• Journal of Chest Surgery
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• v.17 no.1
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• pp.74-77
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• 1984

Left ventricular-Right atrial canal is a rare congenital heart disease. The vast majority of the cases reported in the literature are clinically diagnosed as atrial septal defect or ventricular septal defect. The method of choice in establishing the diagnosis of left ventricular-right atrlal canal is selective left ventriculography. Recently we experienced one case of left ventricular-right atrial canal which was diagnosed as ventricular septal defect preoperatively. The type of defect was tricuspid perforation of infravalvular type, and repaired with direct suture. Postoperative course was uneventful and discharged without complication.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.10a
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• pp.169-174
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• 2012

Reduction unit is one of the most important components for railway vehicle because torque of motor must be transmitted to wheels of vehicle by reduction unit. However, According to advanced studies, it has been often broke down due to the damage, fatigue and wear of gear. To solve this problem, defect diagnosis methods of gear have been mainly using the vibration diagnosis technology through vibration waveform and frequency analysis. However, We should know vibration characteristics of normal state reduction unit prior to defect diagnosis. So in this paper, We had analyzed vibration characteristics of reduction unit in order to utilize monitoring system development. Comparison of targets is the vibration characteristics of normal state reduction unit about Electric Multiple Unit(EMU) and the High-speed trains(KTX, KTX II).

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.72-79
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• 2008

The weak point of the artificial neural network(ANN) is that it is easy to fall in local minima when it learns too much nonlinear data. Accordingly, the classification ratio must be low. To overcome this weakness, the hybrid method has been proposed. That is, the ANN learns data selectively after detecting the defect position by the support vector machine(SVM). First, the SVM has been used for determination of the defect position and then the magnitude of the defect has been measured by the ANN. In off-design condition, the operation region of the engine is wide and the nonlinearity of learning data increases. The module system, dividing the whole operating region into reasonably small-size sections, has been suggested to solve this problem. In this study, the proposed algorithm has diagnosed the defects of triple components as well as single and dual components of the gas turbine engine in off-design condition.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.463-464
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• 2011

Currently, different kinds of diagnosis and inspection technologies are applied to prevent the internal mechanical transformation of transformers. For example, examination of internal Partial Discharge of transformer, analysis of transformer oil gas, and measurement Frequency Response Analyzer(FRA) are used to diagnose defect. Especially, diagnosis technique through Frequency Response Analyzer(FRA) has been used and developed from 1960, when it was first introduced, till now to become an important tool to examine presence of defect and to prove quality of machines for the most electric machine producers electric power company in the world. However, diagnosis through FRA is still in introduction level in Korea and the application method for FRA is not established yet. For that reason, study about the application of domestic electric installation according to the FRA is needed. It is expected that the study play an important part in the prevention of defect due to the internal transformation of transformer by introducing measurement theory, providing measurement method, and analyzing application cases.

• Smart Structures and Systems
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• v.31 no.1
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• pp.79-88
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• 2023

As the number of deteriorated buildings increases, the importance of safety diagnosis, maintenance, and the repair of buildings also increases. Traditionally, building condition assessments are performed by one person or one company and various inspections are needed. This entails a subjective judgment by the inspector, resulting in different assessment results, poor objectivity and a lack of reliability. Therefore, this study proposed a method to bring about accurate grading results of building conditions. The limitations of visual inspection and condition assessment processes previously conducted were identified by reviewing existing studies. Building defect data was collected using the reverse-engineered three-dimensional (3D) model. The accuracy of the results was verified by comparing them with the actual evaluation results. The results show a 50% time-saving to the same area with an accuracy of approximately 90%. Consequently, defect data with high objectivity and reliability were acquired by measuring the length, area, and width. In addition, the proposed method can improve the efficiency of the building diagnosis process.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.2
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• pp.146-153
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• 2011

Model based machine condition diagnosis methods are generally using a normal and many failure models which need sufficient data to train the models. However, data, especially for failure modes of interest, is very hard to get in real applications. So their industrial applications are either severely limited or impossible when the failure models cannot be trained. In this paper, continuous hidden Markov model(CHMM) with only a normal model has been suggested as a very promising machine condition diagnosis method which can be easily used for industrial applications. Generally hidden Markov model also uses many pattern models to recognize specific patterns and the recognition results of CHMM show the likelihood trend of models. By observing this likelihood trend of a normal model, it is possible to detect failures. This method has been successively applied to arc weld defect diagnosis. The result shows CHMM's big potential as a machine condition monitoring method.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.40 no.1
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• pp.61-71
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• 2003

Interconnect test for highly integrated environments like SoC, becomes more important as the complexity of a circuit increases. This importance is from two facts, test time and complete diagnosis. Since the interconnect test between IPs is based on the scan technology such as IEEE1149.1 and IEEE P1500, it takes long test time to apply test vectors serially through a long scan chain. Complete diagnosis is another important issue because a defect on interconnects are shown as a defect on a chip. But generally, interconnect test algorithms that need the short test time can not do complete diagnosis and algorithms that perform complete diagnosis need long test time. A new interconnect test algorithm is developed. The new algorithm can provide a complete diagnosis for all faults with shorter test length compared to the previous algorithms.

• Smart Structures and Systems
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• v.19 no.2
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• pp.195-202
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• 2017

The aim of this paper is to develop a novel method to determine the severity of a damage in a thin plate. This paper presents a novel fault detection and diagnosis approach employing a new electromagnetic acoustic transducer, called EMAT, together with a complex signal processing method. The method consists in the recognition of a fault that exists within the structure, the fault location, i.e. the identification of the geometric position of damage, and the determining the significance of the damage, which indicates the importance or severity of the defect. The main scientific novelties presented in this paper is: to develop of a new type of electromagnetic acoustic transducer; to incorporate wavelet transforms for signal representation enhancements; to investigate multi-parametric analysis for noise identification and defect classification; to study attenuation curves properties for defect localization improvement; flaw sizing and location algorithm development.

• Journal of the Korean Society of Propulsion Engineers
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• v.12 no.3
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• pp.60-67
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• 2008

In this study, the genetic algorithm has been used for the real-time defect diagnosis on the operation of the aircraft gas-turbine engine. The component elements of the gas-turbine engine for consideration of the performance deterioration consist of the compressor, the gas generation turbine and the power turbine. Compared to the on-design point, the teaming data has been increased 200 times in case off-design conditions for the altitude, the flight mach number and the fuel consumption. Therefore, enormous learning time has been required for the satisfied convergence. The optimal division has been proposed for learning time decrease as well as the high accuracy. As results, the RMS errors of the defect diagnosis using the genetic algorithm have been confirmed under 5 %.

• Journal of Chest Surgery
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• v.15 no.1
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• pp.129-135
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• 1982

Congenital pericardial defect is a rare anomaly, which was first described by M. Columbus in 1559. Four hundred years later the first clinical diagnosis was reported by Ellis et al. The congenital pericardial defect Is usually asymptomatic and Is found Incidentally at thoracotomy and autopsy, but it appears that partial absence of pericardium Is not Innocuous because of sudden death due to herniation of a portion of heart. We experienced congenital left pericardial defect in 20 year old female who was diagnosed as left ventricular aneurysm before operation. This patient complained of dyspnea on exertion and anterior chest discomfortness. Physical examination revealed Grade II pansystolic murmur on the 3rd and 4th intercostal space left sternal border. There were specific abnormal findings on the chest plain film, EKG, ultrasonography, and left ventriculography. On 9th July 1981, an operation was performed and found the left partial pericardial defect through which a large portion of left ventricle was herniated Into left pleural space. The method of operation was removal of adhesion and widening of the pericardial defect to avoid Incarceration. After operation, we observed marked Improvement of symptoms and disappearance of cardiac murmur.