• Smart Structures and Systems
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• 제18권6호
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• pp.1217-1231
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• 2016

In this research, a slotted patch antenna sensor is designed for wireless strain and crack sensing. An off-the-shelf RFID (radiofrequency identification) chip is adopted in the antenna sensor design for signal modulation. The operation power of the RFID chip is captured from wireless reader interrogation signal, so the sensor operation is completely battery-free (passive) and wireless. For strain and crack sensing of a structure, the antenna sensor is bonded on the structure surface like a regular strain gage. Since the antenna resonance frequency is directly related with antenna dimension, which deforms when strain occurs on the structural surface, the deformation/strain can be correlated with antenna resonance frequency shift measured by an RFID reader. The slotted patch antenna sensor performance is first evaluated through mechanics-electromagnetics coupled simulation. Extensive experiments are then conducted to validate the antenna sensor performance, including tensile and compressive strain sensing, wireless interrogation range, and fatigue crack sensing.

• 한국구조물진단유지관리공학회 논문집
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• 제22권3호
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• pp.69-74
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• 2018

Fiber-Reinforced Cementitious Composites (FRCCs)는 시멘트 복합체에 혼입한 전도성 섬유로 인해 전기 전도성을 가진다. 이러한 특성은 전기적 응답 계측을 통하여 별도의 센서 설치가 필요 없는 구조물의 균열 모니터링을 가능하게 한다. 하지만 전기적 응답은 균열 발생뿐만 아니라 온도의 변화에도 민감하게 변화하기 때문에 온도 요인은 전기적 응답 계측을 통한 균열 탐지를 방해하는 요소로 작용할 수 있다. 더욱이 전기적 응답을 측정하기 위한 탐침의 개수가 증가 할수록 원하지 않은 접촉 노이즈가 발생하기 때문에 이 논문에서는 탐침의 개수를 줄이기 위해 자체적인 자가센싱 임피던스 회로를 설계하였다. FRCC의 균열 발생과 온도 변화가 임피던스에 미치는 영향성은 자가센싱 임피던스 회로를 이용해 실험적으로 측정되었으며, 실험 결과, 임피던스 응답은 균열 발생보다 온도 변화에 더 민감하게 변화됨을 알 수 있었다.

• 대한원격탐사학회지
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• 제39권4호
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• pp.371-393
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• 2023

Crack detection in structures plays a vital role in ensuring their safety, durability, and reliability. Traditional crack detection methods sometimes need significant manual inspections, which are laborious, expensive, and prone to error by humans. Deep learning algorithms, which can learn intricate features from large-scale datasets, have emerged as a viable option for automated crack detection recently. This study presents an in-depth review of crack detection methods used till now, like image processing, traditional machine learning, and deep learning methods. Specifically, it will provide a comparative analysis of crack detection methods using deep learning, aiming to provide insights into the advancements, challenges, and future directions in this field. To facilitate comparative analysis, this study surveys publicly available crack detection datasets and benchmarks commonly used in deep learning research. Evaluation metrics employed to check the performance of different models are discussed, with emphasis on accuracy, precision, recall, and F1-score. Moreover, this study provides an in-depth analysis of recent studies and highlights key findings, including state-of-the-art techniques, novel architectures, and innovative approaches to address the shortcomings of the existing methods. Finally, this study provides a summary of the key insights gained from the comparative analysis, highlighting the potential of deep learning in revolutionizing methodologies for crack detection. The findings of this research will serve as a valuable resource for researchers in the field, aiding them in selecting appropriate methods for crack detection and inspiring further advancements in this domain.

• Smart Structures and Systems
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• 제29권1호
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• pp.141-151
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• 2022

In recent years, the industry and research communities have focused on developing autonomous crack inspection approaches, which mainly include image acquisition and crack detection. In these approaches, mobile devices such as cameras, drones or smartphones are utilized as sensing platforms to acquire structural images, and the deep learning (DL)-based methods are being developed as important crack detection approaches. However, the process of image acquisition and collection is time-consuming, which delays the inspection. Also, the present mobile devices such as smartphones can be not only a sensing platform but also a computing platform that can be embedded with deep neural networks (DNNs) to conduct on-site crack detection. Due to the limited computing resources of mobile devices, the size of the DNNs should be reduced to improve the computational efficiency. In this study, an architecture called pruned crack recognition network (PCR-Net) was developed for the detection of structural cracks. A dataset containing 11000 images was established based on the raw images from bridge inspections. A pruning method was introduced to reduce the size of the base architecture for the optimization of the model size. Comparative studies were conducted with image processing techniques (IPTs) and other DNNs for the evaluation of the performance of the proposed PCR-Net. Furthermore, a modularly designed framework that integrated the PCR-Net was developed to realize a DL-based crack detection application for smartphones. Finally, on-site crack detection experiments were carried out to validate the performance of the developed system of smartphone-based detection of structural cracks.

• Smart Structures and Systems
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• 제22권1호
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• pp.1-11
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• 2018

This study presents early crack detection of steel fiber-reinforced concrete (SFRC) under varying temperature and humidity conditions using an instantaneous electrical impedance acquisition system. SFRC has the self-sensing capability of electrical impedance without sensor installation thanks to the conductivity of embedded steel fibers, making it possible to effectively monitor cracks initiated in SFRC. However, the electrical impedance is often sensitively changed by environmental effects such as temperature and humidity variations. Thus, the extraction of only crack-induced feature from the measured impedance responses is a crucial issue for the purpose of structural health monitoring. In this study, the instantaneous electrical impedance acquisition system incorporated with SFRC is developed. Then, temperature, humidity and crack initiation effects on the impedance responses are experimentally investigated. Based on the impedance signal pattern observation, it is turned out that the temperature effect is more predominant than the crack initiation and humidity effects. Various crack steps are generated through bending tests, and the corresponding impedance damage indices are extracted by compensating the dominant temperature effect. The test results reveal that propagated cracks as well as early cracks are successfully detected under temperature and humidity variations.

• Smart Structures and Systems
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• 제4권5호
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• pp.565-582
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• 2008

This paper presents a feasibility study of flexible piezoelectric paint for use in wide-band low-profile surface-mount or embeddable ultrasonic sensor for in situ structural health monitoring. Piezoelectric paint is a piezoelectric composite with 0-3 connectivity. Because of its ease of application, piezoelectric paint can be readily fabricated into sensing element with complex pattern. This study examines the characteristics of piezoelectric paint in acoustic emission signal and ultrasonic guided wave sensing. A series of ultrasonic tests including pitch catch and pencil break tests were performed to validate the ultrasonic wave sensing capability of piezoelectric paint. The results of finite element simulation of ultrasonic wave propagation, and acoustic emission generated by a pencil lead break on an aluminum plate are also presented in this paper along with corresponding experimental data. Based on the preliminary experimental results, the piezoelectric paint appears to offer a promising sensing material for use in real-time monitoring of crack initiation and propagation in both metallic and composite structures.

• Structural Engineering and Mechanics
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• 제69권4호
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• pp.407-416
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• 2019

This paper develops a wireless sensor for online fatigue crack detection and failure warning based on crack-induced nonlinear ultrasonic modulation. The wireless sensor consists of packaged piezoelectric (PZT) module, an excitation/sensing module, a data acquisition/processing module, a wireless communication module, and a power supply module. The packaged PZT and the excitation/sensing module generate ultrasonic waves on a structure and capture the response. Based on nonlinear ultrasonic modulation created by a crack, the data acquisition/processing module periodically performs fatigue crack diagnosis and provides failure warning if a component failure is imminent. The outcomes are transmitted to a base through the wireless communication module where two-levels duty cycling media access control (MAC) is implemented. The uniqueness of the paper lies in that 1) the proposed wireless sensor is developed specifically for online fatigue crack detection and failure warning, 2) failure warning as well as crack diagnosis are provided based on crack-induced nonlinear ultrasonic modulation, 3) event-driven operation of the sensor, considering rare extreme events such as earthquakes, is made possible with a power minimization strategy, and 4) the applicability of the wireless sensor to steel welded members is examined through field and laboratory tests. A fatigue crack on a steel welded specimen was successfully detected when the overall width of the crack was around $30{\mu}m$, and a failure warnings were provided when about 97.6% of the remaining useful fatigue lives were reached. Four wireless sensors were deployed on Yeongjong Grand Bridge in Souht Korea. The wireless sensor consumed 282.95 J for 3 weeks, and the processed results on the sensor were transmitted up to 20 m with over 90% success rate.

• 대한기계학회논문집A
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• 제20권4호
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• pp.1263-1274
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• 1996

In this paper, as elastic-plastic fracture toughness test under mixed mode loading was proposed using a single edge-cracked specimen subjected to bending moment(M), shearing force(F), and twisting moment(T). The J-integral of a crack in the specimen is expressed in the form J=$J_I$+ $J_II$$J_III$, where $J_I$, $J_II$ and $J_III$ are the components of mode I, mode II and mode III deformation, respectively. $J_I$, $J_II$ and $J_III$ can be estimated from M-$\theta$ ($\theta$;crack opening angle), F-U(U; crack shear displacement) and T-$\alpha$ ($\alpha$;crack twisting angle). In order to obtain the the M<-TEX>$\theta$, F-U and T-$\alpha$ diagram inreal time, a new deformaiton gage for mixed mode loading was proposed using the optical position sensing device(PSD). The elastic-plastic fracture toughness test was carried out with an aluminum alloy. The loading apparatus was designed and manufactured for this experiment. For the loading condition of the crack initatio in the mixed mode, the MMT -3(mode I+ mode II+ mode III) has the lowest values out of the all specimens. This implies that MMT-3 is possible of the crackinitation at lower load, if the specimen acts on together with the torque under the same loading condition. An elastic-plastic fracture toughness test using the PSD brings a successful experimentation in measuring the crack deformation(mode I+ mode II+ mode III).

• Composites Research
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• 제27권6호
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• pp.219-224
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• 2014

탄소나노튜브(CNT)의 물성은 고분자재료의 기계적, 전도성, 열적 물성을 향상시켜주기 때문에 많은 분야에서 소재개발을 진행 중이다. 본 연구에서는 사전에 CNT 10 wt% 페이스트를 제조하여 나노입자에 대한 분산도와 나노복합재료 생산성을 높일 수 있는 기초 재료를 제조하였다. 제조된 CNT 10 wt% 페이스트를 이용하여 손상 감지용 CNT 나노복합재료를 제조하여 균열에 대한 손상감지능과 균열 보강효과에 대한 영향을 연구하였다. CNT 10 wt% 페이스트를 이용하여 제조된 CNT 1 wt% 나노복합재는 일반 CNT 파우더를 이용하여 CNT 1 wt% 나노복합재료를 제조하였을 경우보다 인장과 굴곡물성이 높음을 확인하였다. CF30wt%/PP에 인위적인 균열을 제조하고, 균열부위에 CNT 나노복합재료를 보강하여 균열 및 파괴 발생 감지능을 균열크기에 따라 전기저항 측정법과 인장물성평가를 통해 분석하였다. CNT 나노복합재료를 균열 부위에 보강하여 CF30wt%/PP의 인장물성을 분석하였을 경우, 균열보강효과가 있었다. 균열크기가 증가함에 따라 CNT 나노복합재료의 보강효과의 증가되었다. 이는 CNT 나노복합재료와 CF30wt%/PP간의 접착면 증가로 균열전파를 지연하기 때문이다. CNT 나노복합재료의 손상감지능에 대해서는 전기저항 평가법으로 분석하였으며, 접착면에서의 분리로 인해 CNT 나노복합재료에 충격이 가해져 높은 전기저항 증가구간을 확인하였다. 손상감지용 CNT 나노복합재료의 균열방지효과와 손상감지에 대한 전기저항 평가법의 가능성을 확인하였다.

• Journal of Mechanical Science and Technology
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• 제16권5호
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• pp.591-598
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• 2002

Leakage magnetic flux is occurred in the cracked area of magnetized specimens, and also it changes the magnetic domain area of the magneto-optical film positioned on the specimen. It causes the change of the optical permeability of the magnetic domain on the crack area. So crack images can be obtained easily using this principle. On the other hand, utilizing a laser in this method makes possible to perform a remote sensing by detecting the light intensity contrast between cracked area and normal area. This paper shows the application of non-destructive inspection system taking advantage of magneto-optical method for micro-cracks and presents examples applied to the several types of specimens having fatigue cracks and fabricated cracks using this method. Also the authors prove the possibility of this method as a remote sensing system under the oscillation load considering application to real fields.