• 비파괴검사학회지
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• 제27권4호
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• pp.299-304
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• 2007

구조물의 주요 부재들은 임의의 부분에 과대 하중이 작용하거나 반복 하중을 받아서 재료가 열화되면 균열이 발생한다. 이러한 균열은 구조물의 안전성을 평가할 수 있는 중요한 인자이며 균열의 진전 여부가 구조물의 안전성을 평가하기 위한 중요한 지표로 사용할 수 있다. 따라서 본 연구에서는 구조물의 기존 균열이 진전하는지를 감시하기 위하여 광섬유 브래그 격자 센서를 개발하였다. 이 센서 시스템은 탐촉자, 파장제어 광원부 및 광수신부, 그리고 가진부로 구성된다. 센서 탐촉자 부분은 광섬유 브래그 격자 소자만으로 구성된다. 파장제어 광원부는 전류공급회로와 DFB(distributed feedback) 레이저 다이오드로 구성되고 파장 제어 회로는 레이저 다이오드의 온도를 바꾸어 파장을 제어한다. 또한 가진부는 강체 낙하구에 의하여 구현한다. 이렇게 구성된 센서의 성능은 알루미늄판에 임의의 균열을 만들고 센서를 작동시키면서 출력 신호를 검토하면서 확인하였다. 광섬유 브래그 격자 센서의 출력 신호의 변화는 균열 길이 변화에 따라서 크게 변화되어 나타나므로 균열 진전 탐지 가능성이 충분함을 확인할 수 있었다.

• 한국생산제조학회지
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• 제22권6호
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• pp.950-956
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• 2013

This paper describes a sensitivity-coefficient-based iterative method for detecting cracks in a structure. The sensitivity coefficients of a cracked structure are obtained by changing its eigenvectors. The proposed method is applied to a cracked cantilever. The crack is modeled as a rotational stiffness. The predicted cracks are in good agreement with those from a structural reanalysis of the cracked structure.

• Transactions on Control, Automation and Systems Engineering
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• 제2권1호
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• pp.24-30
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• 2000

The aim of this paper is to describe an advanced method of the fault diagnosis using Control Theory with reference to a crack detection, a new way to localize the crack position under influence of the plant disturbance and white measurement noise on a rotating shaft. As the first step, the shaft is physically modelled with a finite element method as usual and the dynamic mathematical model is derived from it using the Hamilton-principle and in this way the system is modelled by various subsystems. The equations of motions with a crack are established by the adaption of the local stiffness change through breathing and gaping[1] from the crack to the equation of motion with an undamaged shaft. This is supposed to be regarded as a reference system for the given system. Based on the fictitious model of the time behaviour induced from vibration phenomena measured at the bearings, a nonlinear state observer is designed in order to detect the crack on the shaft. This is the elementary NL-observer(EOB). Using the elementary observer, an Estimator(Observer Bank) is established and arranged at the certain position on the shaft. In case, a crack is found and its position is known, the procedure, fro the estimation of the depth is going to begin.

• Structural Engineering and Mechanics
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• 제73권2호
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• pp.109-121
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• 2020

This study aims to estimate crack location and crack length in damaged beam structures using transfer matrix formulations, which are based on analytical solutions of governing equations of motion. A single variable shear deformation theory (SVSDT) that considers parabolic shear stress distribution along beam cross-section is used, as well as, Timoshenko beam theory (TBT). The cracks are modelled using massless rotational springs that divide beams into segments. In the forward problem, natural frequencies of intact and cracked beam models are calculated for different crack length and location combinations. In the inverse approach, which is the main concern of this paper, the natural frequency values obtained from experimental studies, finite element simulations and analytical solutions are used for crack identification via plots of rotational spring flexibilities against crack location. The estimated crack length and crack location values are tabulated with actual data. Three different beam models that have free-free, fixed-free and simple-simple boundary conditions are considered in the numerical analyses.

• 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.

• 대한기계학회논문집
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• 제17권9호
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• pp.2145-2152
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• 1993

The objective of this paper is to examine the detection limit, growth characteristics and notch curvature radius in short crack problem. Measurement techniques such as ultrasonic method and back-face strain compliance method were adopted. The fatigue crack growth rate of the short crack is slower than that of a long crack for a notched specimen. The characteristic of crack growth and crack closure is same as the case of a delay of crack growth caused by constant amplitude load for an ideal crack or single peak overload for a fatigue crack. The short crack is detected effectively by ultrasonic method. A short surface crack occurs in the middle of specimen thickness and is transient to a through crack depth is larger than the notch curvature radius.

• Structural Engineering and Mechanics
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• 제78권5호
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• pp.599-610
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• 2021

Early detection of small concrete crack or reinforcement corrosion is necessary for Structural Health Monitoring (SHM). Global vibration based methods are advantageous over local methods because of simple equipment installation and cost efficiency. Among vibration based techniques, FRF based methods are preferred over modal based methods. In this study, a new coupled method using frequency response function (FRF) and proper orthogonal modes (POM) is proposed by using the dynamic characteristic of a damaged beam. For the numerical simulation, wave finite element (WFE), coupled with traditional finite element (FE) method is used for effectively incorporating the damage related information and faster computation. As reported in literature, hybrid combination of wave function based wave finite element method and shape function based finite element method can addresses the mid frequency modelling difficulty as it utilises the advantages of both the methods. It also reduces the dynamic matrix dimension. The algorithms are implemented on a three-dimensional reinforced concrete beam. Damage is modelled and studied for two scenarios, i.e., crack in concrete and rebar corrosion. Single and multiple damage locations with different damage length are also considered. The proposed methodology is found to be very sensitive to both single- and multiple- damage while being computationally efficient at the same time. It is observed that the detection of damage due to corrosion is more challenging than that of concrete crack. The similarity index obtained from the damage parameters shows that it can be a very effective indicator for appropriately indicating initiation of damage in concrete structure in the form of spread corrosion or invisible crack.

• Steel and Composite Structures
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• 제46권3호
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• pp.319-334
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• 2023

Localizing damages is an essential task to monitor the health of the structures since they may not be able to operate anymore. Among the damage detection techniques, non-destructive methods are considerably more preferred than destructive methods since damage can be located without affecting the structural integrity. However, these methods have several drawbacks in terms of detecting abilities, time consumption, cost, and hardware or software requirements. Employing artificial intelligence techniques could overcome such issues and could provide a powerful damage detection model if the technique is utilized correctly. In this study, the crack localization in flat and folded plate structures has been conducted by employing a Backpropagated Artificial Neural Network (BPANN). For this purpose, cracks with 18 different dimensions in thin, flat, and folded structures having 15⁰, 30⁰, 45⁰, and 60⁰ folding angle have been modeled and subjected to free vibration analysis by employing the Classical Plate Theory with Finite Element Method. A Four-nodded quadrilateral element having six degrees of freedom has been considered to represent those structures mathematically. The first ten natural frequencies have been obtained regarding healthy and cracked structures. To localize the crack, the ratios of the frequencies of the cracked flat and folded structures to those of healthy ones have been taken into account. Those ratios have been given to BPANN as the input variables, while the crack locations have been considered as the output variables. A total of 500 crack locations have been regarded within the dataset obtained from the results of the free vibration analysis. To build the best intelligent model, a feature search has been conducted for BAPNN regarding activation function, the number of hidden layers, and the number of hidden neurons. Regarding the analysis results, it is concluded that the BPANN is able to localize the cracks with an average accuracy of 95.12%.

• 한국건설관리학회논문집
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• 제25권2호
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• pp.36-44
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• 2024

본 논문에서는 합성곱신경망과 ROI기법을 이용한 콘크리트 균열 분석에 관해 소개한다. 콘크리트 표면, 빔과 같은 구조물은 피로 응력, 주기 부하에 노출되며, 이는 일반적으로 구조물의 표면에서 미세한 수준에서 시작되는 균열을 야기한다. 구조물의 균열은 안정성을 저하시키고 구조물의 견고함을 감소시킨다. 조기 발견을 통해 손상 및 고장 가능성을 방지하기 위한 예방 조치를 취할 수 있다. 일반적으로 수동 검사 결과는 품질이 좋지 않고, 대규모 기반 시설의 경우 접근이 어려우며, 균열을 정확하게 감지하기 어렵다. 이러한 수동검사의 자동화는 기존 방식의 한계를 해결할 수 있기 때문에 컴퓨터 비전 기반의 연구들이 수행되었다. 하지만 다양한 유형의 균열이나, 열화상 카메라 등을 이용한 연구들은 부족한 상태이다. 따라서 본 연에서는 콘크리트 벽의 균열을 자동으로 감지하는 방법론을 개발하여 제시하며, 다음과 같은 연구 내용을 목표로 한다. 첫째, 균열 감지 이미지 기반 분석의 주요 장점인 이미지 처리 기술을 사용하여 기존의 수동 방법과 비교하여 정확도가 향상된 결과 및 정보를 제공한다. 둘째, 강화된 Sobel edge segmentation 기술 및 ROI 기법 기반의 알고리즘을 개발하여 비파괴 시험을 위한 자동 균열 감지 기술을 구현한다.

• 대한건축학회논문집:구조계
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• 제36권3호
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• pp.113-120
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• 2020

The purpose of this study is to compare the models of Deep Learning-based Convolution Neural Network(CNN) for concrete crack detection. The comparison models are AlexNet, GoogLeNet, VGG16, VGG19, ResNet-18, ResNet-50, ResNet-101, and SqueezeNet which won ImageNet Large Scale Visual Recognition Challenge(ILSVRC). To train, validate and test these models, we constructed 3000 training data and 12000 validation data with 256×256 pixel resolution consisting of cracked and non-cracked images, and constructed 5 test data with 4160×3120 pixel resolution consisting of concrete images with crack. In order to increase the efficiency of the training, transfer learning was performed by taking the weight from the pre-trained network supported by MATLAB. From the trained network, the validation data is classified into crack image and non-crack image, yielding True Positive (TP), True Negative (TN), False Positive (FP), False Negative (FN), and 6 performance indicators, False Negative Rate (FNR), False Positive Rate (FPR), Error Rate, Recall, Precision, Accuracy were calculated. The test image was scanned twice with a sliding window of 256×256 pixel resolution to classify the cracks, resulting in a crack map. From the comparison of the performance indicators and the crack map, it was concluded that VGG16 and VGG19 were the most suitable for detecting concrete cracks.