• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.8
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• pp.55-61
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• 2010

In this paper, we proposed selective extraction method of frequency information and PCA-ELM based diagnosis system for three-phase induction motors. As the first step for diagnosis procedure, DFT is performed to transform the acquired current signal into frequency domain. And then, frequency components are selected according to discriminate order calculated by variance As the next step, feature extraction is performed by principal component analysis (PCA). Finally, we used the classifier based on Extreme Learning Machine (ELM) with fast learning procedure. To show the effectiveness, the proposed diagnostic system has been intensively tested with the various data acquired under different electrical and mechanical faults with varying load.

• Smart Structures and Systems
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• v.4 no.6
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• pp.779-794
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• 2008

Observer-based fault detection and isolation (FDI) filter design method is a model-based method. By carefully choosing the observer gain, the residual outputs can be projected onto different independent subspaces. Each subspace corresponds to the monitored structural element so that the projected residual will be nonzero when the associated structural element is damaged and zero when there is no damage. The key point of detection filter design is how to find an appropriate observer gain. This problem can be interpreted in a geometric framework and is found to be equivalent to the problem of finding a decentralized static output feedback gain. But, it is still a challenging task to find the decentralized controller by either analytical or numerical methods because its solution set is, generally, non-convex. In this paper, the concept of detection filter and iterative LMI technique for decentralized controller design are combined to develop an algorithm to compute the observer gain. It can be used to monitor structural element state: healthy or damaged. The simulation results show that the developed method can successfully identify structural damages.

• Journal of the Korean Society of Safety
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• v.26 no.1
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• pp.8-14
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• 2011

Noise and vibration are likely to disturb the sensory system of human body leading to psychological stress and thereby property damage. In this research, a cut out switch(COS) with a built-in acoustic absorber along with a COS fuse broken was developed to reduce percussion noise. This new system is based on a design approach that combines existing absorber systems: expansion type, resonator type, and acoustic absorber type silencer The noise performance of the new system was simulated using the $SYSNOISE^{TM}$ software under optimized parameters: the diameter of perforated plate 2 mm, the plate thickness 3 mm, the width of expansion room 25 mm, the impinging vortex room 14 mm, and the noise absorbtion room 10 mm. The results showed that it reduced noise by approximately 41.1 dB compared to the current systems available in the market. Furthermore, it showed reduced noise by approximately 12 dB more than a product with an acoustic absorber of the Fault Tamer(USA).

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.31 no.1
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• pp.24-28
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• 2018

Insulators used in overhead transmission lines are continuously exposed to a number of mechanical and electrical stresses owing to external environmental factors, resulting in corrosion, reduction in durability, and deterioration. Widely used porcelain insulators are fabricated with cement and porcelain and are especially common in Korea. Changes in the hardness and chemical reactivity of the cement increase the leakage and fault currents and increase the possibility of flashover due to insulation breakdown. Therefore, it is important to evaluate the durability and defects of porcelain insulators. Studies on the reliability of various evaluation methods are needed to prevent accidents by accurately determining the replacement timing and potential defects in porcelain insulators. In this study, the hardness of the cement part of the porcelain insulator was measured using the Vickers hardness test and its composition was analyzed by energy dispersive spectroscopy and X-ray diffraction analysis. The performance of the insulators was compared in two different regions with varying climatic conditions. This study presents an evaluation method of the defects in porcelain insulators by measuring humidity, which can also be used to assess the reliability of the insulators.

• Proceedings of the KIEE Conference
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• 2006.07e
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• pp.25-26
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• 2006

An electrical fault is defined as any abnormal condition caused by reduction in the insulation strength between energized conduction parts and ground or any grounded part of an electrical system. Failure of solid insulation can be caused by excessive mechanical tension being applied on the insulation, harsh service environment, aging, and also by corona phenomena. The number of empty houses during normal working hours is rising. As a result, the number of uninspected electric installation for general use is increasing. To define the potential risk of the electric installation, measurement of leakage current has been getting considered, but because the measured leakage current value also contained leakage current by capacitance, the measured value can not be adapted to absolute reference to the installation. Therefore, in this paper, the correlation between the condition of electric installation and leakage current were analyzed.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.84-88
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• 2008

The UAV propulsion system that will be operated for long time at more than 40,000ft altitude should have not only fuel flow minimization but also high reliability and durability. If this UAV propulsion system may have faults, it is not easy to recover the system from the abnormal, and hence an accurate diagnostic technology must be needed to keep the operational reliability. For this purpose, the development of the health monitoring system which can monitor remotely the engine condition should be required. In this study, a fuzzy trend monitoring method for detecting the engine faults including mechanical faults was proposed through analyzing performance trends of measurement data. The trend monitoring is an engine conditioning method which can find engine faults by monitoring important measuring parameters such as fuel flow, exhaust gas temperatures, rotational speeds, vibration and etc. Using engine condition database as an input to be generated by linear regression analysis of real engine instrument data, an application of the fuzzy logic in diagnostics estimated the cause of fault in each component. According to study results, it was confirmed that the proposed trend monitoring method can improve reliability and durability of the propulsion system for a long endurance UAV to be operated at medium altitude.

• Journal of Drive and Control
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• v.15 no.4
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• pp.30-38
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• 2018

Electronic control units (ECUs) are currently popular, and have evolved further towards the high-end application of autonomous vehicles in the automotive industry. Such digital technologies have also become widespread, in agriculture and construction equipment. Likewise, transmission control of high-speed tracked vehicles is based on the transmission control unit (TCU), performing complex gear change control functions, and diagnostic algorithms (a TCU's self-diagnostic and reporting capability of malfunction data through CAN communication). Since all functions of TCU are implemented by embedded-software, it is hardly possible to analyze specifications by reverse engineering. In this paper a real-time transmission simulator adaptable to TCU is presented, for analysis of diagnosis algorithm and standards. Signal simulation circuits are deliberately designed considering electrical characteristics of TCU inputs and various analysis tools, such as analog input auto scan function, and global output enable switch, are implemented in software. Test results from hardware-in-the-loop simulator verify tolerance time for each error, as well as cause of fault, error reset conditions.

• Smart Structures and Systems
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• v.23 no.3
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• pp.227-242
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• 2019

Seismic isolation systems employ structural control that protect both buildings and vibration-sensitive contents from destructive effects of earthquakes. Structural control is divided into three main groups: passive, active, and semi-active. Among them, semi-active isolation systems, which can reduce floor displacements and accelerations concurrently, has gained importance in recent years since they don't require large power or pose stability problems like active ones. However, their seismic performance may vary depending on the variations that may be observed in the mechanical properties of semi-active devices and/or seismic isolators. Uncertainties relating to isolators can arise from variations in geometry, boundary conditions, material behavior, or temperature, or aging whereas those relating to semi-active control devices can be due to thermal changes, inefficiencies in calibrations, manufacturing errors, etc. For a more realistic evaluation of the seismic behavior of semi-active isolated buildings, such uncertainties must be taken into account. Here, the probabilistic behavior of semi-active isolated buildings under historical pulse-like near-fault earthquakes is evaluated in terms of their performance in preserving structural integrity and protecting vibration-sensitive contents considering aforementioned uncertainties via Monte-Carlo simulations of 3-story and 9-story semi-active isolated benchmark buildings. The results are presented in the form of fragility curves and probability of failure profiles.

• Journal of Korean Society for Quality Management
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• v.47 no.1
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• pp.75-86
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• 2019

Purpose: It is essential for the steel industry to produce steel products without unexpected downtime to reduce costs and produce high quality products. A hot strip rolling mill consists of many mechanical and electrical units. In condition monitoring and diagnosis, various units could fail for unknown reasons. Methods: In this study, we propose an effective method to detect units with abnormal status early to minimize system downtime. The early warning problem with various units was first defined. An autoencoder was modeled to detect abnormal states. An application of the proposed method was also implemented in a simulated field-data analysis. Results: We can compare images of original data and reconstructed images, as well as visually identify differences between original and reconstruction images. We confirmed that normal and abnormal states can be distinguished by reconstruction error of autoencoder. Experimental results show the possibility of prediction due to the increase of reconstruction error from just before equipment failure. Conclusion: In this paper, hot strip roughing mill monitoring method using autoencoder is proposed and experiments are performed to study the benefit of the autoencoder.

• Journal of Information Technology Services
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• v.20 no.3
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• pp.1-12
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• 2021

Reactor Coolant Pump (RCP) is core part of nuclear power plant to provide the forced circulation of reactor coolant for the removal of core heat. Properly monitoring vibration of RCP is a key activity of a successful predictive maintenance and can lead to a decrease in failure, optimization of machine performance, and a reduction of repair and maintenance costs. Here, we developed real-time RCP Vibration Analysis System (VAS) that web based platform using NoSQL DB (Mongo DB) to handle vibration data of RCP. In this paper, we explain how to implement digital signal process of vibration data from time domain to frequency domain using Fast Fourier transform and how to design NoSQL DB structure, how to implement web service using Java spring framework, JavaScript, High-Chart. We have implement various plot according to standard of the American Society of Mechanical Engineers (ASME) and it can show on web browser based on HTML 5. This data analysis platform shows a upgraded method to real-time analyze vibration data and easily uses without specialist. Furthermore to get better precision we have plan apply to additional machine learning technology.