• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.2
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• pp.169-177
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• 2017

In this paper, classification of spall and crack faults of gear teeth is studied by applying the ensemble empirical mode decomposition(EEMD) for the gear transmission error(TE). Finite element models of the gears with the two faults are built, and TE is obtained by simulation of the gears under loaded contact. EEMD is applied to the residuals of the TE which are the difference between the normal and faulty signal. From the result, the difference of spall and crack faults are clearly identified by the intrinsic mode functions(IMF). A simple test bed is installed to illustrate the approach, which consists of motor, brake and a pair of spur gears. Two gears are employed to obtain the TE for the normal, spalled, and cracked gears, and the type of the faults are separated by the same EEMD application process. In order to quantify the results, crest factors are applied to each IMF. Characteristics of spall and crack are well represented by the crest factors of the first and the third IMF, which are used as the feature signals. The classification is carried out using the Bayes decision theory using the feature signals acquired through the experiments.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.4
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• pp.1309-1319
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• 1996

The research for the classification of the natural defects in welding zone is performd using the neuro-pattern recognition technology. The signal pattern recognition package including the user's defined function is developed to perform the digital signal processing, feature extraction, feature selection and classifier selection, The neural network classifier and the statistical classifiers such as the linear discriminant function classifier and the empirical Bayesian calssifier are compared and discussed. The neuro-pattern recognition technique is applied to the classificaiton of such natural defects as root crack, incomplete penetration, lack of fusion, slag inclusion, porosity, etc. If appropriately learned, the neural network classifier is concluded to be better than the statistical classifiers in the classification of the natural welding defects.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.5
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• pp.493-500
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• 2009

An ultrasonic signal processing algorithm was developed for extracting the information of cracks generated around the keyway of a turbine rotor disk. B-scan images were obtained by using keyway specimens and an ultrasonic scan system with x-y position controller. The B-scan images were used as input images for 2-Dimensional signal processing, and the algorithm was constructed with four processing stages of pre-processing, crack candidate region detection, crack region classification and crack information extraction. It is confirmed by experiments that the developed algorithm is effective for the quantitative evaluation of cracks generated around the keyway of turbine rotor disk.

• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.2
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• pp.165-173
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• 2011

The acoustic emission(AE) technique is a well established method to carry out structural health monitoring(SHM) of large structures. However, the real-time monitoring of the crack growth in the roller coaster support structures is not easy since the vehicle operation produces very large noise as well as crack growth. In this investigation, we present the waveform parameter filtering method to classify acoustic sources in real-time. This method filtrates only the AE hits by the target acoustic source as passing hits in a specific parameter band. According to various acoustic sources, the waveform parameters were measured and analyzed to verify the present filtering method. Also, the AE system employing the waveform parameter filter was manufactured and applied to the roller coaster support structure in an actual amusement park.

• Journal of the Korean Society for Nondestructive Testing
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• v.17 no.4
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• pp.248-261
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• 1997

Ultrasonic pattern recognition is the most effective approach to the problem of discriminating types of flaws in weldments based on ultrasonic flaw signals. In spite of significant progress in the research on this methodology, it has not been widely used in many practical ultrasonic inspections of weldments in industry. Hence, for the convenient application of this approach in many practical situations, we develop an intelligent ultrasonic signature classification software which can discriminate types of flaws in weldments based on their ultrasonic signals using various tools in artificial intelligence such as neural networks. This software shows the excellent performance in an experimental problem where flaws in weldments are classified into two categories of cracks and non-cracks. This performance demonstrates the high possibility of this software as a practical tool for ultrasonic flaw classification in weldments.

• Structural Engineering and Mechanics
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• v.89 no.6
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• pp.617-626
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• 2024

The study investigated the behavior of plain and fibered Ultra-High Performance Concrete (UHPC) beams under varying loading conditions using integrated analysis of the flexure and acoustic emission tests. The loading rate of testing is -0.25 -2 mm/min. It is observed that on increasing loading rate, flexural strength increases, and toughness decreases. The acoustic emission testing revealed that higher loading rates accelerate crack propagation. Fiber effect and matrix cracking are identified as significant contributors to the release of acoustic emission energy, with fiber rupture/failure and matrix cracking showing rate-dependent behavior. Crack classification analysis indicated that the rise angle (RA) value decreased under quasi-static loading. The average frequency (AF) value increased with the loading rate, but this trend reversed under rate-dependent conditions. K-means analysis identified distinct clusters of crack types with unique frequency and duration characteristics at different loading rates. Furthermore, the historic index and signal strength decreased with increasing loading rate after peak capacity, while the severity index increased in the post-peak zone, indicating more severe damage. The sudden rise in the historic index and cumulative signal strength indicates the possibility of several occurrences, such as the emergence of a significant crack, shifts in cracking modes, abrupt failure, or notable fiber debonding/pull-out. Moreover, there is a distinct rise in the number of AE knees corresponding to the increase in loading rate. The crack mapping from acoustic emission testing aligned with observed failure patterns, validating its use in structural health monitoring.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.393-396
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• 1995

In this syudy, the researches classifying the artificial and natural flaws in welding parts are performed using the smart pattern recognition technology. For this purpose the smart signal pattern recognition package including the user defined function was developed and the total procedure including the digital signal processing,feature extraction , feature selection and classifier selection is treated by bulk. Specially it is composed with and discussed using the statistical classifier such as the linear disciminant function classifier, the empirical Bayesian classifier. Also, the smart pattern recognition technology is applied to classification problem of natural flaw(i.e multiple classification problem-crack,lack of penetration,lack of fusion,porosity,and slag inclusion, the planar and volumetric flaw classification problem). According to this results, if appropriately learned the neural network classifier is better than ststistical classifier in the classification problem of natural flaw. And it is possible to acquire the recognition rate of 80% above through it is different a little according to domain extracting the feature and the classifier.

• Journal of the Korean Society for Nondestructive Testing
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• v.20 no.2
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• pp.102-109
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• 2000

This paper describes two different theories used to model the scattering of ultrasound by a volumetric flaw and a crack-like flaw. The elastodynamic Kirchhoff approximation (EKA) and the geometrical theory of diffraction (GTD) are applied respectively to a cylindrical cavity and a semi-infinite crack. These methods are known as high frequency approximations. The 2-D elastodynamic scattering problems of a plane wave incident on these model defects are considered and the scattered fields are expressed in terms of the reflection and diffraction coefficients. The ratio of the scattered far field amplitude to the incident wave amplitude is computed as a function of the angular location and compared with the boundary element solutions.

• Journal of Ocean Engineering and Technology
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• v.13 no.3 s.33
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• pp.29-35
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• 1999

At the design of Mark III membrane type LNG tank, an analytical and experimental approach on the fatigue strengths of membrane and its welds are very important in order to assist designers and surveyors. In this study, fatigue tests of lap weld of Mark III membrane type LNG tank were carried out and cumulative damage factor was calculated in order to estimate the fatigue life by probability density function and rule methods. It contained the following tests and reviews : 1) The fatigue tests of lap weld of stainless steel according to statistical testing method recommended by JSME, 2)Preparation of S-N curve for lap welds considering the statistical properties of the results of fatigue tests. 3) Procedure for estimating the initiation life of fatigue crack of lap welds under variable loads by the rule lf classification society and probability density function, 4) Guideline for inspection of lap welds fo membrane type LNG tank.

• Journal of the Korean Institute of Landscape Architecture
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• v.25 no.3
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• pp.1-11
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• 1997

This study aims to estimate the relative importance of quality management items through the defect analysis in the landscape construction process. The RIQMI are decided by the defect coefficient and it's cause weight. The defect items in the landscape construction process were classified by 56 items based on the classification form of '96 landscape architectural construction standard and the cause pattern were categorized 4 types as design, material, construction, and environment factors. To analyze the defect coefficient and the aucse weight by defect, the researcher surveyed the questionnaires on the 103 engineers and the 31 experts on the landscape architectural construction. The result of this study are as follows. The relative importance by facilities pattern turn out to be much higher construction, material fator than design. environment factor in wood facilities, paving facilities, and steel facilities, the RIQMI is very high in timber crack, timber vending, faulty of timber against decay, welding faulty of steel facilities in material factor, and timber crack, faulty of timber against decay, finish faulty of steel facilities, welding faulty of steel facilities in construction factor.