• KEPCO Journal on Electric Power and Energy
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• v.8 no.2
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• pp.93-96
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• 2022

The boiler tubes of thermal power plants are exposed to harsh environment of high temperature and high pressure, and the deterioration state of materials rapidly increases. In particular, parent material and welds of the materials used are subjected to a temperature change and various constraints, resulting in deformation and its growth, resulting in frequent leakage accidents caused by tube failure. The power plant checks the integrity of boiler tubes through non-destructive testing as it may act as huge costs loss and limitation of power supply during power station shutdown period due to boiler tube leakage. However, the current non-destructive testing is extremely limited in the field to detect micro cracks. In this study, the ability of metal magnetic memory technique to detect flaws of size that are difficult to inspect by the visual or general non-destructive methods was verified in the early stage of their occurrence.

• Geomechanics and Engineering
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• v.29 no.6
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• pp.627-643
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• 2022

Water-rock interactions have a significant influence on the mechanical behavior of rocks. In this study, uniaxial compression and tension tests on different water-treated sandstone samples were conducted. Acoustic emission (AE) monitoring and micro-pore structure detection were carried out. Water-rock interactions and their effects on rock mechanical behavior were discussed. The results indicate that water content significantly weakens rock mechanical strength. The sensitivity of the mechanical parameters to water treatment, from high to low, are Poisson ratio (𝜇), uniaxial tensile strength (UTS), uniaxial compressive strength (UCS), elastic modulus (E), and peak strain (𝜀). After water treatment, AE activities and the shear crack percentage are reduced, the angles between macro fractures and loading direction are minimized, the dynamic phenomenon during loading is weakened, and the failure mode changes from a mixed tensile-shear type to a tensile one. Due to the softening, lubrication, and water wedge effects in water-rock interactions, water content increases pore size, promotes crack development, and weakens micro-pore structures. Further damage of rocks in fractured and caved zones due to the water-rock interactions leads to an extra load on the adjoining coal and rock masses, which will increase the risk of dynamic disasters.

• Journal of the Korea institute for structural maintenance and inspection
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• v.3 no.4
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• pp.215-220
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• 1999

Concrete micro-cracks that are grown while the structures are under construction or in service, propagate gradually or rapidly by external forces and environmental effects. As described above, almost concrete structures generally have cracks, so for the safety and durability of structures, studies to detect cracks using nondestructive tests have been treated in great deal. The purpose of this study is to evaluate characteristics of AE signals detected from notched concrete beams bending test with different loading using one of nondestructive test, Acoustic Emission (AE) method. Furthermore this study predicts the location of initial crack and measures direction of crack propagation for on-line monitoring before the crack really grows in structures by using two-dimensional AE source location based on rectangular method with three-point bending test. This will allow efficient maintenance of concrete structures through monitoring of internal cracking based on acoustic emission method.

• The Korean Journal of Ceramics
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• v.6 no.3
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• pp.201-205
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• 2000

Fiber reinforced plastic (FRP) composites and ceramic matrix composites (CMC) which contain electrically conductive phases have been designed and fabricated to introduce the detection capability of damage/fracture detection into these materials. The composites were made electrically conductive by adding carbon and TiN particles into FRP and CMC, respectively. The resistance of the conductive FRP containing carbon particles showed almost linear response to strain and high sensitivity over a wide range of strains. After each load-unload cycle the FRP retained a residual resistance, which increased with applied maximum stress or strain. The FRP with carbon particles embedded in cement (mortar) specimens enabled micro-crack formation and propagation in the mortar to be detected in situ. The CMC materials exhibited not only sensitive response to the applied strain but also an increase in resistance with increasing number of load-unload cycles during cyclic load testing. These results show that it is possible to use these composites to detect and/or fracture in structural materials, which are required to monitor the healthiness or safety in industrial applications and public constructions.

• Journal of the Korean Society of Safety
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• v.37 no.5
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• pp.7-13
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• 2022

Digital image correlation (DIC) is a method used to measure the displacement and strain of structures. It involves transforming and analyzing images before and after deformation using correlation coefficients from irregular light and shade on the surface of structures. In the present study, a microspeckle pattern was applied to the surface of a specimen to identify initial cracking. The test specimen constituted CFRP composites laminated on a curved Al liner The specimen was manufactured by stacking 100 ply of CFRP prepregs in the 0° and 90° directions in a three-point bending test. The equivalent strain was evaluated through DIC analysis after monitoring deformation using a CCD camera. Fracture shape was observed using a microscope. The equivalent strain contour distribution was checked until the maximum load fracture occurred at the center of the test specimen. Variations in the strain indicated the initial occurrence and progression of microcracks. These results can be used to improve the accuracy of detecting micro crack initiation and to achieve structural stability.

• Journal of the Korean Society for Nondestructive Testing
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• v.28 no.5
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• pp.395-400
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• 2008

Alternating magnetic field was used for detection of surface flaws on nonmagnetic and magnetic metallic specimens. The nondestructive sensor probe was composed of the planar coil with inductive magnetic thin film yoke as a sensing component and a single straight typed exciting coil. The planar inductive coil sensor with magnetic yoke was fabricated by sputtering, electroplating, dry etching and photolithography process. The alternative currents with the range of 0.1A to 1.0A (0.7 MHz to 1.8 MHz) were applied to the exciting coil. The specimens were prepared with the slit shaped artificial surface flaws (minimum depth and width; 0.5 mm) on metallic plate (Al; nonmagnetic metal and FeC; magnetic metal). The detected signal for the positions and shapes of surface flaws on specimens were obtained with high sensitivity and high signal to ratio. The measured output signals by the non-contacted scanning on surface of FeC specimen with micron-sized crack were converted to the images of the flaws. And these results were compared with the optical images, respectively.

• Composites Research
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• v.16 no.3
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• pp.58-67
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• 2003

To perform the realtime strain and fracture monitoring of the smart composite structures, two optical fiber sensor systems are proposed. The two types of the coherent sources were used for fracture signal detection - EDFA with FBG and EDFA with Fabry-Perot filter. These sources were coupled to EFPI sensors imbedded in composite specimens. To understand the characteristics of matrix crack signals, at first, we performed tensile tests using surface attached PZT sensors by changing the thickness and width of the specimens. This paper describes the implementation of time-frequency analysis such as short time Fourier transform (STFT) and wavelet transform (WT) for the quantitative evaluation of fracture signals. The experimental result shows the distinctive signal features in frequency domain due to the different specimen shapes. And, from the test of tensile load monitoring using optical fiber sensor systems, measured strain agreed with the value of electric strain gage and the fracture detection system could detect the moment of damage with high sensitivity to recognize the onset of micro-crack fracture signal.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.6
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• pp.555-567
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• 2023

The cracks in the tunnel are currently determined through visual inspections conducted by inspectors based on images acquired using tunnel imaging acquisition systems. This labor-intensive approach, relying on inspectors, has inherent limitations as it is subject to their subjective judgments. Recently research efforts have actively explored the use of deep learning to automatically detect tunnel cracks. However, most studies utilize public datasets or lack sufficient objectivity in the analysis process, making it challenging to apply them effectively in practical operations. In this study, we selected test datasets consisting of images in the same format as those obtained from the actual inspection system to perform an objective evaluation of deep learning models. Additionally, we introduced ensemble techniques to complement the strengths and weaknesses of the deep learning models, thereby improving the accuracy of crack detection. As a result, we achieved high recall rates of 80%, 88%, and 89% for cracks with sizes of 0.2 mm, 0.3 mm, and 0.5 mm, respectively, in the test images. In addition, the crack detection result of deep learning included numerous cracks that the inspector could not find. if cracks are detected with sufficient accuracy in a more objective evaluation by selecting images from other tunnels that were not used in this study, it is judged that deep learning will be able to be introduced to facility safety inspection.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.35 no.10
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• pp.1075-1081
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• 2011

A leak-detection method has been developed by measuring the pressure variation between the inner and outer heattransfer tubes of a double-wall tube steam generator. An experiment was carried out to measure the leak rate in the gap between two surfaces pressed with a hydraulic press in order to simulate the phenomena, and a correlation was determined for the leak rate in a micro gap. However, in the correlation, the gap width and friction coefficient were coupled with the surface roughness, which affects the two parameters. The two parameters were separated using a surface-contact model to develop a correlation for the friction coefficient. The correlation was compared with the existing correlations used for crack analysis. Although the applied ranges of Reynolds numbers were different, the developed correlation for Reynolds numbers of 0.1.0.35 showed similar tendencies to existing correlations used for higher Reynolds numbers.

• Journal of Biosystems Engineering
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• v.33 no.5
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• pp.348-354
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• 2008

Egg grading is determined by exterior and interior quality. Among the evaluation methods for the egg quality, a candling method is common to identify eggs with cracked shells and interior defects. But this method is time-consuming and laborious. In addition, practically, it is challenging to detect hairline and micro cracks. In this study, an on-line inspection system based on acoustic resonance frequency analysis was developed to detect hairline cracks on eggshells. A roller conveyor was used to transfer eggs along one lane to the impact position where each of eggs rotated by the roller was excited with an impact device at four different locations on the eggshell equator. The impact device was consisted of a plastic hammer and a rotary solenoid. The acoustic response of the egg to the impact was measured with a small condenser microphone at the same position as the impact device was installed. Two acoustic parameters, correlation coefficient for normalized power spectra and standard deviation of peak resonant frequencies, were used to detect cracked eggs. Intact eggs showed relatively high correlations among the four normalized power spectra and low standard deviations of the four peak resonant frequencies. On the other hand, cracked eggs showed low correlations and high standard deviations as compared to the intact. This method allowed a crack detection rate of 97.6%.