• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.537-543
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• 2003

Condition monitoring and fault diagnosis of machines are gaining importance in the industry because of the need to increase reliability and to decrease possible loss of production due to machine breakdown. By comparing the vibration signals of a machine running in normal and faulty conditions, detection of faults like mass unbalance, shaft misalignment and bearing defects is possible. This paper presents a novel approach for applying the fault diagnosis of rotating machinery. To detect multiple faults in rotating machinery, a feature selection method and support vector machine (SVM) based multi-class classifier are constructed and used in the faults diagnosis. The results in experiments prove that fault types can be diagnosed by the above method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11b
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• pp.1067-1072
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• 2001

In this study, the vibration diagnosis program for onboard machinery has been developed. The developed program includes signal monitoring module, system diagnosis module, and system modification module. The signal monitoring module is to monitor the vibration signal in time and frequency domains. And the system diagnosis module, which is developed by using Neural Network with error back propagation algorithm, can detect the abnormal symptom indicating the malfunction of the machinery onboard ships. The investigations of the developed system are presented through the experiment using Rotor Kit. Abnormal vibration signals are created by adding additional weight, manually misaligning the shaft, and loosening the bolts.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2004.11a
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• pp.158-161
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• 2004

In recent, the automotive number of korea has risen above 14millions vehicles. The automotive was settled down goods haying to live. In a flood of this automotive the accuracy diagnosis for the vehicle certainly need for people referencing car. To do this diagnosis, the researcher has to experience many example in the field and need to system them. Expecially, the study for failure of the engine nearly research in the korea. When moving parts of engine no problem. In order to work, the engine must operate normality state. In this paper the purpose study the failure for the tribological example of engine.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.26 no.6_spc
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• pp.714-720
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• 2016

Rubbing and misalignment are the most usual faults that occurs in rotating machinery and with them severe effect on power plant availability. Especially blade rubbing is hard to detect on FFT spectrum using the vibration signal. In this paper, the possibility of feature analysis of vibration signal is confirmed under blade rubbing and misalignment condition. And the lab-scale rotor test device provides the blade rubbing and shaft misalignment modes. Feature selection based on GA (genetic algorithm) is processed by the extracted feature of the time domain. Then, classification of the features is analyzed by using SVM (support vector machine) which is one of the machine learning algorithm. The results of features selection based on GA compared with those based on PCA (principal component analysis). According to the results, the possibility of feature analysis is confirmed. Therefore, blade rubbing and shaft misalignment can be diagnosed by feature of vibration signal.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.7
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• pp.694-701
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• 2013

The gear-reduction units of Korean high-speed trains consist of a motor reduction unit, an axle gear box reduction unit, and a tripod joint shaft. A reduction gear unit is a gearbox used to reduce the rotational speed of the input shaft to a slower rotational speed on the output shaft. This reduction in output speed helps to increase torque. Defective reduction gear units in high-speed trains are caused by damage to the gear or by gear fatigue. To diagnose potential problems, it is important to know the vibration characteristics of the reduction gear units. In this study, we analyzed the vibration characteristics of reduction gears under various conditions. The test setup included a full-scale test rig to evaluate reduction gear under both normal and extreme operating conditions.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11a
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• pp.365-370
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• 2001

The purpose of this work is to suggest a new non-contact measurement method applicable to the diagnosis of rotating shafts. Longitudinal elastic waves propagating along the shafts are measured by magnetostrictive sensors that make use of the coupling phenomena between strains and magnetic induction in ferromagnetic shafts. These sensors have been successfully applied in pipes and others, but it appears that the present application of them to rotating shafts is made here for the first time. Several isssues appearing in the present application are carefully investigated and several experimental results are presented to address the usefulness of the present method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.891-894
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• 2007

This study presents fault diagnosis of low speed bearing using support vector machine (SVM). The data used in the experiment was acquired using acoustic emission (AE) sensor and accelerometer. The aim of this study is to compare the performance of fault diagnosis based on AE signal and vibration signal with same load and speed. A low speed test rig was developed to simulate various defects with shaft speeds as low as 10 rpm under several loading conditions. In this study, component analysis was also performed to extract the feature and reduce the dimensionality of original data feature. Moreover, the classification for fault diagnosis was also conducted using original data feature without feature extraction. The result shows that extracted feature from AE sensor gave better performance in faults classification.

• Journal of the Korean Orthopaedic Association
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• v.56 no.5
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• pp.427-432
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• 2021

Delayed treatment of volar dislocation of the distal radioulnar joint can result in wrist pain, limited rotation of the forearm, and degenerative arthritis that could be managed only by salvage procedures. A 24-year-old male patient presented with wrist pain and a loss of forearm rotation after surgery for a radial shaft fracture. The shaft of the radius was fixed with a plate and screws with a volar angulation of 7°. The ulnar head was dislocated volar to the distal radius, and the bone defect in the ulnar head was impacted into the volar rim of the sigmoid notch of the radius, preventing the head from being reduced in the joint. Corrective osteotomy of the malunited radial shaft and sliding osteotomy of the proximal ulnar head were performed to fill the distal bone defect. Pain and range of the forearm rotation were improved at postoperative 19 months.

• The Journal of the Korea Contents Association
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• v.12 no.12
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• pp.335-344
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• 2012

Osteoporosis is increasing in Korea as it becomes an aging society with the rapid economic growth and the development of medical technology. Osteoporosis also develops due to chemo and radiation therapy of cancer which also increases owing to Westernized diet. Osteoporosis is caused by reduced bone density, has close relationship with the change of geometry of proximal femur, which is a factor of hip fracture risk. The purpose of this study was the analysis of the correlations of osteoporosis and the change of geometry of proximal femur, which was observed according to T-score variance. The 350 male and female patients are chosen from D hospital in Busan, who were classified by age, sex and T-score values (normal, osteopenia, and osteo porosis). The results show that the age and gender have significant difference in the incidence of osteoporosis; the disease classification according to T-score value has significant difference in the geometry of the proximal femur such as Cortical ratio calcar, Cortical ratio shaft, Hip/shaft Angle, Strength index, Section modulus, CSMI, and CSA, and is highly correlated with the incidence of osteoporosis. Therefore, the findings of this research is that the change of the geometry of the proximal femur could be used as an indicator in the diagnosis of osteoporosis, could enhance the accuracy of the diagnosis in the future, and could be used as a clinical predictive factors through the analysis of the correlations of T-score variance and the geometry changes of the proximal femur.

• 한국기계연구소 소보
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• s.17
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• pp.61-68
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• 1987

The main objective of this paper is to develop the computer-aided vibrational signal processing and monitoring system of rotating machinery. This system has an automatic data acquisition capability and analyze for machine fault diagnosis. By spectrum analysis, machine’s failure can be identified. The monitoring system enables diagnosis of the fault in rotating machinery. In this study, the conventional electrical fans are selected as a model case. The date processing and fault monitoring system proposed here can be applied to the automation of the inspection process in assembling motor-shaft systems. The automatic inspection can enhance the product quality and keep it stable. Since the proposed system is developed for personal computers, it might be cheap in cost and easy in installation.