• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.3
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• pp.299-306
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• 2001

In this paper, artificial and real defects(delamination and debond) in composite structures were detected by using ESPI system. Three types of specimens, that is, composite laminates, honeycomb structures, and adhesive joints, were used to study the applicability of ESPI to composite structures. To detect defects in specimens, we selected thermal loading method that can easily induce the surface deformation of specimen. Experimental results show that defects in composite structures could be easily detected by ESPI. Moreover, it shows that ESPI could be usefully applied to the detection of defects in various composite structures.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2002.05a
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• pp.35-38
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• 2002

Real defects in composite structures were detected by using laser measuring system. Four types of specimens, that is, a composite laminate, a honeycomb structure, a free-edge delamination and an adhesive joint, were used to study the applicability of ESPI and Shearography to composite structures. Thermal loading method, which can easily induce the surface deformation of specimen, was used to detect defects. Experimental results show that defects in composite structures can be easily detected by ESPI and Shearography. Moreover, it shows that ESPI and Shearography can be usefully applied to the detection of defects in various kinds of composite structures.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.4
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• pp.406-414
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• 1997

A real-time inspection system is developed using line scan cameras. Several improved algorithms are proposed for real-time detection of defects in this automated inspection system. The major improved algorithms include the preprocessing, the threshold decision, and the clustering algorithms. The preprocessing algorithms are for exact binarization and the threshold decision algorithm is for fast detection of defects in 1-D binary images. The clustering algorithm is also developed for fast classifying of the defects. The system is applied to PCBs(Printed Circuit Boards) inspection. The typical defects in PCBs are pits, dent, wrinkle, scratch, and black spots. The results show that most defects are detected and classified successfully.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.3
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• pp.63-69
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• 1996

Recently, vibrational signal processing as a tool of machinery diagnosis has been actively studying. In this study, a new scheme for detection and diagnosis of localized defects in ball bearings, using unwrapped phase spectrum of FFT is described. The characteristic phase spectra for such defects shows linearly varying patterns due to the repetitive impact signals generated by localized defects, i.e., one linear line for single defect and various linearly changing shape according to angle between the two defect located points. The effectiveness of this method is confirmed by computer simulation and experiments on bearing with single or double defects at different locations.

• Composites Research
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• v.15 no.5
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• pp.19-26
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• 2002

Real defects in composite structures were detected by using laser measuring system. Four types of real defects, that is, impact-induced delamination in a composite laminate, debond in a honeycomb structure, free-edge delamination in a composite laminate and debond in an adhesive joint, were made by applying several types of loads to the specimens. Laser measuring system such as ESPI and shearography technique were used to detect those defects. Thermal loading method, which can easily induce the surface deformation of specimen, was used to detect the defects. Experimental results show that the defects in composite structures could be easily detected by ESPI and shearography technique. Moreover, it shows that ESPI and shearography technique could be usefully applied to the detection of defects in various kinds of composite structures.

• Journal of the Semiconductor & Display Technology
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• v.11 no.2
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• pp.45-51
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• 2012

Multilayer co-extrusion blown film construction is a popular technique for producing plastic films for various packaging industries. Automated detection of defective films can improve the quality of film production process. In this paper, we propose a film inspection system that can detect and classify film defects robustly. In our system, first, film images are acquired through a high speed line-scan camera under an appropriate lighting system. In order to detect and classify film defects, an inspection algorithm is developed. The algorithm divides the typical film defects into two groups: intensity-based and texture-based. Intensity-based defects are classified based on geometric features. Whereas, to classify texture-based defects, a texture analysis technique based on local binary pattern (LBP) is adopted. Experimental results revealed that our film inspection system is effective in detecting and classifying defects for the multilayer co-extrusion blown film construction line.

• Journal of the Korean Society for Railway
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• v.10 no.1 s.38
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• pp.1-6
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• 2007

Railway wheels in service are regularly checked by ultrasonic testing, acoustic emission and eddy current testing method and so on. However, ultrasonic testing is sometimes inadequate for sensitively detecting the cracks in railway wheel which is mainly because of the fact of crack closure. Recently, many researchers have actively fried to improve precision for defect detection of railway wheel. The development of a nondestructive measurement tool for wheel defects and its use for the maintenance of railway wheels would be useful to prevent wheel failure. The induced current focusing potential drop(ICFPD) technique is a new non-destructive tasting technique that can detect defects in railway wheels by applying on electro-magnetic field and potential drops variation. In the present paper, the ICFPD technique is applied to the detection of surface and internal defects for railway wheels. To defect the defects for railway wheels, the sensor for ICFPD is optimized and the tests are carried out with respect to 4 surface defects and 6 internal defects each other. The results show that the surface crack depth of 0.5 mm and internal crack depth of 0.7 mm in wheel tread could be detected by using this method. The ICFPB method is useful to detect the defect that initiated in the tread of railway wheels

• Journal of Korea Multimedia Society
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• v.19 no.3
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• pp.633-641
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• 2016

Automatic defect inspection system is composed of the step in the pre-processing, defect candidate detection, and classification. Polarizing films containing various defects should be minimized over-detection for classifying defect blobs. In this paper, we propose a defect detection algorithm using a skewness of histogram for minimizing over-detection. In order to detect up defects with similar to background pixel, we are used the characteristics of the local region. And the real defect pixels are distinguished from the noise using the probability density function. Experimental results demonstrated the minimized over-detection by utilizing the artificial images and real polarizing film images.

• Smart Structures and Systems
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• v.21 no.5
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• pp.687-694
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• 2018

The problem of wheel tread defects has become a major challenge for the health management of high-speed rail as a wheel defect with small radius deviation may suffice to give rise to severe damage on both the train bogie components and the track structure when a train runs at high speeds. It is thus highly desirable to detect the defects soon after their occurrences and then conduct wheel turning for the defective wheelsets. Online wheel condition monitoring using wheel impact load detector (WILD) can be an effective solution, since it can assess the wheel condition and detect potential defects during train passage. This study aims to develop an FBG-based track-side wheel condition monitoring method for the detection of wheel tread defects. The track-side sensing system uses two FBG strain gauge arrays mounted on the rail foot, measuring the dynamic strains of the paired rails excited by passing wheelsets. Each FBG array has a length of about 3 m, slightly longer than the wheel circumference to ensure a full coverage for the detection of any potential defect on the tread. A defect detection algorithm is developed for using the online-monitored rail responses to identify the potential wheel tread defects. This algorithm consists of three steps: 1) strain data pre-processing by using a data smoothing technique to remove the trends; 2) diagnosis of novel responses by outlier analysis for the normalized data; and 3) local defect identification by a refined analysis on the novel responses extracted in Step 2. To verify the proposed method, a field test was conducted using a test train incorporating defective wheels. The train ran at different speeds on an instrumented track with the purpose of wheel condition monitoring. By using the proposed method to process the monitoring data, all the defects were identified and the results agreed well with those from the static inspection of the wheelsets in the depot. A comparison is also drawn for the detection accuracy under different running speeds of the test train, and the results show that the proposed method can achieve a satisfactory accuracy in wheel defect detection when the train runs at a speed higher than 30 kph. Some minor defects with a depth of 0.05 mm~0.06 mm are also successfully detected.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.6
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• pp.56-63
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• 2003

In this study, an automatic ultrasonic testing system is used to detect the defects of the natural flaw test specimen and of the artificial flaw test specimen. We evaluate the detection performance of the acceptance standard for the natural flaw test specimen and of the acceptance standard for the artificial flaw test specimen. We also study the potential problems of those acceptance standards. The results indicate that the acceptance standard for the detection of defects in weldzone is good then the sensitivity correction is performed and that we must clearly specify special check points of the acceptance standard for the system in use.