• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1990.06a
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• pp.7-31
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• 1990

Tribologicsl diagnostics as the ensemble of means and methods of continuous monitoring of the state of friction characteristics of moving junctions is playing an ever important part in the development of friction, lubrication, and wear theory end practice. The scheme presenting the main areas of tribological diagnostics is given in Fig. I. This growing part of TD is determined by the general tendency of modern technology, expressed in an attempt to organically combine the functions of measuring, evaluating,and predicting the parameters and characteristics of the processee taking place in the operating device. The logical result of this integration in future is the closed system correcting its operation in accordance with sn established program. Unfortunately, tribotechnicsl devices are still very far from such an ideal system at the present time. While in the friction assemblies with hydrodynamic lubrication it is possible in the first approximation to realize feed-backs in the lubricant circulation system with the aid of monitoring of the pressure, temperature and filtration, in the systems operating without lubrication and with boundary lubricetion even the process of selection of the diagnostic parameters has not been completed.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.11
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• pp.93-101
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• 1997

Ever since the nonlinearity of machine tool dynamics was established, researchers attempted to make use of this fact to devise better monitoring, diagnostics and control system, which were hitherto based on linear models. Theory of chaos which explains many nonlinear phenomena comes handy for furthering the analysis using nonlinear model. In this study, measuring system will be constructed using multi-sensor (Tool Dynamometer, Acoustic Emission) in end milling process. Then, it will be verified that cutting force is low-dimensional chaos by calculating Lyapunov exponents. Fractal dimension, embedding dimension. And it will be investigated that the relation between characteristic parameter calculated from sensor signal and tool wear.

• Journal of Power System Engineering
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• v.2 no.2
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• pp.73-80
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• 1998

The identification of drilling joint dynamics which consists of drilling and structural dynamics and the on-line time series detection of malfunction process is substantial not only for the investigation of the static and dynamic characteristics but also for the analytic realization of diagnostic and control systems in drilling. Therefore, We have discussed on the comparative assessment of two recursive time series modeling algorithms that can represent the drilling operation and detect the abnormal geometric behaviors in precision roundshape machining such as turning, drilling and boring in precision diemaking. For this purpose, simulation and experimental work were performed to show the malfunctional behaviors for drilling operation. For this purpose, a new two recursive approach (Recursive Extended Instrument Variable Method : REIVM, Recursive Least Square Method : RLSM) may be adopted for the on-line system identification and monitoring of a malfunction behavior of drilling process, such as chipping, wear, chatter and hole lobe waviness.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.3
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• pp.42-51
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• 1999

An experimental modeling of cutting and structural dynamics and the on-line detection of malfunction process is substantial not only for the investigation of the static and dynamic characteristics of cutting process but also for the analytic realization of diagnostic systems. In this regard, We have discussed on the comparative assessment of two recursive time series modeling algorithms that can represent the machining process and detect the abnormal machining behaviors in precision round shape machining such as turning, drilling and boring in mold and die making. In this study, simulation and experimental work were performed to show the malfunctioned behaviors. For this purpose, two new recursive approach (REIVM, RLSM) were adopted fur the on-line system identification and monitoring of a machining process, we can apply these new algorithm in real process for the detection of abnormal machining behaviors such as chipping, chatter, wear and round shape lobe waviness.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.3
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• pp.77-85
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• 2022

In this study, to diagnose the grinding state of a micro drill bit, a sensor attachment location was selected through random vibration analysis of the grinding unit of the micro drill-bit grinding system. In addition, the vibration data generated during the drill bit grinding were collected from the grinding unit for the grinding wheels under the steady and worn conditions, and data feature extraction and dimension reduction were performed. The wear of the micro-drill-bit grinding wheel was diagnosed by applying KNN, a machine-learning algorithm. The classification model showed excellent performance, with an accuracy of 99.2%. The precision, recall and f1-score were higher than 99% in both the steady and wear conditions.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.817-821
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• 1997

Ever since the nonlinearity of machine tool dynamics was established, researchers attempted to make use of this fact to devise better monitoring, diagnostics and system, which were hitherto based on linear models. Theory of chaos, which explains many nonlinear phenomena comes handy for furthering the analysis using nonlinear model. In this study, measuring system will be constructed using multi-sensor (Tool Dynamometer, Acoustic Emission) in end millingprocess. Then, it will be verified that cutting force is low-dimensional deterministic chaos calculating Lyapunov exponents, Fractal dimension, Embedding dimension. Aen it will be investigated that the relations between characteristic parameter caculated form sensor signal and tool wear.

• Journal of Veterinary Science
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• v.23 no.6
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• pp.80.1-80.6
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• 2022

A 10-year-old male neutered Labrador Retriever presented with a history of acute-onset tachypnoea, lethargy and anorexia. The dog was pyrexic, tachypnoeic and dyspnoeic on examination. A rapid antigen test for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) was performed on an oropharyngeal swab and yielded a positive result. SARS-CoV-2 infection was subsequently confirmed by reverse transcription polymerase chain reaction (RT-PCR) analysis. Both of the dog's owners had positive rapid antigen test and RT-PCR analysis results for SARS-CoV-2. Additional diagnostics included computed tomography. Resolution of the dog's clinical signs was achieved with symptomatic treatment.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.7
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• pp.679-686
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• 2013

The reduction unit is one of the most important components in railway cars, due to the transmission of torque from the motor to the wheels. Faulty reduction gears in high-speed trains result from excessive wear on the gear or damage to the gear. These types of gear defects have a significant effect on high-speed rail operation and safety; thus, a diagnosis system for the reduction unit is needed. Vibration diagnosis technology is one of the most effective diagnostics. In this paper, the vibration parameters of a reduction unit were evaluated during a driving-gear test and a full-vehicle test, using kurtosis and the crest factor. These tests were performed under normal operating conditions; a specimen tester was used to diagnose problems in defective gears.