• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.770-773
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• 2007

As higher reliability and accuracy on production facilities are required to detect incipient faults, a diagnostic system for predictive maintenance of the facility is highly recommended. In this paper, it presents a study on the application of vibration signals to diagnose faults for a Rotating Machinery using the Mahalanobis Distance-Taguchi System. RMS, Crest Factor and Kurtosis that is known as the Statistical Methods and the spectrum analysis are used to diagnose faults as parameters of Mahalanobis distance.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.10a
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• pp.66-75
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• 1993

Since information systems have been treated as a management tool, a model is required to express and analyze and organizational point of view. Futher, a systematic methodology is required to analyze and diagnose organizational processes to improve them. To improve existing organizational processes, it is needed to describe all the processes performed in each department and their relationships to staffs, resources, and other processes of the organization. However, because of the complexity and unstructureness of the processes, this task is very difficult. We proposed an organizational process model which expresses organizational information on processes, departments, staffs, and resources. Based on this model, we have developed a management information database and a computerized tool which help analyze and diagnose organizational processes. The organizational process model, management information database, the automated tool may be used for BR(Business Re-engineering).

• Journal of the Korean Society of Safety
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• v.18 no.1
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• pp.50-55
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• 2003

This paper presents an intelligent computer system, which can easily diagnose electrical fire causes, without the help of human experts of electrical fires diagnosis. For this system, a database is built with facts and rules driven from real electrical fires, and an intellectual database system which even a beginner can diagnose fire causes has been developed, named as an Electrical Fire Causes Diagnosis System : EFCDS. The database system has adopted, as an inference engine, a mixed reasoning approach which is constituted with the rule-based reasoning and the case-based reasoning. The system for a reasoning model was implemented using Delphi 3, one of program development tools, and Paradox is used as a database building tool. To verify effectiveness and performance of this newly developed diagnosis system, several simulated fire examples were tested and the causes of fire examples were detected effectively by this system. Additional researches will be needed to decide the minimal significant level of the solution and the weighting level of important factors.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.7
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• pp.556-560
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• 2008

As higher reliability and accuracy on production facilities are required to detect incipient faults, a diagnostic system for predictive maintenance of the facility is highly recommended. In this paper, we present a study on the application of vibration signals to diagnose faults for a Rotating Machinery using the Mahalanobis Distance-Taguchi System. RMS, Crest Factor and Kurtosis that is known as the Statistical Methods and the spectrum analysis are used to diagnose faults as parameters of Mahalanobis distance.

• Journal of Electrical Engineering and Technology
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• v.2 no.4
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• pp.461-467
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• 2007

The paper describes a way to diagnose machine condition based on the expert system. In this paper, an expert system-decision tree is built and experimented to diagnose and to detect machine defects. The main objective of this study is to provide a simple way to monitor machine status by synthesizing the knowledge and experiences on the diagnostic case histories of the rotating machinery. A traditional decision tree has been constructed using vibration-based inputs. Some case studies are provided to illustrate the application and advantages of the decision tree system for machine fault diagnosis.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.160-165
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• 2007

It is well recently recognized that quench is one of the serious problems for the integrity of superconducting magnets, which is mainly attribute to the rapid temperature rising in the magnet due to some extrinsic factors such as conductor motion, crack initiation etc. In order to apply acoustic emission(AE) technique effectively to monitor and diagnose superconducting magnets, it is essential to identify the sources of acoustic emission. In this paper, an acoustic emission technique has been used to monitor and diagnose quenching phenomenon in racetrack shaped superconducting magnets at cryogenic environment of 4.2K. For these purposes special attention was paid to detect AE signals associated with the quench of superconducting magnets. The characteristics of AE parameters have been analyzed by correlating with quench number, winding tension of superconducting coil and charge rate by transport current.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.3
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• pp.65-70
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• 2003

In this paper, an adapted TWC model and its application to the monitoring algorithm are proposed. As TWCs have the different characteristics, the model has to be corrected to diagnose more accurately. In the TWC model oxygen storage and release rate model are adapted to the installed TWC to whose characteristics related. The model learns from the downstream $O_2$ sensor output during the vehicle's operation. From the results, the model is adapted to the Installed TWC's characteristics. using this model, the monitoring algorithm can diagnose the no more accurately. Finally the algorithm is validated with simulations using the data logged from a retail car.

• The Journal of the Korean life insurance medical association
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• v.2 no.1
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• pp.75-81
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• 1985

Urine contains protein and nucleic acid(urea, uric acid, creatinine, ammonia, amino acids), various organic and inorganic materials, vitamin, hormone, enzyme etc. The examination of gualitative or quantitative change of the above mentioned materials and picking up the abnormal materials are useful to diagnose diseases. The test strip for examination of urine is applied to the routine test, monitoring of medical therapy and recurrence, self monitoring, and screeing in preventive medicine. We have been using multitest strip for checking the bacterial infection(nitrite), PH, protein, glucose, ketone body, urobilinogen, bilirubin and occult blood. So it is possible to diagnose three groups of diseases as follows, abnormal metabolism of the carbohydrate, diseases of kidney and other urogenital system, diseases of hepatobiliary system and hemolytic disease causing abnormal metabolism of bile juice.

• Journal of Yeungnam Medical Science
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• v.37 no.1
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• pp.2-12
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• 2020

Drug-induced liver injury (DILI), including herbal and dietary supplement hepatotoxicity, is often passed lightly; however, it can lead to the requirement of a liver transplant or may even cause death because of liver failure. Recently, the American College of Gastroenterology, Chinese Society of Hepatology and European Association for the Study of the Liver guidelines for the diagnosis and treatment of DILI have been established, and they will be helpful for guiding clinical treatment decisions. Roussel Uclaf Causality Assessment Method scoring is the most commonly used method to diagnose DILI; however, it has some limitations, such as poor validity and reproducibility. Recently, studies on new biomarkers have been actively carried out, which will help diagnose DILI and predict the prognosis of DILI. It is expected that the development of new therapies such as autophagy inducers and various other technologies of the fourth industrial revolution will be applicable to DILI research.

• Journal of Biomedical Engineering Research
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• v.31 no.1
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• pp.27-32
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• 2010

Noninvasive detection of patients with probable Alzheimer's disease (AD) is of great importance for assisting a medical doctor's decision for early treatment of AD patients. In the present study, we have extracted quantitative electroencephalogram (qEEG) variables, which can be potentially used to diagnose AD, from resting eyes-closed continuous EEGs of 22 AD patients and 27 age-matched normal control (NC) subjects. We have extracted qEEG variables from mean phase coherence (MPC) and EEG coherence, evaluated for all possible combinations of electrode pairs. Preliminary trials to discriminate the two groups with the extracted qEEG variables demonstrated that the use of MPC as a supplementary or alternative measure for the EEG coherence may enhance the accuracy of noninvasive diagnosis of AD.