• Title/Summary/Keyword: 손상 검출

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Damage Classification by Time Density Function of Ultrasonic Pulse Signal occurred at Tire (타이어에서 발생하는 초음파펄스신호의 시간밀도함수에 의한 손상 분별)

  • Kang, Dae-Soo
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.15 no.6
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    • pp.291-296
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    • 2015
  • The tire damage classification method is researched on the periodicity detection of ramdomness ultrasonic signals to occur at the driving vehicle tire. Setting method of adaptive threshold is proposed in order to valid pulse detection by tire damage in ultrasonic noise on the road and used low pass filter for decrease signal ramdomness as preprocessing. Time interval of detected pulse is setted the density function depend on the vehicle's speed and the method of tire damage detection is proposed that measuring the first peak's time of time density function.The result of time density function in case of one damage material, the first peak's time is measured within the error limit of tire's rotation period, 169.8ms and 97.9ms and 81.8ms, about the speed of 50km/h and 80km/h and 100km/h. In case of more than one damage material, the sum of each peak's time is measured within the error limit of tire's rotation period about the speed.

Ultrasonic Inspection Technology of Defect Detection of Propellant/Liner Debond & Propellant Microcrack (초음파를 이용한 추진제/라이너 미접착 및 추진제 미세 크랙의 결함 검출 기법)

  • Na, Sung-Youb
    • Journal of the Korean Society of Propulsion Engineers
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    • v.11 no.1
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    • pp.34-42
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    • 2007
  • Ultrasonic inspection method is more profitable than X-ray radiographic inspection in cost and effect of defect detection such as debond, damage, and it doesn't need special constructions. The method can also be a possible real time inspection with safety. This report explains 1)the experiment and analysis of ultrasonic property of solid propellant, 2)the inspection methods of propellant/liner debond by inside or outside inspection, and 3)the inspection methods of propellant microcrack by damage. From the results, it is possible to detect the defect of propellant/liner debond by inside or outside inspection. Futhermore, it can be possible to detect the propellant microcrack caused by damage using the ultrasonic attenuation.

Detection and Evaluation Technique of Hydrogen Attack (수소손상 검출과 평가기술)

  • Won, Soon-Ho;Hyun, Yang-Ki;Lee, Jong-O;Cho, Kyung-Shik;Lee, Jae-Do
    • Journal of the Korean Society for Nondestructive Testing
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    • v.22 no.1
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    • pp.32-37
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    • 2002
  • The presence of hydrogen in industrial plants is a source of damage. Hydrogen attack is one such form of degradation and often causing large tube ruptures that necessitate an immediate shutdown. Hydrogen attack may reduce the fracture toughness as well as the strength of steels. This reduction is caused partially by the presence of cavities and microcracks at the grain boundaries. In the past several techniques have been used with limited results. This paper describes the application of an ultrasonic velocity and attenuation in hydrogen damage. Ultrasonic tests showed a decrease in wave velocity and an increase in attenuation. Such results demonstrate the potential for ultrasonic nondestructive testing to quantify damage. Based on this study, reliable recommendation is suggested to detect hydrogen attack.

Bolt-Loosening Detection using Vision-Based Deep Learning Algorithm and Image Processing Method (영상기반 딥러닝 및 이미지 프로세싱 기법을 이용한 볼트풀림 손상 검출)

  • Lee, So-Young;Huynh, Thanh-Canh;Park, Jae-Hyung;Kim, Jeong-Tae
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.32 no.4
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    • pp.265-272
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    • 2019
  • In this paper, a vision-based deep learning algorithm and image processing method are proposed to detect bolt-loosening in steel connections. To achieve this objective, the following approaches are implemented. First, a bolt-loosening detection method that includes regional convolutional neural network(RCNN)-based deep learning algorithm and Hough line transform(HLT)-based image processing algorithm are designed. The RCNN-based deep learning algorithm is developed to identify and crop bolts in a connection image. The HLT-based image processing algorithm is designed to estimate the bolt angles from the cropped bolt images. Then, the proposed vision-based method is evaluated for verifying bolt-loosening detection in a lab-scale girder connection. The accuracy of the RCNN-based bolt detector and HLT-based bolt angle estimator are examined with respect to various perspective distortions.

A Study on Real-Time Fault Monitoring Detection Method of Bearing Using the Infrared Thermography (적외선 열화상을 이용한 베어링의 실시간 고장 모니터링 검출기법에 관한 연구)

  • Kim, Ho-Jong;Hong, Dong-Pyo;Kim, Won-Tae
    • Journal of the Korean Society for Nondestructive Testing
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    • v.33 no.4
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    • pp.330-335
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    • 2013
  • Since real-time monitoring system like a fault early detection has been very important, infrared thermography technique as a new diagnosis method was proposed. This study is focused on the damage detection and temperature characteristic analysis of ball bearing using the non-destructive infrared thermography method. In this paper, for the reliability assessment, infrared experimental data were compared with the frequency data of the existing. As results, the temperature characteristics of ball bearing were analyzed under various loading conditions. Finally it was confirmed that the infrared technique was useful for real-time detection of the bearing damages.

Robust Detection Deep Learning Model in the Various Exterior Wall Cracks (다양한 외벽 균열에 강인한 딥러닝 검출 모델 개발)

  • Kim, Gyeong-Yeong;Lee, Ho-Ryeong;Kim, Dong-Ju
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2021.07a
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    • pp.53-56
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    • 2021
  • 국내 산업화가 들어선 후 산업화 당시 지었던 낙후된 건물의 증가에 따라 구조물의 손상 조사 및 검사 방법의 수요가 늘어나고 있다. 일반적으로 구조물의 손상은 전문 검사원이 현장에서 직접 측량도구와 시각적인 방식으로 검사한다. 그러나 전문 검사원들이 직접 조사하는 수고에 비해 균열을 검사하는 방식 자체가 단순하고, 일반 사람이 검사하기에는 객관성이 떨어지는 한계가 있어 균열을 자동적으로 검출함으로써 객관성과 편의성을 보장할 기술이 필요하다. 본 연구에서는 이미지 기반으로 다양한 환경에서의 외벽 균열을 검출할 수 있는 딥러닝 모델 개발을 소개한다. 균열 검출을 위해 다양한 외벽 균열 관련 데이터셋을 확보 및 구축하고 각 데이터셋의 검출 정보를 보완할 반자동(semi-auto) 라벨링 작업을 수행하였다. 두 번째로 기존 높은 검출 성능을 보였던 모델들을 선정 및 비교하여 YOLO v5 모델을 최종적으로 선정하였고, 도메인이 각각 다른 데이터셋에 대한 교차 학습을 통해 각 데이터셋의 mAP의 편차가 31%에서 11%로 좁히는 작업을 수행하였다. 이를 통해 실제 상황에서의 균열 영상에서 균열을 검출할 수 있는 측량 시스템을 개발함으로써 실질적인 검사의 도구로 활용될 수 있길 기대한다.

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Study on the Failure Case of Potential Transformer for Generator Protection Relay (발전기 보호계전기용 계기용변성기(PT) 손상 사례에 관한 연구)

  • Park, Jin-Yeub;Chin, Soo-Hwan;Park, In-Kyoo
    • Proceedings of the KIEE Conference
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    • 2011.07a
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    • pp.2065-2066
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    • 2011
  • 기계적에너지를 전기적에너지로 변환하는 발전기를 내 외부 고장으로부터 보호하기 위해 보호계전기가 설치되어 있으며, 이러한 보호계전기의 동작신호 중 하나인 전압신호를 검출하기 위해 발전기와 변압기를 연결하는 모선에 설치된 계기용변성기를 이용한다. 본 논문은 발전기의 보호계전기용 계기용변성기 손상원인에 관한 연구로서, 계기용변성기의 철공진에 이한 손상가능성을 고찰하였고 발전소에 많이 사용되는 G사의 계기용변성기와 손상된 I사의 계기용변성기에 대한 전기적 시험결과를 비교하였으며, 계기용변성기를 직접 절개하여 제작 및 적용특성을 분석하였다. 그 결과 발전기 전압신호 검출용 계기용변성기는 발전기 중성점 접지형태에 관계없이 반드시 Line to Line type을 적용해야 함을 도출했다.

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Comparison of FEA with Condition Monitoring for Real-Time Damage Detection of Bearing Using Infrared Thermography Techniques (적외선열화상을 이용한 베어링 실시간 손상검출 상태감시의 전산수치해석 비교)

  • Kim, Hojong;Kim, Wontae
    • Journal of the Korean Society for Nondestructive Testing
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    • v.35 no.3
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    • pp.185-192
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    • 2015
  • Since real-time monitoring systems, such as early fault detection, have been very important, an infrared thermography technique was proposed as a new diagnosis method. This study focused on damage detection and temperature characteristic analysis of ball bearings using the non-destructive, infrared thermography method. In this paper, for the reliability assessment, infrared experimental data were compared with finite element analysis (FEA) results from ANSYS. In this investigation, the temperature characteristics of ball bearing were analyzed under various loading conditions. Finally, it was confirmed that the infrared thermography technique was useful for the real-time detection of damage to bearings.

Damage Detection of Truss Structures Using Nonlinear Parametric Projection Filter (비선형 파라메트릭 사영필터에 의한 트러스 구조물의 손상 검출)

  • Mun, Hyo-Jun;Suh, Ill-Gyo
    • Journal of Korean Association for Spatial Structures
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    • v.4 no.2 s.12
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    • pp.73-80
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    • 2004
  • In this paper, a study of damage detection for 2-Dimensional Truss Structures using the parametric projection filter theorr is presented. Many researchers are interested in inverse problem and one of solution procedures for inverse problems that are very effective is the approach using the filtering algorithm in conjunction with numerical solution methods. In filtering algorithm, the Kalman filtering algorithm is well known and have been applied to many kind of inverse problems. In this paper, the Parametric projection filtering in conjunction with structural analysis is applied to the identification of damages in 2-D truss structures. The natural frequency and modes of damaged truss model are adopted as the measurement data. The effectiveness of proposed method is verified through the numerical examples.

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모터전류를 기초로한 드릴마멸 모델링

  • 김화영;안중환;김선호
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1993.10a
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    • pp.64-69
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    • 1993
  • 최근의 생산시스템은 FMS,FMC와 같은 고도로 자동화된 무인시스템으로 운용되고 있으며, 생산성 향상을 위한 무인운전의 필요성이 증대되고 있으나, 숙련된 작업자를 대신하여 작업상태를 감시하는 신뢰성 있는 감시 시스템의 부족으로 인해 곤란을 겪고 있다.따라서 작업자를 대신할수 있는 신뢰성있는 감시 시스템의 개발을 필요로 한다. 특히 공구파손,공구마멸과 같은 공구손상은 공작물 및 기계에 치명적 손상을 초래하고, 기계정지시간을 증가시키므로 공구파손 검출과 공구마멸의 실시간 센싱은 가공 프로세스의 자동화와 신뢰성을 증가시키는데 가장 중요한 역활을 수행한다. 본 연구에서는 드릴가공시 검출한 주축 및 Z축 모터전류를 기초로 하여 드릴마멸을 추정하는 모델을 개발하고자 한다.

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