와 연동된 피로도 측정 시스템을 개발하였다. 충분히 휴식을 취하면 회복되는 신체적인 피로도와는 달리 정신적인 피로도는 일의 능률이나 집중력을 떨어트릴 수 있으므로 측정을 통해 정신 건강 상태를 모니터링 할 수 있다. 본 시스템은 스마트 웨어러블 디바이스에서 계측한 데이터를 스마트폰으로 전송하고 정신적인 피로도를 계산해주는 기능을 제공한다. 피로도를 측정하기 위한 피로도 인덱스를 개발하여 1부터 5까지의 수치로 표현하였다. 또한 피로도 계산 결과와 설문조사 결과와 비교하여 독립표본 t-검정을 실시한 결과 통계적으로 유의한 값이 나왔다. 본 시스템은 사용자들이 건강을 효율적으로 관리하는 데에 활용될 것이다.

SHM-based probabilistic representation of wind properties: statistical analysis and bivariate modeling

  • Ye, X.W.;Yuan, L.;Xi, P.S.;Liu, H.
    • Smart Structures and Systems
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    • 제21권5호
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    • pp.591-600
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    • 2018
  • The probabilistic characterization of wind field characteristics is a significant task for fatigue reliability assessment of long-span railway bridges in wind-prone regions. In consideration of the effect of wind direction, the stochastic properties of wind field should be represented by a bivariate statistical model of wind speed and direction. This paper presents the construction of the bivariate model of wind speed and direction at the site of a railway arch bridge by use of the long-term structural health monitoring (SHM) data. The wind characteristics are derived by analyzing the real-time wind monitoring data, such as the mean wind speed and direction, turbulence intensity, turbulence integral scale, and power spectral density. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method is proposed to formulate the joint distribution model of wind speed and direction. For the probability density function (PDF) of wind speed, a double-parameter Weibull distribution function is utilized, and a von Mises distribution function is applied to represent the PDF of wind direction. The SQP algorithm with multi-start points is used to estimate the parameters in the bivariate model, namely Weibull-von Mises mixture model. One-year wind monitoring data are selected to validate the effectiveness of the proposed modeling method. The optimal model is jointly evaluated by the Bayesian information criterion (BIC) and coefficient of determination, $R^2$. The obtained results indicate that the proposed SQP algorithm-based finite mixture modeling method can effectively establish the bivariate model of wind speed and direction. The established bivariate model of wind speed and direction will facilitate the wind-induced fatigue reliability assessment of long-span bridges.