• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.230-233
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• 2016

In this paper, we developed the ice machine conditions monitoring system that confirms conditions of the ice machine. The developed system is composed of Communication Board, Server Program, and Web-based User Application. Communication Board which is connected to the ice machine periodically sends various data, such as current, voltage, the refrigerant pressure and temperature, the external temperature and humidity. Server Program stores the data received from Communication Board into database. The manager or the ice machine operator can see the state of the own machine through User Application based on Web. When a symptom is detected on the ice machine, the manager and the operator can checks the current condition of the ice machine by using the data obtained in real time and also prevents the machine troubles by taking proper actions.

• 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 Korea Safety Management & Science
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• v.6 no.2
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• pp.231-239
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• 2004

To keep an enterprise's competitiveness on the condition of the automatic manufacturing system such as FA, FMS and CIM, all the maintenance problems should be considered seriously in not only in production and maintenance but also in related industrial productivity. This paper presents the study of equipment reliability improvement for rotary-machine vibration analysis. Based on these analyses, the maintenance management information system, and the machinery condition diagnosis technique are studied by using of the real-time diagnostic. Therefore, it is expected to improve the efficiency of business processes in the production and safety when we use this system.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1997.04a
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• pp.224-231
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• 1997

Microscopic examination for the morphological estimation of wear debris on the oil-lubrcated moving system is an accepted method for machine condition and fault diagnosis. However wear particle anaysis has not been widely accepted industry because it is dependent on expert interpretation of particle morphology and relies on subjective assessment criteria. This paper was undertaken to estimate the morphology of wear debris on the oil-lubricated movig system by computer image analysis. The wear test was performed under different sliding conditions using a wear test device made in our laboratory and wear testing specimen of the pin-on-disk-type was rubbed in pararline series base oil. In order to describe characteristics of debris of various shape and size, four shape parameters (50% volumetric diameter, aspect, roundness and reflectivity) have been developed and outlined in the paper. A system using such techniques promises to obviate the need for subjective, human interpretation of particle morphology in machine condition monitoring.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.400-405
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• 2005

The diagnosis of mechanical load and of power transmission system failures is usually carried out through mechanical signals such as vibration signals, acoustic emissions, motor speed envelope. If the mechanical load comes from an electrical machine the mechanical failures could be detected previously. Mechanical rotor imbalances and rotor eccentricities are reflected in electric, electromagnetic and mechanical quantities. Therefore, many surveillance schemes apply to the Fourier spectrum of a line current in order to monitor the motor condition. Due to the interaction of the currents and voltages, both these current harmonics are also reflected by a single harmonic component in the frequency spectrum of the electric power. Motor Current Signature Analysis is the usuful technique to assess machine electrical condition.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.6
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• pp.44-49
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• 2003

The morphological analysis of wear debris can provide early a failure diagnosis in lubricated moving system. It can be effective to analyze operating conditions of oil-lubricated tribological system with shape characteristics of wear debris in a lubricant. But, in order to predict and recognize an operating condition of lubricated machine, it is needed to analyze and to identify shape characteristics of wear debris. Therefore, If the morphological characteristics of wear debris are recognized by computer image analysis using the neural network algorithm, it is possible to recognize operating condition of hydraulic driving members. In this study, wear debris in the lubricating oil are extracted by membrane filter (0.45$\mu\textrm{m}$), and the quantitative values of shape parameters of wear debris are calculated by the digital image processing. This shape parameters are studied and identified by the artificial neural network algorithm. The result of study could be applied to prediction and to recognition of the operating condition of hydraulic driving members in lubricated machine systems.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.05a
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• pp.61-65
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• 2001

The conventional tracking testing as IEC-60587 is widely used in surface aging measurement of outdoor insulator because those testing can carry out very short time in Lab-testing. Also IEC-60587 testing is able to offer the standard judgement of relative degradation level of outdoor HV machine/system. Therefore it is very useful method compare to previous conventional tracking testing method and effective Lab-testing method. But surface discharges(SD) have very complex characteristics of discharge pattern so it is required estimation research to development of precise analysis method. In recent, the study of IRR-camera is carrying out discover of temperature of power equipment through condition diagnosis and system development of degradation diagnosis. In this study, SD occurred from procelain insulator, used 22.9[KV] distribution, is measured with partial temperature distribution in real time, the degradation grade of SD is analyzed through produced patterns in SD concentration according to applied time.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.401-406
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• 2006

This paper presents the fault diagnosis of induction motor based on support vector machine(SVMs). SVMs are well known as intelligent classifier with strong generalization ability. Application SVMs using kernel function is widely used for multi-class classification procedure. In this paper, the algorithm of SVMs will be combined with feature extraction and reduction using component analysis such as independent component analysis, principal component analysis and their kernel(KICA and KPCA). According to the result, component analysis is very useful to extract the useful features and to reduce the dimensionality of features so that the classification procedure in SVM can perform well. Moreover, this method is used to induction motor for faults detection based on vibration and current signals. The results show that this method can well classify and separate each condition of faults in induction motor based on experimental work.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.05b
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• pp.71-74
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• 2001

The conventional tracking testing as IEC-60587 is widely used In surface aging measurement of outside insulator because those testing can carry out very short time in Lab testing. Also IEC-60587 testing is able to offer the standard judgement of relative degradation level of outside HV machine. Therefore it is very useful method compare to previous conventional tracking testing method and effective Lab testing method. But surface discharges(SD) have very complex characteristics of discharge pattern so it is required estimation research to development of precise analysis method. In recent, the study of IIR-camera is carrying out discover of temperature of power equipment through condition diagnosis and system development of degradation diagnosis. In this study, SD occurred from IEC-60587 is measured with partial temperature distribution in real time, the degradation grade of SD is analyzed through produced patterns in IEC-60587 according to applied time.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2006.11a
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• pp.46-53
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• 2006

This paper presents the fault diagnosis of induction motor based on support vector machine (SVMs). SVMs are well known as intelligent classifier with strong generalization ability. Application SVMs using kernel function is widely used for multi-class classification procedure. In this paper, the algorithm of SVMs will be combined with feature extraction and reduction using component analysis such as independent component analysis, principal component analysis and their kernel (KICA and KPCA). According to the result, component analysis is very useful to extract the useful features and to reduce the dimensionality of features so that the classification procedure in SVM can perform well. Moreover, this method is used to induction motor for faults detection based on vibration and current signals. The results show that this method can well classify and separate each condition of faults in induction motor based on experimental work.