• Proceedings of the Korea Concrete Institute Conference
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• 1999.04a
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• pp.799-806
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• 1999

This study describes the results of experiment and numerical analysis for heating image by thermographic method when the size of void in concrete are changed. By comparing analytical solution by finite element method with measured image by thermography, the relationships between the surface temperature which can be confirmed by this method, the size of void and optimum time for detection of void and the difference of temperature are cleared.

• International Journal of Highway Engineering
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• v.18 no.2
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• pp.37-42
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• 2016

PURPOSES : The objective of this study is to determine the optimal frequency of ground penetrating radar (GPR) testing for detecting the voids under the pavement. METHODS : In order to determine the optimal frequency of GPR testing for void detection, a full-scale test section was constructed to simulate the actual size of voids under the pavement. Voids of various sizes were created by inserting styrofoam at varying depths under the pavement. Subsequently, 250-, 500-, and 800-MHz ground-coupled GPR testing was conducted in the test section and the resulting GPR signals were recorded. The change in the amplitude of these signals was evaluated by varying the GPR frequency, void size, and void depth. The optimum frequency was determined from the amplitude of the signals. RESULTS: The capacity of GPR to detect voids under the pavement was evaluated by using three different ground-coupled GPR frequencies. In the case of the B-scan GPR data, a parabolic shape occurred in the vicinity of the voids. The maximum GPR amplitude in the A-scan data was used to quantitatively determine the void-detection capacity. CONCLUSIONS: The 250-MHz GPR testing enabled the detection of 10 out of 12 simulated voids, whereas the 500-MHz testing allowed the detection of only five. Furthermore, the amplitude of GPR detection associated with 250-MHz testing is significantly higher than that of 500-MHz testing. This indicates that 250-MHz GPR testing is well-suited for the detection of voids located at depths ranging from 0.5~2.0 m. Testing at frequencies lower than 250 MHz is recommended for void detection at depths greater than 2 m.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.2005-2006
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• 2011

Due to the advantages of small sizes, more I/O ports, etc., Ball Grid Array (BGA) has been used in the production of printed circuit board (PCB). However, BGA voids can degrade the performance of the board and cause failure. To automatically detect the voids in X-ray image, a novel blob filter that makes use of the local image gradient magnitude is proposed in this paper. The utilization of the local image gradient magnitude makes the proposed filter invariant to the image brightness, void shape, void position, and component interference. Furthermore, different sizes of box filters are employed to analyze the image in multi-scale, and as a result, the proposed blob filter is robust to void size. Experimental results show that the proposed method can obtain void detection accuracy up to 96.104% while keep low false ratio.

• Computers and Concrete
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• v.7 no.6
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• pp.511-522
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• 2010

A color based segmentation procedure and a modified signature technique have been applied to the detection and analyses of complicated void shapes in cemented materials. The gray-scale segmentation and available signature methods were found to be inefficient especially for the analyses of complicated void shapes. The applicability of the developed methodology has been demonstrated on artificially prepared cemented materials made of self compacted concrete material. In order to characterize the void shapes in the investigated sample images, two new shape parameters called as coefficients of inclusion and exclusion have been proposed. When compared with the traditional use of the signature method, it was found that the methodology followed herein would better characterize complicated void shapes. The methodology followed in this study may be applied to the analysis of complicated void shapes that are often encountered in other cementitious materials such as clays and rocks.

• Proceedings of the Korea Concrete Institute Conference
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• 1999.04a
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• pp.781-786
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• 1999

One of the major causes of concrete pavement deterioration is the loss of support due to erosion and pumping of subbase and subgrade. In this study, procedures for the detection of voids under concrete pavement slab are presented using nondestructive test method such as FWD(Falling Weight Deflectometer) and GPR(Ground Penetration Radar). The deflection responses of concrete slab obtained in FWD field test are analysed for determining the presence of void. Also, reflection responses in GPR test are interpreted. It was concluded that these procedures are available for detecting the viods under concrete pavement slab.

• Proceedings of the Korea Concrete Institute Conference
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• 2003.05a
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• pp.169-174
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• 2003

The purpose of this study is examine into the application of infrared thermography for voids detect in reinforced concrete structures. In this study, the experiments were carried out for analyze the effect of void size, cover, measurement time and distance on test piece which has artificial voids. Results of this study are as follows. Noiseless and high resolution thermography was acquired 11:00 - 14:00 and the thermography which taken 16:00 was not suitable for void detection. The difference of temperature between voids and solid to identification the existence of voids by eye is $0.3^{\circ}C$.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.11 no.10
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• pp.940-945
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• 1998

In this paper, we obtained the data, which is required in training the neural network and diagnosing the degradation degree, by introducing the AE detection that is effective method in ordinary degradation diagnosis on activation. Aa the results of generalization tests by appling neural network to the unknown AE patterns obtained from two kinds of specimen, firstly as to evaluate an objective performance of neural network, the recognition ration for no-void specimen and 1[mm] -void specimen are appeared to be 98.9% and 92.5%, respectively. Also, in the evaluation of the adaptability of neural network with a new type of 0.2[mm] -void specimen, it is confirmed that the result appears to be 64% of recognition ratio at 94% of confidence interval coefficient in expectation output 0.2. On the other hand, the recognition capability of the neural network was confirmed by data from no-void and 1[mm] void specimen. The results prove the promising possibility of the application of ANN to discriminate specific void affecting as main degradation source at partial discharge condition in insulator containing multi-void by accummulated data base.

• Bulletin of the Korean Space Science Society
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• 1999.09a
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• pp.68-68
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• 1999

No Abstract, See Full Text

• The Bulletin of The Korean Astronomical Society
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• v.24 no.2
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• pp.76-76
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• 1999

• Journal of the Korean Society for Nondestructive Testing
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• v.37 no.2
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• pp.106-114
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• 2017

This paper presents an automated subsurface micro void detection technique based on pulsed infrared thermography for inspecting epoxy molding compounds (EMC) used in electronic device packaging. Subsurface micro voids are first detected and visualized by extracting a lock-in amplitude image from raw thermal images. Binary imaging follows to achieve better visualization of subsurface micro voids. A median filter is then applied for removing sparse noise components. The performance of the proposed technique is tested using 36 EMC samples, which have subsurface (below $150{\mu}m{\sim}300{\mu}m$ from the inspection surface) micro voids ($150{\mu}m{\sim}300{\mu}m$ in diameter). The experimental results show that the subsurface micro voids can be successfully detected without causing any damage to the EMC samples, making it suitable for automated online inspection.