• Industrial Engineering and Management Systems
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• 제8권4호
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• pp.247-256
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• 2009

In mass production industries such as steel making that have large equipment, sudden stops of production process due to machine failure can cause severe problems. To prevent such situations, machine diagnosis techniques play important roles. Many methods have been developed focusing on this subject. In this paper, we propose a method for the early detection of the failure on rotating machine, which is the most common theme in the machine failure detection field. A simplified method of calculating autocorrelation function is introduced and is utilized for ARMA model identification. Furthermore, an absolute deterioration factor such as Bicoherence is introduced. Machine diagnosis can be executed by this simplified calculation method of system parameter distance with weight. Proposed method proved to be a practical index for machine diagnosis by numerical examples.

• Journal of Advanced Marine Engineering and Technology
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• 제23권1호
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• pp.79-87
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• 1999

The most part of the faculty drop a trouble and damage of machine equipment even if whatever cause they break out take place at local and trifling place and the factor dominating their trouble is due to wear debris occurred in the lubricated machine moving surface. This study has been car-ried out to identify morphology of wear debris on the lubricated machine moving system by means of computer image analysis. Namely the wear debris contained in lubricating oil extracted from movable machine equipment will be filtered through membrane filter(void diameter 0.45${\mu}m$) and will be analyzed with its data information such as 50% volume diameter aspect roundness and reflectivity. Morphological characteristic of wear debris is easily distinguished by four shape parameters it is necessary to divide small class of every 100 wear debris in total wear particles in order to distinguish morphological characteristic of wear debris more easily by computer image analysis. We are sure that operation condition diagnosis of the lubricated machine moving surfaces is possible by computer image analysis.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2008년도 춘계학술대회논문집
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• pp.994-999
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• 2008

The necessity of diagnosis of the rotating machinery which is widely used in the industry is increasing. Because vibration diagnosis can avoid sudden breakdown of machine and reduce the maintenance costs. In the factory, Air-Compressor which can affect the performance and capacity of output is important machine. Therefore, in this paper, The measuring and analyzing is carried out for air-compressor in order to the factor of resonance and resonance avoidance for air-compressor. The result of diagnosis and solution is discussed in this paper.

• 한국기계가공학회지
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• 제15권4호
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• pp.134-140
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• 2016

Main Spindle System has effect on performance of machine tools and working quality as well as is required of high reliability. Especially, it takes great importance in producing automobiles which includes a large number of working processes. However, main spindle unit in Machine tools are often cases where damage occurs do not meet the design life due to driving in harsh environments. This is when excessive maintenance and repair of machine tools or for damage stability has resulted in huge economic losses. Therefore, this studying propose a method of accelerated life test for diagnosing and prognosis the state of life assessment main spindle system. Time status monitoring of diagnostic data - through the analysis of the frequency band signals were carried out inside the main spindle bearing condition monitoring and fault diagnosis.

• Industrial Engineering and Management Systems
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• 제4권1호
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• pp.68-74
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• 2005

Among many dimensional and dimensionless amplitude parameters, kurtosis (4-th normalized moment of probability density function) is generally regarded as a sensitive good parameter for machine diagnosis. However, higher order moment may be supposed to be much more sensitive. Bicoherence is an absolute deterioration factor whose range is 1 to 0. The theoretical value of n-th moment divided by n-th moment calculated by measured data would behave in the same way. We propose a simplified calculation method for an absolute index of n-th moment and name this as simplified absolute index of n-th moment. Some favorable results are obtained.

• Industrial Engineering and Management Systems
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• 제2권1호
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• pp.1-8
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• 2003

Among many dimensional or dimensionless amplitude parameters, kurtosis and ID Factor are said to be sensitive good parameters for machine diagnosis. In this paper, a simplified calculation method for both parameters is introduced when impact vibration arise in the observed data. Compared with the past papers' results, this new method shows a good result which fit well. This calculation method is simple enough to be executed even on a pocketsize calculator and is very practical at the factory of maintenance field. This can be installed in microcomputer chips and utilized as a tool for early stage detection of the failure.

• 한국인공지능학회지
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• 제11권1호
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• pp.1-7
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• 2023

In this paper, a study was conducted to compare the prediction model of cardiovascular disease occurrence. It is the No.1 disease that accounts for 1/3 of the world's causes of death, and it is also the No. 2 cause of death in Korea. Primary prevention is the most important factor in preventing cardiovascular diseases before they occur. Early diagnosis and treatment are also more important, as they play a role in reducing mortality and morbidity. The Results of an experiment using Azure ML, Logistic Regression showed 88.6% accuracy, Decision Tree showed 86.4% accuracy, and Support Vector Machine (SVM) showed 83.7% accuracy. In addition to the accuracy of the ROC curve, AUC is 94.5%, 93%, and 92.4%, indicating that the performance of the machine learning algorithm model is suitable, and among them, the results of applying the logistic regression algorithm model are the most accurate. Through this paper, visualization by comparing the algorithms can serve as an objective assistant for diagnosis and guide the direction of diagnosis made by doctors in the actual medical field.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2000년도 제2회 학술대회 논문집 일렉트렛트 및 응용기술전문연구회
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• pp.36-39
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• 2000

This paper presents the technology of condition diagnosis & life estimation on insulation system of the traction motor. In the non-destructive methods for diagnosis of coil insulation state, residual dielectric strength is estimated by the D-map which consist of the partial discharge quantity Q and average degradation degree $\Delta$. In the operating history of machine, the N-Y life estimation method is based on the stop-starting numbers and operating times with considering each degradation factor by the thermal, electrical and heat-cycle stress. With the on-line conditioning monitoring on the currents of traction motors, detecting the abnormal operating state due to bearing faults, stator or armature faults, eccentricity related faults and broken rotor bars can be performed.

• 한국멀티미디어학회논문지
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• 제25권10호
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• pp.1512-1523
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• 2022

Artificial intelligence application in digital health care has been increasing with its development of artificial intelligence. The convergence of the healthcare industry and information and communication technology makes the diagnosis of diseases more simple and comprehensible. From the perspective of medical services, its practice as an initial test and a reference indicator may become widely applicable. Therefore, analyzing the factors that are the basis for existing diagnosis protocols also helps suggest directions using artificial intelligence beyond previous regression and statistical analyses. This paper conducts essential diagnostic prediction learning based on the analysis of blood cancer factors reported previously. Blood cancer diagnosis predictions based on artificial intelligence contribute to successfully achieve more than 90% accuracy and validation of blood cancer factors as an alternative auxiliary approach.

• 한국한의학연구원논문집
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• 제12권2호통권17호
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• pp.103-113
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• 2006

Objectives we intended to know how much did it relate with the results between the instruments of diagnosis by using methods of three factors - QSCCII, PSSC(Phonetic System for Sasang Constitution)-2004, and body measurement which are usually used in diagnosing the Sasang Constitution in clinics Methods We diagnosed Sasang constitution through QSCCII, PSSC(Phonetic System for Sasang Constitution)-2004, Body measurement as a dignosis factors and we used Kappa coefficient to estimate simularity between diagnosis factors, and SPSS 12.0K to analyze data Results and conchusions 1. The orders of agreement statistics are different in the currency of Sasang Constitution diagnosis, Soeum-in was highest and Taeum-in lowest in the the fricency of Sasang Conctitution Diagnosis in the QSCCII, Soeum-in was highest Soyang-in lowest in the PSSC and Taeum-in highest, Soyang-in lowest in the body measurement so, we analogized incorrection in Sasang Constitution Diagnosis 2. Among 443 subjects, 156 (35.3%) had same dignosis in three Sasang Constitution factors. It means agreement statistics among factors of diagnosis are very low, so it is absolutely nessessary to research connection among those, especially Soyang-in part 3. Totally, it is not robust to apply these factors on Sasang Constitution diagnosis, especially agreement statistics between two kinds of Sasang Constitution diagnosis as $0.358{\sim}0.380$. However, we can have a possibility the more we use Sasang Constitution dignosis factors, the higher the agreement statistics is, through the ascending of agreement statistics as $0.526{\sim}0.592$, among three kinds of Sasang Constitution diagnosis To evaluate accuracy of Sasang Constitution diagnosis, it is nessessary to collect data from the subjects who are dignosed through the evidences such as herb medicine, disease and normal symption observation, etc. Using these data, we have to evaluate correction of seperated Sasang Constitution diagnosis methods and to connect those.