• 제목/요약/키워드: Detecting crack

검색결과 116건 처리시간 0.029초

Crack identification with parametric optimization of entropy & wavelet transformation

  • Wimarshana, Buddhi;Wu, Nan;Wu, Christine
    • Structural Monitoring and Maintenance
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    • 제4권1호
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    • pp.33-52
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    • 2017
  • A cantilever beam with a breathing crack is studied to improve the breathing crack identification sensitivity by the parametric optimization of sample entropy and wavelet transformation. Crack breathing is a special bi-linear phenomenon experienced by fatigue cracks which are under dynamic loadings. Entropy is a measure, which can quantify the complexity or irregularity in system dynamics, and hence employed to quantify the bi-linearity/irregularity of the vibration response, which is induced by the breathing phenomenon of a fatigue crack. To improve the sensitivity of entropy measurement for crack identification, wavelet transformation is merged with entropy. The crack identification is studied under different sinusoidal excitation frequencies of the cantilever beam. It is found that, for the excitation frequencies close to the first modal frequency of the beam structure, the method is capable of detecting only 22% of the crack depth percentage ratio with respect to the thickness of the beam. Using parametric optimization of sample entropy and wavelet transformation, this crack identification sensitivity is improved up to 8%. The experimental studies are carried out, and experimental results successfully validate the numerical parametric optimization process.

Semantic crack-image identification framework for steel structures using atrous convolution-based Deeplabv3+ Network

  • Ta, Quoc-Bao;Dang, Ngoc-Loi;Kim, Yoon-Chul;Kam, Hyeon-Dong;Kim, Jeong-Tae
    • Smart Structures and Systems
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    • 제30권1호
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    • pp.17-34
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    • 2022
  • For steel structures, fatigue cracks are critical damage induced by long-term cycle loading and distortion effects. Vision-based crack detection can be a solution to ensure structural integrity and performance by continuous monitoring and non-destructive assessment. A critical issue is to distinguish cracks from other features in captured images which possibly consist of complex backgrounds such as handwritings and marks, which were made to record crack patterns and lengths during periodic visual inspections. This study presents a parametric study on image-based crack identification for orthotropic steel bridge decks using captured images with complicated backgrounds. Firstly, a framework for vision-based crack segmentation using the atrous convolution-based Deeplapv3+ network (ACDN) is designed. Secondly, features on crack images are labeled to build three databanks by consideration of objects in the backgrounds. Thirdly, evaluation metrics computed from the trained ACDN models are utilized to evaluate the effects of obstacles on crack detection results. Finally, various training parameters, including image sizes, hyper-parameters, and the number of training images, are optimized for the ACDN model of crack detection. The result demonstrated that fatigue cracks could be identified by the trained ACDN models, and the accuracy of the crack-detection result was improved by optimizing the training parameters. It enables the applicability of the vision-based technique for early detecting tiny fatigue cracks in steel structures.

상관함수 기반 굴삭기용 과부하 검출 기법 (An Overload Detecting Method for an Excavator Based on the Correlation Function)

  • 유창호;고남곤;최재원;서영봉
    • 제어로봇시스템학회논문지
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    • 제16권7호
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    • pp.703-710
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    • 2010
  • In this paper, an overload detecting algorithm for an excavator is presented. The proposed overload detecting algorithm is based on the time series analysis especially correlation function. The main purpose of this paper is to prevent damage or crack from the fatigue loaded on an excavator in advance. Generally, the larger data, the longer processing time, and the amount of the data used in this paper are also large, especially every sampling period, 1600 data are gathered and calculated. So this paper focuses on minimizing the number of required sensors by using the correlation function. From the cross correlation function, similar pattern sensors are eliminated and dissimilar pattern sensors are considered, and from the auto correlation function, the overload can be detected. To prove the efficiency of the proposed overload detecting algorithm, this paper shows the computer simulation results.

Effect of Elastic Modulus Mismatch on the Contact Crack Initiation in Hard Ceramic Coating Layer

  • Lee, Kee-Sung
    • Journal of Mechanical Science and Technology
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    • 제17권12호
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    • pp.1928-1937
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    • 2003
  • Effect of elastic modulus mismatch on the contact crack initiation is investigated to find major parameters in designing desirable surface-coated system. Silicon nitride coated soft materials with various elastic modulus mismatch, E$\_$c//E$\_$s/=1.06∼356 are prepared for the analysis. Hertzian contact test is conducted for producing contact cracks and the acoustic emission detecting technique for measuring the critical load of crack initiation. The implication is that coating thickness and material strength are controllable parameters to prevent the initiation of contact cracks resulted from the elastic modulus mismatch in the hard ceramic coating layer on the soft materials.

비젼센서를 이용한 콘크리트 터널 라이닝 균열검사 시스템의 개발 (Development of Vision-Based Inspection System for Detecting Crack on the Lining of Concrete Tunnel)

  • 고봉수;조남규
    • 한국정밀공학회지
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    • 제20권12호
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    • pp.96-104
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    • 2003
  • To assess tunnel safety, cracks in tunnel lining are measured by inspectors who observe cracks with their eyes. A manual inspection is, however, slow and subjective. This paper, therefore, proposes vision-based inspection system for measuring cracks in the tunnel lining that inspects cracks fast and objective. The system is consisted of an on-vehicle system and a lab system. An on-vehicle system acquires image data with line CCD camera. A lab system extracts crack then inform their thickness, length and orientation by using image processing. To improve accuracy of crack recognition the geometric properties of a crack was applied to image processing. The proposed system were verified with experiments in both laboratory and field environment.

Detection of crack in L-shaped pipes filled with fluid based on transverse natural frequencies

  • Murigendrappa, S.M.;Maiti, S.K.;Srirangarajan, H.R.
    • Structural Engineering and Mechanics
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    • 제21권6호
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    • pp.635-658
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    • 2005
  • The possibility of detecting a crack in L-shaped pipes filled with fluid based on measurement of transverse natural frequencies is examined. The problem is solved by representing the crack by a massless rotational spring, simulating the out-of-plane transverse vibration only without solving the coupled torsional vibration and using the transfer matrix method for solution of the governing equation. The theoretical solutions are verified by experiments. The cracks considered are external, circumferentially oriented and have straight front. Pipes made of aluminium and mild steel are tested with water as internal fluid. Crack size to pipe thickness ratio ranging from 0.20 to 0.57 and fluid (gauge) pressure in the range of 0 to 10 atmospheres are examined. The rotational spring stiffness is obtained by an inverse vibration analysis and deflection method. The details of the two methods are given. The results by the two methods are presented graphically and show good agreement. Crack locations are also determined by the inverse analysis. The maximum absolute error in the location is 13.80%. Experimentally determined variation of rotational spring stiffness with ratio of crack size to thickness is utilized to predict the crack sizes. The maximum absolute errors in prediction of crack size are 17.24% and 16.90% for aluminium and mild steel pipes respectively.

실시간 레일절손 모니터링 시스템의 현장 적용에 관한 연구 (A Study on the Field Application of Real-Time Monitoring System Detecting the Broken Rail)

  • 최시행;고광남;정수영;이희성
    • 한국철도학회:학술대회논문집
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    • 한국철도학회 2011년도 춘계학술대회 논문집
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    • pp.1399-1406
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    • 2011
  • As a result of the examination analyzed loop type of Detecting the Broken Rail Monitoring System as a part of prevention of train derailment, installed in the Seoul Metro No. 2 subway line 98.51m section which is Samsung to Seolleung, we found that it is possible to detect crack location(Thermit welding: 48.18m) within the margin of error of ${\pm}1m$ accurately As analysis of the first day, third day, fifty day, and seventh day periodically, we found that Fresnel reflection happened where the crack location 48.18m. However other 3 branches show loss by bending of optical cable(spread reflection from the outside impact).

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표면균열 형상측정을 위한 다채널 DCPD 시스템의 개발 (Development of Multi-Channel DCPD System for Surface Crack Measurement)

  • 심도준;박호림;최재붕;김영진
    • 한국가스학회지
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    • 제4권1호
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    • pp.49-54
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    • 2000
  • 구조물에 존재하는 균열을 측정하기 위해 DCPD법이 널리 사용되고 있다. 본 연구를 통해 표면균열의 성장뿐만 아니라 형상변화도 측정 가능한 다채널 DCPD 시스템을 개발하였고, 이를 위한 전용 소프트웨어를 개발하였다. DCPD 시스템을 CT 시편에 적용하여 그 효용성을 검증한 후, 넓은 평판에 존재하는 표면균열 측정실험에 시스템을 적용하였다. 표면균열 성장시 개발한 다채널 DCPD 시스템을 적응함으로써 효과적이고 정확한 균열측정이 가능하다는 결론을 얻었다.

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Moving Window 기반 굴삭기용 과부하 검출 알고리즘 (Moving Window Based Overload Detection Algorithm for Excavator)

  • 유창호;최재원;서영봉
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2007년도 춘계학술대회A
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    • pp.909-914
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    • 2007
  • In this paper, an overload detecting algorithm for an excavator is presented. The proposed overload detecting algorithm is based on the time series analysis especially moving window. The main purpose of this paper is to prevent a damage or crack from the fatigue in advance. 16 channel sensors data are considered and maximum stress is computed by a sensor fusion method every moving window. After the maximum stress every window is compared with a given threshold, this overload detecting algorithm decides overload or not.

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피로 균열 진전에 따른 응력확대계수 측정에 관한 연구 (A Study on the Measurement of Stress Intensity Factors for the Fatigue Crack Propagation)

  • 오동진;김명현
    • Journal of Welding and Joining
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    • 제30권6호
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    • pp.80-85
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    • 2012
  • Fatigue cracks in structural components are the most common cause of structural failure when exposed to fatigue loading. In this respect, fatigue crack detection and structural health assessment are very important. Currently, various smart materials are used for detecting fatigue crack and measurement of SIFs(Stress Intensity Factors). So, this paper presented a measurement of SIFs using MFC(Micro Fiber Composite) sensor which is the one of the smart material. MFC sensor is more flexible, durable and reliable than other smart materials. The SIFs of Mode I(K I) as well as Mode II(K II) based on the piezoelectric constitutive law and fracture mechanics are calculated. In this study, the SIF values measured by MFC sensors are compared with the theoretical results.